Podcast appearances and mentions of brian o'neill

Matthew Coller connects with PFF's cap expert Brad Spielberger to break down cap implications of Jeff Gladney being indicted. Plus they talked about why Brian O'Neill will very likely sign a contract extension with the Vikings despite the fact that it hasn't happened yet, what Harrison Smith's potential future looks like and Danielle Hunter's future options. Plus a note on how long Aaron Rodgers will be in Green Bay. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Matthew Coller and Will Ragatz, who covers the Vikings for Sports Illustrated, sit down at TCO Performance Center to talk about how the Vikings' first day of training camp practice went and what's happening with the cornerback group. Do we think that Harrison Hand is ahead of Kris Boyd and what did Patrick Peterson tell us about his early interactions with the younger cornerbacks. Plus Brian O'Neill and Harrison Smith have not yet been signed to extensions -- will those be on the way soon? And, is the kicker on the current 90-man roster? Learn more about your ad choices. Visit podcastchoices.com/adchoices

Minnesota Vikings predictions on potential trades, Brian O'Neill's potential contract extension, training camp, Week 1 predictions and more on this week's edition of Write That Down!

Host Gabe Henderson and Producer Jay Nelson talk about Danielle Hunter's reworked contract, the return of Sheldon Richardson and they chat it up with Pitt Panther Alums and reunited teammates, Offensive Tackle Brian O'Neill and Defensive End Patrick Jones II. It's all on Episode #100 of the Minnesota Vikings Podcast.

Host Gabe Henderson and Producer Jay Nelson talk about Danielle Hunter's reworked contract, the return of Sheldon Richardson and they chat it up with Pitt Panther Alums and reunited teammates, Offensive Tackle Brian O'Neill and Defensive End Patrick Jones II. It's all on Episode #100 of the Minnesota Vikings Podcast.

Host Gabe Henderson and Producer Jay Nelson talk about Danielle Hunter's reworked contract, the return of Sheldon Richardson and they chat it up with Pitt Panther Alums and reunited teammates, Offensive Tackle Brian O'Neill and Defensive End Patrick Jones II. It's all on Episode #100 of the Minnesota Vikings Podcast.

Brian was born in New York and moved to Florida at age five and spent most of his life there. He attended Florida State University, and then at the age of thirty, he moved to Chicago. Brian has been there for seventeen years now and has a wonderful wife, Katie, who he's been married to for ten years. They have a nine-year-old son named Will. They love spending time together and taking family vacations, just the three of them. In his spare time, Brian likes to play golf, read and play sports with his son. BKW Property Solutions was started to provide flexible real estate solutions for both buyers and sellers. They serve the Greater Chicagoland area and help buyers realize their dream of owning a home. When Brian and Katie experienced many of the common challenges of selling their own home many years ago, they knew there had to be a better way. That is the foundation of BKW Property Solutions and we look forward to serving your needs. There is a better way! Brian is also the Strategy Expert for Smart Real Estate Coach. After spending 25+ years in the corporate world, Brian finally decided to get out of his own way and pursue his dream of running his own business. In this role, Brian helps other aspiring entrepreneurs carve out their path for financial freedom using creative financing strategies in real estate. Curtis and Brian discuss and review his business of helping buyers and sellers with creating financing and how he helps other people achieve their goal of scaling a business. Curtis's motto is that what you learn today and how you position yourself will determine your future financial well-being 5, 10, 20 years from today. To learn more about how to manage your wealth in a practical way, visit www.practicalwealthadvisors.com  Links and Resources from this Episode www.practicalwealthadvisors.com Email Curtis for a free report - curtmay@gmail.com Call his office - 610-622-3121 Connect with Brian O'Neill brian@bkwpropertysolutions.com http://bkwpropertysolutions.com/ Facebook: https://www.facebook.com/bkwpropertysolutions/ Instagram: https://www.instagram.com/bkwpropertysolutions/ LinkedIn: https://www.linkedin.com/in/brian-o-neill-5069216/  Special Listener Gift Schedule a 15-Minute Call with Curtis Free Ebook Financial Planning Has Failed Show Notes A mindset that has to happen - 3:21 Going to college and getting a new job - 4:13 Being sick and tired - 5:32 The real estate business space - 6:03 Finding individuals that are the “ideal buyer” - 13:50 We're looking to help and solve problems - 15:16 About scaling - 18:28 Figuring out what do you want for your life - 25:54 Review, Subscribe and Share If you like what you hear please leave a review by clicking here Make sure you're subscribed to the podcast so you get the latest episodes. Click here to subscribe with Apple Podcasts Click here to subscribe with Spotify Click here to subscribe with Stitcher Click here to subscribe with RSS

The Vikings are on the verge of extending Brian O'Neill. Is that a good idea? Plus, long snapper Andrew DePaola has built a full career out of camp competitions and hanging on by a thread. Support Us By Supporting Our Sponsors! Built Bar Built Bar is a protein bar that tastes like a candy bar. Go to builtbar.com and use promo code “LOCKED15,” and you'll get 15% off your next order. BetOnline AG There is only 1 place that has you covered and 1 place we trust. Betonline.ag! Sign up today for a free account at betonline.ag and use that promocode: LOCKEDON for your 50% welcome bonus. Rock Auto Amazing selection. Reliably low prices. All the parts your car will ever need. Visit RockAuto.com and tell them Locked On sent you. StatHero StatHero, the FIRST Ever Daily Fantasy Sportsbook that gives the PLAYER the ADVANTAGE. Go to StatHero.com/LockedOn for 300% back on your first play. Follow the show: @LockedOnVikings Follow the host: @LukeBraunNFL Join the discord community: https://linktr.ee/LukeBraunNFL Submit Twitter Tuesday questions: https://docs.google.com/forms/d/e/1FAIpQLSc3mA_-Yke_oIwlZ5vOnIW_TK4d9gRwjmOB7YOLzeLLIz_-3w/viewform?usp=sf_link Brian O'Neill article: https://zonecoverage.com/2021/minnesota-vikings-news/minnesota-deserves-credit-for-developing-brian-oneill/ Andrew DePaola: https://www.buccaneers.com/news/road-to-the-nfl-andrew-depaola-14855283 Learn more about your ad choices. Visit podcastchoices.com/adchoices

Minnesota Vikings emerging star right tackle Brian O'Neill is headed into the final year of his rookie deal and stated he would love to be in Purple "long term". Would love to see it. Timestamps: • (0:45) Pay Brian O'Neill • (3:35) Without Danielle? • (7:06) Love Boat 2 • (10:01) CB Tye Smith Signed • (11:34) Irv Smith Jr is Jacked • (14:24) Best of Anthony Barr A Northern Digital Production --- Protect Your Online Privacy with ExpressVPN! https://www.expressvpn.com/purpleftw YouTube: https://www.youtube.com/c/purpleftwpodcast

The virtuoso trombonist, arranger, and cofounder of Bonerama and Mulebone has also recorded with a laundry list of stars, including Sheryl Crow, Maceo Parker, R.E.M., and Tori Amos. Having cut his teeth in the Harry Connick Jr. Big Band, he’s more recently served as an arranger/producer with his own Levee Horns. These productions have included concerts for Blackbird Presents such as the Last Waltz 40 tour, Mavis Staples, Merle Haggard, and Dr John, and featured the legendary Don Was as musical director. It seems like Mark can work with almost anyone. Tonight that’s put to the test when he joins the Troubled Men. Topics include cicadas, the oldest woman, the end of school, rental returns, Mother’s Day, prison listeners, a provocative name, high school, Richard Erb, Loyola U., Dave Ferrato, Rum Boogie, a termite swarm, Brian O’Neill, Charlie Brent, Luther Kent and Trick Bag, George Porter Jr., Jon Langford, OK GO, Eric Traub, live dates, and much more. Subscribe, review, and rate (5 stars) on Apple Podcasts, Spotify, or almost any podcast aggregator. Follow on social media, share with friends, and spread the Troubled Word. Intro music: Styler/Coman Break music: “Frankenstein” by Bonerama Outro music: “Charity” by Mulebone

Tonight we meet Katia Valadeau who has created a fantastic online map that identifies where in Ireland we can enjoy outdoor dining when restrictions lift. Artisan food producer Brian O Neill gives us the lowdown on his company Dublin Hot Sauce and Freelance editor and food writer Kristin Jensen shares details about her kickstarter campaign "Blasta Books" which will change the way that cookbooks are published.

Evolution wasn't enough, we needed more crazy animals that we come up with! So we played Oceans by Nick Bentley, Dominic Crapuchettes, Ben Goldman, and Brian O’Neill. Published in 2020 by North Star Games. Post your comments to Twitter/Instagram @FirstTurnCast or email us at firstturntabletop@gmail.com.  Please remember to rate, review, and subscribe!  Until next week, play more games!

This week we talk to the organiser of an intriguing new boxing-based seminar for coaches from all disciplines across the South-East We hear from former Six Nations winner Alison Miller ahead of Ireland's upcoming campaign in what's the strangest of formats. And Ireland soccer captain Áine O'Gorman chats ahead of their upcoming World Cup qualifying campaign

This episode is going to KNOCK your socks off. This is REAL TALK about pricing and getting paid. Super valuable advice for every working musician, seriously a must-hear. Brian delivers massive value… I can’t wait for you to hear it! The #1 thing you should make sure happens when it comes to getting paid, whether it’s a gig or students How to simultaneously raise your prices AND make it a no-brainer for the one who’s paying for the lessons A strategy for offering different packages (whether it’s lessons or a performing gig) to get you the most money possible Powerful advice if you play wedding gigs or gigs like it - you have to hear this! And SO much more And right now I have a FREE REPORT to help you build in more value (and thus more income!) into your teaching business. Download the report HERE Want to try Fons? Fons.com is a powerful tool to help you streamline your teaching. With automatic payments and scheduling integrated into one platform, Fons transforms your teaching studio into a polished business. Try FREE for a whole 45 days on me here: https://fons.com/join/@tracygfriedlander  

O'Neill and Marlowe talk COVID-19, Comets, careers and a little bit of St. Louis Cardinals in an hour-long installment of the FTWI podcast. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app Support this podcast: https://anchor.fm/ftwinquired/support

Many business owners face significant challenges when it comes to buying or selling a home; because your income comes from your own business, the bank creates serious hurdles to qualifying for a mortgage. And selling a home through a bank comes with its own headaches and costs that can eat into your profits. What can you do? Brian O’Neill is an entrepreneur who specializes in the real estate “terms” niche, circumventing the banks entirely. Brian O’Neill was born in New York and moved to Florida at age 5 and spent most of his life there. He attended Florida State University and then at the age of 30 he moved to Chicago. Brian has been there for 17 years now and has a wonderful wife, Katie, who he has been married to for 10 years. They have a 9 year old son named Will. They love spending time together and taking family vacations, just the 3 of them. In his spare time, Brian likes to play golf, read, and play sports with his son. What you’ll learn about in this episode: Why buying a house as a business owner can be difficult even if you have excellent credit, and why “terms” deals are a great alternative to a bank mortgage loan How Brian got involved in real estate investing in an effort to be able to spend more time with his family Why Brian fell into the habit of talking himself out of starting his business, and how he finally overcame his own limiting beliefs Why having the right mentor and a supportive “inner circle” of connections has been instrumental in Brian’s success as an entrepreneur Why feeling stuck is often due to not realizing all the options you have available, and what to do if you have little equity or even if you’re upside down in your current home What advantages business owners can get from buying or selling a home through “terms” rather than through a traditional bank mortgage How selling a home on terms works, and why it can create monthly income without having to deal with the hassles and headaches of being a landlord What kind of deal structure options are available for buying or selling on terms, and what happens if a buyer is unable to buy the home by the end of the terms period How terms deals can serve as a great option for homeowners who are significantly behind on their property taxes and at risk of forfeiting their home How Brian works to educate buyers and sellers on a different perspective and on other problem-solving options they may not have known about Resources: Phone: (331) 803-8268 Email: brian@BKWPropertySolutions.com Website: www.BKWPropertySolutions.com Facebook: www.facebook.com/bkwpropertysolutions/ Additional Resources: Free Executive Leadership Summary report from Predictive ROI: https://predictiveroi.com/research Sell With Authority by Drew McLellan and Stephen Woessner: https://amzn.to/39y7x13 Predictive ROI Free Resource Library: https://predictiveroi.com/resources/ Stephen Woessner’s LinkedIn: www.linkedin.com/in/stephenwoessner/

Brian was born in New York and moved to Florida at age five and spent most of his life there. He attended Florida State University, and then at the age of thirty he moved to Chicago. Brian has been there for seventeen years now and has a wonderful wife, Katie, who he's been married to for ten years. They have a nine year old son named Will. They love spending time together and taking family vacations, just the three of them. In his spare time Brian likes to play golf, read and play sports with his son. What you'll learn about in this episode: How Brian got started with the Wicked Smart community just over a year ago, and what significant changes have happened over that year Why the decision to commit and take action were key ingredients in Brian's success as a real estate investor Why Brian had to work hard to conquer his fears and take the plunge, and why many of the things he had believed were holding him back were just excuses Why Brian attributes much of his success to patiently taking consistent action on the small things every day How having access to an entire community and powerful resources and support helped Brian get started investing Why success is a choice, and why Brian believes you have the power to make the decision to get started on your road to success Why Brian found the lack of “get rich quick” in the Wicked Smart community to be an appealing feature What advice Brian would offer to anyone who is on the fence and uncertain how to get started as a real estate investor How Brian has been able to get sixteen properties under contract in just the twelve months he's been a part of the community Why the upcoming Wicked Smart Kick Start on January 9, 2021 is the ideal time to become a part of the community, and how to get registered for the event for just $99 Resources: Smart Real Estate Coach podcast episode 191 with Brian O'Neill: https://smartrealestatecoachpodcast.com/podcasts/family-cast-11/ Wicked Smart Kick Start: https://wickedsmartkickstart.com/ Schedule a FREE strategy call with Brian: www.SmartRealEstateCoach.com/action Additional resources: SmartRealEstateCoach.com/action Real Estate on Your Terms by Chris Prefontaine SmartRealEstateCoachPodcast.com/webinar SmartRealEstateCoachPodcast.com/ebook SmartRealEstateCoach.com/QLS

It’s Twitter Tuesday on Locked On Vikings! We’ll talk about the Pro Bowl rosters, and then jump into the mailbag. What are the biggest offseason needs? Does the Vikings draft strategy work? Why won’t Kubiak target Brian O’Neill? All that and more! Support Us By Supporting Our Sponsors!  Built Bar Built Bar is a protein bar that tastes like a candy bar. Go to builtbar.com and use promo code “LOCKEDON,” and you’ll get 20% off your next order. BetOnline AG There is only 1 place that has you covered and 1 place we trust. Betonline.ag! Sign up today for a free account at betonline.ag and use that promocode: LOCKEDON for your 50% welcome bonus.  BuiltGo Visit BuiltGO.com and use promo code “LOCKED,” and you’ll get 20% off your next order. BetterHelp I want you to start living a happier life today. As a listener, you’ll get 10% off your first month by visiting our sponsor at BetterHelp.com/LockedOn Follow the show: @LockedOnVikings Follow the host: @LukeBraunNFL Pro bowl roster: https://www.espn.com/nfl/story/_/id/30576174/kansas-city-chiefs-green-bay-packers-baltimore-ravens-seattle-seahawks-lead-pro-bowl-selections Learn more about your ad choices. Visit podcastchoices.com/adchoices

On this episode of the Minnesota Vikings Podcast, offensive lineman Brian O'Neill joins vikings.com's Chris Corso to discuss his success this year, the Vikings recent stretch and what his expectations are for the rest of the season. Vikings.com's Cy Amundson, Gabe Henderson and Jay Nelson chat about the win against the Panthers and look ahead to the Jaguars game. Vikings.com's Eric Smith is joined by Jaguars Team Reporter Ashlyn Sullivan to preview the matchup.

On this episode of the Minnesota Vikings Podcast, offensive lineman Brian O'Neill joins vikings.com's Chris Corso to discuss his success this year, the Vikings recent stretch and what his expectations are for the rest of the season. Vikings.com's Cy Amundson, Gabe Henderson and Jay Nelson chat about the win against the Panthers and look ahead to the Jaguars game. Vikings.com's Eric Smith is joined by Jaguars Team Reporter Ashlyn Sullivan to preview the matchup.

On this episode of the Minnesota Vikings Podcast, offensive lineman Brian O'Neill joins vikings.com's Chris Corso to discuss his success this year, the Vikings recent stretch and what his expectations are for the rest of the season. Vikings.com's Cy Amundson, Gabe Henderson and Jay Nelson chat about the win against the Panthers and look ahead to the Jaguars game. Vikings.com's Eric Smith is joined by Jaguars Team Reporter Ashlyn Sullivan to preview the matchup.

Everson Griffen is going to Dallas after swooping in and beating out Seattle and Minnesota. Let's take a moment to appreciate his legacy and mourn his departure. We can also decide, separately from that, if we agree with the Vikings' decision not to outbid the Cowboys. To cleanse our bitter palates, we can take a look at Vikings RT Brian O'Neill, what he's done so well, how the offense can use that, and what it means for our 2020 expectations. Support Us By Supporting Our Sponsors!  Rock Auto Amazing selection. Reliably low prices. All the parts your car will ever need. Visit RockAuto.com and tell them Locked On sent you. Follow the show: @LockedOnVikings Follow the host: @LukeBraunNFL Everson Griffen story: https://www.nfl.com/news/cowboys-signing-former-vikings-de-everson-griffen Brian O'Neill vs. Joey Bosa: https://twitter.com/LukeBraunNFL/status/1293610214965407744 Brian O'Neill vs. Za'darius Smith: https://twitter.com/LukeBraunNFL/status/1293670517589725184 Learn more about your ad choices. Visit megaphone.fm/adchoices

Brian O'Neill was born in New York and moved to Florida at age 5 and spent most of his life there. He attended Florida State University and then at the age of 30 he moved to Chicago. Brian has been there for 17 years now and has a wonderful wife, Katie, who he has been married to for 10 years. They have a very soon-to-be 9-year-old son named Will. They love spending time together and taking family vacations, just the 3 of them. In his spare time, Brian likes to play golf, read, and play sports with his son. What you'll learn about in this episode: How Brian has managed to achieve enough success in real estate to resign from his career and turn to full-time investing How Brian first joined the Smart Real Estate Coach team around Thanksgiving of 2019, and how he achieved his goal of leaving his job far earlier than his estimation of 2022 How Brian managed to overcome his fear and jump into investing full-time, and how he came to the realization that now was the time to make the leap Why getting into the right headspace was critical for Brian's success, and how he realized that he needed to “get out of his own way” by starting with small changes How Brian achieved his success so quickly through hard work, paying attention, and taking action every day How Brian starts every day with the same key morning routine, and how that routine sets him up for success How working from home during the global pandemic and realizing how much he enjoyed the extra time with his son became a key motivator for Brian Why it is important to be “the authority” in your marketplace, and how Brian is now focusing on working with people he can help How Brian manages a balance between focusing on his goals while also spending time with his family, and why success requires a “get it done” mentality Why one of the most powerful quotes that Brian lives by is “if you turn the ship just a little bit, you'll end up in a completely different place” Resources: Email support@smartrealestatecoach.com with the subject “Affirmations Book” Be The Authority online course: https://predictiveroi.com/be-the-authority/ Additional resources: LIVE Event September 16-18, 2020: www.qlslive.com Website: www.SmartRealEstateCoachPodcast.com/webinar Website: www.SmartRealEstateCoachPodcast.com/termsbook Website: www.SmartRealEstateCoachPodcast.com/ebook Website: www.SmartRealEstateCoach.com/QLS/ Smart Real Estate Coach Podcast Sponsor: Paul G. Dion CPA, CTC

Show Notes(2:40) Brian discussed his career as a musician and his mission as a consultant to bring design principles into the analytics world.(5:25) Brian talked about his career inception as a UX designer and his interest in human-centered design.(9:48) Brian shared the backstory behind starting Designing for Analytics and his advice for anyone interested in becoming a consultant (hint: finding the minimum viable audience for your craft!).(20:44) Brian shared the common problems that his clients ask him to solve - citing that many of the solutions in engineering-driven organizations are “Technically Right, Effectively Wrong” (listen to Brian’s podcast with David Stephenson).(27:20) Brian explained why data product design goes well beyond user interfaces and helps define what is required to enable the desired user and business outcomes, referring to his post “Does your data product enable surgery or healing?”(33:14) Brian revealed the tactical tips for designing an effective prototype for data products, as shared in his post “Designing MVPs for Data Products and Decision Support Tools.”(40:31) Brian talked about the importance of using human-centered design to measure meaningful engagement in the context of data products, as shared in his post “Why Low Engagement May Not be the Problem with Your Data Product or Analytics Service” (Hint: Think about the last mile and use design to make deliberate choices to improve user engagement).(47:46) Brian unpacked the design framework CED (which stands for Conclusion, Evidence, and Data), which helps build customer trust, engagement, and indispensability around advanced analytics.(54:55) Brian shared his take on how to structure a quad team, including software engineers, UX designers, data scientists, and product managers to build machine learning-powered products.(01:03:25) Brian emphasized the importance of trust in modern data products, after countless conversations with leaders in his podcast Experiencing Data.(01:06:34) Brian unveiled his seminar called Designing Human-Centered Data Products for data scientists, technical product managers, and analytics practitioners.(01:09:47) Closing segment.His Contact InfoDesigning For AnalyticsTwitterLinkedInExperiencing Data PodcastInsights NewsletterHis Recommended ResourcesSeth Godin’s podcast AkimboMinimum Viable ProductWizard of Oz TestingCED FrameworkChris DoScott Berkun (his book “How Design Makes The World”)Juhan Sonin (Involution Studios)Amanda Cox (NYT’s The Upshot)“Good Charts” (by Scott Berinato)“Change By Design” (by Tim Brown)“Infonomics” (by Douglas Laney)“Competing In The Age of AI” (by Marco Iansiti and Karim Lakhani)

Show Notes(2:40) Brian discussed his career as a musician and his mission as a consultant to bring design principles into the analytics world.(5:25) Brian talked about his career inception as a UX designer and his interest in human-centered design.(9:48) Brian shared the backstory behind starting Designing for Analytics and his advice for anyone interested in becoming a consultant (hint: finding the minimum viable audience for your craft!).(20:44) Brian shared the common problems that his clients ask him to solve - citing that many of the solutions in engineering-driven organizations are “Technically Right, Effectively Wrong” (listen to Brian’s podcast with David Stephenson).(27:20) Brian explained why data product design goes well beyond user interfaces and helps define what is required to enable the desired user and business outcomes, referring to his post “Does your data product enable surgery or healing?”(33:14) Brian revealed the tactical tips for designing an effective prototype for data products, as shared in his post “Designing MVPs for Data Products and Decision Support Tools.”(40:31) Brian talked about the importance of using human-centered design to measure meaningful engagement in the context of data products, as shared in his post “Why Low Engagement May Not be the Problem with Your Data Product or Analytics Service” (Hint: Think about the last mile and use design to make deliberate choices to improve user engagement).(47:46) Brian unpacked the design framework CED (which stands for Conclusion, Evidence, and Data), which helps build customer trust, engagement, and indispensability around advanced analytics.(54:55) Brian shared his take on how to structure a quad team, including software engineers, UX designers, data scientists, and product managers to build machine learning-powered products.(01:03:25) Brian emphasized the importance of trust in modern data products, after countless conversations with leaders in his podcast Experiencing Data.(01:06:34) Brian unveiled his seminar called Designing Human-Centered Data Products for data scientists, technical product managers, and analytics practitioners.(01:09:47) Closing segment.His Contact InfoDesigning For AnalyticsTwitterLinkedInExperiencing Data PodcastInsights NewsletterHis Recommended ResourcesSeth Godin’s podcast AkimboMinimum Viable ProductWizard of Oz TestingCED FrameworkChris DoScott Berkun (his book “How Design Makes The World”)Juhan Sonin (Involution Studios)Amanda Cox (NYT’s The Upshot)“Good Charts” (by Scott Berinato)“Change By Design” (by Tim Brown)“Infonomics” (by Douglas Laney)“Competing In The Age of AI” (by Marco Iansiti and Karim Lakhani)

Flip and Ryan continue the Roster Preview Series. We talk about Ryan's favorite Vikings moment, Brian O'Neill's ascension and all things Anthony Barr. PFF fans beware. 2007 Chargers at Vikings - Two records in one game Brian O'Neill the Leader Anthony Barr the Blitzer Learn more about your ad choices. Visit megaphone.fm/adchoices

 This is the second part of the episode of Climbing The Pocket Quick Shots, Jayson Brown sits down with two of the Climbing The Pocket Network’s film watching experts to talk Minnesota Vikings O-Line improvement. Tyler Forness and Matt Fries look in-depth at the skills and possibilities of all the offensive linemen that the Vikings acquired after taking Ezra Cleveland, like Blake Brandel from Oregon State, Kyle Hinton from the football power house of Washburn, and Brady Aiello from Oregon, their all purpose lineman.  There are also the players still on the team that didn’t start last season like Dru Samia, Oli Udoh and Aviante Collins that figure into the new look of the line because we know there is at least one player at right guard, and at left, Pat Elflein will have to show a miraculous improvement to stay in the LG spot. Cleveland could start, Riley Reiff could move over, Garrett Bradbury and Brian O’Neill locked into their spots and a wide open competition at RG. Who will win it? Who will make the squad to back them up?   Those are questions we are all looking forward to seeing answers on. Rick Spielman has been working over the last few years to improve the offensive line. His success rate over Mike Zimmer’s tenure has been questionable at times, but Gary Kubiak and Mike Dennison are on the staff, the 2020 draft in the books, and things are looking up. Agree or disagree? What say you?  Like, subscribe, give us a thumbs up on YouTube and rate us on your favorite podcast aggregator. Share with your Vikings and other friends too. Then shout SKOL!     As always, enjoy the watch and listen! Stay safe, and GO VIKINGS! Fan with us!!! You can follow Matt Fries at @FriesFootball, and Tyler Forness at @TheRealForno, CTP host Jayson Brown can be contacted at @brownjayson and this episode was produced by GMG hosts Dave at @Luft_Krigare. Learn more about your ad choices. Visit megaphone.fm/adchoices

Is deal flow dead or just in a holding pattern? Brian O’Neill, an M&A partner at the law firm of Tucker Ellis, discusses which types of deals are still getting done in these uncertain times and the impact on pending and existing contracts and agreements.

Hello Everyone, The guest we have today is a unique in lot more ways. He took his prior education in Music and runs Music group "orchestrotica" . Also, he is managing his career and interests together. And now he is a Founder of @Analytics Designs which helps companies turn analytics and ML into indispensable decision support applications. While talking about keeping multiple interests and passions, he mentioned that "managing time is more important aspect, one should find the time for it and its possible, so stop complaining that you don't have a time". He has a lot more to share about his interesting career journey, growth as well as Leadership. So, Watch complete episode - https://www.youtube.com/watch?v=qCiTPMvnfro Listen to complete episode - https://anchor.fm/vaishali-lambe/episodes/SoLeadSaturday---Episode-23---Brian-ONeill-edhj1g Do connect with him directly on LinkedIn, if you have any more questions for him. Until we meet, Happy Leading and Let's Lead Together. Stay Safe! Bye for now! Find me on: Twitter - https://twitter.com/vaishalilambeLinkedIn - https://www.linkedin.com/in/vaishali-...Website - https://www.vaishalilambe.com/soleads...Apple Podcasts - https://podcasts.apple.com/us/podcast...Google Podcasts - https://www.google.com/podcasts?feed=...Spotify - https://open.spotify.com/show/0bFOIm9... --- Support this podcast: https://anchor.fm/vaishali-lambe/support

 Should the Vikings start Ezra Cleveland at left tackle from the beginning? The Climbing The Pocket Network is starting a new feature called Quick Shots. The hope is to have those quick strike, short videos and podcasts that talk about some of the latest issues and topics surrounding your Minnesota Vikings. We hope to answer a question of the day, or at least get you thinking about one.  Dave, from Good Morning Gjallarhorn addresses the question. A big proponent of starting him. Brian O’Neill started his first season and never looked back. Dave brings evidence as provided by friend of the show, Mike Renner from PFF. Back in early March, Mike gave his opinion on Ezra Cleveland’s play and performance at the NFL Combine.   You can catch Mike’s show at https://youtu.be/vv-FiE49gsA  There are basically 4 options the Vikings could consider. Option 1: Start Riley Reiff at LT and put Cleveland at LG. Option 2: Start Cleveland at LT and slide Reiff into LG. Option 3: Groom Cleveland as the swing tackle, a spot held by Rashod Hill. Finnally, option 4: completely red-shirt Cleveland and let him just learn in practice all season. Plus, those options include left guard, but do you see someone else starting there, and what about the right side? Will Dru Samia earn a spot, does Josh Kline get re-signed, Aviante Collins get to compete, or even Pat Elflein moving to the right side? Which option do you want? Which option do you see the Vikings actually doing?  Like, subscribe, and rate us on your favorite podcast aggregator. Share with your Vikings and other friends too. Then shout SKOL!     As always, enjoy the watch and listen! Stay safe, and GO VIKINGS! Fan with us!!! You can follow GMG host Dave at @Luft_Krigare. Learn more about your ad choices. Visit megaphone.fm/adchoices

Our guest for this episode is Brian O'Neill, the Founder of Designing for Analytics. Brian helps companies turn analytics and ML into indispensable decision support applications. In short, he ensures the last mile UX—where users and customers interact with the outputs of your analytics and ML investments—is useful, usable, and engaging.  Listen to the episode - Outcome Vs. Output Host - Piyanka Jain, President & CEO of Aryng

Post-Gazette columnist Brian O'Neill joins Marty to talk about a column he recently wrote on state stores and the issues that have come up during the coronavirus pandemic.

Why are some dashboards so meaningless? How can you make information helpful? Today our guest is Brian O'Neil, founder & principal of Designing for Analytics. You'll learn how to approach data visualization thoughtfully, how to help users make their decisions, why you shouldn't go after fancy diagrams, and why "removing everything" isn't always your best strategy.Podcast feed: subscribe to https://feeds.simplecast.com/4MvgQ73R in your favorite podcast app, and follow us on iTunes, Stitcher, or Google Play Music.Show NotesDesigning for Analytics — Brian's companyThe CED Design Framework for Integrating Advanced Analytics into Decision Support Software — Brian's articleInformation Dashboard Design — a book by Stephen FewHow Charts Lie — a book by Alberto CairoGood Charts — a book by Scott BerinatoD3.js — the most popular data visualization libraryGet Brian's free self-assessment guideExperiencing Data — Brian's podcastDrop Brian a line at brian@designingforanalytics.comFollow Brian on Twitter: @rhythmspiceToday's SponsorThis episode is brought to you by Podcast Motor — a podcast editing service for busy professionals. You just show up and record great content, and they handle the rest: audio editing, shownotes, publishing, promotion, and much more. Check them out at podcastmotor.com, and mention UIBREAKFAST to get $50 off your first order.Interested in sponsoring an episode? Learn more here. Leave a ReviewReviews are hugely important because they help new people discover this podcast. If you enjoyed listening to this episode, please leave a review on iTunes. Here's how.

  Vikings vs Bears… Good morning Horners! Your Minnesota Vikings played their backups versus the Chicago Bears and almost pulled out a victory in a meaningless, or at least to the playoff seeding, game. Drew, Ted and Dave discuss the afternoon action and the state of the team. Ted after a bad weekend for his team is not that optimistic going into next week against the Saints or the Seahawks, and at the time of the recording we don’t know which. That will change by the end of the evening though as the Forty Niners and the Seahawks will figure that out for us. A 49’er win means a trip to New Orleans and a Seahawk win means a trip to Seattle. Which would you rather play in next weekend?  There was some good play by some of the backups. Dave like the effort and attitude by Oli Udoh in for Brian O’Neill, even though he got some tick tack calls. Sean Mannion proved why he was just a backup and not a good one. Mike Boone had a much better game than last week with 160 yards of production and 148 of them on the ground. He even got a TD out of that. Alexander Hollins and Bisi Johnson were the two leading receivers but on the day, it was Dan Bailey that scored 13 of the Vikings 19 points. He also earned his $1,000,000 bonus for making more than 90% of his kicks this year… a good thing.  Matt Nagy and the Bears racked up their second win of the season and 4th against Mike Zimmer even though this win was against the second stringers. Does that cause you concern like it does for Ted and Drew? Next comes Pete Carroll or Sean Payton, two other coaches that tend to beat Zimmer teams, but who knows, this could be our year in these playoffs.  GMG wants to wish you all a safe and Happy New Year! We’ll be here to talk your Vikings all the way into and through the playoffs. Go Vikings!  Like, subscribe, and rate us on your favorite podcast aggregator. Share with your Vikings and other friends too. Then shout SKOL!     As always, enjoy the watch and listen! GO VIKINGS! You can follow GMG hosts Dave at @Luft_Krigare and Ted at @purplebuckeye. Unfortunately, Drew is behind the power curve and doesn’t have a Twitter handle… yet. Learn more about your ad choices. Visit megaphone.fm/adchoices

1. Week 15 Takeaways Me: It’s time to put Drew Brees in the discussion as one of the five best QB’s of all time Hal: 49ers with a huge lost opportunity 2. Truth/Exaggeration -The Browns should fire BOTH Freddie Kitchens and John Dorsey -The Jaguars problems will only get worse if they retain Tom Coughlin -Matt Patricia will get fired after the 2020 season if the Lions fail to sniff the playoffs -The Buccaneers should extend Shaq Barrett by February and give Jameis Winston the franchise tag as opposed to a multi-year deal -The Indianapolis Colts should use their first-round pick on Utah State QB Jordan Love if he significantly impresses them during the pre-draft process -With their offense re-discovering its 2018 mojo and their defense playing underrated football, the Kansas City Chiefs are the team the Ravens should fear the most in the playoffs -Kirk Cousins, Dak Prescott, Fred Warner, and Justin Simmons should have made the Pro Bowl as opposed to Aaron Rodgers, Drew Brees, Luke Kuechly and Earl Thomas -ALL NFC playoff teams outside of New Orleans should be praying hard that the Saints don’t get the NFC’s #1 seed again 3. Game of the Week: Bills at Patriots -Should anybody be surprised if the Bills pull off the upset in Foxboro on Saturday? -Is there a case for Tre’Davious White as already being on the level of Stephon Gilmore? -Key matchups: Cole Beasley vs. Devin McCourty, Jordan Phillips and Ed Oliver versus Patriots iOL -Game picks 4. Game of the Week: Packers at Vikings -While some people may see a high-scoring shootout in this game, I also think a defensive struggle is just as likely, especially given the inconsistencies of the Packers offense and Dalvin Cook looking iffy to play. What do you think? -X Factors for each team Packers: Kenny Clark, Jaire Alexander/Kevin King Vikings: Alexander Mattison, Eric Kendricks/Linval Joseph -Key matchups: David Bakhtiari/Bryan Bulaga vs. Danielle Hunter/Everson Griffen, Brian O’Neill vs. Za’Darius Smith, Blake Martinez vs. Alexander Mattison -Game picks 5. Picks for remainder of Week 16 games -Texans at Buccaneers -Rams at 49ers -Jaguars at Falcons -Ravens at Browns -Saints at Titans -Panthers at Colts -Bengals at Dolphins -Giants at Redskins -Steelers at Jets -Lions at Broncos -Raiders at Chargers -Cowboys at Eagles -Cardinals at Seahawks -Chiefs at Bears 6. BOLD PREDICTIONS ME: Matt Prater wins the game for the Lions on an NFL record 65-yard field goal HAL: Mitchell Trubisky throws 3 TD’s, 250 pasisng yards, 100 rushing yards 7. Challenge Flags ME: San Francisco 49ers…let last weekend’s loss against the Falcons hurt as bad as it can and let it be your fuel these final two games and in the playoffs HAL: Jason Garrett, Doug Pederson: WHO WANTS THE NFC EAST????

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This week Brian O’Neill, founder of Designing for Analytics joins Allison Hartsoe in the Accelerator. To design for analytics means thinking through the myriad of human behaviors which support a successful outcome. From planning to process to production, designing for analytics is all about the right way to support decision making.   Please help us spread the word about building your business’ customer equity through effective customer analytics. Rate and review the podcast on Apple Podcast, Stitcher, Google Play, Alexa’s TuneIn, iHeartRadio or Spotify. And do tell us what you think by writing Allison at info@ambitiondata.com or ambitiondata.com. Thanks for listening! Tell a friend! Learn more about your ad choices. Visit megaphone.fm/adchoices

Media Literacy Ireland conference

Media Literacy Ireland conference

This week Brian O’Neill, founder of Designing for Analytics joins Allison Hartsoe in the Accelerator. To design for analytics means thinking through the myriad of human behaviors which support a successful outcome. From planning to process to production, designing for analytics is all about the right way to support decision making.   Please help us spread the word about building your business’ customer equity through effective customer analytics. Rate and review the podcast on Apple Podcast, Stitcher, Google Play, Alexa’s TuneIn, iHeartRadio or Spotify. And do tell us what you think by writing Allison at info@ambitiondata.com or ambitiondata.com. Thanks for listening! Tell a friend! Learn more about your ad choices. Visit megaphone.fm/adchoices

Season 2 Episode 28: J.Brian O'Neill - The Discovery Labs (Live) | Growing Greater On this special episode we had in depth conversation with Brian O’Neill in front of a live audience at one of his newest ventures, The Discovery Labs. He is re-imaging a 200 acre, 1 million square foot space in King of Prussia, Pennsylvania as a fully integrated environment for Big Pharma, emerging biotech start-ups, high tech companies, venture capitalists, and more to cohabitate under one roof. Known as one of the most successful real estate developers in Greater Philadelphia, Chairman, CEO, and Founder of MLP Ventures, Brian discusses how his path to success was in no way conventional and gives key advice as to how to succeed in business.

Vikings Country, presented by Miller Lite, is a chance to get to know your Minnesota Vikings players. This week Muss hangs with #75 Brian O'Neill. Muss and our starting Right Tackle talk about haunted houses, Brian's roommate Ben Gedeon, facial hair, shower beers, life off the field & this week's match up versus the New York Giants!

There's five count 'em FIVE big games in the NFL this weekend, and all four NFC North teams will be going at it. The Green Bay Packers play the Philadelphia Eagles in a game we hope ends in a tie. The Dallas Cowboys play the New Orleans Saints so we can cry about Teddy Bridgewater on Sunday Night. The Detroit Lions host the Kansas City Chiefs and reigning MVP Patrick Mahomes. The New England Patriots travel to upstate New York to Play the 3-0 Buffalo Bills. Our Minnesota Vikings play the Chicago Bears in a huge divisional clash. This week presents a huge opportunity for our Vikes to move up in the NFC standings. And they're healthy for it, after getting back Pat Elflein and Mike Hughes Week 3. Anthony Barr and Mackensie Alexander could be back too. Josh Kline was the only Viking to miss Wednesday practice due his concussion. Chad Beebe got hurt, but the Vikings brought back Marcus Sherels or Laquon Treadwell to replace him. Maybe Jordan Matthews would have been better? On offense, Irv Smith Jr, Kirk Cousins and Brian O'Neill are all streaking. We've gotta love how O'Neill is developing, even though he's got a tough match-up coming up against Khalil Mack. We're not sure yet about Garrett Bradbury, and we're hoping Akiem Hicks doesn't play. On defense, the more Sack Daddy the better. Throw in Danielle Hunter too. They've got to lead the way to victory against Charles Leno. And you know what? Can we please get some more Eric Wilson? Let him chase down Tarik Cohen and David Montgomery. Minnesota has a huge opportunity to strike back in the NFC North. 3-1 or 2-2 will look very different early on. All they need is their best players to STEP UP. Learn more about your ad choices. Visit megaphone.fm/adchoices

Around the League Colts pull out a Victory Dolphins are bad 49ers are 2-0 and look red hot Lamar Jackson is Legit Chiefs put up 28 pts in a single Quarter Rams thrash Saints Teddy Bridgewater in for injured Drew Brees, possibly for several weeks Falcons escape the Eagles Big Ben Roethlisberger done for year Drew Brees out for min 6 weeks The North Face Detroit pulls out a win over the Chargers in the 4th Chicago wins a wacky game in Denver Do they still win if Denver goes for the tie? Vikings GB Recap Packer fan at work said that the Packers didn’t win the game, that the Vikings lost it Game started - GB score - MN missed FG - GB score short field - MIN Fumble - GB score from 33 out Fan Question 1: “Was the 21-0 start more the Packers offense or our defense?”It was a combination of all three phases. Defense was playing GB’s WRs wrong, and giving GB short fields on two back to back possessions hurt  Special Teams Mishaps Missed FG / Blocked XP Bobbled Returns REALLY long XP attempt due to dumb penalty Is Dan Bailey the best option? Defensive Downturn ROUGH first quarter Playing way to soft on Devante Adams Blink - Down by 21 Fan question 2: “How much would have Alexander and Gideon helped in the defensive lapse 1st Quarter?? Thoughts on Meaders and Boyd when our CBs are depleted…”Ben Gedeon less so, although I think we have an easier time stopping the running attack with him. Mackenzie Alexander’s loss was felt, although I don’t think it was largely detrimental. Jayron Kearse can totally play well in the slot, we just weren’t scheming correctly for what GB was doing Shutting down GB the final 3 quarters tells me it wasn’t personnel that was responsible, rather calls and scheme Jayron Kearse and Eric Wilson posted highest defensive grades of the team with 90.6 and 85.4 respectively Xavier Rhodes isn’t back Hercules Mafa’ata shines Erik Kendricks puts on a clinic Baffling Offense Dalvin Cook was eating all day Josh Kline and Brian O’Neill best grades of offense line grades Garrett Bradbury again struggled Gooseeggs off Turnovers Refs were especially horrid There is never *that* much offensive PI BAAAAAAAAAAAAAD Kirk Cousins Several fumbles, interceptions WHY ARE YOU THROWING THAT? PASS LIVE TO PLAY ANOTHER DOWN JESUS EFFING CHRIST Chad Beebe is clearly WR3 at this point Fan question 3: “Why did the broadcast call beebe a speedster?”He’s shown quickness clearly with his returns, and with the splash play he had on offense turning it upfield. I don’t think he’s super fast, just squirrelly. In large part, the Vikings beat themselves. Gave up turnovers, failed on special teams, and gave up too much on defense to start the game Raiders are a team that is really really beatable, and you have to win those games to have a chance. GB isn’t a soft target, and this division WILL be the toughest in the NFL this year Oakland Predictions Learn more about your ad choices. Visit megaphone.fm/adchoices

Around the league - Recapping Cleveland v Titans, Detroit, Green Bay / Chicago, Antonio Brown Saga, Miami's quest to Tank for Tua, Seahawks struggles against the Bengals, and the Colts still rolling behind Jacoby Brissett. Vikings Defense - Anothony Barr makes an immediate impact. Anthony Harris comes out of the gate strong. Rhodes Closed for Julio Jones. Mack Alexander dislocates elbow - Status unknown. Defensive Line dominated the game with stellar games from Danille Hunter and Everson Griffen. Penalties a small downside in an otherwise impressive defensive performance. Vikings Special Teams - Kicking solid - Dan Bailey 4/4 on XPs. Blocked Punt by Eric Wilson - First since 2014. Coverage teams solid. Vikings Offense - Run blocking was spectacular, lead to a grinding game from Minnesota. Brian O'neill didn't skip a beat, and had a solid all-around game. Garrett Bradbury had a less than stellar outing, but held his ground decently in the run game. Dalvin Cook makes fast players look... not fast. Play-action roll-outs from Kirk Cousins helped mask relatively poor pass-blocking. Diggs able to have a lighter workload and rest for GB. Alexander Mattison solid in his debut, C.J. Ham great all-around game. GB Preview - Pressure v. Pressure - Can we limit GB's passrush enough? Kirk Cousins will need to throw more than 10 times, and Thielen and Diggs should have good matchups. Predictions. Learn more about your ad choices. Visit megaphone.fm/adchoices

Brian O'Neill, Gavin Sheridan explored the challenges and opportunities that digital and social media opens in our society and the growing case, across Europe, for online content regulation and controls.

In this episode: What does a typical day at Training Camp look like? “TCO is like a college campus just for football.” Offensive installation was exclusively under center for the 1st four days of practice More specialized drills on special teams. How has the offense looked? More play action. Moving the pocket. Sideline pass to Stefon Diggs has become a daily occurrence. How has the defense looked? Started slow. Dominant after Zimmer’s callout How does the offensive line look? Josh Kline has been one of the biggest surprises of training camp. “Josh Kline has been outstanding.” They’ve been getting to the second level of the defense consistently. Dalvin Cook looks great in this scheme. How has the offensive line held up in pass blocking? Pass blocking has been more of a mixed bag. Brian O’Neill has done a great job staying in front of Danielle Hunter. Ameer Abdullah stepping up in pass protection. How does our depth look? Ifeadi Odenigbo is a dark horse. Jaleel Johnson has looked good so filling in for Linval Johnson Jalyn Holmes and Hercules Mata'afa rotating and looking decent. Chad Beebe is WR3 Wide receiver depth is scary thin. Is Laquon Treadwell going to make the team? Olabisi Johnson starting to emerge. Is this the end for Kyle Sloter? How do Udoh and Samia look? Deepest tight end group in the NFL Kirk Cousins to Kyle Rudolph connection developing Irv Smith has been moved all over the formation How nervous should we be about this kicker news? Matt Wile has looked great. Field goal platoon has not been finalized. Mackensie Alexander and Jayron Kearse stepping up. Learn more about your ad choices. Visit megaphone.fm/adchoices

Good morning Horners! We thought we put out a special episode today, partly to commemorate 50 years ago, and mainly to discuss that rookies report to camp on Monday. 50 years ago today Neil Armstrong was the first man to step on the moon, also 50 years ago the Vikings entered season in which they won the NFL championship. We are going to start hearing and reading stories about the young crop of rookies, that report to camp Monday and will hopefully yield even better results than the team 50 years ago. Ed Brodmarkle of the Skoldiers Podcast joined Dave and Ted on this happy adventure. Discussions ensued over what stories do we expect to see in what Ted calls, "propaganda week?". There will be stories of course over our early draft choices, like how Garrett Bradbury is the second coming of Mick Tinglhoff, Irv Smith Jr and Alexander Mattison should make a difference, along with Dru Samia maybe winning the starting job from Josh Kline similar to how Brian O'Neill did last year, and never giving it back up. We talked about some of the rookie performances we expect, how after a summer of digesting the playbook, they hopefully wouldn't have lost much knowledge, and how having the pads on should help. We ended the show talking again about that 1969 Minnesota Vikings team, and how Joe Kapp was the villain in Super Bowl III. Ted told us of how his dad, Mr. Don Glover, had a theory that after watching the best football team and season ever played, that Joe, fighting with the Vikings over a salary and contract dispute, may have thrown the game. We all miss Don Glover, and I can just imagine him now railing as he told the story. We at Climbing The Pocket Network, your Daily Norseman vod and podcast team hope that you have a fantastic weekend, stay safe, and enjoy. Like, subscribe, and rate us on your favorite podcast aggregator. Then shout SKOL!  As always, enjoy the listen! BREAKING NEWS!!! The Daily Norseman and the Climbing The Pocket Network are joining forces to create a one-stop-shop for Vikings podcasts delivered to your eardrums daily. This collection of shows promises to deliver the top independent voices covering the Vikings from every angle. Subscribe below: Click here for iTunesClick here for StitcherClick here for iHeartRADIOClick here for YouTubeClick here for Google Play MusicYou can follow GMG hosts Dave at @Luft_Krigare and Ted at @purplebuckeye.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Brian T. O'Neill leads the acclaimed dual-ensemble, Mr. Ho's Orchestrotica and has performed at prestigious venues in the US including Carnegie Hall, the Kennedy Center, and the Montreal Jazz Festival. In addition to being a busy independent musician, Brian is also a product designer and founder of the consultancy, Designing for Analytics, which helps enterprise companies turn data into indispensable information products and services. For over 20 years, he has worked with companies including DELL/EMC, Tripadvisor, Fidelity, NetApp, MITRE, JP Morgan Chase, ETrade and numerous SAAS startups. Today Brian focuses on helping clients create more useful, usable, profitable, and engaging decision support software and information products. Brian is also an international speaker and podcast guest, having appeared at multiple O'Reilly Strata conferences, Predictive Analytics World in Berlin, and on the IBM Analytics podcast, Making Data Simple. He also authored the Designing for Analytics Self-Assessment Guide for Non-Designers, maintains an active mailing list, and hosts the new podcast, Experiencing Data. Earlier in 2018, Brian joined the International Institute for Analytics' Expert Network as an advisor on design and UX. Our conversation covers the intersection of music, data, and technology and I hope you find it as fascinating as I did! Episode Links: http://crashandboom.com http://orchestrotica.com/presskit | brian@orchestrotica.com | @orchestrotica https://www.designingforanalytics.com | brian@designingforanalytics.com | @rhythmspice https://www.designingforanalytics.com/podcast-subscribe/

On family, weight gain and the honor roll Follow the show! @LockedOnVikings Follow the host! @LukeBraunNFL Brian O’Neill: https://www.delawareonline.com/story/sports/nfl/eagles/2018/10/05/salesianum-brian-oneill-coming-home-face-eagles-vikings-rookie/1514441002/ Ifeadi Odenigbo: https://www.espn.com/blog/minnesota-vikings/post/_/id/22879/as-ifeadi-odenigbo-reached-vikings-his-nigerian-parents-adopted-football Tito Odenigbo: https://www.palmbeachpost.com/sports/college-football/get-know-the-hurricanes-two-graduate-transfers-tito-odenigbo-and-venzell-boulware/jT1KGohdlvyEXh7bjrMeuI/ Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode Adam and Tyler talk OTA's including Brian O'Neill returning, Jordan Taylor getting looks at WR3, Mike Zimmer's thoughts on the offense so far, Irv Smith Jr and Tyler Conklin creating a buzz, T.J. Clemmings new home and of course Laquon Treadwell is mentioned. The boys also talk with The Draft Network's Jordan Reid about favorite players growing up and the state of the Vikings heading into 2019.

Design. User Experience. Knowing your audience. Empathising with your end user. These are such critical facets of getting analytics right in your organization. Brian O'Neill knows a little bit about this. He is a product designer and founder of the consultancy, Designing for Analytics, which provides design and UX consulting for custom enterprise data products and apps. For over 20 years, he has worked with companies including DELL/EMC, Tripadvisor, Fidelity, JP Morgan Chase, and many others. Today Brian focuses on helping clients create more useful, usable, profitable, and engaging decision support software and information products.

What are some of the most ridiculous song requests we've received? What are some of our favorite venues to play? What venues do we miss that have closed? What guitars does Patrick use? Will we ever hear Blaggards on vinyl? Show notes The coffee mug that Chad uses during this episode (https://amzn.to/2IRFhfI) Blaggards at Brian O'Neill's, 2005 (https://www.flickr.com/photos/microknee/albums/72057594107532099/with/128255993/) (featuring Patrick's Parker Fly guitar) Blaggards at Brian O'Neill's, 2006 (https://www.flickr.com/photos/microknee/albums/72057594107525163) (featuring Patrick's Gibson Les Paul guitar) The Continental Club Houston (https://continentalclub.com/houston) Beebe Gunn Studio (https://beebegunnstudio.com) O'Bannon's Taphouse (https://www.obannonstaphouse.com) (College Station, TX) Ashford Pub (http://www.ashfordpub.com) (Houston, TX) Stuttgarden Tavern on the Strand (https://stuttgardentavern.com/galveston-info) (Galveston, TX) Rochester Jazz Festival (https://www.rochesterjazz.com) (Rochester, NY) Hometown Holidays Music Fest (https://www.rockvillemd.gov/665/Hometown-Holidays) (Rockville, MD) O'Malley's & Weston Brewing Company (https://westonirish.com/omalleys-1842-pub-weston-mo/) (Weston, MO) Sherman Celtic Festival (https://www.shermancelticfest.com) (Sherman, TX) Blaggards at Fadó Irish Pub - Austin, 2006 (https://www.flickr.com/photos/microknee/albums/72057594108155073) Diamond Guitars (https://www.diamondguitars.com) Bill Thomas Guitars (https://www.bthomasguitars.com) Join us in IRELAND this Fall Ireland 2019 - Are you in? (https://blaggards.com/2019/02/ireland-october-2019-are-you-in/) Ireland tour pricing and itinerary (PDF) (https://blaggards.com/blog/wp-content/uploads/blaggards-irelandtour-2019.pdf) Sign up for the Ireland tour online (https://www.hammondtours.com/product/blaggards/) Show dates Blaggards.com (https://blaggards.com/shows/) Facebook (https://www.facebook.com/pg/blaggards/events/) Bandsintown (https://www.bandsintown.com/a/3808) Follow us Facebook (https://www.facebook.com/blaggards/) Twitter (https://twitter.com/blaggards) Instagram (https://www.instagram.com/blaggards/) Become a Patron Join Blaggards on Patreon (https://www.patreon.com/blaggards) for bonus podcast content, live tracks, rough mixes, and other exclusives. Rate us Rate and review SlapperCast on iTunes (https://itunes.apple.com/us/podcast/slappercast-a-weekly-talk-show-with-blaggards/id1452061331) Questions? If you have questions for a future Q&A episode, * leave a comment on Patreon (https://www.patreon.com/blaggards), or * tweet them to us (https://twitter.com/blaggards) with the hashtag #slappercast.

This week Facebook chief executive Mark Zuckerberg travelled to Dublin to meet with TDs to discuss issues such as the spread of misinformation, child protection and future government policies. But when it comes to the regulation of social media giants, such as Facebook, are they publishers or just a public square? Joining Andrea Gilligan in studio to discuss was: Brian O'Neill, Director of Research at TU Dublin Hildegarde Naughton, Fine Gael Senator and Chair of Oireachtas Communications Committee Adrian Weckler, Technology editor at the Irish & Sunday Independent

Customer experience AI has been buzzed about for years, but with little to show for it. That’s finally starting to change, with massive growth in personalization, automation, and more. But how do you SELL AI and automation? And more importantly, how do you introduce it to an existing product line? We interviewed Brian O’Neill of Monetate, a company that’s grown from marketing analytics to full-on AI-enabled customer experience personalization. As Monetate’s CTO, he’s overseen the company's technical strategy and growth, and had a front row seat to major shifts in technology, positioning, and value proposition. Learn more about Monetate over at their website. Produced by Martin R. Schneider. Music by Prox-C and KieLoKaz. 

Good morning Horners! The guys are back and ready to start the 2019 league year. After a couple months of stewing in the disappointment that was the 2018 season, Ted Glover, Drew Bunting, and Dave Stefano return to discuss the state of the Minnesota Vikings. They look at the timeline that ran up to selecting John DeFilippo and Kirk Cousins. The flaws in the decision making of selecting an offensive coordinator that was going to implement a style of offense not conducive to neither the quarterback not the group of offensive linemen that had to block for him, and ask why? The Vikes have since hired the “Denver Mafia” lead by Gary Kubiak and including Rick Dennison. The whole group of new coaches will reportedly be focusing on implementing a more traditional West Coast Offense style of play that is said to be better suited to Kirk Cousins skills and a zone blocking scheme that should help in his protection and in the run game. Mike Zimmer in effect gets to get his guy who can mentor the Kevin Stefanski in the offensive coordinator role and ensure the offense is more productive while he can focus on the defense and the necessary future players needed to fill holes of departing free agents, cuts and trades. The team will see quite a few new faces due to having to clear money to gain cap space. OTC reports the Vikings are sitting $5,340,897 available and that isn’t even enough to sign the rookie class. There is still need money for veteran free agents and eventually the practice squad to cover for the up and coming season. This means so veterans of the squad last year will have to be let go one way or another. With the Vikings not tagging Anthony Barr in any way, just gives you one example of needs that will have to be addressed in some fashion. On signing free agents, the Vikings have already started with in-house guys fullback CJ Ham and punter Matt Wile, signing them to veteran minimum deals. With the offensive line being a factor of last season’s dismal results, the focus will be needed either through free agency, the draft, or both to shore it up. Last year’s rookie Brian O’Neill proved to be a bright spot, but he will have to be combined with 4 other guys in a more mobile system geared to take advantage of their skills. Mike Remmers looks to be a cap casualty, and a logical choice to free up some funds, but his right guard position will have to be filled. Pat Elflein should look forward to a full offseason of strengthening and his level of play improving to where fans thought it would be after his rookie season. The Riley Reiff will sit as the left tackle, for now, with the only questions being in the guard spots. That could change however depending on what is available to the Vikings in the draft and what shuffling of players coach Dennison decides to work best. The NFL Combine is complete, free agency nears, and the draft will follow shortly after that. The guys at GMG hope you join in the laughs, the debate, and the hopes that come with being Minnesota Vikings fans. Tell us what you are hoping to see in the next month as the beloved Purple makes another run at getting better. Like, subscribe, and ring that damn bell! Then shout SKOL! As always, enjoy the watch! Learn more about your ad choices. Visit megaphone.fm/adchoices

We’re back with a special music-related analytics episode! Following Next Big Sound’s acquisition by Pandora, Julien Benatar moved from engineering into product management and is now responsible for the company’s analytics applications in the Creator Tools division. He and his team of engineers, data scientists and designers provide insights on how artists are performing on Pandora and how they can effectively grow their audience. This was a particularly fun interview for me since I have music playing on Pandora and occasionally use Next Big Sound’s analytics myself. Julien and I discussed: How Julien’s team accounts for designing for a huge range of customers (artists) that have wildly different popularity, song plays, and followers How the service generates benchmark values in order to make analytics more useful to artists How email notifications can be useful or counter-productive in analytics services How Julien thinks about the Data Pyramid when building out their platform Having a “North Star” and driving analytics toward customer action The types of predictive analytics Next Big Sound is doing Resources and Links: Julien Benatar on Twitter Next Big Sound website Next Big Sound blog The Data Pyramid model Quotes from Julien Benatar "I really hope we get to a point where people don’t need to be data analysts to look at data." "People don’t just want to look at numbers anymore, they want to be able to use numbers to make decisions." "One of our goals was to basically check every artist in the world and give them access to these tools and by checking millions of artists, it allows us to do some very good and very specific benchmarks" “The way it works is you can thumb up or thumb down songs. If you thumb up a song, you’re giving us a signal that this is something that you like and something you want to listen to more. That’s data that we give back to artists.” “I think the great thing today is that, compared to when Next Big Sound started in 2009, we don’t need to make a point for people to care about data. Everyone cares about data today.” Episode Transcript Brian: I’m really excited today for this episode. We have Julien Benatar on the show and he’s from a company that I’m sure a lot of people here know. You probably have had headphones on at your desk, at home, or wherever you are listening to Pandora for music. Julien , correct me if I’m wrong, you were the product manager for artist tools and insights at Next Big Sound, which is a type of data product that provides information on music listening stats to, I assume, artists’ labels as well to help them understand where their fans are and social media engagement. I love this topic. I’m also a musician, I have a profile on Next Big Sound and I feel music’s a fun way to talk about analytics and design as well because everybody can relate to the content and the domain. Welcome to the show. Did I get all that correct? Julien: Yeah, it was perfect. Brian: Cool. Tell us a little about your background. You’re from France originally? Julien: Yes, exactly. I grew up next to Paris, in Versailles more specifically, and moved to New York in 2014 to join Next Big Sound. Brian: Cool, nice. You’ve been there for about four years, something like that. You have a software engineering background and then now you’re on the product side, is that right? Julien: Exactly yes. I joined the company back when we were a startup. Software engineering was perfect, there was so much to do. To our move to Pandora, I moved to a product manager role around a year ago. Brian: Next Big Sound was independent and then they were acquired by Pandora. I assume there is good stuff about your data. Why did Pandora acquire you and how did they see you guys improving their service? Julien: We got acquired in 2015. The thing is, Next Big Sound was already really involved in the music industry. We already had clients like the three major labels and a lot of artists were using us to get access to their social data. I think it was a very natural move for Pandora as they wanted to get closer to creators and provide better analytics tools. Brian: For people that aren’t on the service, I always like to know who are the actual end users, the people logging in, not necessarily the management, but who sits down and what are some of the things that they would do? Who would log in to Next Big Sound and why? Julien: Honestly, it’s really anyone having any involvement into the music industry, so that can be an artist, obviously, try looking to try their socials and their audience on Pandora. But you can also be a booker trying to book artists in their town. We have a product that can really be used by many different user personas. But our core right now is really artists and labels, having contents on Pandora and trying to tell them the most compelling story about what they’re doing on the platform. Brian: When you think about designs, it’s hard to design and we talk about this on the mailing list sometimes but it’s really hard to design one great thing that’s perfect for everybody so usually you have to make some choices. Do you guys favor the artist, or the label, or as you call them,the bookers or whom I know as presenters,in the performing arts industry? Do you have a sweet spot, like you favor one of those in terms of experience? Julien: I think it’s something we’re moving towards, but it hasn’t always been this way. Like I told you, we used to be a startup or grow us to make a product that could work for as many people as possible. What is funny is we used to have an entity on Next Big Sound called Next Big Book where we used to provide the same type of service for the book industry. If anything, it’s been great to join Pandora because then we could really refocus on creators and it really allowed us to, I believe, create much better and more targeted analytics tools to really fulfill needs for specific people like artists and labels. Brian: I would assume individual artists are your biggest audience or is it really heavily used by the labels or who tends to... Julien: I think it’s pretty much the same honestly. I think the great thing today is that, compared to when Next Big Sound started in 2009, we don’t need to make a point for people to care about data. Everyone cares about data today. I think that everyone has reasons to look at their dashboards and especially for a platform like Pandora with millions of users every month. Our goal is really just telling them a story about what does it mean to be spinning on the platform and the opportunities it opens. Brian: You talked about opportunities, do you have any stories about a particular artist or a label that may have learned something from your data and maybe they wrote to you or you found out like in an interview how they reacted like, “Hey, we changed our tool routing,” or, “Hey, we decided to focus on this area instead of that area.” Do you know anything about how it’s been put into use in the wild? Julien: Yeah, it’s used for so many different reasons. For the people who don’t use Pandora, something I really like about the platform is it’s really about quality. As you use Pandora, you have the opportunity to thumb up or thumb down songs and as you do, you’re going to get recommended more songs like the ones you like. It’s really about making sure that you get the best songs at all times. The reality then is that for artists, their top songs on Pandora can be pretty different than their top songs on other platforms because sometimes their friends are going to be just reacting more to some part of their catalog than another one. I’ve heard many times of artists changing their playlists in looking at which songs where their fans thumbing up the most on Pandora. Brian: Could you go through that again? How would they adjust their playlist? Julien: Usually, people use Pandora as a radio service. While we already have internet today, most people are listening to the radio because they’re usually are very targeted and it just works really well. The way it works is you can thumb up or thumb down songs. If you thumb up a song, you’re giving us a signal that this is something that you like and something you want to listen to more. That’s data that we give back to artists. We tell them, “This are your most thumbed songs on Pandora. These are the songs that people engage with the most on the platform.” Looking at this data, you can actually inform them songs that they believe they should be playing more on the store. Brian: I see. A lot of it has to do with the favoriting aspect to give them idea what’s resonating with their audiences. Julien: Qualitative feedback, yes. Brian: Got it. Actually, it’s funny you mentioned the qualitative feedback. In preparation for this, I was reading an article that you guys put out back in March about a new feature called weekly performance insights, which is really cool and this actually reminds me of something that I talked about in the Designing for Analytics mailing list, which is the act of providing qualitative guides with your analytics. A lot of times they analyze for turnout quantitative data and whenever there’s an opportunity to put stuff into context or provide qualifiers, I think that’s a really good thing and you guys look like you’ve have done some really nice things here. I’ll paraphrase it and then you can jump in and maybe give us some backstory on it. One of the things that I think is really cool is there're concepts of normalcy in here so that, if I’m an artist and I look at my numbers, I have an idea. For your Twitter mentions, for example, you say, “For artists with 26,000 followers, we expect you to get around 44 mentions.” When you show me that I have 146 mentions, I can tell that I’m substantially higher than what my social group would be. I think that’s a really fantastic concept that people not in music could try to apply as well which is, are there normalcy bans where you’d want to sit? Is there some other type of group, maybe, an industry, or apparent group, or another business unit, whatever it may be to provide some context for what these out of the blue numbers mean that don’t have any context? How did you guys come up with that and can you tell us a bit about the design process of going from maybe just showing, “You’re at 826 apples,” as compared to what? How did you move from just a number into this these kind of logical groupings where you provide the comparisons? Julien: I think what’s really fascinating is, we really live in an age of data. As an artist, you need to be on social media for the most part. There still a lot of artists I listen to but just decide not to. It’s part of things but at the same time, real big success in the music industry didn’t change. It’s still being on the Billboard chart, getting a Grammy and all these things. But as we see this, we have millions of artists looking at their data every day and just are not able to understand, like is it good or is it not good. Everyone starts at zero. We have a strong belief that data can only be useful when put in context. Looking at the number on its own can give you a sense of how things are doing but that can also be dismissive. An example is, a very common way to look at data is to look at a number and look at the percent changing comparison to the previous week. You’ve got a bunch of tables and you look at, am I growing or am I not growing. The reality is it’s actually impossible to always have a positive percent change. There’s no artist in the world that always does better week by week. Even Beyonce, I can assure you that the week she released Lemonade, she had more engagement on Twitter than the week after. With that in mind, we really try to give a way for artists to understand how are they doing for who they are and where they are currently in their career. Next Big Sound started in 2009. One of our goals was to basically check every artist in the world and give them access to these tools and by checking millions of artists, it allows us to do some very good and very specific benchmarks. For an artist, like the example you said, for instance an artist with a thousand Twitter mentions in a week, is it good or bad in comparison to their audience size? This feature comes because that’s just the question we’re asked. Artists want to know is it any good? What does this number actually mean for me? That’s why we really wanted to, in some ways, get out of being a content aggregator platform and really be a data analytics platform. How can we actually give information that can help artist make better decisions? Brian: I remember the first time I got what I would call an anomaly detection email from your service and it was about some spike in YouTube views or something like that. I thought it’s fantastic in two reasons. First of all, you identify an anomalous change and I think in this case it’s a positive anomalous change. That tells me that I should log in the tool. Secondly, you proactively delivered that to me. On the Designing for Analytics mailing list, we talk about is that user experience does not necessarily live inside your web browser interface or your hard client or whatever you’re using to show your analytics. Email and notifications are a big part of that. Can you tell me about how you guys also arrived at when you pushed these things out and maybe talk about this little anomaly detection service that you have? Julien: It all started when we got acquired by Pandora. We decided to just invite a bunch of users and just talk to them, understand how to use our product and what did they think about it. We had artists, managers, and label people come over and we just talk to them and basically they all said, “We love it.” But then, by looking at their actual usage, they don’t use it that much. I guess one of their questions was when should I be looking at my data? Everyone is very busy. As you’re an artist, you need to perform, you need to write music, you need to engage with your fans and same goes with everyone. When should I look at data? The reality is by being a data company, we do get all the data, we have all the numbers. We have ways to know when things are supposed to be known, when artists should be acting on something. We just turn this into this email notifications. Anytime we notice that an artist is doing better than expected, we just let them know right away. Brian: That’s great. Do you do it on the opposite end too? If there’s an unexpected drop or maybe like, “Oh, you put a new track out and your socials dropped,” or something like that, do you look at the negative side too or do you tend to only promote the positive changes? Julien: As far as pushes, we decided to only do push for positive. But as you mentioned weekly performance, weekly performance can give you some negative insights, like, “You’re not doing as well as artists with the same size of audience as yours.” The reason we didn’t do it for our notification is, anomalies are really hard to completely control. A reason, for instance, is Twitter removing bots. Basically, every single artist would have had an email telling them, “You lost Twitter followers this week.” It was a lot of work to really tune our anomaly factor to actually only send emails when something legitimate happens. That’s the reason we only decided so far to do it for positive but we actually have been thinking about doing the same for negative but that’s another type of work. Brian: Yeah, you’re right. You have to mature these things over time. You don’t want to be a noise generator. Julien: Exactly. Brian: Too many, then people start to ignore you. I’ve seen that with other data products I’ve worked on which just have really dumb alerting mechanisms that are very binary or they’re set at a hard threshold and just shootout noise and people just tune it out. Julien: I’m glad you mentioned this because this feature was in beta for a year for that specific reason. Brian: Got it. Julien: We had to learn the hard way. We had like a hundred beta users. We’ve got way too many emails because anytime there were an anomaly anywhere, they would just get an email. For the most part, it was things that were supposed to help them. If a notification becomes noise, then that’s absolutely against its purpose. Brian: I don’t know if everybody knows how the music business works, at least from the popular music side, but just to summarize. You have individual artists that are actually performers. They may or may not have an artist manager which takes care of their business affairs, represents them like negotiations with people that book shows. Then you have labels which are sort of like an artist manager except they’re really focused on the recording assets that the artist makes and they actually tend to own the recordings outright at the beginning and then over time, the artist may recoup through sales they make it the ownership act and the sound recordings they make. Of those kinds of three major groups, is there a one that’s particularly hungry or you’re the squeaky wheel that is most interested in what you’re doing? Julien: I really think that into these three groups, we have a subset of users that are really into the data and into the actionability of it. I don’t think it’s one specific group of user. It could be all around the industry like we have the data-savvy, they really want to know. We have some users that actually would rather get more notifications even if they need to on their end to figure what is right from what is wrong. But since we have such a wide user base of different type of people, we decided to go on the conservative side and make sure to only share things that we thoroughly validated through all of our filters. Brian: I assume that your group reports into some division of Pandora, I’m not sure of that. Are you reporting into a technology, like an IT, or a business unit, or marketing? Where do you guys fit in the Pandora world? Julien: We’re part of the creator’s tools. I don’t really have a perfect answer to this. Brian: Okay. I guess my main question being, because when we talk about designing services, we talk about both user experience, which is the end user thing and about business success or organization success. I’m curious, how does Pandora measure that Next Big Sound as delivering value? I can understand, I’m sure our artist can understand how the artists value it through understanding how is my music moving my audiences, et cetera. Is there a way that Pandora looks at it? Are they interested in just time spent? The analytics on the analytics, so to speak, is what I’m asking about. How do you guys look at it like, “Hey, this is really doing a good job,” or whatever? Do you know how that’s looked at? Julien: To be honest, I think you said it right. Our goal is to help artists make their decisions through data and having artists use the platform is currently the way Pandora sees us doing a good job. Actually, it hasn’t changed that much since our acquisition. One of our main KPI for the past and couple of years is something I would call insights consumes. Just making sure that our users, artists, anyone using Next Big Sound are consuming data. That can be them logging into the website or that can be them opening one of our notifications. But so far that was our main KPI. We’re trying to work on some more targeted KPI, potentially like actions taken, that would be the North Star, but we're still working on how to do that right. Brian: Do you guys facilitate actions, so to speak, directly in the tool or are there things people can do with those actions really take place outside of the context of Next Big Sound? Julien: There are actions that artists can take to the other creator’s tools provided by Pandora. For instance, artists have the ability to send audio messages to anyone listening to them. If they go on tour into the US, they can have targeted messages in every single song they’re going to play. If anyone listens to them there, they can just click and buy a ticket. We’re working to make sure that artists are aware of these tools because they are free and they’re generally helping them grow at their careers. But regarding external actions, so far we don’t have any one-click way to tweet at the right time to the right people or with the right content or anything like this. Brian: Sure and that’s understood. Not every analytics product is going to have a direct actionable insight that comes right out of it. You guys may be feeling a longer term picture about trending and maybe for a certain artist to get an idea if they’re releasing music fairly frequently, what stuff is working and resonating, and what stuff is not. I can understand that. There may not be a button to click as a result immediately. Julien: That’s the goal though. Everything we do right now is going towards this objective. Maybe I can tell you a little about the way we think about data and that can give more sense to it. In order to work on any new feature, we follow this concept called the data pyramid. It’s something that you can Google. There’s a Wikipedia page for it. Let me explain to you how it works. The data pyramid, it’s a pyramid formed of four layers. It could be upon each other and each representing an exquisitely useful application of data. At the bottom of the pyramid we have the data layer. Any sort of data that we may have. For our case, Android data, Twitter, Facebook just getting the numbers, getting the raw data. On top of it, we have the information layer. The information layer is going to be ways you have to visualize this data. I guess it’s like the very broad sense of analytics. We’re going to give you tables, graphs, pie charts, you name it. We’re giving you ways to craft stories about this data but it’s on you to figure it out. Then on top of it we have what we call the knowledge layer. That’s where things start to get interesting. The knowledge layer is the contextual part of it. It’s like, “What do this number actually mean?” It has industry expertise. For instance, the way we’re going to work about it for musicians and their true data may be different than any other industry. The knowledge layer goes like a weekly performance. It’s a perfect answer to it. It’s what does it mean for me as a musician with a hundred fans to get two mentions this week. Same for notifications. It’s telling you that you should be looking at your data right now because something is happening. That’s how we get to the North Star and the last part of the data pyramid which is intelligence. The goal of intelligence is actionability. Now that I get to understand what does this number mean to the specific context, what should I be doing? Following your question, everything we’re trying to do here is to get to a point where we can just send an email to an artist and tell them, “Hey, you should be doing this right now because, with all the data that we have, we believe that this is going to have the highest impact for you.” Brian: It‘s really fascinating that you just outlined this data pyramid. I actually haven’t heard of this before. It made me think of one of the kind of, it’s not a joke but in the music community, I’m also a composer and when we write stuff, the kind of running joke is like nothing is new. Your ideas for this new song or this new melody I’m composing, it probably came before you. You heard it there before. I wrote a post on my list that was pretty much exactly the same thing except the knowledge layer. I was calling that insight. Data have been this raw format and information being the first human-readable format that’s like say going from raw data to a chart, a histogram. Now I have a line on a chart and then the insight layer being, I have a line on the chart and another line comparing it to like you said, average, or my social group, or a parent group, or some taxonomy, or an index. Then the action or the prescription for what to do or the prediction those that kind of lead you in about action which would be that fourth state. You’re like, “Oh, is this really a new concept?” It’s like, “Nope. Someone else already thought of that.” I totally want to go read about this data pyramid. Julien: That’s amazing. Brian: I’ll find that link to the data pyramid and I’ll put that in the show notes for sure. I thought that was really funny. Julien: It’s funny that you called it insight because that’s the way we call a lot of our features are working out. The way we define insight is bite-size, noteworthy, sharable content. How can we get into the noise of all of the data that only gives you exactly what you should be looking at. That’s how we got into notification and weekly performances. This is the one thing you should be looking at. Brian: I understand what you’re getting at there. The insights are, like you said, bite-size chunks of interesting stats that someone can put some kind of context around. That’s great and it’s good. One of the things I liked, too, that you talked about was you said, “Oh we got like a hundred users, like a beta group and that kind of inspired some of this.” Your product response to how do we help people know when to come and look at our service. I think this is really good because one of the problems that I see with clients and people on the list, I think is low engagement. This is especially true for internal analytics companies. Low engagement can be a symptom of a difficult product, it doesn’t provide the right information at the right time, it may not have a lot of utility, or it’s a resistance to change. People have done something the old way and they don't want to do it the new way. One of the recipes you can follow if you’re trying to do a redesign or increase engagement is to involve the people that are going to use the service in the design process, both the stakeholders as well as the end customers. This is especially true again for the internal analytics people. Your customers or other employees and your colleagues. By engaging them in the design process, they’re much more likely to want to change whatever they’re doing now. I loved how you guys did some research. Now I want to ask, do you frequently do either usability testing or interviews? Is that an ongoing thing at your company or is it really just in front of a big feature release or something like that? How do you guys do this research? Can you tell me about that? Julien: Of course. It’s consent. We haven’t released any major feature without doing some heavy user testing. I’m very lucky to be working with two designers, Justin and Anabelle who are very user-focused. Honestly, if you come to our office, at least every week we’re going to have some user interview and just talking to them, showing them prototypes, and just see how do they play with it. Brian: So you’re doing a lot of testing it sounds like. That’s fantastic. Julien: At the same time it’s always to find the right balance because you could be overtesting things too. We really are focusing on user testing for new things and make sure that the future that we are working on actually answers their user story that we intended. Brian: I don’t know how involved you get participating in these, but do you have any interesting stories or anecdotes that you got from one of those that you could share? Julien: Let me think. I do participate into a lot of them but I’m not sure I have an example right now. Brian: Are most of the people you interview, are they current users of Next Big Sound or do you tend to focus on maybe artists that haven’t experienced the service yet or you mix it up? Julien: We mix it up. We mostly engage with users that we already have but then we can decide to go with users that haven’t used the platform for a while, or more active users if you want to understand how we’re useful into their day to day. What I would say is that, surprisingly, it’s very easy to get users to chat about their experience with the product. I didn’t assume that we would get so many responses when we tried to have people come over or just hop on the zoom to check a new feature. Brian: I’m glad you actually mentioned that because I think in some places, recruiting is perceived to be difficult and it probably isn’t. Maybe you haven’t done it before but as I tell a lot of my clients, a lot of people love to have someone listen to them talk, tell them all about their life and what’s wrong with it, and how it could be better with their tools. They love having someone listen to them and especially if they know that their feedback is going to influence a tool or a service that they’re using. They tend to be pretty engaged with it. I find it’s really rare that I do an interview with a client’s customer and they don’t want to be included in the future round like, “Hey, when we redesign the service, can we come back to you and show you what we’ve done?” “Oh, I love to do that!” Everybody wants to get engaged with it. There are places where recruiting can be difficult when it’s hard to access the users, some of the enterprise software space that can be an issue sometimes. But generally, if you can get access to them, they tend to be pretty willing to participate. I’m glad you mentioned that. Julien: I think the great part about testing with current users on the platform is to actually show them prototypes with real data, not just show them an abstract idea that we want to work on. As soon as they can see what we’re working on apply to their own career as musicians, for instance, that can lead to fascinating discussions. Brian: You made a really good point on the real data thing. I remember as far back as 10 years ago or whenever, I use to work at Fidelity Investments, we would see this issue when we’re working on the retail site for investors. When you show a portfolio that, for example, has Apple stock trading at $22 in it, you’re not really there to test what is the price of Apple stock but you might be testing something entirely different and the customer cannot bear what is going on? They’re so stuck on this thing. It’s all fake seed data in the prototype. The story here being if you’re a listener, when you test it’s important to have at least realistic data. You don’t want to have noise in the test or whatever your studying or else you can end up on this tangent. Try to make the numbers looks somewhat realistic if you’re using quantitative data. In some cases, people can be taught to roleplay. Pretend you’re Drake or pretend you’re some big artist and then they can get their head around why they have billions of streams instead of thousands which they’re used to. Julien: Absolutely. That also helps us just build better products because the reality is we have a lot of artists with maybe 10 plays in a month. As we build visualizations like something that we built a line of looking at Drake’s data, it’s not going to work as intended for a smaller artist sometimes. Having real data involved as soon as possible into the design process has been such a game changer for us. We really have a multidisciplinary team involved into the research and design of everything we do. I’m working with a data scientist, data engineer, a web engineer, and designer on a daily basis. Obviously, we all have our things to do. But as we get into creating something new, we just make sure to have someone helping us get the real data, interview the right user, and just create prototypes as soon as possible. Working with prototypes is essential into building useful data analytics tools. Brian: Yes, you do learn a lot more with a working prototype. It’s not to say you can’t test with lower fidelity goods, especially early on but for a service like yours when the range of possible use both the personas and also you’ve got the Drakes of the world, big major label artist and then down to really small independents, it’s really important to have an idea how your charts are going to scale, and what’s going to happen with data. Even just small stuff like how many decimal points should you be showing on a mobile device, some of the numbers might cram up. Julien: Exactly. Brian: All this stuff that you never think, if you only look at one version of everything, you can end up with a mess. I’m glad that you brought that up. Julien: I couldn’t say better. The decimal is actually something that we’ve had to discover through real data. Brian: To all of you in the technical people out there, I will say this. If I’ve seen one trend with engineers, is they love precision and there’s a lot of times when there’s very unnecessary precision being added to numbers. Such as charts and histograms. Histograms are usually about the trend, they’re not about identifying what was the precise value on this date at this time. It’s about the change over time. Showing what’s my portfolio worth down to three digits of micro-cents or something like that is just unnecessary detail. You can probably just round up to the dollar or even hundreds of dollars or even thousands of dollars in some cases. It actually is worse. The reason it’s worse is that adds unnecessary noise to the interface, you’re providing all these inks that someone has to mentally process, and it’s actually not really meaningful ink because the change is what’s important. Think about precision when you’re printing values. Julien: This concept of noise is so essential today for any data analytics tools. There is so much data today. There is data for everything. I think it’s our responsibility as a data analytics company to make sure what are we actually trying to help our user with this data set is not just about adding new metrics. Adding new metrics usually is just going to add noise and not be helpful in comparison to fairing what do they need to make the right decision. Brian: Right. Complexity obviously goes up. The single verb, ‘add,’ as soon as you do that, you’re generally adding complexity. One of the design tools that is not used a lot, and this is something I try to help clients with is, what can we take away? If we're not going to cut it out entirely, can we move this feature, maybe this comparison to a different level of detail? Maybe it’s hidden behind a button click, or it’s not the default. But removing some stuff is a way to obviously simplify as well, especially if you do need to add new things. Your only weapon is not the pencil, you’ve got the eraser as well in the battle so to speak. Julien: I couldn’t agree more. On Next Big Sound we have this concept of artist stages. It’s a way for us to put artist into buckets and by looking at their social instrument data. It goes from undiscovered to epic. We do that by looking at all of the data we have and looking at it in context. I don’t have the numbers right now because they update on a daily basis but every artist starts undiscovered. For instance, as they get 1000 Facebook likes, maybe they’re going to get to a promising stage. We have all of these thresholds moving everyday looking at trends among social services. But what is interesting is that for instance, for a booker, a booker doesn’t need to look at the exact number of Twitter followers for an artist. He needs to know that he’s booking for a midsized venue in the city he’s in and he’s probably going to be looking for promising to established artists and not looking for the mainstream to epic artists. It’s always about figuring a way to use the numbers to tell the story. Brian: I’m totally selfishly asking for myself here, but I was immediately curious. I live in Cambridge which is in the Boston area, and I am curious who are the big artists in our area and what is the concentration? I’m in a niche. I’m more in the performing arts market, in the jazz, in world music, and classical music but I’m just curious. Is there a way to look at it by the city and know what your artist community looks like? You guys do anything like that? Julien: We don’t currently. But I think YouTube has actually a C-level chart available. It’s not part of something we do because I think the users it would benefit are not the users we specifically try to work on new features. It’s more something for bookers than artists ,specifically ,but it’s exactly the type of thing that we need to think about when we prioritize new features. Brian: I’m curious just because the topic’s fairly hot. Everybody is trying to do machine learning projects these days. I don’t like the term AI because it tends to be a little bit overloaded but are you guys using machine learning to accomplish any particular problems or add any new value to your service right now? Is that on your horizon? Julien: How do you think about machine learning? Brian: A lot of times I associate it with predictive analytics or understanding where you might be running instead of just using statistics. I don’t know what kind of data you might have for your learning that you can feed in but maybe there’s aspects about artists that can predict. Especially, I would think like in the pop music world where there tends to be more commercialization of the music, I would say, where it’s like we need a two-minute dance track at this tempo specifically because DJs are going to play it. It’s a very commercial thing. It’s very different than what I’m used to. So I’m curious if there’s a way to predict out how an artist may do or what kinds of tracks are performing well. Like these tempo songs, we predict over the next six months that tech house music at 160 beats for a minute is going to do really well based on the trending. I don’t know. I’m throwing stuff out there. The goal, obviously, is not to try to use like, “Oh Home Depot has this new hammer, let’s run out and get it. We don’t even know what it’s for but everyone else is buying it.” That’s how I joke about machine learning. It’s like you need to have a problem that necessitates that particular tool. I don’t ask such that, “Oh there should be some.” I’m more curious as to whether or not it’s a tool that you guys are leveraging at this time. Julien: The Next Big Sound team doesn’t worked on features following the musical aspects of things. We really are focused on the user data. Brian: Engagement and social. Julien: Engagement data mostly, yes. But at the same time, I’m sure teams have worked on this because of the way that genome works. We have a lot of data about the way songs are made. Regarding machine learning, on the Next Big Song team, we actually have something that is called the prediction chart. You said predictions. We have this chart that is available every week. Basically, it really goes back to having data for a long time. The fact that we’ve had data since 2009, we’ve been able to see artists actually get from starting to charting on the Billboard 200. By having all of these data, we’ve been able to see some trends, some things that usually happen for artists at specific times in their career up until they get into the Billboard 200. We actually do have some algorithms that allow us to apply this learning to all of the artists on Next Big Sound right now and have a list every week of artist that we believe are most likely to appear on the Billboard 200 chart next year. Brian: I see. Got it. Do you track your accuracy rate on that internally and change it over time? Do you adjust the model? Julien: Yeah, we do. Brian: Cool That’s really neat. Tell me, this chat has been super fun. I’ve selfishly got a little indulgent because being a musician, it’s fun to talk about these two worlds that I’m really passionate about so I could go on forever with you about this. But I’m curious. Do you have any advice for other product managers or analytics practitioners about how to design good data products and services? How to make either your own organization happy or your customers happy? Do you have any advice to them? Julien: Yeah, of course. I guess it’s all about asking questions, honestly. What is very good with working at Next Big Sound is that it all started in 2009. Maybe actually I can go back and tell you the story about how it started and why it’s so different today. It started in 2009. It was actually a project, a university project by the three co-founders. Basically, they were wondering about one thing. How many plays does a major artist get on the biggest music platform in the world? At that time, it was MySpace. The artist they picked was Akon. Basically, they just built a crawler, went to bed, woke up, and discovered that an artist like Akon was getting 500,000 plays on MySpace in one night in 2009. The challenge in 2009 was to get the data. That’s why for the most part in Next Big Sound as it started was, I really think a data aggregation tool. Our goal was to get as many sources as possible and just make them easily accessible into the same place. We really are much into the information layer here. We’re giving you all the numbers and you can compare Tumblr to Vimeo, to YouTube, to Twitter, to Facebook, to Vine, to you name it into a table or a graph that you want to. The reality is, today things change. We don't need to fight to get data anymore. We don’t need to hike our way into getting the numbers. Now, data is accessible to everyone in a very easy way. It’s kind of a contract. You, by being an artist, you know you’re going to get access to your Spotify, YouTube, Pandora, Apple Music or any other platform data very easily just by signing up and authenticating as an artist. That’s where our goal changes. Thankfully, we don’t need to convince people to care about data, we know they do already. But now the challenge is different. Now, the challenge is to make them understand what does their data mean and how can they turn it into getting even more data, getting into having even more engagement, and having even more plays. I think that’s something that is very interesting because it really resonates into the question we’ve been asked in the past few years like, “What does my data mean and when should I be looking at my data?” If anything, these two things correlated pretty well. People don’t just want to look at numbers anymore, they want to be able to use numbers to make decisions. That’s the core of what we’re trying to achieve today. We couldn’t be there if we didn’t have users that ask us the right questions. Brian: Cool that’s really insightful. Just to maybe tie it off at the end and maybe you can’t share this but what’s your home run? What is your holy grail look like? Is there a place you guys know you want to get? Maybe it’s the lack of data or you don’t have access to the data in order to provide that service. Do you guys have kind of a picture of where it is you want to take the service? Julien: What is very noble about our goal at Next Big Sound specifically is we’re here to help artists. The North Star would be to make sure that any artist at any time in their career is doing everything they can do to play more shows, to reach to more people, and to make sure their music is heard. Brian: Nice. I guess it’s like you’re already there, just maybe the level of quality and improving that experience over time, that’s your goal. It’s not so much that there’s so much unobtainable thing at this moment. Is that kind of how you see it? Julien: I think the more we don’t feel just a data analytics tool, the more we’re getting to that goal. I really hope we get to a point where people don’t need to be data analysts to look at data. We’re always going to provide a very customizable tool for the data-savvy because they know what they need more than we can ever do it for them. We want to make sure that for everyone else, we can just make it very easy and as simple as a click for them to do something that’s going to impact them positively. Brian: Cool, man. This has been really exciting to have you on the show. Julien, can you tell the listeners where can they find you on the interwebs? Are you on Twitter or LinkedIn? How do they find you? Julien: For sure. @julienbenatar on Twitter, nextbigsound.com is free for everyone. Actually, we made our data public recently, so if you ever want to learn more about what we do, please check it out. We try to post on our blog about what we learn through data science, through design, and share more about why we build what we build. I recommend to just check blog and do some commitment to learn more about what we do. Brian: I definitely recommend people check out the site. The fun thing is again, as you said, it’s public. If there’s a band you like or whatever, you can type in any group that you like to listen to and you can get access to those insights. Just kind of get a flavor of what the service does. I’ll put those links in the show notes as well as the data pyramid. Julien, cool. Thanks for coming on. Is there anything else do you like to add before we wrap it up? Julien: No, thank you so much. I love reading your newsletters and I’m very happy to be here. Brian: Cool. Thank you so much. Let’s do it again. Julien: Cool. Brian: Cool. Thank you. We hope you enjoyed this episode of Experiencing Data with Brian O’Neill. If you did enjoy it, please consider sharing it with #experiencingdata. To get future podcast updates or to subscribe to Brian’s mailing list where he shares his insights on designing valuable enterprise data products and applications, visit designingforanalytics.com/podcast. 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We’re back with a special music-related analytics episode! Following Next Big Sound’s acquisition by Pandora, Julien Benatar moved from engineering into product management and is now responsible for the company’s analytics applications in the Creator Tools division. He and his team of engineers, data scientists and designers provide insights on how artists are performing on Pandora and how they can effectively grow their audience. This was a particularly fun interview for me since I have music playing on Pandora and occasionally use Next Big Sound’s analytics myself. Julien and I discussed: How Julien’s team accounts for designing for a huge range of customers (artists) that have wildly different popularity, song plays, and followers How the service generates benchmark values in order to make analytics more useful to artists How email notifications can be useful or counter-productive in analytics services How Julien thinks about the Data Pyramid when building out their platform Having a “North Star” and driving analytics toward customer action The types of predictive analytics Next Big Sound is doing Resources and Links: Julien Benatar on Twitter Next Big Sound website Next Big Sound blog The Data Pyramid model Quotes from Julien Benatar “I really hope we get to a point where people don’t need to be data analysts to look at data.” “People don’t just want to look at numbers anymore, they want to be able to use numbers to make decisions.” “One of our goals was to basically check every artist in the world and give them access to these tools and by checking millions of artists, it allows us to do some very good and very specific benchmarks” “The way it works is you can thumb up or thumb down songs. If you thumb up a song, you’re giving us a signal that this is something that you like and something you want to listen to more. That’s data that we give back to artists.” “I think the great thing today is that, compared to when Next Big Sound started in 2009, we don’t need to make a point for people to care about data. Everyone cares about data today.” Episode Transcript Brian: I’m really excited today for this episode. We have Julien Benatar on the show and he’s from a company that I’m sure a lot of people here know. You probably have had headphones on at your desk, at home, or wherever you are listening to Pandora for music. Julien , correct me if I’m wrong, you were the product manager for artist tools and insights at Next Big Sound, which is a type of data product that provides information on music listening stats to, I assume, artists’ labels as well to help them understand where their fans are and social media engagement. I love this topic. I’m also a musician, I have a profile on Next Big Sound and I feel music’s a fun way to talk about analytics and design as well because everybody can relate to the content and the domain. Welcome to the show. Did I get all that correct? Julien: Yeah, it was perfect. Brian: Cool. Tell us a little about your background. You’re from France originally? Julien: Yes, exactly. I grew up next to Paris, in Versailles more specifically, and moved to New York in 2014 to join Next Big Sound. Brian: Cool, nice. You’ve been there for about four years, something like that. You have a software engineering background and then now you’re on the product side, is that right? Julien: Exactly yes. I joined the company back when we were a startup. Software engineering was perfect, there was so much to do. To our move to Pandora, I moved to a product manager role around a year ago. Brian: Next Big Sound was independent and then they were acquired by Pandora. I assume there is good stuff about your data. Why did Pandora acquire you and how did they see you guys improving their service? Julien: We got acquired in 2015. The thing is, Next Big Sound was already really involved in the music industry. We already had clients like the three major labels and a lot of artists were using us to get access to their social data. I think it was a very natural move for Pandora as they wanted to get closer to creators and provide better analytics tools. Brian: For people that aren’t on the service, I always like to know who are the actual end users, the people logging in, not necessarily the management, but who sits down and what are some of the things that they would do? Who would log in to Next Big Sound and why? Julien: Honestly, it’s really anyone having any involvement into the music industry, so that can be an artist, obviously, try looking to try their socials and their audience on Pandora. But you can also be a booker trying to book artists in their town. We have a product that can really be used by many different user personas. But our core right now is really artists and labels, having contents on Pandora and trying to tell them the most compelling story about what they’re doing on the platform. Brian: When you think about designs, it’s hard to design and we talk about this on the mailing list sometimes but it’s really hard to design one great thing that’s perfect for everybody so usually you have to make some choices. Do you guys favor the artist, or the label, or as you call them,the bookers or whom I know as presenters,in the performing arts industry? Do you have a sweet spot, like you favor one of those in terms of experience? Julien: I think it’s something we’re moving towards, but it hasn’t always been this way. Like I told you, we used to be a startup or grow us to make a product that could work for as many people as possible. What is funny is we used to have an entity on Next Big Sound called Next Big Book where we used to provide the same type of service for the book industry. If anything, it’s been great to join Pandora because then we could really refocus on creators and it really allowed us to, I believe, create much better and more targeted analytics tools to really fulfill needs for specific people like artists and labels. Brian: I would assume individual artists are your biggest audience or is it really heavily used by the labels or who tends to… Julien: I think it’s pretty much the same honestly. I think the great thing today is that, compared to when Next Big Sound started in 2009, we don’t need to make a point for people to care about data. Everyone cares about data today. I think that everyone has reasons to look at their dashboards and especially for a platform like Pandora with millions of users every month. Our goal is really just telling them a story about what does it mean to be spinning on the platform and the opportunities it opens. Brian: You talked about opportunities, do you have any stories about a particular artist or a label that may have learned something from your data and maybe they wrote to you or you found out like in an interview how they reacted like, “Hey, we changed our tool routing,” or, “Hey, we decided to focus on this area instead of that area.” Do you know anything about how it’s been put into use in the wild? Julien: Yeah, it’s used for so many different reasons. For the people who don’t use Pandora, something I really like about the platform is it’s really about quality. As you use Pandora, you have the opportunity to thumb up or thumb down songs and as you do, you’re going to get recommended more songs like the ones you like. It’s really about making sure that you get the best songs at all times. The reality then is that for artists, their top songs on Pandora can be pretty different than their top songs on other platforms because sometimes their friends are going to be just reacting more to some part of their catalog than another one. I’ve heard many times of artists changing their playlists in looking at which songs where their fans thumbing up the most on Pandora. Brian: Could you go through that again? How would they adjust their playlist? Julien: Usually, people use Pandora as a radio service. While we already have internet today, most people are listening to the radio because they’re usually are very targeted and it just works really well. The way it works is you can thumb up or thumb down songs. If you thumb up a song, you’re giving us a signal that this is something that you like and something you want to listen to more. That’s data that we give back to artists. We tell them, “This are your most thumbed songs on Pandora. These are the songs that people engage with the most on the platform.” Looking at this data, you can actually inform them songs that they believe they should be playing more on the store. Brian: I see. A lot of it has to do with the favoriting aspect to give them idea what’s resonating with their audiences. Julien: Qualitative feedback, yes. Brian: Got it. Actually, it’s funny you mentioned the qualitative feedback. In preparation for this, I was reading an article that you guys put out back in March about a new feature called weekly performance insights, which is really cool and this actually reminds me of something that I talked about in the Designing for Analytics mailing list, which is the act of providing qualitative guides with your analytics. A lot of times they analyze for turnout quantitative data and whenever there’s an opportunity to put stuff into context or provide qualifiers, I think that’s a really good thing and you guys look like you’ve have done some really nice things here. I’ll paraphrase it and then you can jump in and maybe give us some backstory on it. One of the things that I think is really cool is there’re concepts of normalcy in here so that, if I’m an artist and I look at my numbers, I have an idea. For your Twitter mentions, for example, you say, “For artists with 26,000 followers, we expect you to get around 44 mentions.” When you show me that I have 146 mentions, I can tell that I’m substantially higher than what my social group would be. I think that’s a really fantastic concept that people not in music could try to apply as well which is, are there normalcy bans where you’d want to sit? Is there some other type of group, maybe, an industry, or apparent group, or another business unit, whatever it may be to provide some context for what these out of the blue numbers mean that don’t have any context? How did you guys come up with that and can you tell us a bit about the design process of going from maybe just showing, “You’re at 826 apples,” as compared to what? How did you move from just a number into this these kind of logical groupings where you provide the comparisons? Julien: I think what’s really fascinating is, we really live in an age of data. As an artist, you need to be on social media for the most part. There still a lot of artists I listen to but just decide not to. It’s part of things but at the same time, real big success in the music industry didn’t change. It’s still being on the Billboard chart, getting a Grammy and all these things. But as we see this, we have millions of artists looking at their data every day and just are not able to understand, like is it good or is it not good. Everyone starts at zero. We have a strong belief that data can only be useful when put in context. Looking at the number on its own can give you a sense of how things are doing but that can also be dismissive. An example is, a very common way to look at data is to look at a number and look at the percent changing comparison to the previous week. You’ve got a bunch of tables and you look at, am I growing or am I not growing. The reality is it’s actually impossible to always have a positive percent change. There’s no artist in the world that always does better week by week. Even Beyonce, I can assure you that the week she released Lemonade, she had more engagement on Twitter than the week after. With that in mind, we really try to give a way for artists to understand how are they doing for who they are and where they are currently in their career. Next Big Sound started in 2009. One of our goals was to basically check every artist in the world and give them access to these tools and by checking millions of artists, it allows us to do some very good and very specific benchmarks. For an artist, like the example you said, for instance an artist with a thousand Twitter mentions in a week, is it good or bad in comparison to their audience size? This feature comes because that’s just the question we’re asked. Artists want to know is it any good? What does this number actually mean for me? That’s why we really wanted to, in some ways, get out of being a content aggregator platform and really be a data analytics platform. How can we actually give information that can help artist make better decisions? Brian: I remember the first time I got what I would call an anomaly detection email from your service and it was about some spike in YouTube views or something like that. I thought it’s fantastic in two reasons. First of all, you identify an anomalous change and I think in this case it’s a positive anomalous change. That tells me that I should log in the tool. Secondly, you proactively delivered that to me. On the Designing for Analytics mailing list, we talk about is that user experience does not necessarily live inside your web browser interface or your hard client or whatever you’re using to show your analytics. Email and notifications are a big part of that. Can you tell me about how you guys also arrived at when you pushed these things out and maybe talk about this little anomaly detection service that you have? Julien: It all started when we got acquired by Pandora. We decided to just invite a bunch of users and just talk to them, understand how to use our product and what did they think about it. We had artists, managers, and label people come over and we just talk to them and basically they all said, “We love it.” But then, by looking at their actual usage, they don’t use it that much. I guess one of their questions was when should I be looking at my data? Everyone is very busy. As you’re an artist, you need to perform, you need to write music, you need to engage with your fans and same goes with everyone. When should I look at data? The reality is by being a data company, we do get all the data, we have all the numbers. We have ways to know when things are supposed to be known, when artists should be acting on something. We just turn this into this email notifications. Anytime we notice that an artist is doing better than expected, we just let them know right away. Brian: That’s great. Do you do it on the opposite end too? If there’s an unexpected drop or maybe like, “Oh, you put a new track out and your socials dropped,” or something like that, do you look at the negative side too or do you tend to only promote the positive changes? Julien: As far as pushes, we decided to only do push for positive. But as you mentioned weekly performance, weekly performance can give you some negative insights, like, “You’re not doing as well as artists with the same size of audience as yours.” The reason we didn’t do it for our notification is, anomalies are really hard to completely control. A reason, for instance, is Twitter removing bots. Basically, every single artist would have had an email telling them, “You lost Twitter followers this week.” It was a lot of work to really tune our anomaly factor to actually only send emails when something legitimate happens. That’s the reason we only decided so far to do it for positive but we actually have been thinking about doing the same for negative but that’s another type of work. Brian: Yeah, you’re right. You have to mature these things over time. You don’t want to be a noise generator. Julien: Exactly. Brian: Too many, then people start to ignore you. I’ve seen that with other data products I’ve worked on which just have really dumb alerting mechanisms that are very binary or they’re set at a hard threshold and just shootout noise and people just tune it out. Julien: I’m glad you mentioned this because this feature was in beta for a year for that specific reason. Brian: Got it. Julien: We had to learn the hard way. We had like a hundred beta users. We’ve got way too many emails because anytime there were an anomaly anywhere, they would just get an email. For the most part, it was things that were supposed to help them. If a notification becomes noise, then that’s absolutely against its purpose. Brian: I don’t know if everybody knows how the music business works, at least from the popular music side, but just to summarize. You have individual artists that are actually performers. They may or may not have an artist manager which takes care of their business affairs, represents them like negotiations with people that book shows. Then you have labels which are sort of like an artist manager except they’re really focused on the recording assets that the artist makes and they actually tend to own the recordings outright at the beginning and then over time, the artist may recoup through sales they make it the ownership act and the sound recordings they make. Of those kinds of three major groups, is there a one that’s particularly hungry or you’re the squeaky wheel that is most interested in what you’re doing? Julien: I really think that into these three groups, we have a subset of users that are really into the data and into the actionability of it. I don’t think it’s one specific group of user. It could be all around the industry like we have the data-savvy, they really want to know. We have some users that actually would rather get more notifications even if they need to on their end to figure what is right from what is wrong. But since we have such a wide user base of different type of people, we decided to go on the conservative side and make sure to only share things that we thoroughly validated through all of our filters. Brian: I assume that your group reports into some division of Pandora, I’m not sure of that. Are you reporting into a technology, like an IT, or a business unit, or marketing? Where do you guys fit in the Pandora world? Julien: We’re part of the creator’s tools. I don’t really have a perfect answer to this. Brian: Okay. I guess my main question being, because when we talk about designing services, we talk about both user experience, which is the end user thing and about business success or organization success. I’m curious, how does Pandora measure that Next Big Sound as delivering value? I can understand, I’m sure our artist can understand how the artists value it through understanding how is my music moving my audiences, et cetera. Is there a way that Pandora looks at it? Are they interested in just time spent? The analytics on the analytics, so to speak, is what I’m asking about. How do you guys look at it like, “Hey, this is really doing a good job,” or whatever? Do you know how that’s looked at? Julien: To be honest, I think you said it right. Our goal is to help artists make their decisions through data and having artists use the platform is currently the way Pandora sees us doing a good job. Actually, it hasn’t changed that much since our acquisition. One of our main KPI for the past and couple of years is something I would call insights consumes. Just making sure that our users, artists, anyone using Next Big Sound are consuming data. That can be them logging into the website or that can be them opening one of our notifications. But so far that was our main KPI. We’re trying to work on some more targeted KPI, potentially like actions taken, that would be the North Star, but we’re still working on how to do that right. Brian: Do you guys facilitate actions, so to speak, directly in the tool or are there things people can do with those actions really take place outside of the context of Next Big Sound? Julien: There are actions that artists can take to the other creator’s tools provided by Pandora. For instance, artists have the ability to send audio messages to anyone listening to them. If they go on tour into the US, they can have targeted messages in every single song they’re going to play. If anyone listens to them there, they can just click and buy a ticket. We’re working to make sure that artists are aware of these tools because they are free and they’re generally helping them grow at their careers. But regarding external actions, so far we don’t have any one-click way to tweet at the right time to the right people or with the right content or anything like this. Brian: Sure and that’s understood. Not every analytics product is going to have a direct actionable insight that comes right out of it. You guys may be feeling a longer term picture about trending and maybe for a certain artist to get an idea if they’re releasing music fairly frequently, what stuff is working and resonating, and what stuff is not. I can understand that. There may not be a button to click as a result immediately. Julien: That’s the goal though. Everything we do right now is going towards this objective. Maybe I can tell you a little about the way we think about data and that can give more sense to it. In order to work on any new feature, we follow this concept called the data pyramid. It’s something that you can Google. There’s a Wikipedia page for it. Let me explain to you how it works. The data pyramid, it’s a pyramid formed of four layers. It could be upon each other and each representing an exquisitely useful application of data. At the bottom of the pyramid we have the data layer. Any sort of data that we may have. For our case, Android data, Twitter, Facebook just getting the numbers, getting the raw data. On top of it, we have the information layer. The information layer is going to be ways you have to visualize this data. I guess it’s like the very broad sense of analytics. We’re going to give you tables, graphs, pie charts, you name it. We’re giving you ways to craft stories about this data but it’s on you to figure it out. Then on top of it we have what we call the knowledge layer. That’s where things start to get interesting. The knowledge layer is the contextual part of it. It’s like, “What do this number actually mean?” It has industry expertise. For instance, the way we’re going to work about it for musicians and their true data may be different than any other industry. The knowledge layer goes like a weekly performance. It’s a perfect answer to it. It’s what does it mean for me as a musician with a hundred fans to get two mentions this week. Same for notifications. It’s telling you that you should be looking at your data right now because something is happening. That’s how we get to the North Star and the last part of the data pyramid which is intelligence. The goal of intelligence is actionability. Now that I get to understand what does this number mean to the specific context, what should I be doing? Following your question, everything we’re trying to do here is to get to a point where we can just send an email to an artist and tell them, “Hey, you should be doing this right now because, with all the data that we have, we believe that this is going to have the highest impact for you.” Brian: It‘s really fascinating that you just outlined this data pyramid. I actually haven’t heard of this before. It made me think of one of the kind of, it’s not a joke but in the music community, I’m also a composer and when we write stuff, the kind of running joke is like nothing is new. Your ideas for this new song or this new melody I’m composing, it probably came before you. You heard it there before. I wrote a post on my list that was pretty much exactly the same thing except the knowledge layer. I was calling that insight. Data have been this raw format and information being the first human-readable format that’s like say going from raw data to a chart, a histogram. Now I have a line on a chart and then the insight layer being, I have a line on the chart and another line comparing it to like you said, average, or my social group, or a parent group, or some taxonomy, or an index. Then the action or the prescription for what to do or the prediction those that kind of lead you in about action which would be that fourth state. You’re like, “Oh, is this really a new concept?” It’s like, “Nope. Someone else already thought of that.” I totally want to go read about this data pyramid. Julien: That’s amazing. Brian: I’ll find that link to the data pyramid and I’ll put that in the show notes for sure. I thought that was really funny. Julien: It’s funny that you called it insight because that’s the way we call a lot of our features are working out. The way we define insight is bite-size, noteworthy, sharable content. How can we get into the noise of all of the data that only gives you exactly what you should be looking at. That’s how we got into notification and weekly performances. This is the one thing you should be looking at. Brian: I understand what you’re getting at there. The insights are, like you said, bite-size chunks of interesting stats that someone can put some kind of context around. That’s great and it’s good. One of the things I liked, too, that you talked about was you said, “Oh we got like a hundred users, like a beta group and that kind of inspired some of this.” Your product response to how do we help people know when to come and look at our service. I think this is really good because one of the problems that I see with clients and people on the list, I think is low engagement. This is especially true for internal analytics companies. Low engagement can be a symptom of a difficult product, it doesn’t provide the right information at the right time, it may not have a lot of utility, or it’s a resistance to change. People have done something the old way and they don’t want to do it the new way. One of the recipes you can follow if you’re trying to do a redesign or increase engagement is to involve the people that are going to use the service in the design process, both the stakeholders as well as the end customers. This is especially true again for the internal analytics people. Your customers or other employees and your colleagues. By engaging them in the design process, they’re much more likely to want to change whatever they’re doing now. I loved how you guys did some research. Now I want to ask, do you frequently do either usability testing or interviews? Is that an ongoing thing at your company or is it really just in front of a big feature release or something like that? How do you guys do this research? Can you tell me about that? Julien: Of course. It’s consent. We haven’t released any major feature without doing some heavy user testing. I’m very lucky to be working with two designers, Justin and Anabelle who are very user-focused. Honestly, if you come to our office, at least every week we’re going to have some user interview and just talking to them, showing them prototypes, and just see how do they play with it. Brian: So you’re doing a lot of testing it sounds like. That’s fantastic. Julien: At the same time it’s always to find the right balance because you could be overtesting things too. We really are focusing on user testing for new things and make sure that the future that we are working on actually answers their user story that we intended. Brian: I don’t know how involved you get participating in these, but do you have any interesting stories or anecdotes that you got from one of those that you could share? Julien: Let me think. I do participate into a lot of them but I’m not sure I have an example right now. Brian: Are most of the people you interview, are they current users of Next Big Sound or do you tend to focus on maybe artists that haven’t experienced the service yet or you mix it up? Julien: We mix it up. We mostly engage with users that we already have but then we can decide to go with users that haven’t used the platform for a while, or more active users if you want to understand how we’re useful into their day to day. What I would say is that, surprisingly, it’s very easy to get users to chat about their experience with the product. I didn’t assume that we would get so many responses when we tried to have people come over or just hop on the zoom to check a new feature. Brian: I’m glad you actually mentioned that because I think in some places, recruiting is perceived to be difficult and it probably isn’t. Maybe you haven’t done it before but as I tell a lot of my clients, a lot of people love to have someone listen to them talk, tell them all about their life and what’s wrong with it, and how it could be better with their tools. They love having someone listen to them and especially if they know that their feedback is going to influence a tool or a service that they’re using. They tend to be pretty engaged with it. I find it’s really rare that I do an interview with a client’s customer and they don’t want to be included in the future round like, “Hey, when we redesign the service, can we come back to you and show you what we’ve done?” “Oh, I love to do that!” Everybody wants to get engaged with it. There are places where recruiting can be difficult when it’s hard to access the users, some of the enterprise software space that can be an issue sometimes. But generally, if you can get access to them, they tend to be pretty willing to participate. I’m glad you mentioned that. Julien: I think the great part about testing with current users on the platform is to actually show them prototypes with real data, not just show them an abstract idea that we want to work on. As soon as they can see what we’re working on apply to their own career as musicians, for instance, that can lead to fascinating discussions. Brian: You made a really good point on the real data thing. I remember as far back as 10 years ago or whenever, I use to work at Fidelity Investments, we would see this issue when we’re working on the retail site for investors. When you show a portfolio that, for example, has Apple stock trading at $22 in it, you’re not really there to test what is the price of Apple stock but you might be testing something entirely different and the customer cannot bear what is going on? They’re so stuck on this thing. It’s all fake seed data in the prototype. The story here being if you’re a listener, when you test it’s important to have at least realistic data. You don’t want to have noise in the test or whatever your studying or else you can end up on this tangent. Try to make the numbers looks somewhat realistic if you’re using quantitative data. In some cases, people can be taught to roleplay. Pretend you’re Drake or pretend you’re some big artist and then they can get their head around why they have billions of streams instead of thousands which they’re used to. Julien: Absolutely. That also helps us just build better products because the reality is we have a lot of artists with maybe 10 plays in a month. As we build visualizations like something that we built a line of looking at Drake’s data, it’s not going to work as intended for a smaller artist sometimes. Having real data involved as soon as possible into the design process has been such a game changer for us. We really have a multidisciplinary team involved into the research and design of everything we do. I’m working with a data scientist, data engineer, a web engineer, and designer on a daily basis. Obviously, we all have our things to do. But as we get into creating something new, we just make sure to have someone helping us get the real data, interview the right user, and just create prototypes as soon as possible. Working with prototypes is essential into building useful data analytics tools. Brian: Yes, you do learn a lot more with a working prototype. It’s not to say you can’t test with lower fidelity goods, especially early on but for a service like yours when the range of possible use both the personas and also you’ve got the Drakes of the world, big major label artist and then down to really small independents, it’s really important to have an idea how your charts are going to scale, and what’s going to happen with data. Even just small stuff like how many decimal points should you be showing on a mobile device, some of the numbers might cram up. Julien: Exactly. Brian: All this stuff that you never think, if you only look at one version of everything, you can end up with a mess. I’m glad that you brought that up. Julien: I couldn’t say better. The decimal is actually something that we’ve had to discover through real data. Brian: To all of you in the technical people out there, I will say this. If I’ve seen one trend with engineers, is they love precision and there’s a lot of times when there’s very unnecessary precision being added to numbers. Such as charts and histograms. Histograms are usually about the trend, they’re not about identifying what was the precise value on this date at this time. It’s about the change over time. Showing what’s my portfolio worth down to three digits of micro-cents or something like that is just unnecessary detail. You can probably just round up to the dollar or even hundreds of dollars or even thousands of dollars in some cases. It actually is worse. The reason it’s worse is that adds unnecessary noise to the interface, you’re providing all these inks that someone has to mentally process, and it’s actually not really meaningful ink because the change is what’s important. Think about precision when you’re printing values. Julien: This concept of noise is so essential today for any data analytics tools. There is so much data today. There is data for everything. I think it’s our responsibility as a data analytics company to make sure what are we actually trying to help our user with this data set is not just about adding new metrics. Adding new metrics usually is just going to add noise and not be helpful in comparison to fairing what do they need to make the right decision. Brian: Right. Complexity obviously goes up. The single verb, ‘add,’ as soon as you do that, you’re generally adding complexity. One of the design tools that is not used a lot, and this is something I try to help clients with is, what can we take away? If we’re not going to cut it out entirely, can we move this feature, maybe this comparison to a different level of detail? Maybe it’s hidden behind a button click, or it’s not the default. But removing some stuff is a way to obviously simplify as well, especially if you do need to add new things. Your only weapon is not the pencil, you’ve got the eraser as well in the battle so to speak. Julien: I couldn’t agree more. On Next Big Sound we have this concept of artist stages. It’s a way for us to put artist into buckets and by looking at their social instrument data. It goes from undiscovered to epic. We do that by looking at all of the data we have and looking at it in context. I don’t have the numbers right now because they update on a daily basis but every artist starts undiscovered. For instance, as they get 1000 Facebook likes, maybe they’re going to get to a promising stage. We have all of these thresholds moving everyday looking at trends among social services. But what is interesting is that for instance, for a booker, a booker doesn’t need to look at the exact number of Twitter followers for an artist. He needs to know that he’s booking for a midsized venue in the city he’s in and he’s probably going to be looking for promising to established artists and not looking for the mainstream to epic artists. It’s always about figuring a way to use the numbers to tell the story. Brian: I’m totally selfishly asking for myself here, but I was immediately curious. I live in Cambridge which is in the Boston area, and I am curious who are the big artists in our area and what is the concentration? I’m in a niche. I’m more in the performing arts market, in the jazz, in world music, and classical music but I’m just curious. Is there a way to look at it by the city and know what your artist community looks like? You guys do anything like that? Julien: We don’t currently. But I think YouTube has actually a C-level chart available. It’s not part of something we do because I think the users it would benefit are not the users we specifically try to work on new features. It’s more something for bookers than artists ,specifically ,but it’s exactly the type of thing that we need to think about when we prioritize new features. Brian: I’m curious just because the topic’s fairly hot. Everybody is trying to do machine learning projects these days. I don’t like the term AI because it tends to be a little bit overloaded but are you guys using machine learning to accomplish any particular problems or add any new value to your service right now? Is that on your horizon? Julien: How do you think about machine learning? Brian: A lot of times I associate it with predictive analytics or understanding where you might be running instead of just using statistics. I don’t know what kind of data you might have for your learning that you can feed in but maybe there’s aspects about artists that can predict. Especially, I would think like in the pop music world where there tends to be more commercialization of the music, I would say, where it’s like we need a two-minute dance track at this tempo specifically because DJs are going to play it. It’s a very commercial thing. It’s very different than what I’m used to. So I’m curious if there’s a way to predict out how an artist may do or what kinds of tracks are performing well. Like these tempo songs, we predict over the next six months that tech house music at 160 beats for a minute is going to do really well based on the trending. I don’t know. I’m throwing stuff out there. The goal, obviously, is not to try to use like, “Oh Home Depot has this new hammer, let’s run out and get it. We don’t even know what it’s for but everyone else is buying it.” That’s how I joke about machine learning. It’s like you need to have a problem that necessitates that particular tool. I don’t ask such that, “Oh there should be some.” I’m more curious as to whether or not it’s a tool that you guys are leveraging at this time. Julien: The Next Big Sound team doesn’t worked on features following the musical aspects of things. We really are focused on the user data. Brian: Engagement and social. Julien: Engagement data mostly, yes. But at the same time, I’m sure teams have worked on this because of the way that genome works. We have a lot of data about the way songs are made. Regarding machine learning, on the Next Big Song team, we actually have something that is called the prediction chart. You said predictions. We have this chart that is available every week. Basically, it really goes back to having data for a long time. The fact that we’ve had data since 2009, we’ve been able to see artists actually get from starting to charting on the Billboard 200. By having all of these data, we’ve been able to see some trends, some things that usually happen for artists at specific times in their career up until they get into the Billboard 200. We actually do have some algorithms that allow us to apply this learning to all of the artists on Next Big Sound right now and have a list every week of artist that we believe are most likely to appear on the Billboard 200 chart next year. Brian: I see. Got it. Do you track your accuracy rate on that internally and change it over time? Do you adjust the model? Julien: Yeah, we do. Brian: Cool That’s really neat. Tell me, this chat has been super fun. I’ve selfishly got a little indulgent because being a musician, it’s fun to talk about these two worlds that I’m really passionate about so I could go on forever with you about this. But I’m curious. Do you have any advice for other product managers or analytics practitioners about how to design good data products and services? How to make either your own organization happy or your customers happy? Do you have any advice to them? Julien: Yeah, of course. I guess it’s all about asking questions, honestly. What is very good with working at Next Big Sound is that it all started in 2009. Maybe actually I can go back and tell you the story about how it started and why it’s so different today. It started in 2009. It was actually a project, a university project by the three co-founders. Basically, they were wondering about one thing. How many plays does a major artist get on the biggest music platform in the world? At that time, it was MySpace. The artist they picked was Akon. Basically, they just built a crawler, went to bed, woke up, and discovered that an artist like Akon was getting 500,000 plays on MySpace in one night in 2009. The challenge in 2009 was to get the data. That’s why for the most part in Next Big Sound as it started was, I really think a data aggregation tool. Our goal was to get as many sources as possible and just make them easily accessible into the same place. We really are much into the information layer here. We’re giving you all the numbers and you can compare Tumblr to Vimeo, to YouTube, to Twitter, to Facebook, to Vine, to you name it into a table or a graph that you want to. The reality is, today things change. We don’t need to fight to get data anymore. We don’t need to hike our way into getting the numbers. Now, data is accessible to everyone in a very easy way. It’s kind of a contract. You, by being an artist, you know you’re going to get access to your Spotify, YouTube, Pandora, Apple Music or any other platform data very easily just by signing up and authenticating as an artist. That’s where our goal changes. Thankfully, we don’t need to convince people to care about data, we know they do already. But now the challenge is different. Now, the challenge is to make them understand what does their data mean and how can they turn it into getting even more data, getting into having even more engagement, and having even more plays. I think that’s something that is very interesting because it really resonates into the question we’ve been asked in the past few years like, “What does my data mean and when should I be looking at my data?” If anything, these two things correlated pretty well. People don’t just want to look at numbers anymore, they want to be able to use numbers to make decisions. That’s the core of what we’re trying to achieve today. We couldn’t be there if we didn’t have users that ask us the right questions. Brian: Cool that’s really insightful. Just to maybe tie it off at the end and maybe you can’t share this but what’s your home run? What is your holy grail look like? Is there a place you guys know you want to get? Maybe it’s the lack of data or you don’t have access to the data in order to provide that service. Do you guys have kind of a picture of where it is you want to take the service? Julien: What is very noble about our goal at Next Big Sound specifically is we’re here to help artists. The North Star would be to make sure that any artist at any time in their career is doing everything they can do to play more shows, to reach to more people, and to make sure their music is heard. Brian: Nice. I guess it’s like you’re already there, just maybe the level of quality and improving that experience over time, that’s your goal. It’s not so much that there’s so much unobtainable thing at this moment. Is that kind of how you see it? Julien: I think the more we don’t feel just a data analytics tool, the more we’re getting to that goal. I really hope we get to a point where people don’t need to be data analysts to look at data. We’re always going to provide a very customizable tool for the data-savvy because they know what they need more than we can ever do it for them. We want to make sure that for everyone else, we can just make it very easy and as simple as a click for them to do something that’s going to impact them positively. Brian: Cool, man. This has been really exciting to have you on the show. Julien, can you tell the listeners where can they find you on the interwebs? Are you on Twitter or LinkedIn? How do they find you? Julien: For sure. @julienbenatar on Twitter, nextbigsound.com is free for everyone. Actually, we made our data public recently, so if you ever want to learn more about what we do, please check it out. We try to post on our blog about what we learn through data science, through design, and share more about why we build what we build. I recommend to just check blog and do some commitment to learn more about what we do. Brian: I definitely recommend people check out the site. The fun thing is again, as you said, it’s public. If there’s a band you like or whatever, you can type in any group that you like to listen to and you can get access to those insights. Just kind of get a flavor of what the service does. I’ll put those links in the show notes as well as the data pyramid. Julien, cool. Thanks for coming on. Is there anything else do you like to add before we wrap it up? Julien: No, thank you so much. I love reading your newsletters and I’m very happy to be here. Brian: Cool. Thank you so much. Let’s do it again. Julien: Cool. Brian: Cool. Thank you. We hope you enjoyed this episode of Experiencing Data with Brian O’Neill. If you did enjoy it, please consider sharing it with #experiencingdata. To get future podcast updates or to subscribe to Brian’s mailing list where he shares his insights on designing valuable enterprise data products and applications, visit designingforanalytics.com/podcast.

Jason Krantz is the Director of Business Analytics & Insights for the 135-year old company, Weil McLain and Marley Engineered Products. While the company is responsible for helping keeping homes and businesses warm, Jason is responsible for the creation and growth of analytical capabilities at Weil McLain, and was recognized in 2017 as a “Top 40 Under 40” in the HVAC industry. I'm not surprised given his posts on LinkedIn; Jason seems very focused on satisfying his internal customers and ensuring that there is practical business value anchoring their analytics initiatives. We talked about: How Jason’s team keeps their data accessible and relevant to the issue they need to solve for their customer. How Jason strives to keep the information simple and clean for the customer. How does Jason help drive analytics in a company culture with a lot of legacy (from its people to its parts) The importance of focusing on context How Jason drives his team to be business partners, and not report generators Resources and Links: Jason Krantz on LinkedIn Quotes from Jason Krantz: "You realize that small quick wins are very effective because, at its core, it’s really important to get executive buy-in." "I’m a huge fan of simplicity. As analytics pros, we could very easily make very complex, very intricate models, and just, 'Oh, look at how smart we are.' It doesn’t help our customers. …we only use about two or three different visual types and we use mostly the exact same visual set-up. I can train a sales rep for probably five minutes on all of our reporting because if you understand one, you’re going to understand everything. That gets to the theme again of just simplicity. Don’t over complicate, keep it simple, keep it clean.” "…To get buy-in, you really got to have your business case, even to your internal customers, really dialed in. If you just bring them a bunch of crap, that’s how you’re going to lose credibility. They’re going to be like, “I don’t have the time to waste with you,” even though we’re trying to be helpful.” "What my team and I do is we really help companies weaponize their data assets." Episode Transcript Brian: Jason, are you there? Jason: I’m here my friend. Brian: Sweet. How’s it going? Jason: It’s going very well today. How’s your Friday going? Brian: I’m doing awesome. We’re going to talk a little bit about analytics. Is it Wile McLain or Weil McLain? Jason: I say Weil McLain. If I’ve been saying it wrong, I’ve been saying it wrong for a while. Brian: As I recall from my musical training, I think in German, the second syllable is the one that says its name. I guess it would be Wile McLain, like if it was W-I-E-L it would be ‘Weil.’ But I don’t know. Its anglicized as they come over the pond. Jason: I’m going to go with you on that when you sound like an expert. Brian: Nice. Well, you sound like an expert in analytics at Weil McLain. Tell us about what you’re doing over there. We met on LinkedIn, I’ve been enjoying your postings on the social feed about your approach. You seem really passionate about what you’re doing and I’m like, “I don’t know who this guy is, but that was really interesting.” I just have. Tell us about the company, what they do. I know they’re in heating, right? Jason: Yes, absolutely. The company I work for, and I work in the HVAC space, we’re a 135-year-old boiler manufacturer. Whether you realize it or not, you probably have one of our products in your house or building or very close to where you live. What my team and I do is we really help companies weaponize their data assets. As you know, a lot of companies are very skilled at acquiring data since the Big Data Movement. But the reality is that a lot of these companies don’t know what to do with all this data. That’s where we really come in. What I always tell my team and our business partners that we work with internally and externally is that our focus is on solving business problems. In order to do that, you have to identify what is the business problem that you’re trying to solve or strategic agenda that you’re trying to address. In order to do that, you really have to be anchored in the biz. Again, that’s just my perspective, but if you’re in the business day in, day out, you develop this very keen stand of what the business would need to accomplish its objectives. Just like right now, we are based in the marketing group and it’s a great spot to be. I’m a firm believer that every analytics team should be based in the business for a reason that I just talked about. But what that does being business-first is that gives us a great lens to look at data from. Sometimes analytics people would be IT-centric and they can do a lot of academic work against the data set or different data sets. But the business might look at the output and be like, “Yeah, that doesn’t help us.” We always, always, always start with, “What is the business problem we’re trying to solve or strategy we’re looking to address?” It also helps us when it comes to curating data also. That’s one of our primary response [00:03:21] this too, is to look for different data sets both internal and external that can help us identify strategic opportunities. It sounds really unsexy, I’m not going to lie. I think some of my LinkedIn post just say that data is boring. It really is. It’s mind-numbing, too, about 85% of my customers. But that’s the important part is understanding what do our customers need and that’s really the lens that we look at this through. We are a service provider, our customers are internal and external, we have customers just like any other business. We have to take this really boring, but really potent product in data and make it accessible to them. That’s really where we use design to really try to make that magic happen. Brian: I love that you said, “Trying to understand what the problem is.” This is something we talk about on the mailing list quite a bit. In fact, falling in love with the problem is a good basis for doing good work instead of kind of jumping to solutions or feeling […]. As I tell my clients sometimes like, “Our job is not to go and visualize the data. It’s not […] available for someone to put into another tool or whatever the heck it is. The job is to find an insight that already is used. Probably they’re already in your job and you’re there to make […] if you’re doing internal analytics. Help them do a better job at what they’re doing, offer more value. You need to figure out how to work that into their life.” For example, for you guys then, your customer, I assume is it primarily sales people that you’re working with? Who are your customers and your […]? Jason: Yes. Great question. One of our biggest customers is sales. Sales has been one of my biggest customers for the past 10 years of my career. I’m very intimately involved with the sales team, sales operation, sales optimization, insight gathering, pricing, things like that, but also marketing. We do a lot in terms of competitive intelligence gathering, market research. We also do a lot of operations in finance obviously related to the prices, that sort of thing. We really touch all areas of the business, but without question, our biggest customers are going to be sales and marketing. Brian: If you were to bring a new initiative like, “Hey, we have access to…” I don’t know what it might be but for you maybe your point, [might be a line 00:05:49] of data that could actually give them more leverage. We know what the negotiation brings, better than […], we know we kind of have an idea now from what the industry is doing for their sales such that we can now tell the CRM like, “This is your […] or something.” When do you get that sales person involved? Do you deliver a solution and get feedback? Do you bring [...] early and say, “Hey, we think we can tell you more about how to do better pricing on the spot with this thing.” Do you bring them in or when do they fit into your process? Jason: Great question. A lot of times because we spend so much time actually in the trenches, that’s one of things I think is unique about the way that I design my teams to do analytics. It’s not like hand off product and we’re like, “Godspeed. Good luck.” Once we deliver a solution, we’re actually in the trenches with the business trying to implement what we’re talking about because it just works better. The team work is just more effective and they know that they’ve got back up, they know they’ve got air support. Really, a lot of times when we come up with something new, a lot of times we will frame it from the lens like, “Hey, we know that we’ve got opportunity A or issue B, or whatever it is. This has been an issue or an opportunity for months or years or whatever.” We think that we’ve identified something that could help us in solving that issue or realizing the potential of that opportunity and then it becomes, “Okay, let’s sit down and talk about, do you agree that this might actually help us in this process?” Because the one thing that I’ve learned is, in order to get buy-in, you really, really got to have your business case, even to your internal customers, really dialed in. If you just bring them a bunch of crap, that’s how you’re going to lose credibility. They’re going to be like, “I don’t have the time to waste with you,” even though we’re trying to be helpful. What we found out is if you really dial in what are we trying to address with this, just as you would with any business case, and you bring that to them, I have found that they tend to be much more receptive. It’s not to say there’s not going to be resistance—resistance comes with any change—but we found that typically framing it from that lens and saying, “We’re trying to solve a problem that you have, we think that this data will help,” that’s a great starting point. Brian: Do you have an example of a before/after with that? I don’t want you to get into proprietary stuff you can’t talk about but is there like a, “Before they did it this way,” and then we brought them in and said, “Hey, we think we can get […].” and how you went [00:08:19]. Jason: Yeah. What I can talk about is just the manner in which we distribute sales information, specifically insights. I think that, for your listeners, this is going to ring true to a lot of sales forces. I know for all them that I’ve been in or worked with, this case was true 100% of the time. But one of the things that, again, keeping the customer-centric focus, that if you look at your sales reps, a lot of time is you’re going to be what I call casual data consumers. By that, I mean that these are guys and gals that aren’t really into data day in and day out like guys like you and I or some of the listeners maybe. What we have to do is, as I always encourage my team to take empathetic lens and look at, “Okay, if we give them what our first […] is going to look like, how are they going to interpret this?” A lot of times, to be honest, it’s not very good. Now that’s where we have to look at internally and kind of rationalize and say, “Okay, let’s find this. One of us will find [00:09:14].” But one example of that is traditionally, sales reps and sales teams will get the information in a flat Excel table. Just lots of rows and columns and just gibberish everywhere. That’s a very financial-centric view of sales data. But the reality is—I don’t know about the rest of mankind but I know for myself—I can’t remember much more than 10 numbers. The mental computational cost of extracting insights is just gargantuan. What happens is, I just don’t even bother to do it. I’m just like, “Yeah, whatever.” An equivalent of that is, you know if you get a big block of text in email? Even though if you took that same block of text and broke it up into two paragraphs or two sentence segments which is very easy to read when you put the effort in, but for me, if I get a big block of text, I’m not even going to read that. It’s kind of one of the same things that we see on the sales side. What we do is just say, “You know what? There’s a lot of really good information here and we need to make it digestible for our customers.” That’s where we found traditionally, visualization can be an incredibly effective tool to communicate insights to this casual data audience, to this casual data consumer. Brian: Do you have to work through the visuals with them? Do they tend to get it the first time? Is it a process of you share, “Here’s a report or here’s some new view on X.” How do you know if the visualization is actually allowing them to pull the insight out of what other [00:10:46] broad data? How do you know they’re actually “getting it”? Jason: That’s a great question. I’m a huge fan of simplicity. As analytics pros, we could very easily make very complex, very intricate models, and just, “Oh, look at how smart we are.” It doesn’t help our customers. It doesn’t help anything. Really what we do—this is going to get to the theme of simplicity—is we only use about two or three different visual types and we use mostly the exact same visual set-up. Just to kind of frame it, what I’m a big fan of is a simple bar chart. There’s more details attached to it but to the right of the bar chart, we’ll typically put a tabular data set. What we do is, as you think in US at least, we start in that left-hand side of the page or we […]. What we do is we look at the visual real estate. We say, “Our customers are going to start in the left-hand side. We want them to look at the bar chart because it allows them to very rapidly assimilate it at a high-level what’s going on.” It’s great at communicating at top-level churn very quickly but the trade-off is, is this horrible imprecision. You have no precision at all. What we like to do is then we address that issue by putting a simple table, very clean, very simple table over to the right. What that does is that then provides the precision that the customers are seeing in most financial-centric tables. What we found that does is that we have to train our sales team on one set-up and then that set-up is used virtually universally on all of our solutions. As an example, I can train a sales rep for probably five minutes on all of our reporting because if you understand one, you’re going to understand everything. That gets to the theme again of just simplicity. Don’t over complicate, keep it simple, keep it clean. Brian: I think those are good. A lot of times, when I work with engineering clients, they fall in love with consistency. I guess one point to maybe just the contrary of this is that, I think consistency is generally a good rule with design. We want to minimize unnecessary change but at the same time, I would recommend to listeners is to always look at context first, and context should always come in. Let’s say Jason comes up with report number 12 and they have 11 now or whatever, and it doesn’t feel right for number 11. That’s a place where a designer would probably push for, “Well, no. The 12th one actually needs to be different because it’s not […] 11th and even though it’s not consistent, in this context, we don’t need it to win. This version will deliver the usability and the utility that we’re looking for better than the other 11 will.” In general, I think it’s smart to not get creative unnecessarily with meaningless ink on the screen like, “Let’s try it this way. Let’s change the color palette. I’m tired of this.” Those are not good reasons for […], you’re just introducing noise and it’s unnecessary. But I like that you guys are thinking about simplicity and trying to reuse templates and not looking at it as a creative tableau. Ironically, people think it’s a creative “design” tool, but at the same time with all those weapons, you have a lot of different weapons you can use in that toolkit and part of that is knowing how to use this. It’s the same thing with Photoshop, a million buttons and all this stuff. The Photoshop doesn’t make you a designer. It’s being aware of your customer’s pain and the problems they need and knowing when to use all those filters and all those different things that it can do. I like that you guys are looking into that simplicity and reusing templates when it’s meaningful to do so. Jason: You bring up some great points and I 100% agree. My team that’s listening there, they’ll laugh because I beat it in their heads, “Context. Context, context, context.” Both in design as you’ve talked but especially with numbers in general. Like, “If I give you a number, a billion, that doesn’t mean anything, you got to have context.” I’d say the same is true for design just as you articulated. Great point. Brian: Where does the impetus for “everybody is a data company, everybody wants to do analytics”? But then there’s operationalizing that, there’s getting buy-in, leadership behind it. Where does that come from in your org? Where is the interest in taking a 130-year-old company and getting it to care about this? Where does that come from, your influence and all of that? Jason: That was driven by our current president because he saw it as part of a digital transformation. Obviously, this was an essential component of that. Obviously, we do a lot with analytics, but we’re also involved in a lot of other digital components that lead to that overall digital maturation. Analytics is a very, very big part of what we do but it’s not all that we do. We serve as kind of that quarterback for a lot of the digital initiatives to help basically, guide them through the process. Because even though some of the nuances of each of this project, each one will have its own nuances, they all come back to data. Data is the currency. We found out pretty quickly that if you want to stay relevant in this day and age, you need to be digitally evolved but more importantly, as you look at it, do you [compare the 00:16:02] advantage that you can derive from analytics? I would argue that gap is slowly closing known certain industries like manufacturing, but we probably have a little bit more runway [00:16:10] it. But for a lot of industries, analytics is becoming table stakes. It’s one of those where you can certainly expect incremental value and competitive advantage, but the question becomes how much longer. That was kind of the impetus of saying, “Hey, we got to get this going sooner rather than later.” Brian: Do you have people in sales that are resistant to using the reporting or taking advantage of your information or is it pretty ingrained in the company culture that it’s like, “This is a tool. Why would you not want to use it?” Or did you guys have a […] getting adoption? Jason: Yeah. I would say anytime you’re going through a transformation of this magnitude, it’s hard and I would say especially for other manufacturers. I found in general, manufacturing in general, tends to be one of the laggards industry-wise in analytical maturity. Unquestionably, it’s tough for no other reason than change is tough. You’re taking legacy plants, legacy steer pieces, legacy process, and some people has been around the company for decades potentially, and we’re asking them to change almost on a dime on their time scale how they do business. It’s not that it’s right or wrong but what we try to point out is that, as I always say, we have to acknowledge the past. We’ve been where we’ve been, we’ve been successful at where we been. But there’s been more change in the past two or three years than maybe you’ve seen in the past 15-20 years. In order to stay relevant, you really have to be ready to evolve, not only evolve but evolve quickly. But I have to openly acknowledge that that’s hard. It’s a hard proposition for a lot of people. Again, it comes down to change management and managing not only expectations but supporting that change. Change doesn’t happen by itself, we have to support that. That’s really what we try to coach through. The way that we try to do that is by developing a product with our customers. I’m sure as you can […], if you force something upon somebody, it doesn’t get received too well. But if you develop it in conjunction with them and do tie it around their needs, it tends to get better adaptation. Brian: You used the word product in there and I’m interested, do you see the outputs of your efforts? Primarily, it’s BI reporting as I understand it. Do you look at that as the product that you offer to sales? Is that kind of how you see it? Jason: Yeah. We offer a product in the form of the insight packages but it’s also the service. Service that goes with it where again, we serve as essentially internal consultant to help them along. If you take just the product-centric approach, you just deliver an insight package and you’re like, “Good luck. It’s [00:19:35]. Have at it.” What we do is we deliver the product and then we partner with them and say, “Okay, here’s what we see. Now, remember you’re talking about this going on in the channel last year and our note show that there’s been a lot of competitive activity in this area. Here’s some of the question that we have. You’re the expert, so what do you think?” What we found is that working together like that, we tend to get pretty good results versus just leaving these guys on an island to kind of figure it out themselves because they virtually always know the answer but sometimes it’s up to us using these products and then offering the service is to ask question that maybe aren’t getting asked. A lot of times, we find out that they know the answer it’s just that you kind of have to ask the question. Brian: Is that often like, “I was using XYZ report. Could you break this down by county instead of just by whatever because I feel there’s more people living in the East side of town and the average is here or […] the whole county. I really just need this one county because that’s where everyone lives. Is that really underserved? Blah, blah, blah,” that kind of stuff and then you guys will go off and work with them for more of that detail then maybe you release that back into the product as a feature if it seems like a one-off or something. Is that how it works? Jason: It’s actually a very fluid process. An example of what you just described is exactly what happens if hey come to us with questions. But we also do it where we flip it around because a lot of products that we create are more aggregate discussion tools. We don’t design a lot within our primary visualization package. To really get into the weeds and everything just becomes overwhelming. We have other tools like your traditional [00:21:22] pivot table to kind of dig into that stuff. But the exact example that you just gave, they will ask us those questions, but we will also flip the script and say, “Hey, we saw that the mechanical chain in the Northeast is up 50%,” I’m just making up a number, “and at a higher level, you can see that but when we segment it out, here’s what we see. Not only when we break this down to this level, we see that’s specifically being driven by A, B and C.” That gets to where I push heavier at my team to do root cause analysis. That’s really where we provide value is by digging into it and asking questions like that. Again, operating from the lens of trying to solve a problem or answer a question or root cause something in conjunction with the business. A lot of times, we will ask those questions and at the same time, they will ask us, which is great. It’s amazing because you get the better solution faster. Brian: I think that’s great. I’ve worked on several different tools that have varying sophisticated means of doing root cause analysis and I think it’s a really powerful way to bring some why to a what that has happened in the past. Most of the time, why is really where the money is at. The value comes in being able to understand why. A lot of times, we don’t have all the data. You can’t know for sure but a lot of times I tend to say, “Our guess, if they’re just going to make a WAG—a wild ass guess—then our guess, as long as we qualify what ingredients went into the pie, our guess may be better than any WAG.” They’re going to make one already. If they’re going to make a decision here and go off gut, there is maybe a chance they’re right and their experience will say something. But maybe our elementary root cause analysis, which we can improve over time, will actually be better and we can get out of the total guessing game and start with something that’s kind of a macro ballpark thing. Then overtime, you can improve that analysis as new data becomes available or maybe learn about how two variables are related in the business and you can bring that knowledge into the system. I totally hear what you’re saying. It’s a nice mix of internal product plus services and also, it sounds like it gets you guys do good discovery work as well. You guys are not just responding to questions but you’re maybe asking them questions together as a group. You kind of work through what opportunities maybe latent that no one’s talking about by asking questions using data to do that. Jason: Yeah. In the lens that we’ve been talking through, this is really sales-centric, but this applies to any group that we interact with. We have the same level of proactive discussion with any group that we interact with. In some of these, in our market research side, it’s 100% proactive. We’re going out there scouring for information and trying to see the other things that we see. That one it’s completely proactive and now we bring insights to the business and say, “What do you guys think?” The sales one is the most fun because, let’s be honest, there’s no business if you’re not selling anything and nothing happens until a sale is made. Brian: Right. I get that. You talked about other clients, do you work at all with the actual hardware, is there any IoT type of analytics going on with the boilers and machinery that you guys create? Jason: We’re early in that process. We actually are getting ready to go down that task very soon. On the hardware side, we tend to not have as much involvement. That’s really more on the engineering group. I think for any manufacturer product or engineering groups probably going to be the most involved in that. But obviously, we get involved into the discussions of answering the fundamental question. What are we actually going to do with this data when we collect it? Because as you can imagine, IoT can spit out a lot of data real quick. They can become incredibly burdensome very quickly if you don’t have a plan on how to manage it. But then, if you’re going to go through the effort of managing that, you got to be able to say, “What are we going to do with this?” Brian: Yeah. I guess the first thing that would come to mind for me would be predictive maintenance, like, “Is it going to break down soon?” I worked on a cooling company that does cooling and really as the guy told me is like, “We’re not selling refrigeration. We’re selling consistent temperature to our clients. It’s not really about coolers and all of that, so we need to deliver consistent temperature. If we don’t do that, they lose products, they can lose whatever is being stored in cold storage.” That is significant business. I’m sure for you guys, it’s heat, you want to sell heat so how do you get in front if there’s a maintenance plan or whatever, how do you stay on top of that kind of stuff? Jason: Absolutely. Brian: [00:26:13] IoT. One of my clients used this word one time, which I now use all the time which is like, “We don’t want a metrics toilet.” An example of you can get to a metrics toilet really quickly with every stat under the gun and how many ounces of water per minute through this pipe, that’s great because that’ll help me do, as a sales guy or as a technician, how am I going to use that information just because there’s a sensor on that pipe. It’s working something around like, “Oh, there’s a sensor. Put the data in the grid.” Jason: I’m going to have to borrow that. I’ll give credit whenever I use ‘metrics toilet,’ that’s a pretty good one. I may actually [00:26:56]. Brian: Nice. Tell me, where does it go from here? You had mentioned like, “Oh, the competitive edge, maybe it’s closing.” Or maybe you guys feel your competitors are all kind of maybe they’re doing the same thing that you guys are doing and we are all aware of where the data can be used to drive the business. Are there other places where you see design or technology like predictive analytics or machine learning and some of these other new technologies that are out there to help drive predictions and things like that? Are you guys leveraging any of that or have plans to look to the future? What does that look like? I know you probably can’t talk about everything but maybe broadly. Jason: Absolutely. I would say that that’s content that’s definitely, if it’s not already being done then it’s on our radar. We’ve got a pretty talented team here that goes a lot of your traditional data science turf. As you can probably surmise in this conversation, is in addition to having all skills, we’re probably the most heavily focused on the business side. As we say, we explore opportunities for a lot of this. We always look at it, again, like machine learning. Great, but we got to make sure it’s very powerful stuff. We got to make sure that whatever we’re embarking upon, because we have finite work capacity, if you pursue something, machine learning, it means we’re not doing something else. It’s not to say that it’s not important, but we really have to be able to answer to that question. Again, come back to, “This is our anchor. What are we going to do with it?” I love this stuff. I love the stats. I love machine learning, AI, all that stuff. If you’re not careful, you can really quickly get into an academic exercise that we think is really cool. “Oh wow, look at this. We’ve got this awesome algorithm here. It does all this magical stuff,” and then the business looks at it and goes, “Yeah, so what? I don’t care. How does that generate revenue? How does that improve our margins? How does that reduce our cost? How does that enable to build the sales pipeline?” If we can’t answer those base questions and we don’t get alignment, that’s probably the most important thing is executive buy-in on exactly what we’re going to be working on, why it’s important. No, we don’t pursue it but those things are most definitely, as with any analytics teams today, I think that that content is definitely being done and/or on your radar. Brian: You make a really good point. Sometimes I almost hesitate to ask the question. But I think it’s an exciting space in terms of predictive capability and removing viable analysis and what we call time tool time in the design world, there is there. But at the same time, you make a really good point which is again, these are tools that need to be leveraged to service an opportunity or a problem. The goal is not to go do the machine learning, the goal is to solve a business problem by which machine learning maybe applied a better […] do it, reduce cost or reduce effort, speed, something like that. I completely respect that. I’m glad to hear that you guy are looking that as not a leading step. I know there’s conflicting signals out there. I’ve been talking to people in the International Institute for Analytics about this and at the same time you hear a lot of stuff which is, “If AI is not part of your strategy, you’re going to be missing out,” and boards just want to hear that people are doing AI. At the same time, you’ve got academic exercises going on, you’ve got people trying to take on massive like, “We’re going to shoot for the moon,” and it’s like, “You don’t even have an airplane and you’re trying to go to the moon with this thing. Show us a small win if you’re going to do an investment in AI.” It’s okay to go try it out and say, “Let’s do a small thing but let’s try to solve a business problem or have some definable output that we’re looking to do here such that we’re not just writing code and doing experiments.” I hear there’s a problem with people putting this on their resume. It’s like people just want to have machine learning. Everyone’s a data scientist now that used to stay in analytics. [00:30:47] It’s scary in the sense of just wasting opportunity and wasting money because at some point, your smarter competitors are going to be saying, “This is a new hammer. Let’s find some nails that we can use for it. But we think […] right nails and it needs to be the right application before we whack at it. It’s not just […].” Jason: I really like your point because again, if my peers were listening to this they will laugh because they say, “We are professionals of this trade and the tools that we might want to use might not be the right tool to use for a specific job.” I couldn’t agree more with that sentiment. It’s one of those core philosophies that I have and share with my team. Also to it is with the AI. I think that you truly made a very astute observation here and comment in that, I think a lot of companies do feel compelled to have to make significant investment in AI like today. It’s not to say that there’s not merit. There clearly is plenty of merit and plenty of potential there, but kind of your point, I really believe that it’s much more beneficial when you really minimize the risk of project and budget flow and minimize overall project risk. You take that small bite and try a little bit, then try a little bit more. When you get to win, socialize the win, and your executives feel comfortable because I’ve done it on the analytics side. I went for a big bang approach and after nine months they were like, “Hey, man. Where’s the output?” All you need is to get bit by that once and then you realize that small quick wins are very effective because at its core, it’s really important to get executive buy-in. A lot of executives are not willing to wait nine months or a year for something when they’re expecting to see at three months. I totally agree with your sentiment. Brian: When you talked about the wins, I totally understand if you’re close to it and maybe hard to remember those, but is there a particular story or time where something in the product and the insights that you guys put out to your customers that it was like a real win, like a sales guy said something to you or maybe an executive said something to you about how this moved the needle, like this was a memorable moment for us. Like, “I changed a customer’s mind with this,” or, “We closed the sale that we never would have been looking over here if we didn’t do it.” Do you have any anecdotes like that that you can share? Jason: One that we had recently, again, just for confidentiality purposes I can’t get too deep. Brian: Sure. Jason: We did have one recently where we just basically revamped our insights packages that we distribute to our internal team. We really, really gathered feedback. We had version one, we gathered ton of feedback, kind of refined, iterated, got the feedback without making it a major release. Got feedback, refined it, refined it, and then what we did was, with a small group, we got that beta in their hand, they look at it and they’re like, “This is great. This is exactly what we need.” Because what we were doing, what we found was—I’m sure you’ve experienced this—everybody wants their own part of things. Everybody wants certain view of a report or they want certain insights or whatever it is, and it’s great. But if you have limited resources, really high-powered resources like an analytics team or data science team, you’re going to look at the opportunity cost of trying to do one of these one-offs, we were getting a ton of report flow. Again, what I tell my team, I don’t mean to be derogatory to the DI guys in this comment, but my team’s side, I always tell them, “We don’t create value if we’re just creating reports. We create value when we’re actually partnering with business to extract insights, identify opportunities amidst all that stuff that goes well with it.” What we realized though is that, what started out as a nice, clean, three- or four-page insights package and blow it up to like 20 and [34:21] doesn’t that meet our original criteria? Essentially, what we do is once we have the rationalization enough to say, “Okay, we’ve got all these stuffs right across 20 pages. We can actually distill it down to four pages.” It will give you the exact same information, but it might not look the exact way that you wanted it to look. The question becomes, are you willing to deal with less stuff and maybe have it look a little different, but you’ll get it in a much more concise package that you’re actually able to use and process? What we found out is that a lot of people were doing these packages and getting the reports that they want but they weren’t actually using them to drive decision-making because they can’t see the paragraph or the block of text story before. They look at it and they’re like, “I don’t know what the hell to do with this.” We would dial that in and it just been a screaming success. It’s really nice to have it where something like that you see the evolution of it. This is just one of those things that we had, and this was kind of a side package or wasn’t a primary, but it’s become a primary now because it’s so effective. Brian: Would you say that when you talk about reducing this, is the report like a PDF or do they access it through a browser the insights package? Jason: Yeah, we have the options to do both. We distribute it initially via PDF, sometimes along with our comments if there’s really, really big stuff in there. We’ll say, “Hey, we see this. Here’s a driver. Here’s a supplemental package.” A lot of times it’s PDF first and then if they want to go on the web, start interacting with it, they can do that. Those are nice, but the reality is a lot of them don’t do that which is understandable. Brian: You took it from 20 pages down to 4, is that what you’re saying? Jason: Yeah. Same information. Brian: This is a really good point. I’ve frequently had clients come in and they’re with data products and their concern is information overload. We’ve heard this a lot of times and the irony is that, the issue is usually not information overload. It’s usually a design problem that the information is not presented properly because sometimes, it can increase the density and increase the utility and usability, not the other way around. In fact, removing data can actually make it worse. A basic example of that is when you’re trying to compare A and B. If A and B are not on the same, what we call a viewport like in a browser world, it would be within the browser window there. When you require someone to toggle between two screens, they have to change context and visually, your eye can process the information a lot better when it’s within proximity. Sometimes, increasing the density actually will give you a better design. It takes more care in how you do it, but it’s not always about information overload, “Oh, it’s too crazy.” They may not get it on the first time but your sales people, if they’re looking at this stuff weekly or monthly, at some point they’re going to be pretty comfortable with this. I always tell my clients, “You need to look at the switch frequency as well because if it’s going to be used a lot, you can actually get more detailed and you can really push the, what you might see as complexity or the information density, can go up because they’re going to get familiar with the formatting. Typically, the density is actually going to probably improve the utility as long as care is given to the choices. But having that eyeball comparison without having to change pages and all of that, typically you’re going to give a better story as a broad rule. I like hearing that you guys went down in page count, up in density and in turn a better user experience at the end so that’s great. I think we’re about done here. I don’t have too many questions for you, but this is super great. One of the reasons I contacted Jason is because I remember seeing this quote, “Jason is like a category five hurricane in the data analytics world.” I’m like, “Who the hell is this guy? No one talks like that.” I started reading your stuff and I enjoyed watching your LinkedIn social posts and things like that. Where can people find out more about you? You’re obviously on LinkedIn, I can put LinkedIn in the show notes and stuff, but are you on Twitter, any social media places they can follow you? Jason: No, actually, I’m not on Twitter. But the best place unquestionably is going to be LinkedIn. I’m pretty involved there. I do like to engage. If you want to direct message me with questions, just talk, meetup, connect, whatever it is, I welcome that. I love the platform, it’s a great family. I just really started using it maybe nine months ago, really getting into it. It’s been great meeting guys like yourself. It’s actually phenomenal. Brian: Cool. I’ll put a link to Jason’s LinkedIn profile on there and you guys can find him. I recommend, especially if you’re in an internal analytics type of role at your company, to follow Jason and then check out what he has to say on there. This has been great. Thanks for coming on the show. I look forward to meeting you at some point in person. Jason: Dude, thank you for having me on here. I really appreciate it. We hope you enjoyed this episode of Experiencing Data with Brian O’Neill. If you did enjoy it, please consider sharing it with #experiencingdata. To get future podcast updates or to subscribe to Brian’s mailing list where he shares his insights on designing valuable enterprise data products and applications, visit designingforanalytics.com/podcast. Never forget to look up the online HTML CheatSheet when you forget how to write an image, a table or an iframe or any other tag in HTML! [bws_google_captcha] Subscribe for Podcast Updates Get updates on new episodes of Experiencing Data plus my occasional insights on design and UX for custom enterprise data products and apps. Email Address [text-blocks id="eu-consent-checkbox-textblock" plain="1"]

Hey, everyone. I’m Brian O’Neill and I’m excited to share my new podcast with you called Experiencing Data. I’m a consultant specializing in design and user experience for custom enterprise data products and apps. I’m also the founder and principal of Designing for Analytics. My goal with this podcast is to expose you to you or rather to other professionals like you. Who is you? Like any good designer, I had a persona in mind when I started designing this podcast. This persona is basically, modeled on my past clients, conversations at data and analytics conferences that I’ve spoken at, and email exchanges with subscribers on my mailing list. My guest and I assume my listeners are usually going to be data product managers, engineering and analytics leaders, data scientists, and executives. Regardless of the title though, Experiencing Data is really a podcast for business leaders responsible for turning data into useful, usable, and valuable decision support via custom software applications. Maybe you’re wondering why I’m doing this and I am too a little bit. But here is why, I believe the success of analytics software and data products intended for people, since some of them obviously, don’t have interfaces as many of you probably know is, products that are intended for people are only as good as the experiences that they afford, sometimes I refer to that as kind of the last mile of this large technology projects and products that we put out. Because not all companies have trained designers and UX professionals on staff, I was curious to learn how my guests consider user experience as they design these enterprise data products and software tools. On this podcast, we’re not going to go deep on design implementation topics such as data viz and user interface design, some of these things are inherently visual, and I think reading about them and seeing examples is more relevant. But more importantly, I want to look more broadly at what I sometimes call Capital D Design. Capital D Design looks more at defining business objectives, user needs, the problem spaces especially, and the success criteria for new products and services. We’re also going to stay clear off heavy technology discussions since there’s already plenty of that kind of stuff out there and that’s not my area of expertise. Also, on occasion, I may record some solo episodes and share some of my insights on designs that you can put them into play in your daily work. If you’re looking for this kind of insight on a regular basis, you can head over to my Insights mailing list which is at designingforanalytics.com. I write pretty regularly to my list. Feel free to subscribe there if you’re interested in learning more about designing UX. I’m also a professional percussionist. I’m a professional musician and performing artist. In addition to my design consulting work that I do, I wanted to find a way to bring my two worlds together. I’m going to have occasional episodes with music technologies when it’s relevant to Experiencing Data. To kick that off, we’re going to have an upcoming episode featuring a guest who’s a product manager, and his name is Julien Benatar, he’s over at Pandora which I’m sure many of you know. He’s going to come in and talk about how Pandora has gone about designing their services analytics platform which is called Next Big Sound, so looking forward to that one. I hope you will be too. One of the things about podcasting, in general, is ironically how few analytics, we, the publishers and the producers and hosts, receive about our listeners. As those of you on my mailing list already know, I routinely going out and interviewing your customers on a one-on-one fashion; customers, users, whether they’re paying for your software or using an internal tool, I really advocate going out to uncover latent problems they’re having and latent needs that may not be necessarily expressed. But since the podcast environment though doesn’t let me eat my own dog food and do this type of research since we’re kind of in a one-way broadcast modality, with me speaking and you listening, I hope you’ll leave me feedback, either in iTunes or via email. You can reach me at brian@designingforanalytics.com. This show is my MVP, and I’m sure this show may change over time. If you don’t know what an MVP is, well, stay tuned because we will probably cover that as well. If this show sounds interesting to you, please head over to iTunes or your favorite podcast app, and click the subscribe button, and then you can join my mailing list at designingforanalytics.com/podcast. That page will be the homepage for this show. Thanks again. I’m Brian O’Neill and welcome to Experiencing Data. Subscribe for Podcast Updates Get updates on new episodes of Experiencing Data plus my occasional insights on design and UX for custom enterprise data products and apps. Email Address I understand and agree to this website's Terms of Use and Privacy Policy and consent to receiving email from Designing for Analytics, LLC.

Good Morning Gjallarhorn Episode 031 – Ode To The Gjallarhorn Group   Good morning Horners! It is the bye week, and the gang is altogether along with a special guest, Mr. Manbear Pig. This fine artist who loves his Vikings football took his handle from the famous Southpark episodes of that great show. He joins Ted, Drew, and myself for a sit-down and talk that focuses on our love for the Minnesota Vikings.   I'd like to give everybody a heads up… This episode very much focuses on a group of Vikings fans that get together and talk football. For the first 15 1/2 minutes, we do just that. After that, however we get into some of our group specifics with some fantasy games and roll into our fantasy football midseason update. I will not be hurt if you skip to the trailers at the end of the show at that point.   We start to show with introductions and then talking about that wonderful victory over the Detroit Lions. We go over some of the histories of the folks that wore #77 briefly mentioning Vikings greats like Gary Larson, Kory Stringer, and Mark Mullaney. We talk about how our beloved team seems to have made adjustments, not only on the defensive side of the ball but as to the offense as well. We are getting unexpectedly good play from rookie Brian O'Neill who has yet to give up a sack since he is started. It is pretty much a done deal that he is earned his starting job at right tackle. It was good to see Dalvin Cook break off such a nice run against the Detroit Lions, of which Brian O'Neill had a couple of key blocks. Also, just how sweet that victory actually was.   More talk of actually how well quarterback Kirk Cousins is doing, the adjustments made by coach Mike Zimmer, how players like Anthony Harris and Jayron Kearse have stepped up and made contributions, along with the wonderful play by Danielle Hunter in the defensive line.   We move on to discuss coming out of the bye week and playing the Chicago Bears in prime time next Sunday after being flexed into that spot. This will be a big contest, especially with all the history involved to include Coach Mike Ditka comments about the Vikings and the roller dome. Our guest doesn't like Coach Ditka a whole lot. I'm curious to how many of you have memories and opinions of Coach Ditka as well?   At this point, at the 15 1/2 minute mark, we move on to talking about our guest, Mr. Manbear Pig, inventing the fantasy game that you've heard us talk about called The Game of Skol. We discuss how it came about and how it is played. We go over some of the prizes that participants have a chance of winning if their choices, with a little bit of luck, like Danielle Hunter and the Lions game, turn out to be good ones. It is an extremely fun game that I think a lot of you would be interested in playing in the future.   From there it's onto our fantasy league update and we know most people don't care about your fantasy league. Feel free to scrub through a portion of the show you're not interested in. We want to thank the Gjallarhorn group for giving us our inspiration that  led to the creation of this vodcast and to talk Minnesota Vikings football. The show is dedicated to them.   Like, subscribe, and ring that damn bell! Then shout SKOL!   As always, enjoy the watch!   The show’s theme music is licensed through AudioJungle, the song is Stylish Powerful Energetic Rock.   (All rights go to The National Football League, the Minnesota Vikings, and all their broadcasters. I do not own any of the music and the footage used in this video. No copyright infringement intended. We do not gain any profit from our videos, and they are for entertainment and educational purposes only) "Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use." Learn more about your ad choices. Visit megaphone.fm/adchoices

Friend of the Program and former NFL scout Dan Hatman (@Dan_Hatman) of The Scouting Academy joined the show to do a deep dive on the Minnesota Fightin' Vikings defensive line, what the ceiling for Brian O'Neill could be, and his own personal Adam Thielen-adjacent scouting prospect (you will know the name). Plus I take a look at the Vikes PFF grades from Sunday Night, look ahead to the next three games (all in division), and offer a rebuttal to my guy Mike Freeman's Bleacher Report piece on Kirk Cousins.  All that and more "You Win, Universe" chatter on this edition of the Purple FTW! Podcast! A Carlson Digital Joint Twitter: http://twitter.com/purpleforthewin Facebook: https://www.facebook.com/purpleftwpodcast/ Instagram: https://www.instagram.com/purpleftwpodcast/ Website: http://purpleftw.com --- iTunes: http://purpleftw.com/itunes 1500ESPN: http://www.1500espn.com/tag/andy-carlson/ Spotify: https://open.spotify.com/show/1FGlIOB1EyR8Ubut71HDla?si=mB2l8dmZQeC0U_nlz3pA-w Google Play: https://play.google.com/music/listen?u=0#/ps/Ivvcg4ohg4tprswcn6g2yy3w3u4 PodcastOne: http://www.podcastone.com/purple-ftw Stitcher: http://purpleftw.com/stitcher iHeart Radio: http://www.iheart.com/show/263-Purple-FTW-Podcast/ YouTube: https://www.youtube.com/c/purpleftwpodcast https://www.youtube.com/channel/UC6Xt29Fi1ES6C1fEtWFUFIw?sub_confirmation=1 Bookmark us on Amazon & show some love! http://purpleftw.com/amazon Music for the Purple FTW! podcast is created by & produced by deeB. To hear more of his tracks, check out http://soundcloud.com/deeb #MinnesotaVikings

Di and Ted are back, and in this episode, they: Say all there is to say when you tie your arch rival. We recap the game on both sides of the ball, AND special teams, and talk Brian O’Neill, Laquon Treadwell, and former Vikings kicker Daniel Carlson. In Vikings news, we say hello to Dan Bailey, Tom Johnson, and Aldrick Robinson, and discuss expectations for all of them. And sadly, Di will no longer get to hang Stacey Coley over Ted’s head, because he was released. Then we preview the Bills game, and words like ‘bad’, ‘preseason game’, and ‘lol Josh Allen’ were thrown around discussing Sunday’s matchup. Also, Vontae Davis retired at halftime this team is so bad. Finally, we wrap up the show with the few remaining questions we didn’t hit during the other segments. Let us know what you think of the show by leaving a comment below, or even better, a review on iTunes or Stitcher. Thanks for listening!

On this episode of the Wobcast, vikings,com's Mike Wobschall and Chris Corso are joined by rookie tackle Brian O'Neill. Wobby and Corso recap a historic game at Lambeau Field on Sunday, talk some NFL news and notes and answer fan mail.

On this episode of the Wobcast, vikings,com's Mike Wobschall and Chris Corso are joined by rookie tackle Brian O'Neill. Wobby and Corso recap a historic game at Lambeau Field on Sunday, talk some NFL news and notes and answer fan mail.

With the preseason under way, we take a look at what’s happening in Minnesota and […]

With the preseason under way, we take a look at what’s happening in Minnesota and […]

New host Jordan Reid introduces himself, remembers Tony Sparano, discusses Vikings rookies reporting for training camp and gives an overview of what to expect from rookie cornerback Mike Hughes, offensive tackle Brian O'Neill and defensive tackle Jalyn Holmes. Learn more about your ad choices. Visit megaphone.fm/adchoices

Segment 1- Mindie   Kinsale – County Cork – off the coast of southern Ireland   Kinsale isn’t a thin place… sometimes you need to relax and rejuvenate and have fun. Most lovers of thin places and liminal spaces also love history and stories of local people – heroes, villains – and Kinsale is very rich in history that impacted the evolvement of society in the western world with the famous “Battle of Kinsale.” Kinsale has two historic forts, Charles and James Forts. And so many other bits of interesting history.   Kinsale is of my favorite towns for relaxing.  I love the vibe.  The town is clean, vibrant It’s an art and foodie town. The people are friendly. It’s totally walkable and everywhere you look is color and light.   When you go to Kinsale a good way to get your bearings is to go on a tour guided by Don or Barry – on Don and Barry’s Historic Strolls. I was lucky enough to get an interview with Barry when I was in Kinsale recently.   segment 2 – guest interview   Barry Moloney – Don and Barry’s Kinsale Historic Stroll   Don and Barry’s Historic Stroll in Kinsale offers a walking tour full of history and interesting information about this seaside town in County Cork.     SEGMENT 3– Kinsale ghost tour   There are a few consistently operated ghost tours in Ireland.  Being the owner of a ghost tour company here in the states, I always like to see what other companies and groups do when crafting and putting on a ghost tour. I’ve been on the ghost tour in Belfast and the Ghost Bus in Dublin.  Both were great experiences through very different.   Kinsale has an interesting ghost tour.  The term Ghost tour is so subjective. It can have multiple definitions in people’s minds. People can perceive ghost tours as anything from paranormal investigations to history walks to people dressed in character leading a theatrical performance.    Kinsale ghost tour is that kind of ghost tour – a performance and it’s quite comedic.  Two actors, Brian O’Neill and Don Herlihy dress in character and lead their group of guests around the historic Kinsale town center and recount stories of ghosts and historical figures in way that keeps the guests’ attention and keeps guests laughing. This performance is so well done. And there are some elements of surprise.   The tour starts at Kinsale’s oldest tavern - the Tap Tavern, which has been owned by Brian O’Neill’s family since 1886.  His mother, Mary O’Neill still owns it today and she and Brian manage the operations. Mary is often there when guests gather for the ghost tour. I had the pleasure of meeting her while I waited to speak to Brian.   The tour takes about 90 minutes. It covers all the interesting parts of the town and it is very entertaining. An evening well spent.   Don’t miss it if you’re in Kinsale.   Kinsale Ghost Tours http://kinsaleperformanceevents.com/hentertainment/ghost-tout/       SEGMENT 4 – Ardmore in County Waterford   Ard Mohr means Great Height Ardmore: Great Height – blog post by Mindie Burgoyne A seaside resort and fishing village. It’s near Youghal in the south of Ireland – not too far from Kinsale or Cork City.   Ardmore is a thin place. I guess I sense the thinness of a place on the approach. Maybe there’s something about the round tower, maybe something about the old ruins. But as you climb the hill to the old monastic ruins you get a jolt of something when the round tower comes into view. It’s a seaside town with a beautiful beach and sheltered bay. It’s a resort town for tourists with stunning views of the bay and a cliff walk above the town. There are also ecclesiastical ruins in Ardmore are associated with St. Declan, a 5th-century saint who established this monastic community here on a hill at Ardmore… in fact the name Ard Mor – means “Great Height.” The devotional stops in Ardmore are traveled by pilgrims and associated with St. Declan. They include the ecclesiastical ruins up on the hill, a holy well, and a large stone on the beach. According to one of the Lives written about him, St. Declan was born in this region and later went to Rome and became a bishop. He left Rome and returned to County Waterford - - to Ardmore with plans to build a monastery. However, he left without his bell. A bishop’s bell was similar to his crozier. A symbol of his authority. But because Declan was so special and so blessed, the angels set his bell afloat on a stone that traveled all the way across the sea to Ardmore. It still sits on the beach. It’s a large stone sitting atop two smaller ones and the stone is said to have curative powers for those who crawl under it. That would be a task. But these old legends were begun in a different and told to people who have a different perspective. Thinking patterns were very abstract. The meaning of the story was rooted in the understanding that an object could connect people in this world to the powers and graces of the eternal world. Maybe that connection brought healing. Maybe it brought wisdom. But being close to these sacred monuments elevates our awareness and spiritual vibration. I’ve stood by that stone and thought about the stories and all the pilgrims who have stood in the same place. I’ve even found one small stone in the shape of a heart on that rocky beach around St. Declan’s stone that I brought home with me. Holding it in my hand 3000 miles away from Ardmore can take me back there in my mind. There is value in these thin places. From the stone on the beach, the pilgrims travel up the main road where there is access to a path that turns into a gorgeous cliff walk. On the path is St. Declan’s Holy well. It is a beautiful spot. The well has clean water (also said to have curative powers) and a little shrine has been built around it with stone. It has an opening for the well and then three stone crosses atop. Actually, that’s only two now. The crosses were said to represent Calvary. One cross on the left for the unrepentant thief, a high cross in the middle to represent Jesus and a cross on the right to represent the repentant thief. Sadly, the cross representing the unrepentant thief has vanished. The locals say it was stolen. … which is ironic. Farther past the well is a pathway that winds along the cliffs with spectacular views of the bay and ocean. Then atop the hill behind the village are the remains of an old monastery. The buildings date back to the eighth century and were placed atop the site where Declan had his monastery in the 5th century. Those building – likely made of wood are long gone. The oldest of the ruins is St. Declan’s oratory which is said to have been erected overtop the remains of the saint. There is also a 12th century round tower which is in beautiful shape. It’s about 100 feet high, which is typical for round towers. Human remains were found facing east below the Ardmore’s round tower, which indicates that it was built over graves in a graveyard. There’s a sorrowful tale associated with the round tower. It was a refuge for Irish being pursued by English forces. About 20 of them were holed up in the tower on various floors. They surrendered and were all hanged. There’s also a roofless 13th-century church ruin with a giant 8th century carving from an earlier church attached to the gable wall. The carving nearly spans the width of the gable wall and the designs are similar to what you see on high crosses. There’s an image of Adam and Eve, Gift of the Magi and of the Judgement of Solomon. These were likely used for teaching the local people about the faith. I stood in front of the Gable wall and pointed out the carving to my tour group and they like most visitors, thought the carvings were beautiful. But when I told the story of the Judgement of Solomon to the group in front of the carving, there was a moment of transformation. I said … "You remember the story. Two women claim to be mother to the same baby and they go to King Solomon to get him to resolve the matter. King Solomon said, since you two can’t agree, I will cut the baby in half and give each of you a share. He called for his swordsman to do the deed and one of the women cried out, 'No. Don’t. The child is not mine.' And pointing to the other woman said, 'She is the real mother.' Solomon in his wisdom knew that this woman who was speaking had to be the baby’s rightful mother because only a mother’s love would be so unselfish as to sacrifice her own her own happiness and endure almost unbearable sorrow in order to save her child. So, Solomon made his judgment and gave the child to the woman who cried out. At the end of the story, the etched images in the gable wall seemed to have so much more depth, meaning. There’s something about marrying the spoken word of a sacred story to a physical image that represents the story. Something greater than the sum of those two elements grows. It becomes an experience. One of the guests said she imagined the artist, what he was thinking as he carved those images so long ago - - and she wondered if he ever imagined people would be admiring his work ten centuries after he carved it. It was such a powerful moment for all of us. Inside the church ruins in a little niche is a very well-preserved ogham stone. This is a tall stone with old Irish writing that consists of etch marks along the sides. These were often personal inscriptions… the name of the person etching the stone – a mark of memory to leave behind. Ardmore may not be one of the top sights that pilgrims seek out, but it’s every bit as powerful as the other sacred sites. Thank you for listening to the Thin Places Travel Podcast. You can find us on the web at thinplacespodcast.com. You can also find me on twitter at @travelhags and facebook.com/thinplaces.

The newest crop of Minnesota Fightin' Vikings have been harvested. We recap the wild three days of trades, head scratching moves, and where the 8 draft picks (and undrafted free agents) will fit in with the Vikes. 1. (30) Mike Hughes, CB - Central Florida 2. (62) Brian O’Neill, OT - Pittsburgh 4. (102) Jalyn Holmes, DE - Ohio State 5. (157) Tyler Conklin, TE - Central Michigan 5. (167) Daniel Carlson, K - Auburn 6. (213) Colby Gossett, G - Appalachian State 6. (218) Ade Aruna, DE - Tulane 7. (225) Devante Downs, LB - CAL All that and more "FRESH FISH" chatter on this edition of the Purple FTW! Podcast! A Carlson Digital Joint Twitter: http://twitter.com/purpleforthewin Facebook: https://www.facebook.com/purpleftwpodcast/ Instagram: https://www.instagram.com/purpleftwpodcast/ Website: http://purpleftw.com iTunes: http://purpleftw.com/itunes 1500ESPN: http://www.1500espn.com/tag/andy-carlson/ PodcastOne: http://www.podcastone.com/purple-ftw Stitcher: http://purpleftw.com/stitcher iHeart Radio: http://www.iheart.com/show/263-Purple-FTW-Podcast/ YouTube: https://www.youtube.com/c/purpleftwpodcast https://www.youtube.com/channel/UC6Xt29Fi1ES6C1fEtWFUFIw?sub_confirmation=1 Bookmark us on Amazon & show some love! http://purpleftw.com/amazon Music for the Purple FTW! podcast is created by & produced by deeB. To hear more of his tracks, check out http://soundcloud.com/deeb

20170716 Everyday Ordinary Lives: David's Worship (Brian O'Neill) by Every Nation Somerset West

Brian Oneill has been a product designer for more than twenty years and in the last ten years has been an independent consultant and started his company Designing For Analytics last year. Brian has helped designed products for companies ranging from startups to enterprises including NetApp, TripAdvisor, Infinio, Fidelity, and DataXu.   In this episode, Brian talks about:   The differences between UI and UX and what the role of the product designer is   How to measure the user experience and go about discovering UX issues   Common mistakes he sees people make   How being a musician influences the way he approaches product design   Links from today’s episode:   Designing For Analytics   How to Self-Assess the UI/UX Design of Products Using Analytics   Contact Brian   Brian on Twitter   Harvest   Waze   Kyruus   Dispatch   Jonathan Stark   Brennan Dunn   Jared M. Spool   Sketch and Invision   Sketching User Experiences   Beautiful Evidence   If you liked this episode:   Follow the podcast on Twitter   Subscribe on iTunes or your podcast app and write a review Get in touch with feedback, ideas, or to say hi: nic {AT} startupbostonpodcast [DOT] com   Music by: Mr Ho’s Orchestrotica  

Rochester has a rocking art scene, and we discuss it in this episode. Fun fact: The Little Cafe has a new art gallery every month! October artists Brian O’Neill, Suzi Zefting-Kuhn and Diane Bellenger join Movies and a Microphone to discuss their three-person exhibit: Wild Things - Animals in Art. Curator Zanne Brunner also joins the fun, and previews upcoming Little galleries.

After reading Brian O'Neill's play, Flat and Gently Sloping Toward the Bay, actors Skipp Sudduth and Kohl Sudduth join Brian and Chris in remembering Brian's late brother, Jimmy, and Skipp's odd fascination with lucky pennies.

Episode 6 features the works Flat & Gently Sloping Toward the Bay, by Brian O'Neill, and You Haven't Changed a Bit, by Donna Hoke. Casts include Skipp Sudduth, Kohl Sudduth, Nancy Johnston, and Bill McHugh.

Outtakes from Amy's Horse Episode 3 The full version of the discussion of why Joe Boover was in Florida. With Chris Flockton, David Manis, Brian O’Neill, Wally Dunn, Joe Boover, Andrea Lynn Green, and Tracy Sallows.

Episode 3 features the works, Walmart Comes To Our Town, by Mort Milder, and Fly Home In My Dreams, by Jason Furlani. The casts include David Manis, Brian O’Neill, Wally Dunn, Joe Boover, Andrea Lynn Green, Tracy Sallows, Dena Tyler, and Margaret Ladd. Recorded live from different locations in Vermont, New York, and Florida.

Episode 2 features the works, The Card, by Boston playwright, Michele Markarian, and The Day And The Hour by New York actor and writer, Tracy Sallows.   The casts include Scott Schafer, Melinda Buckley, Tracy Sallows, and Brian O’Neill, recorded live from different New York City locations.

Episode 1 features the works, Ruth Judges The Non-Fiction Humor Novelist, by author and syndicated humor writer, B. Elwin Sherman, and Of Your Peers, by New York playwright, Andrew Dolan.   The casts include Brian O’Neill, Jason Kravits, JoAnna Rhinehart, Channing Jackson, and Chris Henry Coffey, all recorded live from different New York City locations.

This episode of InConversation features Mark Gaster and Brian O'Neill, two of the three co-directors of 'How to be Happy'(along with Michael Rob Costine). The feature film is written by award winning writer/director, Conor Horgan ('One Hundred Mornings'). The development of the script was a collaborative effort between Conor and the students of the Filmbase/Staffordshire University MSc Digital Feature Film Production Course.

Brian O'Neill reads "Winter Run" and "Joe, Born 1895 Near Bean Blossom Creek, Indiana."

Brian O'Neill reads his poems "Late March," "The Stock Girl," and "Revise, Revise."

Bloomington-based poet Brian O'Neill reads "After a Long Drought (for Polymer)" and "Sodbusters."

Summary Designer Brian O'Neill tells me what it takes to make a well designed piece of software. Details who he is and what he does; role as a designer vs developer; how to find out what is needed, getting feedback, including engineers in feedback process; what is great design, invisible interface, task flow, google as an example of good design, good task flow example, db tables should not dictate the view; who is responsible for good design; bridging the gap between designers and developers, learning design; steps in making a good design from the perspective of a designer and an engineer, laddering, sketch on whiteboards rather than using fancy software, user testing; why not to start from the data model; flexibility vs usability; engineers should be involved in user testing, self reflection; agile, incrementing rather than iterating, lack of user representative is common, design runway – designers stay ahead of engineers by a sprint, validation loops, don't worry about what people like about an interface only what they do; definitions of success from different perspectives; working as an insider rather than as an external contractor; conflicts between engineers and designers, justifying decision making and intuition, sum of design errors reflect on overall product, building respect between engineers and designers; just because the big boys do it doesn't mean you should; Brian's music; author recommendations, Edward Tufte, Stephen Few.

Dr Brian O'Neill discusses DIT research on how young people in the EU are using the internet.

Guest Brian O'Neill, leader of Mr. Ho's Orchestrotica talks about his newest albums, plus new issued exotica

We talk to Brian O'Neill QC, who took time out of his busy Old Bailey schedule to share his experiences with us. We also hear from Admissions Tutor and Law Lecturer Christine Riefa about the type of student she's looking for and the type of course offered here at Brunel. Current Law student Evelyn Asuen also pops into the pod to say hello. Visit http://www.brunel.ac.uk/law Brian O'Neill's profile can be found here http://www.2harecourt.com Voices: Admissions Tutor and Law Lecturer - Christine Riefa Current Law Student - Evelyn Asuen Brunel Law Alumnus - Brian O'Neill QC Presented by Adam Larking of LittleSmasher.com Links: http://brunel.ac.uk http://brunel.ac.uk/courses Postal Address for Enquiries: Course Enquiries Office Brunel University Uxbridge UB8 3PH Telephone Number for Enquiries: +44(0)1895 265 935 Virtual Open Day: http://brunel.ac.uk/VirtualOpenDay Email: podcast@brunel.ac.uk http://brunel.ac.uk/podcast

We talk to Brian O'Neill QC, who took time out of his busy Old Bailey schedule to share his experiences with us. We also hear from Admissions Tutor and Law Lecturer Christine Riefa about the type of student she's looking for and the type of course offered here at Brunel. Current Law student Evelyn Asuen also pops into the pod to say hello. Visit http://www.brunel.ac.uk/law Brian O'Neill's profile can be found here http://www.2harecourt.com Voices: Admissions Tutor and Law Lecturer - Christine Riefa Current Law Student - Evelyn Asuen Brunel Law Alumnus - Brian O'Neill QC Presented by Adam Larking of LittleSmasher.com Links: http://brunel.ac.uk http://brunel.ac.uk/courses Postal Address for Enquiries: Course Enquiries Office Brunel University Uxbridge UB8 3PH Telephone Number for Enquiries: +44(0)1895 265 935 Virtual Open Day: http://brunel.ac.uk/VirtualOpenDay Email: podcast@brunel.ac.uk http://brunel.ac.uk/podcast

Gerald Costanzo discusses the history of the Carnegie Mellon University Press, what the future holds and Brian O'Neill's record-setting book, “The Paris of Appalachia: Pittsburgh in the Twenty-First Century.”