Podcasts about dashboards

WHAT YOU'LL LEARN Why retail is now a demand chain, not a supply chain How AMRs deliver 6–12 month ROI in high-variability e-commerce Why robotics-as-a-service changes peak capacity planning The real bottleneck in AI adoption: structured WMS data Why dashboards are dying and exception-based orchestration is rising How consolidation will reshape 3PL economics Why operational excellence remains the ultimate differentiator HIGHLIGHTS 00:01–00:12 | Consumer expectations and the “fast + free + cheap” reality 00:12–00:15 | AMRs, ASRS, RaaS, and 6–12 month automation ROI 00:15–00:16 | Buy vs build: what's commodity vs “secret sauce” 00:16–00:19 | Agentic AI in warehouse ops: labor planning + execution 00:19–00:22 | AI proof, case studies, and demand planning as the next frontier 00:22–00:24 | Dashboards vs operators: turning analytics into actions 00:24–00:28 | Operator advice: efficiency, mechanization, and competition shifts 00:29–00:31 | Manifest trends: retail channels evolving + tech-driven 3PL future QUOTES  [00:04:10] “One of the biggest changes is you used to have a choice. You could either have it fast, you could have it free, or you could have it cheap. The consumer today wants all three.” – Jeff Wolpov [00:05:10] “We as logistics supply chain companies need to lean in and figure out how to do more with less. Today it's a necessity.” – Jeff Wolpov [00:07:30] “You need automation... We need to be faster and more flexible. Peaks have gotten much higher.” – Jeff Wolpov [00:16:00] "The hard part isn't building AI or using AI. It's what do you do with the results?" - Gary Allen [00:16:50] “Operators shouldn't hunt dashboards, they should get alerts, exception-based triggers. AI takes analytics to the next level.” – Gary Allen [00:23:00] "Reporting is the death of analytics." - Gary Allen  ABOUT THE GUESTS Jeff Wolpov Jeff Wolpov is Senior Vice President of E-commerce and Ryder Last Mile at Ryder System, Inc., where he leads the vision and strategy for omnichannel fulfillment and big & bulky home delivery. Previously, he served as CEO of Whiplash (formerly Port Logistics Group), achieving nearly 30% year-over-year revenue growth before its acquisition by Ryder in 2022. Earlier in his career, Jeff founded Distribution Solutions, scaling it from a startup into a $50 million regional logistics firm that became the foundation of Whiplash's national network. He holds a degree from the University of Michigan. Gary Allen Gary Allen is Vice President of Supply Chain Excellence at Ryder, overseeing Solution Design, Continuous Improvement, Data Analytics, and Automation across the supply chain organization. With more than 32 years of experience, he previously led EY's logistics consulting practice and held leadership roles at DHL and FedEx in product innovation, solution design, sustainability, and operations. Gary helped launch and co-author the “Annual Third Party Logistics Study” with Dr. John Langley of Penn State University and holds a Bachelor of Arts in Materials and Logistics Management from Michigan State University. LINKS MENTIONED Ryder report: https://www.ryder.com/en-us/insights/white-papers/e-comm/2025-ryder-e-commerce-consumer-study Ryder website: https://www.ryder.com/en-us Subscribe and Keep Learning!If you're a logistics leader looking to scale sustainably, don't miss out! Subscribe for more expert strategies on tackling modern supply chain challenges.Be sure to follow and tag the eCom Logistics Podcast on LinkedIn and YouTube

Link zum Buch: https://www.kaiuwestahl.com/download-buch-aiordie/ Seit über 15 Jahren bauen wir Dashboards. Von den ersten BI-Projekten mit absurden Ladezeiten bis zu modernen Tools wie Power BI und SAP Analytics Cloud. Und trotzdem stellt sich heute wieder eine provokante Frage: Brauchen wir Dashboards überhaupt noch – oder übernimmt KI jetzt alles? In dieser Folge sprechen Andreas Wiener und Kai-Uwe Stahl über eine der zentralen Disziplinen der datengetriebenen Unternehmenssteuerung. Sie blicken zurück auf die Entwicklung des Dashboardings, auf die größten Missverständnisse in Unternehmen und auf die Rolle, die KI künftig spielen wird. Dabei wird eines deutlich: Viele Unternehmen springen heute direkt auf den KI-Hype – ohne ihre Hausaufgaben gemacht zu haben. Denn bevor KI wirklich Mehrwert liefern kann, müssen Unternehmen ihre Zahlen kennen. Und genau dafür bleiben Dashboards unverzichtbar. In der Folge geht es unter anderem um: • Die Evolution von Dashboarding in den letzten 15 Jahren • Warum Tools heute kaum noch der entscheidende Faktor sind • Weshalb viele Unternehmen den falschen Fokus auf Self-Service-Analytics legen • Warum Standard-Reporting oft mehr bringt als komplexe Analyseumgebungen • Wie KI künftig die tiefe Analyse übernimmt – während Dashboards das Monitoring liefern Die klare Botschaft dieser Episode: KI ersetzt Dashboards nicht. Aber sie verändert, wofür wir sie nutzen. Wer seine Daten nicht im Griff hat, wird auch mit KI keine besseren Entscheidungen treffen.  ⸻ Timestamps 00:00 – Intro: 15 Jahre Dashboarding 00:54 – Was ist eigentlich ein Dashboard? 01:32 – Warum Monitoring-Dashboards unverzichtbar bleiben 02:53 – Das Buch und Feedback aus Unternehmen 05:12 – Warum viele Berater dem falschen Hype folgen 07:35 – Neue Hausaufgaben: Dashboards statt nur Datenqualität 10:03 – Die Anfänge: Dashboarding mit Excel und PowerPoint 11:15 – Erste BI-Tools und extrem lange Ladezeiten 13:22 – Erste große Projekte und technologische Entwicklung 14:32 – Warum viele Unternehmen Dashboarding nie richtig umgesetzt haben 15:52 – Warum klassische Trainings oft nicht funktionieren 18:29 – Online-Kurse vs. Präsenzschulungen 19:10 – Power BI als Gamechanger im Dashboarding 20:34 – Tableau, Visual Analytics und der Visualisierungstrend 21:22 – Warum sich der Markt auf wenige Tools konzentriert 23:38 – Konsolidierung im BI-Markt 25:09 – Datenvisualisierung und Storytelling im Dashboard 26:00 – Self-Service Analytics: Realität vs. Wunschdenken 27:08 – Wo KI künftig die Analyse übernimmt 28:21 – Fazit: Dashboards bleiben ein zentraler Baustein der Datenstrategie

AI Is the Tool. The Fundamentals Still Win. Welcome to this episode of the podcast. In this session, I want to reset how we think about artificial intelligence and small business. I am positive about AI. I believe it will be one of the biggest shifts small business owners experience over the next few years. But not for the reasons most people are being sold. The Real Mistake Small Businesses Are Making Everyone is rushing to integrate AI into systems and processes. Automation. Dashboards. Workflows. Platforms. That is fine. But it misses the bigger point. As I mentioned in the last podcast, the real advantage for small business owners is focusing on what does not change. What Keeps Changing in Business Business never stands still. Legislation changes Employment law evolves Marketing channels rise and fall Technology updates constantly The way work gets done keeps shifting This has always been true. What Does Not Change The fundamentals. Customers still want problems solved. Sales still rely on trust. Cash flow still matters. Clear thinking still beats busy activity. Good decisions still outperform clever tools. These things are constant. The Carpenter Analogy Think about a carpenter. A hundred years ago, they used: Straight edges Measuring tapes Hammers and chisels Today, they use: Lasers and mobile phone measuring tools Battery-powered equipment Automated machinery The tools have changed completely. The job has not. They still turn up every day to build something solid that fits and lasts. AI sits in exactly the same place. It is machinery. Not the craft. Why Business Owners Get Stuck Most people do not stop to think. They keep working through problems. They hope clarity will appear later. It rarely does. Busyness creates noise. Noise hides the real issue. The problem grows instead of shrinking. Where AI Actually Helps Used properly, AI supports thinking. It helps you: Step back from the noise Question assumptions Test ideas safely See simpler routes forward But only if you stay grounded in the fundamentals. The Core Message Forget the hype. Forget the panic. Forget the race to automate everything. AI is just another tool. The fundamentals still do the heavy lifting. Get those right and AI helps. Get them wrong and no system will save you. Need a Way Forward? If you feel stuck, overwhelmed, or buried in noise, you already know something needs to change. You can find out more about me at: https://www.therichardsmith.com If you need hands-on help with your small business, visit: https://smallbusinessninja.co.uk Get In Touch Please enable JavaScript in your browser to complete this form.Name *Email *Subject *Comment or Message *PhoneSend Message

“Wir wollen unser Marketing skalieren und dafür brauchen wir Daten”. Ja, absolut korrekt - meine volle Zustimmung! Aber Wachstum braucht noch viel mehr als einfach nur Daten. Damit Daten wirklich auf die Marketing-Strategie einzahlen und Wachstum supporten kann, braucht es einen strukturierten Prozess: von der Definition von KPIs über das Tracking, Kampagnen-Monitoring, Insights und Aussteuerung - alles muss ineinander greifen. In dieser Folge spreche ich mit Hannes Krause, Paid Media Experte mit 10+ Jahren Erfahrung und Gründer von Rabau:x Media. Rabau:x Media ist eine Paid Media Agentur, die darauf spezialisiert ist, große Media Budgets und komplexe Kampagnen zu betreuen. Hannes Fokus liegt also nicht darauf, die ersten Experimente zu starten, sondern ganz klar darauf, den Überblick über die Budgets und die Performance in komplexen Kampagnen-Setup zu behalten und jede Stellschraube zu finden, an der noch gedreht werden kann. Und wie nicht anders zu erwarten: Das geht nur mit Daten! Wir sprechen darüber: - warum es ein daten-basiertes Framework für das Media Management braucht - wie der Prozess konkret aussieht (von Planung über Monitoring bis Insights) - wie Daten die Kommunikation mit Stakeholdern wahnsinnig vereinfachen - wie KPIs, KPI trees und “North Star” Metriken wirklich effektiv werden Dieser Prozess ist deswegen so wertvoll, weil er datenbasierte Entscheidungen ermöglicht und weil er eine gemeinsame Kommunikationsgrundlage im Unternehmen bietet - und das ist es, was am Ende den Outcome bringt. Timestamps: (00:00) - Intro und Vorstellung von Hannes (02:52) - Die Bedeutung einer Jahresstrategie (05:49) - Leitplanken für strategisches Handeln (08:57) - Fallstudie: Umsatzoptimierung vs. Marge (11:51) - Kommunikationsprobleme und KPI-Transparenz (14:58) - Stakeholder-Management und Zieldefinition (17:44) - Datenanalyse und Automatisierung (20:46) - Dashboards und KPI-Überwachung (23:50) - Herausforderungen und Verbesserungspotenziale (26:58) - Zukunft der Datenanalyse und KI-Einsatz (29:47) - Abschluss und Tipps für Marketing-Teams Hier findest du Hannes Krause auf Linkedin: [https://www.linkedin.com/in/hannes-krause-rabaux-media/](https://www.linkedin.com/in/hannes-krause-rabaux-media/) Connecte dich mit mir auf LinkedIn: [https://www.linkedin.com/in/mlmatysik/](https://www.linkedin.com/in/mlmatysik/) Unsere Website findest du hier: [https://analyticsfreaks.com/](https://analyticsfreaks.com/) Ich freu mich immer über Anmerkungen, Fragen oder einfach deine Gedanken zum Podcast! :) Schreib mir gern eine Mail an marialena.matysik@analyticsfreaks.com oder auf Linkedin [https://www.linkedin.com/in/mlmatysik/](https://www.linkedin.com/in/mlmatysik/)

Welcome back to the Multifamily Collective with Mike Brewer.Today's operations tip delivers a clear message:Dashboards are tools — not operators.You can stare at data all day, but until a human takes action, your property won't move an inch.Mike explores:Why dashboards only highlight, not solveThe danger of outsourcing leadership judgment to softwareHow dashboards support prioritization, but not decision-makingWhy context, nuance, and empathy still belong to humansHow engaged leadership turns dashboards into leverage — not crutchesIt's tempting to say, “That's what the numbers said.”But smart operators stay curious, ask better questions, and take responsibility for the outcomes.Dashboards are only as powerful as the leaders interpreting them.This is one of many tips being compiled into a 2027 desk reference for multifamily professionals who are serious about leading with intention.MultifamilyCollective Blog: https://www.multifamilycollective.comThe Daily Collective Book: https://amzn.to/3YI6BDaHosted by: https://www.multifamilymedianetwork.com

What's on your mind? Let CX Passport know...Technology is loud. Agentic AI. Automation. Platforms. Dashboards.Meanwhile, the person who greets the customer at the door still determines whether that experience succeeds.April Sabral spent more than 30 years leading over 350 physical retail stores. In this episode, she explains why the answers to better customer experience aren't sitting in a conference room … they're already in the field.And y'all will not want to miss the Starbucks name-on-the-cup story … including how it started in a Miami Beach store and solved a real operational problem overnight.What You'll LearnWhy frontline managers … not technology … determine store performanceHow the Starbucks “name on the cup” idea started as a simple operational fixThe danger of promoting high performers without leadership trainingWhy skill-building beats “just be friendly” every timeThe leadership test: If you left your job … would your team follow you?CHAPTERS00:00 Introduction to April Sabral02:00 Where the CX conversation misses reality05:00 The Starbucks name-on-the-cup origin story08:20 Why simple solutions outperform complex tech10:40 Bridging the gap between field and head office14:15 What actually makes in-store CX work19:40 Process discipline vs. customer experience23:40 Would your team follow you?26:00 Why retail promotes too fast29:00 The future of physical retail in an AI world31:00 How to connect with AprilGuest LinksWebsite: https://www.aprilsabral.com/Listen: https://www.cxpassport.comWatch: https://www.youtube.com/@cxpassportNewsletter: https://cxpassport.kit.com/signupI'm Rick Denton and I believe the best meals are served outside and require a passport.Disclaimer: This podcast is for informational and entertainment purposes only. The views and opinions expressed are those of the hosts and guests and should not be taken as legal, financial, or professional advice. Always consult with a qualified attorney, financial advisor, or other professional regarding your specific situation. The opinions expressed by guests are solely theirs and do not necessarily represent the views or positions of the host(s).

Das Burj Khalifa in Dubai: 828 Meter hoch, das höchste Gebäude der Welt. Während alle fasziniert nach oben blicken, übersehen sie das wahre Meisterwerk: 200 Betonsäulen, 70 Meter unter dem Meeresspiegel. Ohne sie? Keine 828 Meter. Bei BI-Projekten ein ähnliches Bild: Alle wollen in die 163. Etage – schicke Dashboards, Self-Service, KI. Aber nur wenige denken ans Fundament. Das Ergebnis: Die Fassade glänzt – aber die Datenstrategie steht auf Sand. Wer direkt mit Dashboards startet, bastelt schnelle Provisorien. Wer mit Datenstrategie, Architektur und Governance beginnt, baut stabil. Fundament vor Fassade.

As a leader, you can use AI to turn raw data into clear dashboards, spot patterns in customer feedback, and monitor performance. That's powerful, and you should be using AI for that. But the next step – getting AI to make decisions for you – is a step too far. Use AI to inform your thinking, not to do your thinking for you.https://swiy.co/go-dashboards-not-decisionsAs a leader, how are you planning to use AI in 2026, and how are you planning not to use AI? AI is evolving so quickly you need to keep both of those things in mind.My very first job was as a software developer, working for a small company in Perth that was subcontracted to large companies – for example, in the mining industry. Our software monitored their equipment, reported faults, and transferred data into their databases.My first work trip was to a cable station in a remote corner of Hong Kong Island, overseeing the installation of our system to monitor the lasers in an undersea optical fibre cable between Hong Kong and Taiwan.Every day at that cable station, I saw our customer do the same thing when he walked in: He greeted us, then walked over to the printout of the error report over the last 24 hours, hoping there would be zero errors from all the lasers.Why? Because even a single error was a signal to alert his boss, and the team would then keep watch for a few days for more errors. The worst case scenario was a laser that was likely to fail, because it meant sending a ship out to sea, dragging for the cable from the ocean floor, pulling it up, breaking it, replacing the laser, and then dropping it down again. This could cost thousands – or hundreds of thousands – of dollars.That error report was just a big matrix of errors from all the lasers over the last 24 hours (think of it like printing an Excel spreadsheet).So what does this have to do with AI now?That report, which thirty five years ago was just a paper printout on a dot matrix printer, is what we would now call a dashboard. And with AI, somebody without much technical skill can use AI to create a dashboard from their data.They don't have to hire a tech company.They don't have to ask their IT team.They don't have to wait weeks, months, or years for it to be ready.They can do it NOW. With AI, they might even be able to do it themselves.It could be equipment error data.Or site safety data.Or sentiment feedback on social media.Or patient data from medical devices.Or ongoing equipment monitoring.Or workplace data showing employee engagement or office use.I want to make two points about this use of AI.First, AI has reached the point where even non-technical people (like you!) can create those sorts of reports and dashboards.And you should.Second, you're using AI to create a dashboard to help you make better decisions. It's NOT to use AI to make those decisions FOR you.I'm emphasising this because AI HAS evolved to the point where an AI autonomous agent could make decisions for you based on data. It doesn't need the dashboard; it just monitors the data, gathers the results, and makes the decision.But this is not the way to use AI now. Just because you can doesn't mean you should.And in this case, you shouldn't.Thirty five years ago, when my customer and his bosses examined the report, THEY made the decision about when to bite the bullet and send out a ship. In theory, now AI could make that decision, but it shouldn't.Use AI for dashboards, not decisions.For more about AI do's and don'ts for 2026, join my online presentation about AI for leaders in 2026. It's free, public, and open to all.Register for the virtual masterclass:https://swiy.co/go-dashboards-not-decisions Hosted on Acast. See acast.com/privacy for more information.

There's an easy button for hard conversations now, and it's dangerously good. You've got something complicated to say. It needs nuance. It needs empathy. It probably needs a little courage. The AI will draft the whole thing in seconds. It sounds smart. It sounds reasonable. You skim it. You send it. And most of the time, nothing bad happens. The problem is that the time it does go bad is the exact situation where you thought you were being thoughtful. This week's Raw Data walks straight through one of those moments, from both sides of the exchange, and it's a reminder that outsourcing the structure of your thinking is not the same thing as being clear. Then there's the part that's almost more interesting. Thirteen years ago, the first real client engagement couldn't get traction around dashboards. The connection between "this is my business" and "data should change how I run it" just didn't stick. Same people, same company, different conversation recently around AI. Immediate traction. Leaning forward. Connecting dots in real time. That difference isn't about better slides or better storytelling. Dashboards improved a slice of the business. AI shows up in the messy motion of the whole thing. In workflows. In manual processes. In strategic questions leaders don't have time to chase down. That shift in surface area changes everything. AI isn't a toy and it isn't a ghostwriter. It's leverage. Real leverage. The kind that can remove friction across an organization faster than dashboards ever could. But leverage only works if you're still the one steering. That's really what this episode comes down to. Listen in, then decide where AI belongs in your workflow and where it needs to stay out of your head.

Organizations are moving fast on AI. New tools are being piloted. Hackathons are being hosted. Dashboards are lighting up with sentiment data, productivity metrics, collaboration trends, and predictive signals.But most companies are missing the harder question: who owns the output?AI can surface cultural risk, burnout signals, innovation pockets, communication breakdowns, pipeline friction, and brand perception shifts. That part is getting easier by the day. What remains rare is structured accountability for turning those signals into operational change.This conversation challenges HR and executive leaders to rethink AI adoption beyond installation. It explores why many AI initiatives lose momentum after the demo, why insight without ownership becomes noise, and why every meaningful AI deployment requires a defined six-month execution layer tied to measurable outcomes.The future of AI in large organizations won't be defined by model sophistication. It will be defined by whether leaders build the infrastructure, roles, and decision authority required to translate intelligence into behavior change.The tool is not the transformation. The operational discipline behind it is.

In this episode, I talk with Amanda Makulec about what it really takes to design dashboards and data products that people can understand and use. We dig into why so many dashboards fail, how designers and analysts often misjudge their audiences, and what it means to take a truly human-centered approach to data visualization. Amanda shares insights from her work leading the Data Visualization Society and from her book, including practical ways to think about context, cognition, and decision-making. We also discuss common misconceptions about dashboards, stakeholder expectations, and the gap between technical correctness and real-world usefulness. This conversation is packed with ideas for anyone building data tools meant to inform decisions, not just look impressive.Subscribe to the PolicyViz Podcast wherever you get your podcasts.Become a patron of the PolicyViz Podcast for as little as a buck a monthPick up the new book, Dashboards That Deliver.Follow me on Instagram, LinkedIn, Substack, Twitter, Website, YouTubeEmail: jon@policyviz.com

Manufacturers do not have a data problem. They have an execution gap. The dashboards exist. The reports are generated. The KPIs are reviewed. Yet too often, action stalls between insight and impact. In this episode, Jan Griffiths and Tom Roberts sit down with Zack Sosebee, SVP of Operations & Customer Success at Redzone, to explore what changes when data moves beyond visibility and into the hands of the people closest to the work.Zack shares a clear and practical vision of the connected workforce. Not as another layer of software. Not as another reporting system. But as a system of action. By giving frontline operators simple, real-time visibility through red, yellow, and green performance signals, manufacturers create clarity in the moment decisions are being made. That clarity builds accountability. And accountability drives results.What makes this approach powerful is its simplicity. Instead of overwhelming teams with endless metrics, Redzone focuses on a few meaningful signals that operators can influence hour by hour. When teams see performance in real time, they respond in real time. Maintenance is called sooner. Problems are escalated faster. Peer-to-peer competition becomes a positive force. Execution accelerates because ownership shifts to the frontline.But technology alone does not transform a factory. Coaching does. Zack explains how culture change happens when leaders reinforce new behaviors, close feedback loops, and respond quickly to issues raised by operators. When a long-tenured employee logs a safety concern and sees it fixed the same day, trust is built. When a retiring expert captures knowledge that strengthens the next generation, pride returns to the shop floor. These are not software wins. They are human wins.This conversation is a reminder that digital transformation is not about collecting more data. It is about empowering people to act with confidence and clarity. When operators think like supervisors and supervisors think like leaders, performance improves. More importantly, culture evolves. And in today's manufacturing environment, the companies that win will be the ones that move from reporting yesterday to deciding what happens next.Themes Discussed in This EpisodeWhat “connected workforce” really means in manufacturingWhy digital transformation often stalls at dashboardsOverall Equipment Effectiveness explained in simple termsRed, yellow, green real-time visibility on the shop floorCoaching vs training in culture changeTurning skeptics into championsEliminating paper logs and manual downtime reportingUsing simplicity to accelerate adoptionTechnology as an enabler of ownership, not oversightEmpowering operators to think like leadersFeatured GuestName: Zack SosebeeTitle: SVP Operations & Customer Success, RedzoneAbout: Zack is Senior VP of Operations & Customer Success at

This week's guest says we need to be careful if our focus is on our status indicators always showing green. If having a green dashboard is more important than your resilience capability, you could be at risk of sleepwalking into a crisis.   Hello everyone and welcome to episode 222 of the Resilient Journey Podcast, presented by Anesis Consulting Group!   This week we are joined by resilience industry icon Terry Downing. Terry catches us up with some of the excellent work he's doing writing articles on LinkedIn and his new podcast - "Resilience By Default". Terry and Mark talk about why business continuity and operational resilience programs fail. He emphasizes the need for senior executive leadership engagement. And he says that a green dashboard isn't the sign of resilience, it's the sign of fear. But Terry doesn't leave it there - he provides great advice for what we can do about it.   =============================================================== Be sure to follow The Resilient Journey!  We sure do appreciate it! Check out the Resilient Journey Hub! Want to learn more about Mark? Click here or on LinkedIn. Special thanks to Bensound for the music.

Guest post by Crystel Robbins Rynne, CEO, HRLocker Irish SMEs are no strangers to pressure. They are the backbone of the economy, the employers of local communities, and the innovators driving Ireland's next wave of growth. Yet beneath that resilience lies a quieter, more pervasive anxiety. It surfaced clearly in HRLocker's recent research. As revealed in our Irish SME HR Report 2025, three-quarters (74%) of Irish SMEs fear they would fail a surprise Workplace Relations Commission (WRC) inspection. That figure is not about negligence. It is about confidence. Or more accurately, the lack of it. And it signals that the compliance burden on SMEs has reached a tipping point. The Confidence Gap: Why Good Businesses Still Feel Exposed Most SMEs want to do the right thing. They want fair contracts, accurate time records, transparent policies, and safe workplaces. But intent alone does not create compliance readiness. The reality is that many SMEs are operating with: Outdated or inconsistent employment contracts Patchy training records Manual time tracking that does not reflect modern hybrid work Policies stored across inboxes, desktops, and filing cabinets HR processes that rely on one overstretched person remembering everything This is not a failure of leadership. It is a failure of bandwidth. When regulations evolve quickly, inspections become more rigorous, and hybrid work adds new layers of complexity, SMEs often lack the internal infrastructure to keep pace. The result is a growing sense of audit anxiety. A fear that something important has slipped through the cracks. The Emotional Toll of Compliance Uncertainty Compliance is not just a legal obligation. It is an emotional one. For founders and HR leads, low confidence shows up as worry about reputational damage, fear of fines or enforcement actions, stress around documentation gaps, and sleepless nights before audits. When compliance becomes a source of dread, it drains energy from the work that actually grows a business. Innovation, culture, and customer experience all take a hit. Why Technology Is the Turning Point The good news is that the confidence gap is not inevitable. It is structural, and structural problems can be solved. HR technology is transforming compliance from a reactive scramble into a proactive and predictable process. The shift is significant. 1. Audit readiness becomes automatic. Modern HR platforms centralise contracts, policies, training records, and time data in one secure system. Version control, digital signatures, and automated updates give SMEs clarity about where they stand. 2. Gaps surface before they become liabilities. Dashboards highlight missing documents, expired certifications, or overdue reviews. Issues can be addressed long before an inspection. 3. Hybrid work becomes compliant by design. Accurate time tracking, remote attendance logs, and digital leave management remove the guesswork from flexible work arrangements. 4. Documentation becomes a strength, not a stressor. With everything stored, searchable, and timestamped, SMEs can demonstrate compliance with confidence rather than hope. 5. Leaders reclaim headspace. When the administrative burden lifts, founders and HR teams can focus on people, culture, and strategy. The Irish Context: Why Local Matters Ireland's regulatory landscape is unique. WRC inspections, GDPR obligations, and the rapid shift to hybrid work have created a compliance environment that is both demanding and fast-moving. The pace of change has been extraordinary. In the past three years, Irish employers have navigated statutory sick leave, auto-enrolment pensions, the right to request remote and flexible working, gender pay gap reporting, and domestic violence leave, with pay transparency requirements now on the horizon. Parental leave entitlements have also expanded. Each change, even when welcome, adds another layer of documentation, policy updates, and process adjustments. For SMEs that are already stretched thin, k...

Konzernen sagt man oft nach, dass sie bürokratisch, kompliziert und behäbig sind. Keine gute Voraussetzung für schnelles, datengetriebenes Marketing … könnte man jedenfalls meinen. Aber das ist ein Irrtum und bei weitem nicht immer der Fall! In dieser Folge spreche ich mit Marco Jenzer, Team Lead Digital Marketing bei Würth Schweiz. Würth ist ein internationales Handelsunternehmen mit nationalen Landesgesellschaften und verkauft Schrauben (und alles andere, was Handwerksbetriebe so brauchen). Marco bringt daher eine super spannende Perspektive mit! Denn das Konzernumfeld ist in vielerlei Hinsicht komplex: viele Teams, Infrastrukturen und Best Practices. In dieser Episode geht es also darum, wie Marketing-Teams es schaffen, Komplexität zu reduzieren und auf Basis ihrer Daten wirklich handlungsfähig zu werden - ohne Over-Engineering, ohne riesige Dashboards und super komplizierte Excel-Modelle. Wir sprechen über: - warum ein pragmatisches 80/20-Vorgehen oft der bessere Weg ist - wie sich die Konzernstruktur auf die Arbeit mit Daten auswirkt - wie Würth es schafft, Best Practices über Ländergesellschaften hinweg zu entwickeln - wie Marketing-Teams herausfinden, wo sie starten sollen - wie „Funnel Thinking“ und das “Pirate Framework” dabei helfen können Am Ende geht es darum, Komplexität zu strukturieren und herunterzubrechen - bis die Quintessenz übrig bleibt und wir wissen, was zu tun ist. Timestamps: (00:00) Einführung und Vorstellung von Marco Jenzer (01:57) Erkenntnisse aus der Arbeit mit Daten (05:56) Die Bedeutung von Daten im Marketing (09:58) Strategien zur Datenanalyse und KPI-Definition (13:51) Interdisziplinäre Zusammenarbeit und Datenverständnis (17:57) Best Practices und Lessons Learned (21:54) Zukünftige Herausforderungen und Entwicklungen (25:57) Empfehlungen für andere Teams Hier findest du Marco Jenzer auf Linkedin: [https://www.linkedin.com/in/marcojenzer/](https://www.linkedin.com/in/marcojenzer/) Connecte dich mit mir auf LinkedIn: [https://www.linkedin.com/in/mlmatysik/](https://www.linkedin.com/in/mlmatysik/) Unsere Website findest du hier: [https://analyticsfreaks.com/](https://analyticsfreaks.com/) Ich freu mich immer über Anmerkungen, Fragen oder einfach deine Gedanken zum Podcast! :) Schreib mir gern eine Mail an marialena.matysik@analyticsfreaks.com oder auf Linkedin [https://www.linkedin.com/in/mlmatysik/](https://www.linkedin.com/in/mlmatysik/)

This episode is a re-air of one of our most popular conversations, featuring insights worth revisiting. Thank you for being part of the Data Stack community. Stay up to date with the latest episodes at datastackshow.com.This week on The Data Stack Show, John welcomes back repeat-guest Ben Rogojan, Owner and Data Consultant of Seattle Data Guy. John and Ben discuss the evolving relationship between data teams and businesses, highlighting the challenges of proving value in a cost-conscious environment. Ben explores the impact of technological advancements, the rise of AI, and the critical skills data professionals need to succeed. Key insights include the importance of understanding business context, being proactive, and focusing on delivering tangible outcomes rather than just producing dashboards. Ben also emphasizes the need for data teams to communicate value effectively, show rather than tell, and be willing to take calculated risks. The conversation provides practical advice for data professionals looking to advance their careers, with a focus on developing business skills, understanding organizational needs, creating meaningful impact beyond technical expertise, and so much more. Technical Freelancer Academy & Consulting Community (1:21)Evolution of Data Teams and Technology (2:52)Data Team Growth and Output vs. Outcome (4:47)Internal Optimization vs. Client-Facing Data Work (7:23)Audience, Delivery Mechanisms, and Actionability (12:40)Proving ROI and Prioritizing Work (15:27)Practical Tips for Data Team-Business Alignment (18:31)Dealing with Vanity and Security Blanket Metrics (23:39)AI's Impact on Data Workflows (27:07)BI Tools, AI Integration, and Dashboards (32:25)Top Skills for Data Professionals (37:27)Career Growth: Technical, Communication, and Business Skills (42:02)Show, Don't Tell: Prototyping and Feedback (44:37)Taking Initiative and Risk in Data Roles (50:21)Parting Advice and Closing Thoughts (51:16)The Data Stack Show is a weekly podcast powered by RudderStack, customer data infrastructure that enables you to deliver real-time customer event data everywhere it's needed to power smarter decisions and better customer experiences. Each week, we'll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this conversation, Alon Gorbonos, General Partner and Founder of RE Angels, shares his journey from real estate operator to venture capitalist. He discusses the skills necessary for aspiring real estate operators, the challenges of transitioning to venture capital, and the importance of understanding market dynamics. Alon emphasizes the need for effective fundraising strategies, the identification of trends in real estate technology, and the significance of networking. He also provides insights into the future of real estate tech, highlighting areas of saturation and opportunity.   Takeaways   Alon Gorbonos transitioned from real estate to venture capital. Understanding market dynamics is crucial for success. Real estate is not a passive investment; it requires active involvement. Fundraising is a humbling experience for both VCs and founders. Networking and personal introductions are key to effective fundraising. AI can enhance productivity in real estate operations. The future of real estate will involve a hybrid of humans and AI. There is a need for innovative solutions in procurement processes. Founders should do their homework before pitching to investors. Real estate tech is rapidly evolving with significant opportunities.   Chapters   00:00 Introduction to Alon Gorbonos and RE Angels 02:11 Challenges in the Real Estate Journey 03:56 Becoming a Real Estate Operator 08:58 Fundraising for a Venture Fund vs. Startup 09:16 Surprises in Fundraising 12:45 Effective Fundraising Tips 14:40 Forming an Investment Thesis 17:51 Call for Ideas in Real Estate Tech 22:34 Opportunities in Under-Saturated Areas 24:37 Common Mistakes in Pitching to Investors 28:24 Possibilities of Rapid Growth in Real Estate 32:39 Future of Real Estate Tech and Networking Events  

In this episode, we explore why high ad performance numbers don't always lead to a profitable business. Matt Raminick, Founder and CEO of Sunnyside, explains how brands can grow themselves into a corner by following the wrong data. He shares why traditional metrics like ROAS can be misleading and how looking at your total bank account balance is the ultimate truth. You will learn how to use better tools to track real profit and why a brand-first approach is the secret to scaling a lifestyle business.Topics discussed in this episode:  Why a 3x ROAS might still mean losing money.How vanity metrics point brands in the wrong direction.What makes MER a cleaner way to track impact.Why ROAS is easy for media buyers to inflate.How to sync Shopify and Meta for better tracking.What "A-plus players" with brand experience offer.How a 12-month forecast ensures future profitability.Why lifestyle brands keep creative close to home.What CFO-grade tools reveal about true contribution. Links & Resources Website: https://www.sunnysidecalifornia.com/LinkedIn: https://www.linkedin.com/in/mattraminick/ Instagram: https://www.instagram.com/sunnysidecaliforniaGet access to more free resources by visiting the show notes at https://tinyurl.com/5enfjcrb______________________________________________________ LOVE THE SHOW? HERE ARE THE NEXT STEPS! Follow the podcast to get every bonus episode. Tap follow now and don't miss out! Rate & Review: Help others discover the show by rating the show on Apple Podcasts at https://tinyurl.com/ecb-apple-podcasts Join our Free Newsletter: https://newsletter.ecommercecoffeebreak.com/ Support The Show On Patreon: https://www.patreon.com/EcommerceCoffeeBreak Partner with us: https://ecommercecoffeebreak.com/partner-with-us/

Chase Warrington, Head of Operations at Doist, joined us on The Modern People Leader to break down how async-first work enables faster decision-making, stronger culture, and scalable operations. We talked about building trust without offices, the systems and rituals behind Doist's execution velocity, and why async workflows are foundational to effective AI adoption.----  Downloadable PDF with top takeaways: https://modernpeopleleader.kit.com/episode280Sponsor Links:

Research is everywhere in HR. Surveys. Dashboards. Trend reports. Predictions for what comes next.  But having more research available does not automatically mean leaders feel more confident using it. HR and compensation teams are under pressure to make decisions that are fair, competitive, and explainable, often while the market feels uncertain and noisy.  In this episode of Comp and Coffee, Ruth Thomas sits down with Stacey Harris from Sapient Insights Group and Amy Stewart from Payscale to move beyond headlines and rankings and talk about what the research is actually telling us right now.  Episode resources: Sapient Insights Group HR Systems Survey Report: https://bit.ly/4rB1zos Payscale 2026 Salary Increase Preview Report: https://bit.ly/3NWIQ8a Payscale Salary Budget Survey: https://bit.ly/4qYwlaD Payscale Pay Trends and Market Pricing Research: https://bit.ly/4kj5hk4 Email: coffee@payscale.com for listener questions and suggestions 

In this episode, I sit down with Mike Driscoll, founder of Rill Data, to discuss the evolving landscape of business intelligence and data engineering. We explore why the industry keeps "rediscovering" old concepts like the semantic layer and how the rise of AI agents is forcing us to rethink how we structure data.Mike shares his insights on the "shape" of analytics, debating whether conversational interfaces will replace dashboards or simply complement them. We also dig into the growing demand for data engineering, the importance of watermarks and temporal semantics, and why data visualization remains a critical tool for "trust but verify" in an AI world.Rill Data Mike's Podcast: Data Talks on the Rocks

In this episode of Building the Premier Accounting Firm, Roger Knecht and guest Matt Putra discuss the critical differences between budgeting and forecasting in accounting, emphasizing data-driven decision-making for e-commerce businesses. They explore how financial management, including KPIs and cash flow strategies, helps fast-growing consumer brands optimize profitability and scale effectively, with a focus on AI's transformative impact. In This Episode: 00:00 Introduction to Matt Putra and 8x 01:03 Matt's Journey to 8x and Data-Driven Decisions 02:52 Budget vs. Forecast: Key Differences 05:57 The Importance of Budgeting and Planning 08:24 Budgeting for External Stakeholders and Accountability 11:18 Lessons Learned from Ambitious Budgeting 15:00 Financial Management for Scaling Businesses 17:49 Scorecards vs. KPIs and Dashboards 21:55 Go-To Metrics and the Island Analogy 24:51 The Impact and Application of AI in Business 31:11 Advising Founders: Selling Peace of Mind 34:16 Gratitude and Divergent Thinking 37:51 Closing Thoughts and Resources Key Takeaways: Differentiate between budgets as fixed annual plans and forecasts as malleable, frequently updated financial outlooks for data-driven decisions. Implement scorecards with 5-15 critical metrics and clear targets to simplify problem-solving and boost team accountability. Prioritize cash flow management, customer lifetime value (LTV), and customer acquisition costs (CAC) for sustainable business growth and profitability. Integrate AI into business operations to enhance efficiency, reduce costs, and gain a competitive edge in the accounting profession. Understand that financial management services sell "peace of mind and confidence" rather than just data or models, addressing emotional components for founders. Featured Quotes: "If we're not in the, call it the top 10% of AI adopters, we're going to be left behind fairly quickly." — Matt Putra "We don't sell financial models. We do not sell cash flow forecasts. We do not sell scorecards. We sell peace of mind and confidence." — Matt Putra "If the business owner can hit within, say, 5%, 10%, their budget for the next year, it means they know well that business model." — Roger Knecht Behind the Story: Matt Putra recounts his transition from a CFO role with a grueling commute to founding eightx, a financial operations company. His desire for work-life balance during COVID-19 propelled him to create a business that simplifies finance for e-commerce brands. He stresses the emotional aspect of financial consulting, focusing on delivering confidence rather than just numbers. Matt Putra also shares a personal anecdote about his wife's support, which allowed him to take significant risks in building his company. Conclusion: Thank you for joining us for another episode of Building the Premier Accounting Firm with Roger Knecht. For more information on how you can establish your own accounting firm and take control of your time and income, call 435-344-2060 or schedule an appointment to connect with Roger's team here. Sponsors: Universal Accounting Center Helping accounting professionals confidently and competently offer quality accounting services to get paid what they are worth.   Offers: I'll have a call with someone to help them go from 0-1 on their first AI agent Be more efficient and improve your profit margin with AI Connect with Matt on LinkedIn: https://www.linkedin.com/in/mattputra/  matt@eightx.co    Get a FREE copy of these books all accounting professionals should use to work on their business and become profitable.  These are a must-have addition to every accountant's library to provide quality CFO & Advisory services as a Profit & Growth Expert today: "Red to BLACK in 30 days – A small business accountant's guide to QUICK turnarounds" – This is a how-to guide on how to turn around a struggling business into a more sustainable model. Each chapter focuses on a crucial aspect of the turnaround process - from cash flow management to strategies for improving revenue. This book will teach you everything you need to become a turnaround expert for small businesses. "in the BLACK, nine principles to make your business profitable" – Nine Principles to Make Your Business Profitable – Discover what you need to know to run the premier accounting firm and get paid what you are worth in this book, by the same author as Red to Black – CPA Allen B. Bostrom. Bostrom teaches the three major functions of business (marketing, production and accounting) as well as strategies for maximizing profitability for your clients by creating actionable plans to implement the nine principles. "Your Strategic Accountant" - Understand the 3 Core Accounting Services (CAS - Client Accounting Services) you should offer as you run your business. Help your clients understand which numbers they need to know to make more informed business decisions. "Your Profit & Growth Expert" - Your business is an asset. You should know its value and understand how to maximize it. Beginning with the end in mind helps you work ON your business to build a company you can leave so that it can continue to exist in your absence or build wealth as you retire and enjoy the time, freedom, and life you want and deserve. Follow the Turnkey Business plan for accounting professionals.  This is the proven process to start and build the premier accounting firm in your area.  After more than 40 years we've identified the best practices of successful accountants and this is a presentation we are happy to share.     Also learn the best practices to automate and nurture your lead generation process allowing you to get the bookkeeping, accounting and tax clients you deserve.  GO HERE to see this presentation and learn what you can do today to identify and engage with your ideal clients.   Check it out and see what you can do to be in business for yourself but not by yourself with Universal Accounting Center.   It's here you can become a:   Professional Bookkeeper, PB Professional Tax Preparer, PTP Profit & Growth Expert, PGE   Next, join a group of like-minded professionals within the accounting community.  Register to attend GrowCon and Stay up-to-date on current topics and trends and see what you can do to also give back, participating in relevant conversations as they relate to offering quality accounting services and building your bookkeeping, accounting & tax business.   The Accounting & Bookkeeping Tips Facebook Group The Universal Accounting Fanpage Topical Newsletters: Universal Accounting Success The Universal Newsletter   Lastly, get your Business Score to see what you can do to work ON your business and have the Premier Accounting Firm. Join over 70,000 business owners and get your score on the 8 Factors That Drive Your Company's Value.   For Additional FREE Resources for accounting professionals check out this collection HERE!   Be sure to join us for GrowCon, the LIVE event for accounting professionals to work ON their business. This is a conference you don't want to miss.   Remember this, Accounting Success IS Universal. Listen to our next episode and be sure to subscribe.   Also, let us know what you think of the podcast and please share any suggestions you may have.  We look forward to your input: Podcast Feedback   For more information on how you can apply these principles to start and build your accounting, bookkeeping & tax business please visit us at www.universalaccountingschool.com or call us at 8012653777  

Gabriel did a session at Acumatica Summit 2026 last week where he showed new Excel templates for construction, best practices for Dashboards, a redesigned Query Builder for no-code data exploration, and new AI features that speed up reporting work. I really wanted to attend, but wasn't able to make it, so Gabriel is going to show me that stuff on this Episode, with the added benefit that I get to pester him with questions

Great leaders don't just have clarity. They create clarity for everyone around them.Building your own Leadership Dashboard is step one. Getting your team to build theirs is step two.That's how you go from a group of talented individuals to a high-performance team.LinkedIn

In dieser Episode dreht sich alles um Datenvalidierung und darum, wie sich das Prinzip "Garbage In, Garbage Out" vermeiden lässt. Mira und Michelle erklären, warum eine gründliche Prüfung der Datenqualität direkt zu Projektbeginn entscheidend ist. Im Fokus stehen typische Checks wie Schema-Validierung, Vollständigkeit, Konsistenz und statistische Auffälligkeiten. Außerdem geht es darum, wie Datenvalidierung hilft, Daten besser zu verstehen und Fehler frühzeitig aufzudecken. Abschließend werden praktische Techniken und Tools vorgestellt, die von manueller Analyse bis zur automatisierten Pipeline reichen. **Zusammenfassung** Datenvalidierung prüft die Datenqualität vor der Modellierung Ziel: Probleme früh erkennen und Ressourcen sparen Wichtige Aspekte: Datentypen, Duplikate, fehlende Werte Logik- und Plausibilitätschecks (z.B. Alter nicht negativ, Prozentwerte im richtigen Bereich) Statistische Methoden zur Erkennung von Anomalien und Verteilungen Univariat: einfache Kennzahlen, Histogramme, Boxplots, Zeitreihenanalysen Multivariat: Korrelationen, Scatterplots, Kreuztabellen, Multikollinearität Tools reichen von Notebooks und Reports bis zu Dashboards und automatisierten Pipelines **Links** Great Expectations (Datenvalidierung in Python): https://greatexpectations.io/ Pandera (Schema-Validierung für Pandas): https://pandera.readthedocs.io/ dataMaid (Datenvalidierung in R): https://cran.r-project.org/web/packages/dataMaid/index.html Pydantic (Datenvalidierung & Settings in Python): https://docs.pydantic.dev/ Wikipedia-Eintrag zum Prinzip "Garbage In, Garbage Out": https://de.wikipedia.org/wiki/Garbage_In,_Garbage_Out

"Reden wir überhaupt über das gleiche?!" Wie kann die Schnittstelle zwischen Teams auf Basis von Daten funktionieren? Jedes Team - sei es Marketing, Produkt oder Sales - hat eine eigene Perspektive, einen eigenen Fokus ... und natürlich eigene KPIs. Und dazwischen: viel Platz für Frust, Missverständnisse und verlorenes Potenzial. In dieser Folge spreche ich mit Lena Dierolf, Marketing Director bei Avenit. Avenit ist eine Digitalagentur, die mittelständische Unternehmen beim Aufbau von digitalen Strategien und Marketing unterstützt. Lena bringt damit gleich mehrere Perspektiven mit: Agentur, Inhouse-Marketing und tiefe Einblicke in die Marketing- und Sales-Setups ihrer Kunden. Ihr Schwerpunkt: Lead Gen & Lead Marketing. Wir sprechen darüber: - wie es unterschiedliche Teams schaffen, ihre Daten gemeinsam zu analysieren und zu verstehen - wie ein einfacher Report am Anfang mehr Wert schafft ist als ein fancy Dashboard - und wie ein gemeinsamer "Daten-Verständnis-Prozess" aussehen kann - und darum wie das “data as a conversation” Konzept dabei helfen kann Am Ende geht es um mehr als “nur” KPIs: Daten schaffen Wert, wenn und weil Menschen gemeinsam darüber sprechen, Handlungen ableiten und umsetzen. Timestamps: (0:00:00) - Vorstellung von Lena Dierolf (0:01:27) - Fokus auf Lead-Gen Marketing. (0:04:07) - Notwendigkeit der Betrachtung des gesamten Funnels. (0:07:14) - Gemeinsame Sprache mit Sales. (0:10:57) - Analyse von Lead-Interaktionen. (0:14:07) - Entwicklung von Reports zu Dashboards. (0:17:34) - Starte mit Gesprächen, nicht Tools. (0:20:52) - Data as a Conversation Konzept. Hier findest du Lena Dierolf auf Linkedin: [https://www.linkedin.com/in/lenadierolf/](https://www.linkedin.com/in/lenadierolf/) Connecte dich mit mir auf LinkedIn: [https://www.linkedin.com/in/mlmatysik/](https://www.linkedin.com/in/mlmatysik/) Unsere Website findest du hier: [https://analyticsfreaks.com/](https://analyticsfreaks.com/) Ich freu mich immer über Anmerkungen, Fragen oder einfach deine Gedanken zum Podcast! :) Schreib mir gern eine Mail an marialena.matysik@analyticsfreaks.com oder auf Linkedin [https://www.linkedin.com/in/mlmatysik/](https://www.linkedin.com/in/mlmatysik/)

Join us for a 30-minute masterclass exploring how brands can move from raw data to meaningful narrative, and use insight-led storytelling to shape strategy, influence decision-making, and drive measurable outcomes.This session will focus on transforming complex datasets into clear, compelling stories that align marketing activity with broader business objectives.What You'll Learn & Why It Matters:Understand the role of data in modern brand storytelling and how insight-led narratives support strategic direction.Learn how to analyse and interpret key data points, including customer behaviour, trends, demographics, and engagement metrics.Translate complex datasets into clear, actionable messages that resonate with both technical and non-technical stakeholders.Structure insights into a cohesive narrative that supports decision-making, drives engagement, and influences action.Build data-driven consumer personas and customer journey maps to inform personalised marketing strategies.Align data insights with brand strategy, messaging, content planning, and tactical execution.Turn insights into action by setting clear KPIs and measuring the effectiveness of data-driven initiatives.All attendees can request a FREE GA4 Audience Audit, pulling key user insights from your analytics to create a tailored audience profile with strategic recommendations, demonstrating how data-driven storytelling can optimise future marketing efforts.

#335: Observability tools have exploded in recent years, but most come with a familiar tradeoff: either pay steep cloud vendor markups or spend weeks building custom dashboards from scratch. Coroot takes a different path as a self-hosted, open source observability platform that prioritizes simplicity over flexibility. Using eBPF technology, Coroot automatically instruments applications without requiring code changes or complex configuration, delivering what co-founder Peter Zaitsev calls opinionated observability—a philosophy of less is more that aims to reduce cognitive overload rather than drowning users in endless metrics and dashboards. The conversation explores how Coroot differentiates itself in a crowded market with over a hundred observability vendors. Rather than competing head-to-head with cloud giants like Datadog and Dynatrace, Coroot focuses on developers who need answers fast without building elaborate monitoring systems. The platform combines systematic root cause analysis with AI-powered recommendations, using deterministic methods to trace how errors propagate through microservices before handing off to LLMs for actionable fix suggestions. Darin and Viktor dig into Coroot's business model with Peter, examining why the company chose Apache 2.0 licensing instead of more restrictive options, and how staying bootstrapped with minimal angel funding allows them to play the long game without pressure to chase every hype cycle.   Peter's contact information: X: https://x.com/PeterZaitsev Bluesky: https://bsky.app/profile/peterzaitsev.bsky.social LinkedIn: https://www.linkedin.com/in/peterzaitsev/   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

We're closing out January with a bang—and a whiteboard marker—as we round up our favourite tools for strategy and planning. From digital whiteboards to the unavoidable CRM groan, we're getting real about the tech we love, the tools we tolerate, and the dashboards that make us feel like data wizards. There's talk of Notion (if you can stay disciplined), the mighty Power BI, and a nod to Trello and Asana. We also get a bit deep on risk matrices, reclaiming downtime, and whether the weather is just gaslighting us. If your strategy plan includes "panic and wing it," this one's for you.

Performance technology is everywhere right now.Force plates. Dynamometry. Movement analysis. Dashboards full of numbers that look impressive and explain nothing. In Part 1 of this two-part series, Dr. Michael “Dr. G” Giammarco breaks down how performance technology should actually be used in clinical and performance settings. Not as a diagnosis machine, but as a decision-support tool that adds context, clarity, and confidence to your reasoning.This conversation focuses on cutting through the noise. Instead of chasing more data, Dr. G explains how to select the right metrics, interpret them intelligently, and integrate technology into real-world workflows without slowing sessions, overwhelming staff, or confusing patients.If you have ever felt stuck between ignoring tech completely or drowning in dashboards you do not fully trust, this episode provides a clear reset. This episode is especially valuable for: Healthcare providers, rehab professionals, strength coaches, athletic trainers, and clinic owners who want technology to support their thinking, not replace it.In This Episode, You'll Learn:What performance technology actually includes and what it does notWhy collecting more metrics often leads to less clarityHow dashboards create analysis paralysis without a guiding frameworkHow to choose metrics that match the person in front of youThe real-world realities of implementation, including needs analysis, staff training, workflow bottlenecks, and ROIWhy technology should add context rather than override clinical reasoningThis is Part 1 of a two-part series. Tune in for Part 2 (Episode 121) in two weeks.

Automotive manufacturing leaders have no shortage of data, but only those who turn it into action are winning, and AI is the accelerator.In this milestone episode, Jan Griffiths is joined by Sanjay Brahmawar, CEO of QAD, and Dr. Bryan Reimer, MIT Research Scientist and author of How to Make AI Useful, for a grounded conversation about how AI is creating real advantage in automotive manufacturing.The challenge facing automotive manufacturing leaders is not visibility. Leaders know where problems exist. The issue is that action often stalls between insight and execution. Dashboards explain what happened. They do not decide what happens next.Sanjay and Bryan draw a clear distinction between systems of record and systems of action. Systems of record observe. Systems of action decide, execute, and learn. Agentic AI belongs in the second category. It creates value when it removes friction from work, accelerates routine decisions, and gives people better context at the moment action is required.Frontline teams in automotive manufacturing do not resist AI. They adopt it when it respects their expertise and helps them do their jobs better. Adoption follows usefulness, not mandates. When AI amplifies human judgment instead of supervising it, execution speed improves and results follow.This episode challenges automotive manufacturing leaders to stop treating AI as a reporting layer and start using it as an execution engine. The organizations pulling ahead are not waiting for perfect conditions. They are starting small, learning fast, and letting action build confidence.Themes Discussed in this episode:Why data visibility alone does not drive performance in automotive manufacturingSystems of record vs systems of actionHow AI removes friction from automotive manufacturing operationsFrontline-first AI adoption in plantsAgentic AI as an execution multiplierLeadership ownership of decisionsBuilding momentum with 60 to 90-day winsFeatured Guests: Name: Sanjay BrahmawarTitle: CEO of QAD About: Sanjay Brahmawar is the CEO of QAD, a cloud software company delivering cloud-based solutions for manufacturers and global supply chains. With more than two decades of experience leading global technology businesses, he brings deep expertise in digital transformation, AI, IoT, and data-driven platforms, built through senior leadership roles at IBM and Software AG.Connect: LinkedInName: Dr. Bryan ReimerAbout: Dr. Bryan Reimer is a Research Scientist at the MIT Center for Transportation & Logistics and a key member of the MIT AgeLab. He is also the author of How to Make AI Useful: Moving beyond the hype to real progress in business, society and life. His work focuses on how...

On this episode of the Shared Practices Podcast, George sits down with Dr. Aditi Agarwal, co-founder of Practice by Numbers and practicing dentist, to unpack how AI and data are transforming private practice ownership. Aditi shares the origin story of PBN, practical examples of Operations AI, revenue finding, and call analytics, and why embracing technology is becoming essential for private practices competing with DSOs. They close with a candid look at team-led tech adoption and how to reduce stress for your front office while increasing performance.

In this episode of The New Warehouse Podcast, Kevin chats with Alex Ramirez, CEO and co-founder of Cognitops. They discuss why warehouse data decision-making often fails the people who need it most. Ramirez draws from years spent on warehouse floors, not conference rooms, to explain how operators are overwhelmed by dashboards, reports, and status updates that don't help them act in real time. Cognitops changes that reality. The conversation explores why most warehouses are “data rich and decision poor,” how decades-old WMS thinking still shapes modern systems, and why context and time matter more than static metrics. Ramirez also shares how Cognitops helps operators turn data into decisions that drive flow, improve productivity, and reduce chaos when plans inevitably break down.Learn more about The Brecham Group here. Follow us on LinkedIn and YouTube.Support the show

In this episode of FP&A Unlocked, host Paul Barnhurst welcomes back Jordan Goldmeier, Excel expert, author, and longtime friend of the show, for a wide-ranging and honest conversation about careers, technology, and growth. Jordan reflects on his unconventional career path, from auditing and operations research to becoming a Microsoft MVP, author, and entrepreneur. The discussion covers Excel's evolution, why many finance professionals underuse powerful tools, and Jordan's latest projects aimed at modernizing how power users work with spreadsheets.Jordan is an entrepreneur, event producer, author, and Microsoft Excel MVP based in the Lisbon Metropolitan Area. He is widely known for his work helping professionals master Excel, data analysis, and modern spreadsheet practices. Jordan has authored several well-known books, including Advanced Excel Essentials, Dashboards for Excel, and Becoming a Data Head. In addition to his work in Excel education, he produces global events that bring together leaders across finance, technology, and entrepreneurship.Expect to Learn:How Jordan's career twists shaped his approach to Excel, data, and problem-solvingWhy most professionals only scratch the surface of Excel's capabilitiesJordan's perspective on why VBA is outdated and what could replace itWhy vertical learning beats beginner–intermediate–advanced training pathsHere are a few quotes from the episode:“Excel isn't dead, but the way we develop in it needs to change.” – Jordan Goldmeier“You don't become great by learning everything. You become great by going deep where it matters.” – Jordan GoldmeierJordan also shares the story behind his latest project: a developer-style environment designed to help Excel power users work faster, cleaner, and more confidently, without relying on outdated tools like VBA. He explains why Excel should be treated as part of a broader finance tech stack and how modern coding concepts could dramatically improve spreadsheet workflows. Campfire: AI-First ERP:Campfire is the AI-first ERP that powers next-gen finance and accounting teams. With integrated solutions for the general ledger, revenue automation, close management, and more, all in one unified platform.Explore Campfire today: https://campfire.ai/?utm_source=fpaguy_podcast&utm_medium=podcast&utm_campaign=100225_fpaguyFollow JordanLinkedIn - https://www.linkedin.com/in/jordangoldmeier/Earn Your CPE Credit For CPE credit, please go to earmarkcpe.com, listen to the episode, download the app, answer a few questions, and earn your CPE certification. To earn education credits for the FP&A Certificate, take the quiz on Earmark and contact Paul Barnhurst for further details.In Today's Episode:[02:15] – Jordan's Career Journey[08:30] – Setbacks, Resets, and Growth[15:00] – Writing Books on Excel[25:59] – How Excel Is Really Used[29:12] – Why VBA Is Outdated[33:54] – Building Better Tools for Excel[42:25] – Advice for FP&A Professionals[47:16] – Creating Your Own Network[52:12] – Rapid-Fire & Final Thoughts

In this episode, I'm thrilled to welcome back Duncan Clark from Flourish and Canva to talk about the incredible evolution of both tools over the past few years. We dig into how the Flourish and Canva teams have grown, how they now collaborate, and what that means for users who care about data visualization, storytelling, and workflow. Duncan walks through major updates—including the new Start With Data feature, expanded enterprise security options, and deeper presentation-focused capabilities. We also explore long-standing user requests, dashboarding, and how AI may soon accelerate data-viz workflows. It's a wide-ranging and deeply insightful conversation for anyone who uses—or teaches—data visualization.Keywords: Flourish, Canva, Duncan Clark, data visualization, data storytelling, interactive graphics, data design, data tools, newsroom visualization, enterprise data security, Start With Data, presentations, dashboards, API visualization, data workflows, information design, PolicyViz PodcastSubscribe to the PolicyViz Podcast wherever you get your podcasts.Become a patron of the PolicyViz Podcast for as little as a buck a monthCheck our FlourishFollow me on Instagram, LinkedIn, Substack, Twitter, Website, YouTubeEmail: jon@policyviz.com

This week on The Geek in Review, we sit down with Jennifer McIver, Legal Ops and Industry Insights at Wolters Kluwer ELM Solutions. We open with Jennifer's career detour from aspiring forensic pathologist to practicing attorney to legal tech and legal ops leader, sparked by a classic moment of lawyer frustration, a slammed office door, and a Google search for “what else can I do with my law degree.” From implementing Legal Tracker at scale, to customer success with major clients, to product and strategy work, her path lands in a role built for pattern spotting, benchmarking, and translating what legal teams are dealing with into actionable insights.Marlene pulls the thread on what the sharpest legal ops teams are doing with their data right now. Jennifer's answer is refreshingly practical. Visibility wins. Dashboards tied to business strategy and KPIs beat “everything everywhere all at once” reporting. She talks through why the shift to tools like Power BI matters, and why comfort with seeing the numbers is as important as the numbers themselves. You cannot become a strategic partner if the data stays trapped inside the tool, or inside the legal ops team, or inside someone's head.Then we get into the messy part, which is data quality and data discipline. Jennifer points out the trap legal teams fall into when they demand 87 fields on intake forms and then wonder why nobody enters anything, or why every category becomes “Other,” also known as the graveyard of analytics. Her suggestion is simple. Pick the handful of fields that tell a strong story, clean them up, and get serious about where the data lives. She also stresses the role of external benchmarks, since internal trends mean little without context from market data.Greg asks the question on everyone's bingo card, what is real in AI today versus what still smells like conference-stage smoke. Jennifer lands on something concrete, agentic workflows for the kind of repeatable work legal ops teams do every week. She shares how she uses an agent to turn event notes into usable internal takeaways, with human review still in the loop, and frames the near-term benefit as time back and faster cycles. She also calls out what slows adoption down inside many companies, internal security and privacy reviews, plus AI committees that sometimes lag behind the teams trying to move work forward.Marlene shifts to pricing, panels, AFAs, and what frustrates GCs and legal ops leaders about panel performance. Jennifer describes two extremes, rigid rate programs with little conversation, and “RFP everything” process overload. Her best advice sits in the middle, talk early, staff smart, and match complexity to the right team, so cost and risk make sense. She also challenges the assumption that consolidation always produces value. Benchmarking data often shows you where you are overpaying for certain work types, even when volume discounts look good on paper.We close with what makes a real partnership between corporate legal teams and firms, and Jennifer keeps returning to two themes, communication and transparency, with examples. Jennifer's crystal ball for 2026 is blunt and useful, data first, start the hard conversations now, and take a serious look at roles and skills inside legal ops, because the job is changing fast.Links:Jennifer McIver's LinkedIn pageWolters Kluwer ELM Solutions homepageLegalVIEW Insights reports homepageLegalVIEW DynamicInsights pageTyMetrix 360° pageListen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Chrome tanks gleaming in the bed, four hydraulic pumps ready to dance, and a pearl-white El Camino built from love and discipline—Rudy joins us to share how lowrider craft, family tradition, and clean engineering come together in a car that means more than metal. He walks us through paint choices, a four-pump setup, 13-inch whitewalls, and the geometry behind extended control arms that make three-wheeling possible, plus the real-world trade-offs like accelerated tire wear and why alignment becomes a balancing act. The story moves beyond parts as Rudy traces a path from street conflict to cage fighting to calmer streets and showgrounds, paying that focus forward to his kids and a near-original '96 Impala SS.We switch lanes to explore six iconic dashboard styles that collectors love, each one a time capsule of design and technology. From the bold clarity of American muscle to the wood-and-leather elegance of European classics, the sweeping Art Deco forms of the '30s and '40s, the minimalist pragmatism of Scandinavian design, and the digital, driver-centric supercar era, we show how a dashboard can reveal a car's soul. Custom hot rods cap the tour with one-off faces that speak the owner's language in billet, color, and gauge selection.To round out the ride, we map festive road trips through San Antonio: River Walk lights cascading over the water, SeaWorld's massive displays and live shows, hot-chocolate trolley tours, Zoo Lights, skating at Hemisphere Park, and Fiesta Texas in full holiday mode. Don't miss the transformed Alamo experience, complete with Phil Collins' narration and a collection that reframes the site's true scale. Whether you're tuning hydraulics, studying dashboards, or planning a family cruise, you'll find ideas, history, and heart.Enjoyed the show? Subscribe, share it with a car-loving friend, and leave a review so more enthusiasts can join the ride.Be sure to subscribe for more In Wheel Time Car Talk!The Lupe' Tortilla RestaurantsLupe Tortilla in Katy, Texas Gulf Coast Auto ShieldPaint protection, tint, and more!Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.---- ----- Want more In Wheel Time car talk any time? In Wheel Time is now available on Audacy! Just go to Audacy.com/InWheelTime where ever you are.----- -----Be sure to subscribe on your favorite podcast provider for the next episode of In Wheel Time Podcast and check out our live multiplatform broadcast every Saturday, 10a - 12nCT simulcasting on Audacy, YouTube, Facebook, Twitter, Twitch and InWheelTime.com.In Wheel Time Podcast can be heard on you mobile device from providers such as:Apple Podcasts, Amazon Music Podcast, Spotify, SiriusXM Podcast, iHeartRadio podcast, TuneIn + Alexa, Podcast Addict, Castro, Castbox, YouTube Podcast and more on your mobile device.Follow InWheelTime.com for the latest updates!Twitter: https://twitter.com/InWheelTimeInstagram: https://www.instagram.com/inwheeltime/https://www.youtube.com/inwheeltimehttps://www.Facebook.com/InWheelTimeFor more information about In Wheel Time Podcast, email us at info@inwheeltime.com

Everyone keeps asking whether AI kills Power BI or makes it stronger. Rui Romano flips that entire question on its head. As the Microsoft PM behind PBIP, TMDL, and all the file format work that rebuilt Power BI's foundation, he explains how the platform accidentally became one of the most AI-ready systems in analytics - and it wasn't by accident, not really. His team was solving problems for real developers who were tired of unsupported workarounds and offshore relay races. They weren't training agents. But the work they did means AI now feels native instead of duct-taped on. What we learned was that the semantic model is still the highest ground in this whole space. While other tools let AI stumble through raw tables and pray the math holds up, a proper model gives AI the one thing it absolutely cannot fake: context. Relationships. Business logic that works at every level of granularity without falling apart. Rui breaks down why that matters now more than ever, why all the hardening work his team did keeps your models from exploding when an agent gets ambitious, and why the future of BI isn't about cranking out another hundred pixel-perfect dashboards. It's about fast iteration, lower friction, and answers you can trust at scale. Dashboards still matter - but only the ones people use. This conversation goes deep on architecture, not hype. Rui talks about what's changing right now, what still needs work, and why natural language will eventually beat drag-and-drop for a lot of what we do today. If you've been wondering whether to invest in real semantic modeling or just let AI figure it out from scratch every single time, this episode makes the case for why foundations always win. Always. Listen in and get ahead of the shift. And if the episode lands for you, leave us a review to help other folks find the show.

Excel Data Visualization & Dashboards: Turn Raw Data into Executive-Ready StoriesExcel is the foundational tool for analysis, but simply having data isn't enough; you need to tell the story behind the numbers.In this episode of What's New at CFI on FinPod, CEO Tim Vipond introduces the new Excel Data Visualization and Dashboards course. Learn how to transform raw data into clean, clear, and powerful visuals that drive business decisions, no matter your industry.This course is a masterclass in building executive-ready dashboards from scratch, making it essential for FP&A, Marketing, Operations, and all analytical roles.This episode covers:The Power of Excel: Why Excel remains the ultimate "blank canvas" for visualization and the foundational skill set for tools like Power BI or Tableau.Mastering the Visual Toolkit: Learn to build and use advanced charts like Waterfall Charts (for variance analysis), Combo Charts (for margin vs. revenue), Sparklines, and Football Field Charts (for valuation ranges).End-to-End Dashboard Creation: Gain the confidence to plan, set up, and build complete, beautiful dashboards that are clearly sectioned, titled, and formatted for maximum impact.Highlighting Insights: The critical skill of moving beyond just building a chart to actively using color, arrows, and annotations to highlight the specific insights that drive business change (e.g., maximizing margins or accelerating growth).Developing Taste: Tim shares career advice on how to develop "good taste" in data visualization by actively seeking out and being inspired by varied internal and external reports (pitch decks, board reports, operations decks).

Most companies still rely on dashboards to understand their data, even though AI now offers new ways to ask questions and explore information. Barry McCardel, CEO of Hex and former engineer at Palantir, joins a16z General Partner Sarah Wang to discuss how agent workflows, conversational interfaces, and context-aware models are reshaping analysis. Barry also explains how Hex aims to make everyone a data person by unifying analysis and AI in one workflow, and he reflects on his post about getting rid of their AI product team and the process behind Hex's funny launch videos.Timecodes: 0:00 – The problem with dashboards1:20 – The evolution of data teams and AI's role2:05 – Democratizing data: challenges and opportunities3:45 – The rise of agentive workflows9:48 – Threads and the changing UI of data analysis13:16 – Building AI agents: lessons from the notebook agent16:12 – Model capabilities and the future of AI in data19:10 – The importance of context and trust in data analysis24:34 – Semantic models and context engineering29:27 – Data team roles in the age of AI31:52 – Accuracy, trust, and evaluating AI systems37:43 – Building Hex: embracing AI as core, not an add-on48:48 – Pricing, value capture, and the future of SaaS55:55 – The modern data stack and industry consolidation1:04:26 – Acquisitions and owning the data insight layer1:06:46 – Lessons from Palantir: forward-deployed engineering1:13:11 – Commitment engineering and customer collaboration1:17:25 – Brand, launch videos, and having fun in SaaSResources:Follow Barry McCardel on X:  https://x.com/barraldFollow Sarah Wang on X: https://x.com/sarahdingwang Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn:https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see http://a16z.com/disclosures.  Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode of the ETA Insider Podcast, we are joined by Jake Bitz, Director of Client Accounting & Advisory Services and Consulting CFO at Boulay. Jake breaks down the accounting realities that searchers and newly minted CEOs face before and after acquiring a small business. He outlines the most common red flags uncovered during diligence, offers practical steps searchers can take early to avoid costly surprises, and explains how outsourced accounting models support operators as they scale. Jake also shares guidance on post-acquisition pitfalls, how CEOs should think about cash oversight, and where AI is already reshaping the accounting and finance function.

Le sujet :L'IA et le vibe coding ont révolutionné la création de side business : plus besoin d'être un expert de la tech pour lancer un site, une application ou un média. L'essentiel est ailleurs : savoir identifier les bonnes opportunités business et utiliser les meilleurs outils.L'invité du jour :Esther Moisy-Kirschbaum est responsable du développement de Magma, une newsletter d'identification de tendances et d'opportunités de business.Aux côtés de Matthieu Stefani, Esther et Christofer Ciminelli nous expliquent comment créer un side business rentable grâce au vibe coding et aux outils d'IA les plus accessibles.Découvrez : Pourquoi l'entrepreneuriat est un pilier de l'investissementComment identifier les opportunités de side businessQu'est-ce que le vibe coding et comment se lancerLes opportunités du faceless et du live shoppingComment combiner vibe coding, IA et APIAvantages :Bonne nouvelle ! Nous avons négocié pour vous un avantage exceptionnel. Avec le code BFLAMARTINGALE, obtenez 50% de réduction sur l'abonnement annuel à la newsletter Magma. Offre valable jusqu'au 31/12/2025 (au-delà, le code vous offre tout de même 50€ de réduction

In this episode of the Transform Sales Podcast: Sales Software Review Series, Amir Reiter, CEO at CloudTask, sits down with Luke Marshall, CEO at Baremetrics, to reveal how Baremetrics turns raw Stripe data into the actionable insights founders need to scale. Baremetrics delivers real‑time dashboards for MRR, churn, LTV, cohort retention, and more, lets you annotate revenue spikes, segment by any customer attribute, and recover failed payments automatically—so you can ditch clunky spreadsheets and incomplete Stripe reports. The result? Faster, data‑driven decisions that cut churn, boost expansion, and supercharge growth. If you're a SaaS founder, CFO, or growth lead, Baremetrics is your single source of truth for subscription analytics. Try Baremetrics here: https://software.cloudtask.com/baremetrics-ce250d #TransformSales #SalesSoftware #Baremetrics #StripeAnalytics #SaaSmetrics #RevenueGrowth

In this episode Kim talks with Andrew Ranson, High School Instructional Coach at Shanghai American School (and graduate of The Coach Certificate and Mentorship Program) about how he got started using a coaching dashboard - and how it helped transform conversations with his school leaders! We know that leadership support is a critical aspect of the success of a coaching program and the idea is to share a birds-eye view summary of the coaching work that has been happening in their building or division. When the building or divisional leader knows that coaching work is happening - and helping them move forward on their strategic goals, it immediately sparks more curiosity about what is happening and how they can support it. Find the show notes for this episode here. Let's Connect: Our website: coachbetter.tv EduroLearning on LinkedIn EduroLearning on Instagram EduroLearning on YouTube Subscribe to our weekly newsletter Join our #coachbetter Facebook group Learn with Kim Explore our courses for coaches Watch a FREE workshop Read more from Kim: Finding Your Path as a Woman in School Leadership (book) Fostering a Culture of Growth and Belonging: The Multi-Faceted Impact of Instructional Coaching in International Schools (chapter) The Landscape of Instructional Coaching in International Schools (chapter)  

"What gets measured gets managed."Everyone knows this.But here's the question most leaders never ask:Are you measuring what actually matters?I see this all the time: Leaders drowning in data. Dashboards full of metrics. Weekly reports. KPIs tracked religiously.But when I ask them, "What are you actually measuring? And why?" they can't answer clearly.They're measuring everything. Which means they're measuring nothing that matters.Here's the problem: Most leaders measure lag indicators—outcomes that already happened. Revenue. Profit. Customer churn. Employee turnover.These tell you what happened. But they don't tell you what's going to happen. Or what you can actually control.Lead indicators predict the future. They're the activities and behaviors that drive outcomes. But most leaders don't track them.In this week's newsletter (LinkedIn) and podcast, I'm diving into:Why most performance metrics are useless (lag indicators only)The difference between lead and lag indicators (and why you need both)How to measure what actually matters (based on your Mission)Why Performance is a core element of your Leader's DashboardBecause if you're measuring the wrong things, you're managing the wrong things.And that's costing you.

In this week's episode, I talk with Chris Parmer, co-founder of Plotly, about how the company is integrating AI into the next generation of data visualization and analytics tools. Chris walks me through the thinking behind Plotly Studio, their new AI-native environment where natural language prompts generate real, auditable code for charts, dashboards, and data apps. We discuss how this approach reduces bottlenecks for data teams, empowers non-technical users, and reshapes the role of the data visualization expert. We also dive into the limits of public dashboards, the rise of generative interfaces, and what a future of AI-driven exploratory analysis might look like. It's a fascinating look at where data tools are heading and how analysts can stay ahead.Keywords: Plotly, Plotly Studio, data visualization, AI tools, generative AI, dashboards, data apps, Python, code generation, data workflows, data analysis, natural language interfaces, data science, analytics, enterprise data security, data storytelling, Jon Schwabish, Chris ParmerSubscribe to the PolicyViz Podcast wherever you get your podcasts.Become a patron of the PolicyViz Podcast for as little as a buck a monthCheck out Plotly at: https://plotly.com/Follow me on Instagram, LinkedIn, Substack, Twitter, Website, YouTubeEmail: jon@policyviz.com

"92% of all POCs today in the US are failing because they're trying to use bad data and LLMs that are standardized or generalized."   At Money 2020 I sat down with Deuna (www.deuna.com) co-founder Roberto Kafati (REKS) and their US head of GTM Chase Foster to explore the critical importance of leveraging high-quality, actionable data and intelligent systems to drive business value, especially in complex enterprise environments. The core challenge today is that while most companies possess vast amounts of data, a staggering 92% of AI pilot projects fail because they rely on data that isn't "AI-ready" that is lacking the necessary context, cleanliness, and standardization to be effectively used by large language models (LLMs). The key is transforming raw data, such as the 638 direct and indirect data points per payment transaction, into a strategically usable asset that goes beyond cost-cutting to unlock significant revenue growth across the organization.   The company's platform, Athia, is designed to solve this by acting as an agentic intelligence platform that utilizes merchant-specific data from massive commerce operations (like major airlines, movie chains, and retailers) to provide proactive, highly focused insights. Instead of forcing teams to manually analyze hundreds of performance dashboards, Athia surfaces the most critical information, alerting teams to revenue leakages and recommending direct, real-time actions, such as optimizing payment routing or detecting opportunities in developing economies. This approach allows businesses to embrace the future of "agentic commerce" by maintaining control over the customer experience and ensuring data-driven decision-making is implemented automatically and continuously across all critical functions, fostering a new era of cross-departmental collaboration between areas like payments and marketing.

Building B2B analytics and AI tools that people will actually pay for and use is hard. The reality is, your product won't deliver ROI if no one's using it. That's why first principles thinking says you have to solve the usage problem first. In this episode, I'll explain why the key to user adoption is designing with the flow of work—building your solution around the natural workflows of your users to minimize the behavior changes you're asking them to make. When users clearly see the value in your product, it becomes easier to sell and removes many product-related blockers along the way. We'll explore how product design impacts sales, the difference between buyers and users in enterprise contexts, and why challenging the “data/AI-first” mindset is essential. I'll also share practical ways to align features with user needs, reduce friction, and drive long-term adoption and impact. If you're ready to move beyond the dashboard and start building products that truly fit the way people work, this episode is for you.   Highlights/Skip to:  The core argument: why solving for user adoption first helps demonstrate ROI and facilitate sales in B2B analytics and AI products  (1:34) How showing the value to actual end users—not just buyers—makes it easier to sell your product (2:33) Why designing for outcomes instead of outputs (dashboards, etc) leads to better adoption and long-term product value (8:16) How to “see” beyond users' surface-level feature requests and solutions so you can solve for the actual, unspoken need—leading to an indispensable product (10:23) Reframing feature requests as design-actionable problems (12:07)  Solving for unspoken needs vs. customer-requested features and functions (15:51) Why “disruption” is the wrong approach for product development (21:19)   Quotes:  “Customers' tolerance for poorly designed B2B software has decreased significantly over the last decade. People now expect enterprise tools to function as smoothly and intuitively as the consumer apps they use every day.  Clunky software that slows down workflows is no longer acceptable, regardless of the data it provides. If your product frustrates users or requires extra effort to achieve results, adoption will suffer. Even the most powerful AI or analytics engine cannot compensate for a confusing or poorly structured interface. Enterprises now demand experiences that are seamless, efficient, and aligned with real workflows.    This shift means that product design is no longer a secondary consideration; it is critical to commercial success.  Founders and product leaders must prioritize usability, clarity, and delight in every interaction. Software that is difficult to use increases the risk of churn, lengthens sales cycles, and diminishes perceived value. Products must anticipate user needs and deliver solutions that integrate naturally into existing workflows.  The companies that succeed are the ones that treat user experience as a strategic differentiator. Ignoring this trend creates friction, frustration, and missed opportunities for adoption and revenue growth. Design quality is now inseparable from product value and market competitiveness.  The message is clear: if you want your product to be adopted, retain customers, and win in the market, UX must be central to your strategy.” —   “No user really wants to ‘check a dashboard' or use a feature for its own sake. Dashboards, charts, and tables are outputs, not solutions. What users care about is completing their tasks, solving their problems, and achieving meaningful results.  Designing around workflows rather than features ensures your product is indispensable. A workflow-first approach maps your solution to the actual tasks users perform in the real world.  When we understand the jobs users need to accomplish, we can build products that deliver real value and remove friction. Focusing solely on features or data can create bloated products that users ignore or struggle to use.  Outputs are meaningless if they do not fit into the context of a user's work. The key is to translate user needs into actionable workflows and design every element to support those flows.  This approach reduces cognitive load, improves adoption, and ensures the product's ROI is realized. It also allows you to anticipate challenges and design solutions that make workflows smoother, faster, and more efficient.  By centering design on actual tasks rather than arbitrary metrics, your product becomes a tool users can't imagine living without. Workflow-focused design directly ties to measurable outcomes for both end users and buyers. It shifts the conversation from features to value, making adoption, satisfaction, and revenue more predictable.” — “Just because a product is built with AI or powerful data capabilities doesn't mean anyone will adopt it. Long-term value comes from designing solutions that users cannot live without. It's about creating experiences that take people from frustration to satisfaction to delight.  Products must fit into users' natural workflows and improve their performance, efficiency, and outcomes. Buyers' perceived ROI is closely tied to meaningful adoption by end users. If users struggle, churn rises, and financial impact is diminished, regardless of technical sophistication.  Designing for delight ensures that the product becomes a positive force in the user's daily work. It strengthens engagement, reduces friction, and builds customer loyalty.  High-quality UX allows the product to demonstrate value automatically, without constant explanations or hand-holding. Delightful experiences encourage advocacy, referrals, and easier future sales.  The real power of design lies in aligning technical capabilities with human behavior and workflow.  When done correctly, this approach transforms a tool into an indispensable part of the user's job and a demonstrable asset for the business.  Focusing on usability, satisfaction, and delight creates long-term adoption and retention, which is the ultimate measure of product success.” — “Your product should enter the user's work stream like a raft on a river, moving in the same direction as their workflow. Users should not have to fight the current or stop their flow to use your tool.  Introducing friction or requiring users to change their behavior increases risk, even if the product delivers ROI. The more naturally your product aligns with existing workflows, the easier it is to adopt and the more likely it is to be retained.  Products that feel intuitive and effortless become indispensable, reducing conversations about usability during demos. By matching the flow of work, your solution improves satisfaction, accelerates adoption, and enhances perceived value.  Disrupting workflows without careful observation can create new problems, frustrate users, and slow down sales. The goal is to move users from frustration to satisfaction to delight, all while achieving the intended outcomes.  Designing with the flow of work ensures that every feature, interface element, and interaction fits seamlessly into the tasks users already perform. It allows users to focus on value instead of figuring out how to use the product.  This alignment is key to unlocking adoption, retaining customers, and building long-term loyalty.  Products that resist the natural workflow may demonstrate ROI on paper but fail in practice due to friction and low engagement.  Success requires designing a product that supports the user's journey downstream without interruption or extra effort.  When you achieve this, adoption becomes easier, sales conversations smoother, and long-term retention higher.” —

Alicia is joined by Blake Oliver and David Leary from The Accounting Podcast, fresh from Intuit Connect with detailed notes on everything announced for QuickBooks Online and the accounting profession. The discussion covers Intuit's consolidation strategy to reduce reliance on third-party apps, the new tiered pricing structure for the Intuit Accountant Suite launching in 2026, and how AI agents are currently performing in bank feeds and transaction categorization. They also examine QuickBooks' move into CRM and marketing tools, the role of QuickBooks Live in Intuit's strategy, and what alternatives small businesses and accountants might consider.SponsorsDigits - https://uqb.promo/digits(00:00) - Introduction and Guest Welcome (04:15) - The New Customer Hub and MailChimp Integration (05:43) - Concerns About AI and QuickBooks Ecosystem (10:59) - ProAdvisors' Role in the AI Era (19:01) - Addressing Reporting and Automation Issues (26:57) - The Future of QuickBooks Online Accountant (27:11) - Introduction to QBO A Refresh (27:35) - New Features and Paid Tiers (28:38) - Intuit Accountant Suite Overview (29:54) - Core and Accelerate Versions (30:08) - Client Management and Dashboards (32:36) - Practice Management Tools (33:15) - Intuit's Market Strategy (37:18) - ProAdvisor and QuickBooks Live (38:21) - Quicken's Comeback (41:25) - AI and Automation in Accounting (51:43) - Intuit's Future Plans and Innovations (54:35) - Conclusion and CPE Information LINKSProducts, Services, and Inventory, Nov 18: http://royl.ws/qbo-Inventory?affiliate=5393907QB Payments Merchant Services, Nov 25: http://royl.ws/QB-Payments-Course?affiliate=5393907BUY ALICIA'S NEW BOOK!https://www.amazon.com/QuickBooks-Online-Bootcamp-Setup-Time-ebook/dp/B0FWZ2NHTQ/Companion Course on Royal Wise:https://learn.royalwise.com/visitor_catalog_class/show/153822/QuickBooks-Online-BootcampWe want to hear from you!Send your questions and comments to us at unofficialquickbookspodcast@gmail.com.Join our LinkedIn community at https://www.linkedin.com/groups/14630719/Visit our YouTube Channel at https://www.youtube.com/@UnofficialQuickBooksPodcast?sub_confirmation=1 Sign up to Earmark to earn free CPE for listening to this podcasthttps://www.earmark.app/onboarding 

Alicia Katz Pollock joins the show fresh from Intuit Connect with detailed notes on everything announced for QuickBooks Online and the accounting profession. The discussion covers Intuit's consolidation strategy to reduce reliance on third-party apps, the new tiered pricing structure for the Intuit Accountant Suite launching in 2026, and how AI agents are currently performing in bank feeds and transaction categorization. They also examine QuickBooks' move into CRM and marketing tools, the role of QuickBooks Live in Intuit's strategy, and what alternatives small businesses and accountants might consider.SponsorsCloud Accountant Staffing - http://accountingpodcast.promo/cas Rippling - http://accountingpodcast.promo/ripplingBILL - http://accountingpodcast.promo/billChapters(00:00) - Introduction and Guest Welcome (00:56) - Intuit Connect Conference Overview (01:32) - Changes in QuickBooks and Intuit's Strategy (02:03) - AI Integration in QuickBooks (05:26) - The New Customer Hub and MailChimp Integration (06:54) - Concerns About AI and QuickBooks Ecosystem (12:10) - ProAdvisors' Role in the AI Era (19:44) - Addressing Reporting and Automation Issues (27:43) - The Future of QuickBooks Online Accountant (28:21) - New Features and Paid Tiers (29:24) - Intuit Accountant Suite Overview (30:40) - Core and Accelerate Versions (30:54) - Client Management and Dashboards (33:22) - Practice Management Tools (34:01) - Intuit's Market Strategy (38:04) - ProAdvisor and QuickBooks Live (40:31) - Quicken's Comeback (43:34) - AI and Automation in Accounting (53:52) - Intuit's Future Plans and Innovations (56:44) - Conclusion and CPE Information  Show NotesComing soon!Listen and Subscirbe to The Unofficial QuickBooks Accountants Podcast!https://uqb.show/subscribeConnect with Alicia Katz Pollock!https://www.linkedin.com/in/aliciakatzpollock/https://royalwise.com/ Need CPE?Get CPE for listening to podcasts with Earmark: https://earmarkcpe.comSubscribe to the Earmark Podcast: https://podcast.earmarkcpe.comGet in TouchThanks for listening and the great reviews! We appreciate you! Follow and tweet @BlakeTOliver and @DavidLeary. Find us on Facebook and Instagram. If you like what you hear, please do us a favor and write a review on Apple Podcasts or Podchaser. Call us and leave a voicemail; maybe we'll play it on the show. DIAL (202) 695-1040.SponsorshipsAre you interested in sponsoring The Accounting Podcast? For details, read the prospectus.Need Accounting Conference Info? Check out our new website - accountingconferences.comLimited edition shirts, stickers, and other necessitiesTeePublic Store: http://cloudacctpod.link/merchSubscribeApple Podcasts: http://cloudacctpod.link/ApplePodcastsYouTube: https://www.youtube.com/@TheAccountingPodcastSpotify: http://cloudacctpod.link/SpotifyPodchaser: http://cloudacctpod.link/podchaserStitcher: http://cloudacctpod.link/StitcherOvercast: http://cloudacctpod.link/OvercastClassifiedsCollective by DBA - https://collective.cpa/ Want to get the word out about your newsletter, webinar, party, Facebook group, podcast, e-book, job posting, or that fancy Excel macro you just created? Let the listeners of The Accounting Podcast know by running a classified ad. Go here to create your classified ad: https://cloudacctpod.link/RunClassifiedAdTranscriptsThe full transcript for this episode is available by clicking on the Transcript tab at the top of this page