Raw Data By P3

Sakiko Stickley joins Raw Data to share a story that is part inspiration, part revelation, and a whole lot of truth-telling. From the first moment she discovered Power Pivot, Sakiko did not just learn data. She lived it. She rewired reporting systems, survived micromanagers, and navigated the strange realities of big consulting firms, all while quietly proving that one person, one model, and a little bit of DAX can change everything. In this episode, we get an inside look at how a passion for smarter systems can collide with corporate inertia, what it really feels like to challenge the status quo, and why Sakiko believes AI could someday outperform human leadership, not just in data crunching but in ethics and decision-making too. (Spoiler: She might be right.) If you have ever felt like a lone voice in a world that clings to inefficient processes, Sakiko's journey will feel like a kindred spirit calling from across the data universe. Listen in for a conversation filled with hard truths, breakthrough moments, and a reminder that true data people do not just build models. They build better futures.

What's the value of a long-awaited feature? Well, that depends. Have you ever tried explaining a fiscal calendar that doesn't believe in months? This week, Rob Collie and Justin Mannhardt dive into the latest Microsoft Fabric updates, including the long-rumored, almost-mythical custom calendar support in DAX, the highly requested user-defined functions, and the Copilot expansion that might finally be worth the hype. These updates aren't just bells and whistles; they're fixes to problems that have been quietly driving your team up the wall for a decade. And while the tech is cool, the real story is what it unlocks for the people trying to build reliable reporting, reuse their logic across models, and stop wrestling with edge cases in Excel at 10 p.m. If you've ever been told, “that's just how it works,” this episode is a breath of fresh air, and a reminder that progress doesn't always come with a parade. Sometimes it shows up in patch notes.

What happens when you hand off your Power BI output to ChatGPT and ask it to make sense of your world? You might be surprised. This week, Rob shares a deeply personal use case. One that ties together two major themes we've been exploring: Gen AI is reshaping the way we think about dashboards. To get real value out of AI, you need more than just data. You need metadata. And yes, that kind of metadata—the kind you create in Power BI when you translate raw data into something meaningful. Along the way, we revisit the old guard of data warehousing. The mighty (and now dusty?) ETL priesthood. And we uncover a delicious little irony about how the future of data looks a lot like its past, just with better tools and smarter questions. The big twist? We're all ETL now. But the "T" might not mean what you think it does anymore. Listen now to find out how a few rows of carefully modeled data, a table visual, and one really good AI assistant changed the game. For Rob and, just possibly, for all of us. Also in this episode: Blind Melon – Change (YouTube) The Data Warehouse Toolkit Raw Data Episode - The Human Side of Data: Using Analytics for Personal Well-Being

AI agents are making big waves, but are they the future of business or just another passing trend? In this episode, Rob Collie and Justin Mannhardt explore the rise of AI agents, what they actually do, and why the excitement might be a little premature. They unpack the risks, the rewards, and how leaders can navigate the hype with a bit of caution and a lot of curiosity. Rob and Justin discuss the fine balance between automation and human oversight, tackling questions about when it's smart to embrace AI and when it might be better to pause. They also share thoughts on the current SaaS landscape, where new AI tools are popping up fast and why it pays to be thoughtful before jumping in. Ultimately, this episode is about finding clarity in a fast-moving space. It's about understanding where AI agents can add real value, where they might introduce unnecessary risk, and why critical thinking still matters. Rob and Justin reflect on the challenges of trusting AI, the dangers of locking into technology too early, and how the best decisions come from balancing curiosity with skepticism. If you're wondering how to separate the genuine innovations from the passing fads and how to be strategic about adopting AI in your business, this conversation is for you.

Listener John sent in a classic question: should you build one all-encompassing data model, or should each part of your business have its own? If you think the answer is black and white, well, welcome to the world of data modeling, where nuance reigns supreme. Rob and Justin dive deep into the pros, cons, and inevitable mistakes of both approaches. Along the way, they call out the biggest modeling traps, expose the myths that make projects stall, and introduce a revolutionary new acronym: JGS (Just Get Started). Because, spoiler alert, the best data model is the one that actually gets built. This is an episode you won't want to miss!

Ever find yourself overthinking a problem until you've thought yourself right into a corner? Yeah, we've been there too. But what if there was a way to cut through the noise and just know when something is a good idea? Enter Miller's Theorem, a simple but sneaky-effective thought experiment that's been kicking around in our conversations for years. It's the kind of thing that sounds like nonsense at first until it doesn't. In this episode, we unpack how a casual visit to a bougie home décor store in Seattle turned into an existential crisis over tariffs, pricing psychology, and whether customers actually care if their overpriced alpaca throw just got 25% more expensive. But it's not just about economics. It's about how we make decisions, avoid self-inflicted complexity, and maybe stop outsmarting ourselves into bad choices. Also on the table: the contrapositive, the dangers of taking political soundbites at face value, and why abolishing the IRS is an idea so catastrophically bad it might actually make the Great Depression look like a mild inconvenience. It's a wild ride through logic, business, and just enough existential dread to keep things interesting. Listen now, then hope over to LinkedIn and tell us what you think! Got a topic you would like to have Rob and Justin cover? Join our Raw Data by P3 Adaptive Steering Committee and let us know!   Also in this episode: Pokerbots, Adware, and Burning Man, w/ Brad Miller & Kai Hankinson

For years, dashboards have been the go-to for business intelligence. Built with the best intentions, loaded with visuals, and meant to empower decision-makers. But are they actually delivering? A recent Reddit thread raised a tough question: "Has anyone here moved away from dashboards as their main source of insights?" It's not the usual “Dashboards are dead” hype. It's a real challenge from BI pros who build them. The problem? Analysts say dashboards can't keep up with how they really explore data. Executives and business users aren't using them as intended, leading to more ad hoc requests, not fewer. The result? Dashboards end up underused, misused, or worse, ignored. In this episode of Raw Data, Rob and Justin cut through the noise and get to the heart of the issue. Are dashboards the problem, or is it how we're designing and using them? And more importantly, what's the right way forward? Also in this episode: Reddit discussion

Ever sat in a meeting, watching a decision unfold that makes zero sense—bad for business, bad for employees—while the data that should be guiding the way is ignored? You're not alone. In this solo episode, Rob Collie takes on a question that's been circling for years: why aren't more people with a data-driven mindset in leadership positions? The answer isn't as simple as “because they should be.” There are deep-rooted reasons why persuasion often wins over precision and why data folks get stuck in support roles instead of calling the shots. But here's the thing, change is possible. Whether you're an analyst looking to break into leadership or a decision-maker wondering how to get the most from your data-savvy team, this episode is for you. Tune in as Rob unpacks the hidden forces at play, the skills that can help data professionals move up the ladder, and why learning the art of influence might be just as important as mastering the numbers.

What happens when you mix fantasy football, data analytics, and a little bit of chaos? You get a conversation that refuses to follow a straight line—but somehow lands exactly where it needs to. Rob Collie welcomes back fantasy football guru Adam Harstad for his third appearance on Raw Data, alongside first-time guests Heather Zimmer and Molly Ferguson, two self-proclaimed newcomers who are anything but casual. They dive into the unexpected ways fantasy football rewires your brain, from strategic obsession to the unshakable belief that your lucky jersey actually controls the game. Adam breaks down the numbers behind the game—how expected points added (EPA) became the gold standard of football analytics and why your gut feeling about a "bad matchup" might just be a statistical illusion. Meanwhile, Heather and Molly prove that fantasy football isn't just a game; it's a full-blown data-driven lifestyle. Whether it's crunching Power BI models for next season or convincing family members to clear out during game time, they've gone all-in—and they're not looking back. But beyond the spreadsheets and the smack talk, this episode is about something bigger: the sheer joy of unexpected obsessions. Whether you're in it for the data, the competition, or just the chance to prove someone wrong (we see you, Heather), fantasy football is a reminder that the best things in life are the ones you never saw coming. Also in this episode: Guide to EPA Protect the Spots with NO Bulletholes, w/ Adam Harstad Epistemic Path Dependency, w/ Adam Harstad

What if we told you that, before Power BI, most of the money spent on data projects didn't go where you thought it did? In this episode, Rob Collie and Justin Mannhardt peel back the layers of inefficiency, miscommunication, and just plain bad luck that have haunted data projects for decades. Spoiler: it's not all doom and gloom. Some of those old headaches are finally getting the boot, thanks to tools like Power BI and the rise of generative AI. Rob and Justin take an honest look at how data projects have changed over the years, sharing hard-earned lessons and surprising insights from their time in the trenches. They reflect on the glacial pace of old-school BI, how Power BI changed the game, and why AI might be the next big shift. If you've ever wondered why your pre-Power BI data project cost more than a new car, this episode has the answers (and maybe a little therapy). Listen now for insights, laughs, and a sneak peek at the not-so-distant future of data. As always, be sure to leave us a review on your favorite platform or share the link with a friend to help new listeners find us. Rob's Visual Aid

Gil Raviv has spent years shaping how we use data. From his early days at Microsoft, where he played a key role in developing Power Query, to his work refining how dashboards serve their users, Gil's career is a masterclass in making data tools both practical and powerful. In this episode, we sit down with Gil to dig into why usage data is the missing ingredient for truly effective BI. He explains how understanding what users do with your dashboards can completely change the way you design and deliver them. We also talk about his journey through the world of business intelligence, the lessons he learned along the way, and why he's so passionate about building tools that meet people where they are. Whether you're a Power BI power user or just starting to think about how data fits into your business, Gil's insights will get you thinking differently.

The Spirit of “Why Not” with Bob Pop Collie The Life of a WW2 Navy Pilot Cadet (Bonus), w/ Bob Pop Collie    

The world of data technology moves in fascinating ways, and we're excited to have Microsoft MVPs Ed Hansberry and Kristyna Ferris join Justin to unpack what's really happening. This conversation is all about understanding the technologies that are reshaping how we work and think about data. Microsoft Fabric has been a hot topic, and for good reason. Is it the breakthrough platform everyone's talking about, or are there nuances that aren't making headlines? Ed and Kristyna bring their hands-on experience to share what they've learned—the moments of excitement, the unexpected challenges, and the real potential they see. Artificial intelligence continues to be a transformative force. We're not just talking about theoretical possibilities, but how AI is actually changing the way data professionals approach problems. What does this mean for teams, for individual careers, for the way we think about technology? Tune in to find out!

The world's moving fast, sometimes too fast. Whether it's AI taking over ad campaigns, fake LinkedIn profiles popping up, or the healthcare system extracting more than it gives, the threads connecting our modern chaos are all too clear. Misaligned incentives and unchecked technologies are reshaping industries, culture, and even how we trust each other. Progress can be exciting, but it's also raising some tough questions: Are we losing our humanity in the race to optimize everything? Take Coca-Cola, the apex predator of branding. This holiday season, they swapped their usual creative mastery for AI-generated ads, and people noticed. The results weren't just underwhelming; they were unsettling. It's a perfect example of what happens when we try to replicate the human touch with machines that aren't there yet. But this isn't just about Coke. It's about a broader trend of trading quality for convenience and innovation for cost-cutting—and the ripple effects it has on culture, trust, and livelihoods. This week, we're unpacking the tension between innovation and integrity, exploring how businesses, governments, and individuals can find a better balance. From the rise of fake AI personas to headlights designed to cheat brightness tests, we'll dig into what these examples say about the systems we rely on and what happens when those systems fail us. It's a wild ride, but one thing's for sure: the way forward has to be more thoughtful than the path that got us here.

The AI revolution is here, and if you're in the data space, you're sitting in the best seat in the house—whether it feels that way yet or not. Rob takes you on a straight-talking journey through why our industry isn't just surviving but thriving in this moment of upheaval. Forget the hype and the fearmongering; this is about recognizing the unique position we're in to expand into unmet demand. It's not just about keeping our jobs—it's about making them better, more impactful, and yes, more secure. Here's the deal: this isn't a time to coast. The same tools that can help us shine also require us to step up and adapt. Rob breaks down how the drudge work that used to define so many roles has been swept away by tools like Power BI—and why that's not a threat but a gift. The value isn't in the grind; it's in the thinking. The problem-solving. The expertise. If you're clinging to old ways, you're missing the whole point of what's happening right now. Listen now to hear why this moment is one of the biggest opportunities our industry has ever seen. Rob unpacks how unmet demand is changing the game, why our skills matter more than ever, and what it takes to not just ride the wave but come out ahead. Don't miss it.

Rob and Justin are back, catching up after a short break with an episode that's part big ideas, part funny stories, and full of surprises. They kick things off with the Crutches Paradox. Their take on why we hang onto things we'll probably never use, “just in case.” From there, the conversation moves into all kinds of unexpected territory: why politeness might not matter when working with ChatGPT, the infamous New Coke conspiracy theory from the 80s, and why some of the world's top software engineers just don't seem too concerned about AI. Rob even shares a few personal moments, including how his old Pontiac Bonneville managed to become a legend among tow truck drivers. Between the laughs and the thought-provoking moments, this grab bag episode has a little something for everyone. Whether you're here to explore big questions or just enjoy a good story, this one will keep you hooked from start to finish. As always, if you enjoyed the episode, be sure to leave us a review on your favorite podcast platform.

A little note from Rob to share about this week's episode, and what's coming!

This week on Raw Data, Justin's flying solo and catching up with Brian Julius, a true data veteran with a unique journey from government work to AI exploration. Brian's path has been anything but typical. Starting in high-stakes federal roles, he later moved into management; only to find himself pulled back to his roots in hands-on analytics, just as AI started turning the industry on its head. Brian digs into the moments that shaped his career and how curiosity led him back to data. Now, he's diving into AI, pushing the tools to see how far they can go, and discovering where human intuition still has the edge. In this conversation, he and Justin explore what it means to keep evolving in a field that doesn't stand still, and why staying open and curious might just be the most important skill. With Rob away this week, Justin and Brian take a deeper dive into what it's like to adapt to constant change, and why there's more to data than just knowing the latest tools. It's an honest, down-to-earth look at the power of a lifelong learner's mindset in an era of rapid transformation. Also in this episode: DAX/ChatGPT Ideogram

Rob Collie records his final episode from the cozy, sound-dampened basement studio where over 170 Raw Data conversations have taken place. With moving boxes waiting to be loaded onto a truck bound for Seattle, Rob reflects on his unexpected 15-year journey in the Midwest—an adventure filled with personal challenges, growth, and life lessons that only make sense in hindsight. What started as a sudden and overwhelming shift became a series of hard-earned lessons that shaped not just his career but his entire outlook on life. In this episode, Rob explores the universal nature of those journeys where we step away from the familiar, confront unexpected challenges, and return changed. It's not about grand, heroic feats but about navigating uncertainty, learning as you go, and finding meaning in what's hard. Rob shares candid moments of struggle, success, and everything in between, offering reflections on fear, growth, and the reality of being human. This isn't a story of perfection, it's a journey full of wrong turns, lessons learned the hard way, and the humility that comes from embracing both the light and dark sides along the way. Don't forget, if you enjoyed this episode, be sure to leave us a review on your favorite podcast platform to help new users find us.

In this episode, Rob Collie and Justin break down life lessons learned from a simple tool: the Green Biscuit puck. It's a perfect example of how resilience sometimes beats prevention—because you can't avoid every bump in the road, but you can adapt and keep moving forward. That same idea applies to AI and Power BI, where working with messy, real-world data is part of the process. Rob and Justin draw easy parallels between solving problems on the ice and in business, making complex topics feel less stuffy and refreshingly practical. When it comes to adopting AI, Rob and Justin talk about how it's not a magic fix but a friendly co-pilot, ready to help with everything from writing tasks to brainstorming. The goal isn't necessarily perfection. Sometimes it's simply getting off the starting line. Their advice? Don't overthink it. Take that first step, see where it leads, and let AI surprise you. Tools like ChatGPT can boost productivity, helping you overcome the blank-page syndrome. Be sure to subscribe on your favorite podcast platform for more great episodes on data, tech, and the unexpected lessons hiding in everyday experiences.

This week Rob shares his disdain for CFL light bulbs, but it's not necessarily about light bulbs here!  It's more of an analogy as to why the status quo weighs absolutely nothing.  Something better and disruptive came along, and now it's everywhere. We barely even remember the transition, because the new "light bulb" is far superior to what was previously the standard!

In this episode, Rob Collie and Justin Mannhardt step onto the data gridiron to test if AI can tackle the complexities of fantasy football data. Rob starts with a Power Query puzzle, full of messy stats, player names, and tricky injury codes—solving it manually in over 30 steps. But can ChatGPT, with Justin's guidance, run the same play and simplify fantasy football data management? Justin and ChatGPT take their shot at transforming the chaos into organized data. While ChatGPT makes some impressive moves, there are a few fumbles that leave us wondering—can AI truly handle the ever-changing landscape of fantasy football stats? Want to know how this battle played out? Tune in to find out if AI has what it takes to streamline your fantasy football data or if human instincts still win the day. Here is the companion Blog Post to follow along - Can AI Write an M Script When it Requires Inspiration? Rob Collie Squares Off Versus ChatGPT

Have you noticed the phrase "Dashboards Are Dead" popping up on LinkedIn? It's catchy, provocative, and designed to grab your attention. But is there any truth to it, or is it just another clickbait strategy? In this episode, Rob Collie dives into the psychology behind these viral statements and why they get under our skin. While dashboards aren't going anywhere, there is a shift happening. Generative AI and chatbot interfaces are set to change how we interact with dashboards, making it easier to find, use, and even build them on the fly. But that doesn't mean dashboards are obsolete—far from it. Visuals still offer unparalleled insights that AI simply can't replicate...yet. Listen in as we break down the manipulative tactics behind "Dashboards Are Dead" and explore the exciting future of dashboard design in a world enhanced by AI.

In this episode, Rob Collie talks about how anyone can learn to "predict the future"—not with superpowers, but with a normal ability we all have. Rob shares his own stories of seeing big changes coming, like the rise of Power Pivot and the early signs of COVID-19. It's not about being right all the time, but about recognizing when something big is shifting and knowing how to act on it. One of the biggest lessons here? The status quo isn't permanent. Rob's decision to start P3 Adaptive came from trusting what he was seeing, even when others didn't. His story is proof that when you're willing to trust your gut and take action, amazing things can happen. With AI on the rise, that same approach matters more than ever. The world is changing fast, and those who can adapt will thrive. Tune in to hear how you can tap into your own ability to spot shifts and make smart decisions with confidence. And, as always, if you enjoyed this episode, be sure to leave us a review on your favorite podcast platform to help new users find us!

In this episode, Rob and Justin explore how AI is making waves not just in tech-heavy industries but in everyday businesses like construction and manufacturing. They talk about how AI tools can help streamline processes, create custom solutions, and make even the most hands-on industries run smoother and more efficiently. They dive into the common worry that AI will replace jobs, but they quickly turn that idea around. Instead of taking jobs away, AI is stepping in to handle repetitive tasks, allowing employees to focus on the big-picture work that sparks innovation and growth. It's not about replacing people—it's about enhancing what they do best. Rob and Justin also make the case that AI isn't out of reach, even for companies that don't see themselves as tech-savvy. With tools like Power BI and the rise of generative AI, businesses of all sizes can use AI to improve their operations without a major overhaul. AI is becoming more accessible, and it's something that can make a real difference no matter your industry. Be sure to leave us a review on your favorite podcast platform to help new listeners find us!

Ever think about how data can solve real-world problems? Rob and Justin are here to break it down! They're diving into how data analytics is changing the game in industries like manufacturing, agriculture, and construction—where the work is hands-on, and the results matter. From managing logistics to cutting downtime and optimizing inventory, they show how data is becoming the go-to tool for getting things done. Justin shares a personal "aha!" moment from his days in manufacturing, where stepping out of the office and onto the floor opened his eyes to data gaps you just can't catch from behind a desk. Rob also reflects on his time in construction and how those real-world experiences shaped his view of business today. Rob and Justin keep it real, cutting through the noise to show how understanding the world behind the numbers is the key to solving real problems. Enjoyed the conversation? Leave us a review on your favorite podcast platform to help us reach more listeners!

Think farming and data don't mix? Think again! In this episode, Paul Grissom from Pacific Ag Rentals (PAR) brings the heat, showing how data is shaking things up in agriculture. From slashing manual work to making on-the-spot decisions with real-time insights, Paul shares how technology is helping PAR not just keep up, but thrive. Whether you're a data geek or just curious about how tech is fueling growth in unexpected ways, this episode is a fun, eye-opening ride into the future of farming. Paul doesn't hold back—he shares an honest take on what it's like to bring data into a hands-on industry like agriculture. You'll hear how PAR is using data to optimize equipment, streamline their operations, and seriously level up their business. And the best part? It's not just about crunching numbers; it's about seeing real growth and making smarter moves every day. If you think data is only for tech companies, Paul's story will change your mind—and maybe even get you excited about what data can do for your business. What makes this episode a must-listen? Paul's down-to-earth vibe and no-fluff approach. He breaks it all down so anyone can understand how data is making a real-world impact, even in an industry as hands-on as farming. It's the kind of story that shows how a little tech can go a long way, no matter what field you're in. If you're looking for inspiration on how data can fuel growth in your own world, this is the episode for you! Loved what you heard? Let us know! Leave a review and tell us what you think—your feedback helps us bring you more awesome stories like Paul's, packed with insights you can use right now.

Is the Midmarket Secretly Winning with the Microsoft Data Platform? In this episode, host Rob Collie explores a surprising quirk in how Microsoft's powerful data tools like Power BI and Fabric are being used. It turns out that midsize companies - not big enterprises - are actually getting the most bang for their buck from these game-changing data platforms. The episode explains how the speed and affordability of the new Microsoft tools give smaller organizations a real advantage. Rob also shares an unexpected lesson he's recently uncovered through his own personal analytics projects. Even with just two basic data points per player, he was able to unlock a crazy amount of useful insights and stories. It just goes to show the hidden richness that can be found in even the most simple datasets. Check out the Hockey Dashboard referenced! So tune in to find out how a "bathtub" of data can hold an "ocean" of information - plus hear about the midmarket's secret winning strategy. It's an episode you won't want to miss! Subscribe now for new episodes every week, packed with practical data insights!

Join us for a down-to-earth chat with Microsoft's Scott Sewell, a guy who's seen it all when it comes to the crossroads of tech, business, and just being human. Scott's got a front-row seat to how empathy—yeah, that often-overlooked human quality—is actually a game-changer in today's tech-driven world. We talk about why understanding what makes people tick isn't just good for the soul, it's critical for delivering solutions that really hit the mark. But let's get real: no one loves the drudge work, and Scott's here to tell us why those days are numbered. We dig into how AI, especially within the Microsoft Fabric and Dynamics world, is cutting out the busy work that bogs us down. Imagine freeing up your time to focus on the stuff that truly matters—Scott shows us how it's not just possible, it's happening right now. Scott's got some great stories up his sleeve, too, about how embracing AI isn't just a cool thing to do—it's essential if you want to keep up. Whether it's getting rid of those tedious manual tasks or unlocking insights that were once out of reach, Scott makes it clear: the clock's ticking on drudge work, and the future is all about working smarter, not harder. So, if you're ready to hear how empathy and AI can transform your business (and your day-to-day), tune in. Scott's insights will have you rethinking what's possible—and why the mundane should be left in the dust. If you enjoyed this episode, we'd love for you to leave a review! Your feedback helps us reach more listeners who are looking to transform their business with data, tech, and a bit of empathy. Plus, it helps new listeners discover the show so they can join in on the conversation.

We're still buzzing with excitement over here at P3 Adaptive about Microsoft Fabric and this week, Rob and Justin take a look at some client use cases. The gist of it? This tool is seriously shaking things up for our clients in the best way possible. The P3 Adaptive team has been playing around with Fabric, and let me tell you, it's a game-changer. It's like giving your data superpowers - speeding things up, putting more control in users' hands, and tackling those pesky data hurdles. We're seeing companies out there not just dipping their toes in but really diving deep with Fabric. They're zeroing in on specific pain points and watching Fabric work its magic. The cool part? Teams are becoming data ninjas on their own, without always having to run to the BI department for help. It's all about exploring data your way and making smarter decisions, faster. The impact of Fabric isn't just hype - it's real and it's happening now. Across different industries, we're seeing Fabric turn data challenges into opportunities. Teams that used to struggle with data are now working through it smoothly. Companies are not only handling their data more efficiently but are also uncovering insights they never knew existed. It's like watching businesses unlock a whole new level of data mastery, and the results are seriously impressive. Fabric is proving that when it comes to data, the future isn't just bright - it's already here and making waves. Want to stay in the loop on all things Fabric and data innovation? Don't miss out on our future episodes! Subscribe now and get the latest insights, tips, and success stories delivered straight to your inbox.

Ever feel like everyone's got an opinion on AI these days? Rob and Justin sure do, and in this episode of Raw Data, they're not afraid to call it as they see it. Fresh off Rob's solo deep dive into AI, they sit down to unpack the good, the bad, and the overhyped in the world of artificial intelligence. No jargon, no buzzwords - just straight talk about what AI can (and can't) do. From chatbots that sound eerily human to the reality of AI "hallucinations," Rob and Justin break it all down in a way that actually makes sense. They're not here to sell you on AI being the next big thing or convince you it's all smoke and mirrors. Instead, they offer a refreshingly honest take on where AI shines and where it falls flat. Want to know how AI might change your job? Rob and Justin dig into real-world examples, from call centers to coding. Power BI folks, there's something in here for you too - turns out AI might be a game-changer for some tasks, but it's not gunning for your job just yet. By the end of the episode, you'll have a clearer picture of what AI means for you, your work, and the world at large. No tech degree required - just bring your curiosity and maybe a healthy dose of skepticism. Got thoughts on AI? Rob and Justin want to hear them. Join the Raw Data Steering Committee on LinkedIn to be part of the conversation!

Dive into the world of manufacturing where data meets decision-making with Madison Brooks, an expert from P3 Adaptive who brings her chemical engineering and industry experience to the forefront. This episode zeroes in on why the manufacturing sector is the ideal ground for leveraging Power BI and Power Apps, tools that transform raw data into actionable insights and streamlined processes. Madison discusses the integration challenges and triumphs, illustrating how these technologies drive efficiency and innovation in manufacturing operations. Throughout the discussion, Madison provides practical examples from her extensive background, demonstrating how Power BI and Power Apps optimize everything from production lines to inventory management. She highlights specific case studies where these tools have enabled manufacturers to pivot quickly, reduce waste, and better understand their operational dynamics through enhanced data visualization and application development. For professionals in the manufacturing industry or those exploring how to enhance operational efficiencies with technology, this episode offers invaluable insights. Madison breaks down complex tech solutions into understandable and implementable strategies that can profoundly impact business outcomes in Manufacturing Data Analytics. Listen now and discover how you can transform your manufacturing operations. Be sure to subscribe to our podcast for ongoing episodes where we simplify the complex, through down-to-earth conversations about data, tech, and the real business impact.

Today we are coming at you a day early for a timely bonus episode with Rob Collie diving deep into the digital disruption that shook the world: The Great CrowdStrike Hiccup of 2024. Picture this: a day when the antivirus behemoth stumbled, and the digital realm felt the shockwaves, akin to a #VALUE! error in your perfectly tuned DAX formula—but on a colossal, global scale. Before you start placing the blame on IT, let's take a step back to see the broader view. This incident with CrowdStrike, while jarring, underscores the exceptional resilience typically woven into our digital fabric. Consider it the outlier in your data set that highlights how well everything else aligns. Every day, countless professionals from coders to IT support keep our digital infrastructure running as smoothly as a finely tuned Power Query. The key lesson from this event? Our digital networks are sturdier than they appear, much like a robust pivot table equipped with slicers. Despite the hiccup, the swift response from tech teams worldwide to rectify the issue was nothing short of remarkable. It's a nod to the everyday heroes in tech who ensure that our systems run without a hitch. So, the next time you see that meme mocking "the other side," remember, we're all part of the same intricate data model of life. And, don't worry, we are still on track for a full-length release tomorrow. Be sure to tune in then when we welcome special guest Madison Brooks to share some behind-the-scenes insight on Power BI, Power Apps, and the manufacturing industry!

It's time to dive back into the wild world of AI with Rob Collie. Get ready to cut through the hype and uncover the real deal on artificial intelligence. In today's episode, Rob examines the varied faces of AI, from its potential to revolutionize industries with breakthrough innovations to its ability to streamline our daily activities and make routine tasks more efficient. Have you ever wondered how AI might be influencing your life without you even noticing? Rob brings these abstract concepts down to earth. He provides a fresh perspective on how AI operates silently yet significantly in the background of our daily interactions and decision-making processes. You'll leave this episode with a clearer understanding of how to interact with AI effectively, recognizing its benefits while being mindful of its limitations. Rob's insights will help you navigate the AI landscape with confidence, armed with the knowledge to identify genuine opportunities and avoid common traps. Don't miss out on your weekly dose of tech reality! Subscribe to Raw Data on your favorite podcast platform. Stay ahead of the curve and discover how technology is reshaping our world!

This week we're talking with Power BI MVP Kristyna Ferris about flipping the script on how we look at business data. She has some cool ideas about viewing things from the outside that might change how you think about your company's data. Kristyna walks us through her approach, showing how she used Power BI to get a bird's eye view of an organization It's eye-opening - like she's put her company under a giant microscope, revealing all sorts of connections and patterns hiding in plain sight. She catches all sorts of interesting things, from what customers are really up to, to where things are getting gummed up in operations. But here's the kicker - Kristyna doesn't just sit there admiring the view. She takes what she sees and makes real changes. She'll run through some examples of how this outside-in perspective led to actual improvements. We're talking streamlined processes, new market opportunities - the whole nine yards. The best part? Kristyna's figured out how to get everyone else on board with this way of thinking. She's got some great tips for creating a culture where people are itching to step back and look at the big picture. It's about building a team that's always on the lookout for the next big "aha!" moment. If you're tired of staring at the same old dashboards and want to see your business in a whole new light, you'll want to tune in. And be sure to hit subscribe  for new weekly content. And remember, sometimes, you've gotta step outside to really see what's going on inside.

Dive into an intriguing exploration with Shawn Rogers, CEO of BARC US, as we delve into whether Power BI is a stepping stone to mastering Artificial Intelligence (AI) and Machine Learning (ML), or if it's the other way around. This episode isn't just about technology—it's a deep dive into the symbiotic relationship between business intelligence tools and the latest advancements in AI. With his extensive background in analytics and business intelligence, Shawn unravels how Power BI can serve as both a platform leveraging AI capabilities and a beneficiary of AI-driven enhancements. He discusses the dynamic interplay where AI not only complements but also extends the functionalities of Power BI, transforming how businesses interpret and act on data. Listeners will gain a nuanced understanding of how to strategically prepare their Power BI setups to both utilize and enhance AI technologies. Tune in and see firsthand how Power BI and AI are reshaping the analytics landscape together. Whether you're deep into data or just starting to see its potential impact on your business, Shawn Rogers brings a wealth of expertise that bridges the technical with the practical. Are you looking for a podcast that cuts through the noise? Raw Data by P3 Adaptive breaks down complex data topics into business value you can use. From business intelligence and dashboards to AI and digital transformation, we make it simple and relatable. Don't forget to subscribe and leave a review on your favorite platform!

Last week, Rob talked about his personal use Power BI Model for tracking his wife's changes in medicine and symptoms.  This week, Rob and Justin explore a bit more about this model, and its readiness for AI and Machine Learning - and discuss how this readiness factor applies to other PBI models in business!

This week's Raw Data Podcast features a thoughtful discourse with host Rob Collie, who shares how his expertise in data analytics plays a crucial role far beyond the confines of office walls. Rob discusses the sophisticated data model he has developed to manage the health of a family member, detailing the careful balance of medication, symptoms, and environmental influences that the model helps orchestrate. As Rob walks us through the system, he reflects on the transformative impact that this data model has had on their lives. It's a practical example of “analytics nirvana,” where data handling becomes second nature, fully integrated into the rhythm of everyday life. Rob's story illustrates the seamless intersection of data management and personal care, providing a powerful testimony to the versatility of data analytics. Join Rob as he delves into how data can not only guide business decisions but also anchor critical personal health strategies. It's an exploration of how data models can deeply embed themselves into our personal lives, making the management of complex health conditions more navigable. And, as always, if you enjoyed the show, be sure to leave us a review on your favorite podcast platform to help new users find the show.

In this week's episode of The Raw Data Podcast, we're excited to reconnect with Chris Finlan, a pivotal figure at Microsoft in the evolution of SQL Server Reporting Services and now a leading advocate for Power BI. Chris invites us on a journey from his early career breakthroughs to his current pioneering work in data analytics. Joined by host Rob Collie, Chris revisits an extraordinary story: a data model he crafted over a decade ago that still powers significant operations at a major organization. This isn't merely a conversation about the durability of technology—it underscores the lasting impact of thoughtfully designed data solutions that continue to perform year after year. If you're curious about how innovations in technology continue to shape business today, or if you love hearing the personal stories behind the tech, this episode is definitely for you. Tune in for a perfect blend of nostalgia and insightful reflections, delivered in Chris's unique style from his experiences at Microsoft. Be sure to subscribe to The Raw Data Podcast on your favorite platform for more down-to-earth conversations about data, tech, and biz impact, and join us in exploring the fascinating intersection of technology and practical business solutions. Also in this episode: The Persistent Power of Pagination, w/Microsoft's Chris Finlan

Dive into this week's episode where we explore the fascinating intersection of technology and creativity with Forrest Brazeal. Forrest, a former software engineer turned tech educator, uses his unique talents in art and music to break down the barriers of traditional tech communication. This episode features Forrest sharing his journey from coding complex software to crafting educational and engaging content that lights up the tech community. He discusses how artificial intelligence is woven into the fabric of our daily tools, making it essential yet invisible, and gives practical examples that bring this technology to life for listeners of all backgrounds. Forrest also takes us behind the scenes of his creative process. Whether it's sketching out a cartoon that simplifies cloud computing or composing a catchy tune about network security, his methods are as effective as they are enjoyable. It's a fresh take on tech education that proves learning about technology doesn't have to be daunting—it can actually be a lot of fun. Intrigued by the blend of tech and creativity? Subscribe to The Raw Data Podcast on your favorite podcast platform for new content on data, tech, and their business impacts delivered to your inbox every week. Good Tech Things The AI Cartoon - Pile of Complexity

On this episode Rob and Justin sit down with Miguel Myers, Principal Program Manager for Power BI at Microsoft, who plays a pivotal role in overseeing core visuals and the report experience in Power BI. Together, they explore how Miguel is steering Power BI to cater to both new users and data experts alike. Miguel shares his intricate strategies for balancing the dual objectives of simplicity and robust functionality within Power BI. He details the collaborative efforts that bring these visions to life, highlighting how his team engages with various departments across Microsoft to ensure that every update to Power BI is deeply informed by user feedback. This integration of real-world insights is critical in maintaining Power BI's position as a leading tool in data visualization, making complex data analysis more accessible and impactful for all users. This episode provides a deep dive into the innovative strategies Miguel employs to make Power BI more intuitive and efficient, underscoring his dedication to enhancing the user experience. And, if you enjoyed this episode, be sure to leave us a review on your favorite podcast platform to help new listeners find us!

In this episode, we unpack the 'Faucets First' philosophy, a cornerstone of how we approach data projects at P3 Adaptive. Imagine bypassing complex infrastructures and instead, using a straightforward method that brings immediate results and clarity. It's about being agile, practical, and impactful right from the start. Join us as we explore how modern tools, especially from Microsoft, enable this transformative approach, moving away from the traditional, cumbersome methods. We'll dive into real-life applications and discuss the dramatic improvements in speed and efficiency it brings to data projects. With exciting guests like Miguel Myers and Chris Finlan from Microsoft, viral comic creator Forrest Brazeal, and industry veteran Shawn Rogers lined up, you won't want to miss an episode! Subscribe now on your favorite podcast platform for new content delivered weekly!

In this episode, join Rob as he navigates two significant topics that are shaping the landscape of modern business. In this solo episode, Rob reflects on the dynamic journey of P3 Adaptive, discussing our recent transition into a new growth era propelled by evolving market conditions and internal strategies. He delves into the intricacies of sustaining and fostering this growth, sharing the challenges and strategic decisions that define our path forward. Additionally, Rob has a bit of a Mea Culpa to share about his previous understanding of the Parquet file format and the comparison between Direct Lake and Import Mode in Power BI. The conversation then shifts to a critical development in employment law. Rob unpacks the recent FTC ruling that renders non-compete agreements illegal, exploring its broad implications across various industries, from tech to professional services. He sheds light on how P3 Adaptive uses non-solicitation agreements to safeguard client relationships, emphasizing the balance between competitive edge and ethical practices. Love what you're hearing? Make sure you don't miss an episode by subscribing to The Raw Data Podcast on your favorite podcast platform! Also in this episode: Direct Lake VS Import Mode in PBI

Dive into this episode where we're unraveling the threads of data analytics like never before. This week, we're zeroing in on the seismic shifts in technology that are reshaping our understanding and use of data. Imagine stepping into a world where data isn't just numbers, but the lifeblood that pushes businesses forward. We're going to take a deep dive into semantic models. Once confined to back-end operations and report generation, these models are stepping into the limelight, becoming powerhouse tools for strategic decision-making. We're not just talking about the mechanics—we're exploring how these developments touch everything in the business world and open up a world of possibilities you might never have considered. Plus, here's your chance to steer the ship: join our LinkedIn steering committee. It's your chance to propose topics, suggest guests, and help us chart the course toward the most pressing issues and innovative ideas in data analytics. Your voice can help direct our journey, bringing fresh perspectives to the table. And, as always, be sure to leave us a review on your favorite podcast platform to help new listeners find us! P3 NCAA March Madness

This week we're diving into the heart of Microsoft Fabric, armed with fresh insights from our team of experts -- Will Gillingham, Mark Beedle, and Chris Haas who've just returned from the conference. These veterans in SQL and Power BI share their firsthand experiences and dissect the potential of Microsoft's evolving data architecture. Together, they'll explore crucial questions around Microsoft Fabric's capabilities and implications: What exactly is it? How does it shift our traditional approaches to data management? Our experts will simplify these complex topics, offering clear, actionable insights for both technical professionals and strategic decision-makers. And if you enjoyed this episode, don't stop here! Explore more with our detailed Fabric webinar and browse our comprehensive Microsoft Fabric FAQ for additional insights. Remember to subscribe and join the fun—get fresh, exciting episodes loaded with insights delivered straight to your feed every week!

Navigating the world of AI can sometimes feel like you're trying to solve a puzzle with half the pieces missing. That's where, in this episode, Rob and Justin come in, offering a helping hand with their down-to-earth framework designed to uncover the real-world benefits of AI for businesses. They'll guide you through the practical journey of assessing roles, tasks, and workflows to spotlight where AI can genuinely lend a hand. Their approach is all about making the concept of AI more approachable, helping you differentiate the practical uses from the buzzword-filled fantasies. In this enlightening episode, they cover essential ground, from understanding the implications of decisions made without full information to distinguishing tasks that could really benefit from AI's touch, like optimizing gas delivery routes. Plus, they introduce the "AI sniff test" to help identify processes that are ripe for an AI upgrade. This detailed exploration is aimed at giving you the clarity to spot AI opportunities that are custom-fit for your business's unique needs, whether you're just dipping your toes into AI waters or looking to dive deeper. Rob and Justin are essentially extending an invitation to stop wondering "What if?" about AI and start exploring "What can be?" Their friendly guidance demystifies the process, making AI seem less like a distant dream and more like a tangible tool within your reach. For anyone curious about integrating AI into their business but unsure where to start, this episode promises to be an eye-opener, turning curiosity into actionable insight. And, as always, if you enjoyed this episode, be sure to leave us a review on your favorite podcast platform to help other users find us and hit subscribe for new content delivered weekly. Framework for Spotting Legitimate AI Use Cases PDF

Dive into the depths of AI with Rob and Justin in our latest episode where we peel back the layers of AI's current facade. In this compelling discussion, we take a critical look at the hyped-up narratives surrounding artificial intelligence, focusing on a crucial issue at its core: the "hallucination problem." Rob and Justin navigate through the intriguing landscape of AI advancements, debunking myths and uncovering the reality behind AI's ability to produce outputs that, while often impressive, can lead to misleading and incorrect conclusions. This episode promises to enlighten you with a fresh perspective on AI, challenging the status quo and urging listeners to question what lies beyond the surface of this technology's glittering promise. But it's not all critique and caution; our hosts also delve into the implications of AI's limitations for businesses and technologists alike, fostering a dialogue on how we can navigate this evolving landscape with both optimism and pragmatism. "Hallucination" is a Fancy Word for Being Wrong is more than just a critique; it's a journey to understanding the nuances of AI, encouraging listeners to embrace the complexity of this revolutionary technology. And as always, if you enjoyed this episode be sure to leave us a review on your favorite podcast platform to help new listeners find us. Also, click subscribe for new content delivered weekly! Also in this episode: The Manhattan Project Midjourney

Everyone talks about digital transformation, but it seems like no one really explains what it means... until now. In today's episode, Rob and Justin dive deep to cut through the buzzwords and lay out the reality. They're tackling why digital transformation isn't about making huge, instant changes but rather about the smart, subtle tweaks in areas that usually get ignored but badly need a digital lift. They dive into how leveraging tools like the Power Platform can spark significant improvements, showing that it's the small changes that can really boost efficiency and smooth out your workflow. Ever found yourself wondering how to translate all the chatter about digital evolution into actionable steps? That's exactly what Rob and Justin are unpacking. They're guiding you through how minor, yet clever adjustments can transform your processes. It's all about enhancing the routine, one step at a time. And, as always, if you enjoyed the episode, be sure to leave us a review on your favorite podcast platform to help new listeners find us. EPISODE TRANSCRIPT: Rob Collie (00:00): Hello, friends. In today's episode, Justin and I demystify what is meant by the phrase digital transformation. Phrases like that are one of my least favorite things. Why do I say that? Well, these are phrases that get used a lot. They cast a big shadow. You encounter them almost anywhere you go. That's fine by itself. But in the case of digital transformation, that massive shadow is multiplied by no one understanding what it actually means.  (00:30): Now earlier in my career, I used to be really intimidated by things like this. Everyone seems to know what this means because they're using it all the time. I don't know what it means, so should I just pretend and play along like everyone else? But at some point, many years ago, I had this moment where I realized that the Emperor has no clothes. It almost never has clothes. Now when I encounter phrases like this, instead of being like paralyzed or intimidated, I instead start working in my own definition and this process takes time. I've been picking apart and stewing on the definition of digital transformation now for probably the better part of a year plus. Somewhere along the way in that process, I realized that we at P3 are doing quite a bit of digital transformation work, I just hadn't realized it yet because I didn't have a good enough definition.  (01:18): Lately, I've been noticing that my definition for digital transformation has reached a steady state. It's not changing over time anymore, which tends to be my signal that I've arrived at a definition that works. Now seemed like a good time to sit down and compare notes with Justin, who's been following his own parallel process of arriving at a definition. I'm very pleased with where we landed. A practical and specific definition that can be reduced to practice with an almost paint-by-numbers type of approach.  (01:47): If you asked someone for a definition of something like digital transformation, and by the time they're done giving you their definition, you can't practically boil that down to what it means for you, that's not a problem with you, that's a problem with the definition. A lot of times, people's definitions for terms like this are almost like deliberately vague, as a means of projecting power, as a means of actually controlling you. You'll get a lot of definitions that are engineered to sound smart, engineered to sound authoritative, but not engineered to provide anything resembling clarity. Because if you sound smart, and you sound authoritative but you leave your audience hungry, you create a feeling of dependency. Folks, I just think that's yucky. That's just gross.  (02:35): To show you what I mean, I just ran the Google search, "What does digital transformation mean?" The very top hit, enterprisersproject.com, defines digital transformation as "the integration of digital technology into all areas of a business resulting in fundamental changes to help businesses operate in how they deliver value to customers." Did that clear it up? Nope. Boiling that one down, it sounds a lot like you should use computers and use them to make changes. But it sounds smart, sounds authoritative.  (03:06): Here's the second result from our old favorite, McKinsey. McKinsey defines digital transformation as "the process of developing organizational and technology based capabilities that allow a company to continuously improve its customer experience and lower its unit costs, and over time sustain a competitive advantage." All right, so that one sounds like McKinsey is almost starting with that original definition and adding additional value to it. They're saying use computers to improve, and to make money, and to compete. If you have $1 million to spend, you can get advice like that.  (03:43): All right, with those two definitions, we don't even need an episode. We can just skip it? Because everyone knows exactly what they're talking about. These are the top two hits on Google, folks. Useless. Part of the reason these definitions are useless, again, is because they're designed to be useless. But I also think though, that a lot of times you hear definitions like this is because the people writing them actually cannot boil them down. By the time you come up with a truly useful definition, or a framework, or a guide for understanding a topic like this, it almost by its definition, it's not going to sound nearly as sexy, nearly as smart. It's going to sound relatively simple, mundane. But those are the valuable definitions, the ones that we can actually apply, that make a difference in how we actually view our own business. (04:29): That's what we set out to do in this episode. I think we succeeded, came up with a very practical, applicable definition that you'll never find on McKinsey's website. Let's get into it.  Speaker 2 (04:42): Ladies and gentlemen, may I have your attention please?  Speaker 4 (04:46): This is the Raw Data by P3 Adaptive Podcast, with your host, Rob Collie, and your cohost, Justin Mannhardt. Find out what the experts at P3 Adaptive can do for your business. Just go to p3adaptive.com. Raw Data by P3 Adaptive is data with the human element.  Rob Collie (05:12): Justin, one of the things that we really like to do, I really like to do, I think you do as well, is to take a phrase or topic, and demystify it. Especially phrases that you hear repeated over, and over, and over again, and everyone has to pretend that they understand what they mean. But even when they do, they often have very different pictures in their heads.  (05:33): One that I think is due for a treatment, and we've hinted at it once before on this podcast but not with any depth, is digital transformation. What does it mean?  Justin Mannhardt (05:45): What does it mean, what does it not mean, all parts in between.  Rob Collie (05:50): Starting with the places where I hear it. I often hear it in the context of this is something that's already done. The big talking head analysts at places like Gartner- Justin Mannhardt (06:00): Yeah.  Rob Collie (06:00): Will talk about it like it's in the rearview mirror. "The shift to digital, the pivot to digital has forced the following things," so has forced, it's a past tense thing. Which further underlines the idea that well, if it's already happened, clearly everyone knows what it means. They don't stop to define it, they're just tossing that aside as a means of getting to the next point. I find that to be one of the most troubling habits of the talking heads.  (06:28): The first few times I encountered this phrase, I didn't really know what it meant. I imagined that it meant switching to ecommerce from brick-and-mortar. Justin Mannhardt (06:37): Yeah.  Rob Collie (06:37): I didn't even realize that that was the impression I had, it was just this vague feeling in the back of my head.  Justin Mannhardt (06:42): The word digital, I'm just thinking about this now because a lot of times, you'll look at one of these diagrams, it's like, "Your digital transformation wheel includes all these things." You'll see something like, "Move to the cloud." I'm like, "Okay, were the servers with the software, was that software analog or something?"  Rob Collie (06:59): Yeah, we've been digital for a long time, right? Justin Mannhardt (07:01): Yeah.  Rob Collie (07:01): Most broadly defined, you could say that the digital transformation really got going with the adoption of the PC.  Justin Mannhardt (07:09): Right.  Rob Collie (07:10): That was when digital transformation started. In the sense that it started in the 1980s, maybe it is something worth talking about somewhat in the rearview mirror, but that's not what they mean. They don't mean the adoption of the PC. Justin Mannhardt (07:23): No. But it's interesting, when you think about the timeline of technology evolution. People say, "Oh, you described it as past tense." Digital transformation has occurred in en masse in market. Now today, it's like AI is here, en masse in market. But the pace at which new things are coming out, what's really happening is just the long tail is longer back to where companies were at in this journey. It's not like the entire industrial complex has been collectively moving to the modern current state across the board. There's companies that are still running SQL 2000, that's their production world still. This isn't something that's happened.  Rob Collie (08:09): I think that the big talking head analysts often tend to really only talk about the most elite sub-strata of even their own clients. When they talk about this as something that's completely done, even most of Gartner's paying clients, I would suspect, aren't anywhere close to done. But we still haven't really started talking about what it actually means.  (08:32): Let's say it is not the switch from paper and pencil systems to electronic line-of-business systems. Not only do we have the PC, and that's been long since mainstreamed, the notion of line-of-business software, server based software, whether cloud or otherwise, line-of-business software is also I think incredibly well entrenched. We're done with having key business systems running in a manual format. That's long since rearview. That also isn't what they mean by digital transformation. (09:07): Of course, both of those are digital and they were huge transformations, but that's not the digital transformation we're talking about. It's anything that's happened after that.  Justin Mannhardt (09:15): Yeah.  Rob Collie (09:16): It's a lot harder to pin down the things that happened after that.  Justin Mannhardt (09:20): In general, I agree with you because the big blocks, software, the availability of the cloud, not having intensive paper process in most companies, that's largely been accomplished. To different levels, of course. Then, what's left? What's the definition? What are we trying to do?  Rob Collie (09:41): Well, if you think of the line-of-business application and the PC, the PC interfaces with all the line-of-business apps. I would say that, and even this is not 100% true, but I would say that the conversion to digital systems is complete, or complete-ish. Justin Mannhardt (09:59): Okay.  Rob Collie (09:59): When you look at your business as individual silos. Justin Mannhardt (10:03): Say more. You've got a digital environment for finance, digital environment for sales, is that what you mean?  Rob Collie (10:09): Yeah. Core workflows have largely been digital for a while. All the workflows that take place between systems, or the workflows that take place adjacent to a system, those are the things that we're talking about when we talk about digital transformation, going after those workflows.  (10:30): Everything we've been doing in the world of business software since at least the 1980s has been digital transformation.  Justin Mannhardt (10:38): Yeah.  Rob Collie (10:39): But our digital transformation, we're really talking about at least the third chapter. It's not chapter one or two. It's like the next frontier, identifying and going after a new class of workflows that would benefit from essentially software support.  Justin Mannhardt (10:56): Right.  Rob Collie (10:56): Okay. Now because almost by definition, just by subtraction ... We're saying, "Look, we've got the PC, we've got the line-of-business systems that handle the core workflows within a silo. What's left?" Well, it's almost like a perfect mathematical proof. What's left is the stuff between and outside. (11:14): Given that everyone's mix of line-of-business systems is, I like to say, best of breed, meaning random. It's whatever we decided at the time. It seemed like a good idea at the time. Legacy.  Justin Mannhardt (11:25): Yeah.  Rob Collie (11:26): You're never going to have anything off-the-shelf that helps you solve the workflows. The middleware problem between your systems is always going to be a custom solution.  (11:38): We should give examples of these. When I said outside or adjacent to, there's even workflows that they're not really between systems, they're just the offline portion of working with the system. I'm thinking about a budgeting process, for instance. The world's first budgeting systems were mostly there to record your budget that you enter into it. As those budgeting systems have gotten better, they've included more and more of the human workflow that goes into creating, and evaluating, and kicking the tires before it's finalized. Those offline human workflows, getting more and more structured about them, can make a huge difference. Justin Mannhardt (12:19): Not just structured, Rob, more tightly integrated with the adjacent system itself. I like that adjacency, because if you have a financial system where your budget or your forecast lives, there's a martialing of activity, analysis, input. Then you say, "Okay, we need to get it look like this," and then we put it in the thing. What happens in that processes, you get all sorts of scattered iterations of ideas and it gets loose. But if you could have all that iteration tight, the final submission is already handled or much easier.  Rob Collie (12:51): Yeah. Sticking with the budgeting example for a moment, it still echoes one of the themes I mentioned for the between systems, the between silos case. Which is that one-size-fits-all systems, off-the-shelf systems, they really struggle to address all the nuances of your particular business. It's very, very difficult. The more, and more, and more you try to get the offline processes, the human processes brought into the digital workflow, the more an off-the-shelf software package is going to struggle. It's getting further and further away from the safety of the core of the task.  (13:28): This is why the Power Platform approach to budgeting and planning is often, in fact almost always, a more effective, in terms of cost-effective, time effective, results effective. The core libraries for doing all of the things that you need to do are basically already there and it's inherently designed to be customizable.  Justin Mannhardt (13:48): And very nimble. Even the big players in FP&A software, they're not that great, in our opinion, at the end of the day. But the price points just exclude anybody that's not a very sizeable, formidable company. You're not looking to spend that kind of money if you're even a few hundred million a year type operation. You're just not going to sign up to that agreement. You are left with a middleware type of a problem, that you're either solving with spreadsheets, pen and paper, or something else. Our platform can slide right in there.  Rob Collie (14:26): Of course, there is a huge advantage to performing a "digital transformation" on a process like that because the human, offline, pen and paper, sending random emails, getting answers, tracking them, it's incredibly tedious, it's incredibly error-prone. Just super, super slow. It's not like you can perform many iterations. You're not even really going to be able to pull off one iteration and you call it good. But you're just going to miss so much. The budget could have been so much better. If you've got a bad budget, of course you're going to pay for that later.  (14:58): That's the adjacent case. Let's talk about the between a little bit as well. What's an example of a workflow that would span across different line-of-business systems but require a human being essentially, or humans, to essentially carry the buckets of water between those different pipes?  Justin Mannhardt (15:18): We'll make up a company today, Rob, we'll start a new company and it's going to be called I Manufacture Things, Inc. Hey. At I Manufacture Things, Inc., I've got a sales team.  Rob Collie (15:28): Do we make things other than ink?  Justin Mannhardt (15:30): No, that's incorporated.  Rob Collie (15:32): Oh, okay.  Justin Mannhardt (15:32): We just make things.  Rob Collie (15:34): Can't help it. Can we be We Manufacture Things Ink, Inc.?  Justin Mannhardt (15:38): Sure.  Rob Collie (15:39): All right. But anyway, we manufacture things.  Justin Mannhardt (15:41): There you go. We've got a sales team and they're using a CRM system, such as Salesforce, or HubSpot, or whatever. They're out there, they're doing quotes, they're tracking opportunities, and eventually someone says, "Yeah, I'd love to buy a palette of ink," or whatever. Our company, we're not using the CRM to deal with the production and fulfillment of that order. Okay, so now there's this process where my order form, let's not use any paper in this example, it's still digital but it lands as a PDF form in someone's email inbox that says, "Hey, Customer Service Rep, here's an order." Oh, okay. Now I'm keying said order into our production system that says, "Go manufacture this thing." Now we need to ship the thing out somewhere, and now we're in our logistics system.  (16:33): There's all these little hops between systems. Which technology has become more open, and sure there's things like APIs and code based ways to integrate them, but that's not in range for a lot of companies. That's an example of where you could stitch in these little Power Platform type solutions to just, "Hey, let's map the relevant fields and information from the CRM into the order management system." If there's some blanks that need to get filled in, that's okay. Maybe I'm just starting from a queue of new orders right in the system, and I'm maybe adding three or four pieces to that puzzle instead of all of it. Rob Collie (17:12): Okay. I want to make a global note here. Note that we're talking about this broad topic, digital transformation. We're already way down into very detailed, specific use cases. In my opinion, that's what digital transformation is, it's a collection of all of these individual use cases where things can get faster, more efficient, more accurate. It is the sum of many small things. Each one of them might have tremendous impact. This is the way.  (17:46): In this particular example, I've been describing the Power Platform as the world's best middleware for a while now. Even Power BI is middleware. It's beautiful, beautiful, beautiful capability is that it can simultaneously ingest data from multiple different line-of-business silos that have never once talked to each other. The only place that they meet is in a Power BI semantic model.  Justin Mannhardt (18:10): Yeah.  Rob Collie (18:10): And they play a symphony together that Power BI makes them play. They still have never seen each other, but Power BI is what bridges the gap. Now, Power BI is read-only by itself, it doesn't make changes to any systems. (18:25): In this particular case, it sounds like Power App's and Power Automate's music. Let's just get really tangible here. I know that it's a very specific, but it's a fictional example. But lots of people have almost exactly this problem. Justin Mannhardt (18:39): Yeah.  Rob Collie (18:39): Just talk me through what a solution to that particular problem might look like if we implemented it in the Power Platform. How much work, how much elapsed time do you think it would take? Let's dig into this one a little bit.  Justin Mannhardt (18:51): If what I want to do is, when we receive an order or close a deal in our CRM, I want that to move some data to another system, let's just say that's assumed. Power Automate can solve this need. Obviously there's a lot of detail, you can look some things up online, or you can email robandjustin@p3adaptive.com and we can trade some ideas here. But there are tons of out-of-the-box connectors, and in those connectors they have what's called a trigger. I could say, "When this happens in Salesforce," for example, "I want to start building a flow." I can say, "Okay, I want these fields, and I want to write them from Salesforce to this destination." Maybe that destination's a database, maybe that destination is another system that Power Automate supports that you can write to.  (19:37): It could be just this simple mapping exercise. When this happens over here, grab this data, and create a new record over here in this system. Rob Collie (19:46): Okay. A trigger in this case would look something like, "When a record in Salesforce is marked as a win," we've signed a deal, someone wants to buy a palette of whatever. Then automatically, it wakes up, looks at the record in question that the data associated with the sales win in Salesforce, grabs certain fields out of the Salesforce record, certain pieces of information. Let's keep it simple for a moment, and just pushes them into a simple SQL database or something, that could be stood up in minutes. We don't have to spend a lot of time. Or maybe, we just drop it into OneLake.  Justin Mannhardt (20:23): Lots of options there. I think this is a nice little simple example, because when you talk about Power BI, that's a very tangible apparatus. These are the things you set up, and you never really go ... You monitor it of course, but you never really go engage with it. You put the glue in place, and it's magic and it's cool. That's a simple version. (20:44): But sometimes, the data coming from its source is incomplete relative to what it's destination requires to take the next action. In this type of scenario you could either say, "Well okay, once it gets over there, we're just in that system, maybe we're adding to it." But this is where you might insert a Power App into the process. Win a deal in Salesforce that triggers, grab these fields. Let's go ahead and write it over to Dataverse, this is a back end of a Power App, for example. Or a database, or SharePoint, who knows. It depends on what makes sense.  (21:18): Now we've got a Power App that maybe has a little work cue that says, "Hey, Rob, you've got new orders." You're either approving them, or you're annotating them with additional information. You're doing the human process, like you were describing before, maybe ensuring some hygiene, completeness, whatever. Then you do something in Power App that says, "Okay, go ahead and kick this down the line from here."  Rob Collie (21:40): Yeah. Here's an example. In the CRM system where the sale is being executed, there's probably an address for this customer that is associated with that account, especially if we've done business with them before. But this customer might have many different physical locations. A palette of stuff showing up at the wrong physical location would be a real problem. Justin Mannhardt (22:06): Yeah.  Rob Collie (22:08): Even just a sanity check Power App that hits the sales rep back, shows up in their inbox or something, shows up in Teams, somehow there's a cue for them to process these things, where they need to just glance at the order and validate that the shipping address is the right one.  Justin Mannhardt (22:28): Yeah. Rob Collie (22:28): Even if that's all it is, that's the only additional piece of information is yes, no, that's the right address. Justin Mannhardt (22:34): Yeah. Or sometimes there's a material that is sold is related to a bill of materials to produce. Maybe there's some choices that need to get made in the manufacturing process, such as what specific raw materials are we going to use for this order? Which machine are we going to produce it on this week? Maybe you're just adding the execution instructions.  Rob Collie (22:59): This is interesting because you could stop yourself at this moment and go, "Wait a second. Shouldn't those questions be encoded and implemented into the CRM?" The answer is of course, they could be. But your CRM might not be a nimble place to make those sorts of changes. Justin Mannhardt (23:20): That's right. Rob Collie (23:22): It's also a dangerous thing to be customizing. Justin Mannhardt (23:24): Yes. Rob Collie (23:25): There's a lot of validation and testing that's required. There's a reason why modifying and writing custom code into one's CRM doesn't happen all that frequently. Whereas this process you're describing is relatively safe, by comparison. It doesn't rock the boat. It's between. Forcing these sorts of modifications and customizations into the individual silo line-of-business applications, if that were so feasible, that would already be happening.  Justin Mannhardt (23:55): I've worked for companies like this, I've engaged with companies in my consulting career like this, where they have done that. They said, "We've got the talent in-house, so we're going to customize this thing." Then you get into a conversation of, "We'd like to upgrade to the newer version." They realized, "Oh, we can't."  Rob Collie (24:18): Yeah. "It'll break out customizations," yes.  Justin Mannhardt (24:20): Or sometimes, the programming language that the customizations are done in is not the same programming language in the newer version. While it's possible, if you have the resources, the time, and the money, it becomes a heavier lift. It begs the question, why?  Rob Collie (24:36): I was describing the heavy lift being that the original line-of-business system might be resistant to change, resistant to the customizations that you want to implement. You're describing it as also, even if you do perform those customizations, the next major software upgrade is going to be a problem. That rings true for me. I remember the object model in Office- Justin Mannhardt (24:59): Oh, yeah.  Rob Collie (25:00): All the VBA solutions that were out there, being incredibly paralyzing in terms of the things we could do with the product, because if you broke people's macros, they wouldn't upgrade to the new version of Office. Justin Mannhardt (25:09): Yeah, been there. Yeah.  Rob Collie (25:12): I promise you that, at Microsoft, we took that problem and approached it with a level of discipline that it was probably 10 times greater than the average line-of-business software vendor. Because most line-of-business software vendors see themselves as platform vendors. They want to be considered like that, but they don't want to pay the price of it. So that's good. (25:30): But then, the other thing is is if you built it into the line-of-business system, then inherently you're saying, "Okay, whatever that extra logic is, then it's up to that line-of-business system to then push those records across the wire." The new information has to go from the CRM to the other system. That kind of customization, both ends of the process are going to be very non-cooperative with this. This is another reason why doing this in a lightweight, nimble, intermediate layer provides a shock absorber to the system. Justin Mannhardt (26:08): I like that analogy.  Rob Collie (26:09): It's pretty easy for Power Automate, all it's doing is pushing a handful of doing to something and that other something is going to take care of all the validation, all of the retry. Validation with human beings, but also the logging in to the other system and all of that. Coding all of that into your CRM is almost a non-starter. This is why the between workflows have remained so non-digitized. Justin Mannhardt (26:42): Yeah. There's also a lot of tedium should be in play here, too. You have a written process, you look at your SOP documents and you say, "Oh, when this happens, Jan sends an email to Rob." Okay, well we could probably just get the Power Automate to send the email to Rob, if that what needs to happen.  (26:59): An example of this is something I built for myself at P3. When a potential new customer reaches out to us, and they want to meet with us and just chat, I wanted a process that reminded myself to go check out who that company is, understand who I'm going to talk. I just had a trigger that said, "When a meeting gets scheduled from this arena, just create a task for me to remember to do this before the meeting." Even little things like that, that are just personally useful, have been really beneficial as well. (27:33): It's much easier to say well yeah, dashboards, charts, graphs, cool. Or even fabric, even though that needs some demystifying still. This middleware, it's invisible, there's so many options. There's 100,000 little improvements you could make with it.  Rob Collie (27:48): The world has spent a long time coming around to why dashboards could be valuable.  Justin Mannhardt (27:55): They still are.  Rob Collie (27:56): Yes. When you say the word dashboards and you show that work product, even in the abstract to someone, the communication of what the value is benefiting from all of that history of the world waking up to the value of dashboards. Honestly, it wasn't that clear 15 years ago. It wasn't clear to people, most people anyway, why they needed them, why they were better than just running the reports out of each line-of-business system. But because it's such an inherently visible work product, it is a lot easier, I'm going to use the word, it's a lot easier to visualize what the impact will be, what it does for you. Whereas these other workflows, until you know that they're improvable, this is why digital transformation is so hard to understand because it is really talking about spaces where it's hard to visualize software helping because it's never been able to help.  (28:53): Let's go back to this example where the sale happens in the CRM system. Some information just automatically gets dropped in a data store, off to the side for the moment. There's potentially some Power App clarification. There are human inputs that are required here and you still want a human being to provide those. Justin Mannhardt (29:16): I want to point out here too, it's easy to get into a situation where that data store is simply being read by a report, even a Power BI report. But if the human's going to say, "Yes, no," or add to it, the Power App is just a way better piece to put there.  Rob Collie (29:32): Yeah. Let's have this example be like an example that we would look at and smile, be proud of. The Power App is involved. Then when the human interaction is done, they press okay or approve in the Power App. Take me to the next step.  Justin Mannhardt (29:49): Well ideally, we are pushing data and information into the next system or workflow.  Rob Collie (29:57): This is a two silo problem. We have the CRM system and then we have the manufacturing, work order and shipment system, the fulfillment system. Justin Mannhardt (30:06): The WMS.  Rob Collie (30:08): Is that what that is?  Justin Mannhardt (30:08): Yeah.  Rob Collie (30:09): Okay. We've already covered the first silo. We've gotten the human interaction. Now it's time to send it on to the second silo. How does that work?  Justin Mannhardt (30:20): This just comes down to what the point of integration is in the second silo. We could be inserting records into a SQL database, we could be making a post request to an API endpoint. In Power Automate, most of these things are WISIWIG in nature. There is an open code interface if you need to get to that and want to do that, need it. But usually, it's just mapping. You find your destination and it says, "Oh, here's the fields to map to." You say, "Okay," you just drag and drop. It just depends on what your destination system is, but you're just creating a target in your workflow, and the data goes.  Rob Collie (30:55): The way I like to look at this is that, even though each line-of-business silo system, they're never really built to talk to each other. Justin Mannhardt (31:04): Right, they need a translator.  Rob Collie (31:05): Yeah. The translator and the shock absorber. But at the same time, it's not hard to get the information you want out of one system, and it's not hard to write the information you need into another. But when you try to wire them directly through to each other- Justin Mannhardt (31:23): Yeah.  Rob Collie (31:23): That is actually really difficult. You need this referee in the middle, that's able to change gears, like the ambassador between the two systems. When you think about a translator system, an ambassador system, a shock absorber, whatever you want to call it, whatever metaphor you want, you can also imagine an incredibly expensive, elaborate piece of custom software that's being written to do that. That's not what we're talking about. Justin Mannhardt (31:47): No. Rob Collie (31:48): Let's recap. Trigger fires in CRM system, some data gets slurped out related to that sale, dropped in an intermediate location that then powers a Power App. Power App is able to read that information, it knows who to reach back to to get the clarification, the approval, et cetera. It might be multiple people that need to provide some input. Justin Mannhardt (32:09): It could be a whole workflow that lives right there. Rob Collie (32:12): But eventually at the end of that workflow, in this case we'll just assume it's one step, one human being, the sales rep just needs to sign off, then the Power App's job is done. That's the human interaction part. Now we're back to Power Automate, correct?  Justin Mannhardt (32:24): That's right.  Rob Collie (32:25): Power Automate will notice there's another trigger that the Power App is done with its part, the approval button was pressed. Justin Mannhardt (32:31): Clicked, yeah.  Rob Collie (32:33): Then it turns around, and it knows, because again we wire it up ... It sounds like we might be lucky, it's just drag and drop, one time development. But if it's not, it's probably not that much code, to go inject the new work order into the WMS system?  Justin Mannhardt (32:52): Yeah, it's the WMS, warehouse management system. Rob Collie (32:53): Let's call that the end of the story for this one integration. Let's say things go incredibly well in this project. We don't really encounter any hiccups. Best case scenario, how long on the calendar would it take for us to wire something like this up?  Justin Mannhardt (33:12): Yeah, best case scenario this is something that gets done inside of a week. Rob Collie (33:15): That's the difference.  Justin Mannhardt (33:16): Yeah.  Rob Collie (33:18): All right. Worst case scenario, both of these systems are more stubborn than usual, the connectors aren't built into the system, and they still have some relatively rudimentary ways of data access, but it's nothing WISIWIG off-the-shelf. We just get unlucky with these two stubborn line-of-business systems. How bad can that be?  Justin Mannhardt (33:37): Well, instead of being inside of a week, maybe it's weeks, like two or three. The only reason that gets extended would be okay, instead of pure WISIWIG drag and drop, maybe we are having to do some light handling of adjacent array. But there's tools for that. You can say, "Parse this into fields so I can now drag and drop it." Maybe instead of our Power Automate workflow having three, four steps, maybe there's 10. Some of those steps have a little bit more involvement. Maybe there's some time because we got to troubleshoot a little bit more and make sure we've got it all right. But I think the overall point here is these are relatively light touch on the calendar.  Rob Collie (34:18): I had a job in college that I've never brought up on this show. Justin Mannhardt (34:23): Ooh.  Rob Collie (34:23): I was obsessed about this workflow for nearly a whole decade afterwards. Where I was working for a construction company, and there's this thing in the construction industry that I'm sure is still a thing, and it's called the submittals process. Where it turns out, when you're going to build a building, there's an ingredients list for a building. You were talking about different material options for manufacturing. So we're going to make a brick exterior. Okay, what kind of brick? There are many different colors, kinds, textures, levels of quality. Literally, the owner of the building, the person paying to have the building built, that owner and their architect, and sometimes their structural engineers, are going to want to hold a physical brick in their hand. Justin Mannhardt (35:05): Right. Rob Collie (35:06): This is the brick that you are going to use. They want to inspect it with their eyes, whatever, they want to feel ... Maybe even run tests on it.  Justin Mannhardt (35:14): Smack it with a hammer. Rob Collie (35:16): Right. Then, when you build the building, you better use that brick because they're holding onto the brick, the sample, the reference brick. You think about the number of ingredients that goes into building a building, and the building in question that I was working on helping out with this process was the new chemistry building at Vanderbilt University. It was not just a regular building, it had all kinds of specialized hardware, and exhaust, and crazy stuff that wouldn't be in a normal building.  (35:44): There's this long list of materials that need to have submittals produced for them, samples. The requests all go to a million different vendors. You have to ask the subcontractor, the plumbing contractor, what pipe they plan to use. You find out what pipe they plan to use and then you say, "Okay, where do I get a sample of that pipe?" Sometimes you have to send the request for the sample to the pipe manufacturer, or something the subcontracting, the plumber, people will do it for you. Ah! It's awful. (36:14): I was brought in to just be the human shock absorber in this process. I was constantly taking information from one format, copying and pasting it, if I was lucky. Usually, re-hand entering into another one. I have to do this multiple times. I have to do this on the outgoing request, and then the incoming materials coming back. Ugh, and then the shipping labels and everything. It was just they brought me in because they had their assistant project manager for the construction company, the general contractor, on this site. All of this was having to go through him. It turns out, he had another job which was called build the building.  Justin Mannhardt (36:54): Just a minor, little job.  Rob Collie (36:56): Yeah. The job of push the samples around was a fine thing to subcontract to a college student. I swear, I did 40 hours a week on that for a whole summer, and then part-time for the next two years. That's all I did.  Justin Mannhardt (37:13): Make note, students. If you take an internship and you end up like Rob, learn how to do Power Automate stuff and use that for your internship.  Rob Collie (37:22): By the way, we already had Lotus Notes with a tremendous amount of customized Lotus Note template for this process.  Justin Mannhardt (37:30): Yeah.  Rob Collie (37:30): But all that really was was just another line-of-business system that didn't talk to anything. It spit out paper is what it did, it spit out printed slips that announced, "This is your brick."  Justin Mannhardt (37:42): Congratulations.  Rob Collie (37:44): That would be a really, really challenging digital transformation process today, because not only is it cross system, it's also cross companies. But I'm sure that, if we looked at that process today, we would find things that could be optimized.  Justin Mannhardt (37:56): Oh, yeah. Your example reminded me of a really important opportunity in the construction industry or lots of trades. You're talking about people that are out in the field, on job sites, on location, they're not sitting in offices at workstations. All of these things we're talking about, especially these Power App interfaces, can be optimized for mobile. Instead of, "Oh, I'm going to write this down so when I get back to my home office," I can put something on the smartphone. Even if you're not picking from a list of material SKUs or whatever, you can say, "Hey, Rob needs a brick."  (38:36): Now this goes back to your central office, and it's into a work queue, and another screen in the Power App, then they can go navigate the vendors and all that sort of stuff, too. That's a great example of where you can just put a little spice on it.  Rob Collie (38:50): I said that was the only thing I did in that job, that's not true. I had other jobs. One of them was the plumbing contractor was deemed to be running well behind schedule, they were not installing pipe fast enough, pipe and duct work. They assigned me, the construction company assigned me the job of going out there, walking through the building and seeing how much had been installed, linear feet of various materials, and writing it down. I was terrible at this. It's not a good fit for me at any age, but at age 20, I was just constantly under-reporting how much work they'd actually done and getting them in trouble.  Justin Mannhardt (39:32): This does not sound like a good use of Rob.  Rob Collie (39:34): Eventually, everyone bought me the little thing that wheels along on the ground and counts distance. What I would do is I'd be looking overhead at these copper pipes that were hanging from the ceiling, and I'd just stand beneath one end of them and walk across the building, tick, tick, tick, tick, tick, tick. But then, what would I do? I would write it down. I'd write down a number. What floor am I on? What side of the building am I on? Which pipes am I looking at? "Oh yeah, 150 linear feet." By the way, have I already counted those pipes? Did I count those pipes last week? I don't know.  Justin Mannhardt (40:11): There's errors in the world that have Rob Collie's fingerprints on them. There's a building somewhere that's had some pretty serious issues over the years and it's Rob's fault.  Rob Collie (40:21): The plumbing contractor had a pretty good sense of humor about it. They knew I was a youngster. Anyway, really just another example of something that could be digitally transformed today and it doesn't have to be difficult.  (40:33): This is not something that's a global, let's go digitally transform the whole company all at once. You can pick and choose some high value examples. And decide if that's a sufficient win for you, you might be encouraged to do it elsewhere. There's no thou shalt do all of these things, there's nothing like that. You get to choose where your cost benefit curve lies. But just even knowing that this is possible I think and what it entails.  Demystifying ... The process we just walked through, with today's technology, is not difficult. We're talking, as you said, within a week to several weeks on the worst case end. You do realize a bunch of benefits from that.  Justin Mannhardt (41:16): Yeah. I love how well the Power Platform, and this idea of it being middleware, just leans right into an idea that's been around for a long time in companies, which is continuous improvement. You can look at a problem, like the ones we've been describing, and you can go down the path and you say, "Okay, is there a piece of software that would solve or improve this problem?" You could look into something like that. Or you could say, "Actually, we have these other tools that we've been learning how to use and integrate into our organization, and we'll just take a week, or three weeks and make it better." If you decide to replace a silo down the road, like, "Hey, we're going to do a CRM take out," you've not saddled yourself up with this huge level of tech debt. Rob Collie (42:05): Yeah, that's huge.  Justin Mannhardt (42:06): Because a lot of these decisions have so much pressure because you're like, "If we don't get this right, then we'll have all this." It's actually okay to be like, "Yeah, we're going to throw this away and build a different one." I think that's an important aspect of these things. You can empower a team of people who are just interested in making things better and it's not this huge sunk cost or investment that you're never going to get back. You're going to get value from it, even if you're only going to leverage it, say for a year. It's like, "Hey, that week was worth it because it eliminated this many errors," or lost time, or whatever. Then we did something else. Rob Collie (42:44): This really hearkens back to something that I struggled to explain to people in my time at Microsoft. I had an intuition, and a lot of people had the same intuition, we weren't doing a great job of explaining it. What I'm going to talk about is the XML revolution. (43:01): XML, and JSON, and all these sorts of things, are just taken for granted today. There's nothing magic about them, it's completely commoditized and that's the way it should be. But those of us who saw this XML thing coming as a real game changer, I think we're really just keying in on exactly this thing we're talking about. The world had been obsessed with APIs up until that point. Every system had an API on it that was capable of doing verby things. Read/write, make changes. These APIs tended to be very heavy. Anyone that's ever written any macro code against Excel will know that the Excel API is incredibly complicated. I'm talking about the desktop VBA comm automation. Go play around with the range object for a couple of days.  (43:49): The idea that two systems with good APIs could then talk to each other was still this myth that I think most of the software world believed. Our belief was stubbornly that we just hadn't gotten the APIs right yet. The next standard in API was going to get it done. What XML did, all it was really doing was saying, "Look, there's going to be a data transmission format that is completely separate from any API, and it's super, super readable, and it's super, super simple." It's the beginning of this shock absorber mentality. Since then, we've discovered that it doesn't have to be XML. Justin Mannhardt (44:30): Oh, yeah. Rob Collie (44:31): But the XML thing did eventually lead us down the road of Hadoop, and DataLakes, and all of that. But yeah, this notion that you get the necessary data from system one, and there's this temporary ah, breath that you can take, and you can disconnect the process of slurp from system one and inject new into the other system. You can ever so slightly disconnect those two so they're not talking directly to each other. When you do that, you gain just massive, massive, massive benefits. (45:03): Yeah, it's kind of neat to connect that now. Again, I used to talk to people all the time like, "No, XML is magic. It's going to blah, blah, blah." People would go, like my old boss did, again would be like, "I don't get it. Why is it magic?" I'd be like, "Well, it just is, man. You don't understand." He beat that out of me. It was one of the greatest that anyone's ever given me. By the time I was done with him, I could explain why XML was valuable but not at the beginning. I certainly didn't envision where we've landed here.  (45:27): Okay, so I think this was pretty straightforward, right? If you want to identify what digital transformation means for your organization ... This actually really parallels the talk I gave on AI the other night here in Indy.  Justin Mannhardt (45:39): Oh, right. Yeah.  Rob Collie (45:40): Don't talk about it from the tech point of view. Justin Mannhardt (45:43): Yeah.  Rob Collie (45:43): Think about it from the workflow point of view. Where are the workflows in your company? What's really beautiful about digital transformation is that we can provide this extra guidance that, what are the workflows that happen between systems or adjacent to systems?  Justin Mannhardt (46:00): Yeah.  Rob Collie (46:00): It helps you focus on what we're talking about. It's not often you get a cheat code like that, so you can really zero in on something.  (46:08): I suspect that once you have that algorithm for looking, you're going to find lots of things. The Power Platform makes it- Justin Mannhardt (46:18): Ah, it transforms them in digital ways. Rob Collie (46:20): It puts that completely within range, completely within budget in a way that you wouldn't necessarily even expect. It's just kind of magic. It's the same level of magic that you'd get from Power BI, but in a read/write workflow sense.  Justin Mannhardt (46:33): Between and adjacent to, that's magic. That's a magic algorithm because I bet a lot of people, when you say digital transformation, they are thinking on or within the system, not between it. Rob Collie (46:45): Yeah. It's another one of these marketing terms that's almost deliberately meant to be mystical. Everyone's supposed to pretend that they know what it means, but then it's left for all of us out here in the real world, close to where the rubber meets the road, to actually do something real with it. (46:59): I wonder what percentage of the time people use the phrase digital transformation, if you scratch the surface, you'd find that they were completely bluffing?  Justin Mannhardt (47:07): Yeah. There's a category of thinking digital transformation, or even data analytics, where there's just all these abstract, conceptual statements or diagrams that mean very little. Let's just zoom into an actual problem, even if it's a little one, and fix it. Then, we'll go to the next one and fix that. We don't need big, fancy frameworks, teams, and steering committees to do any of that.  Rob Collie (47:35): I've got another example. Justin Mannhardt (47:36): Oh, yeah?  Rob Collie (47:37): It's one that we've implemented here at P3. We have these Power BI dashboards that measure the effectiveness of our advertising. It turns out that advertising in particular on Google AdWords is not a global thing. It's the sum of many micro trends, your overall performance. It's highly, highly, highly variable based on which keywords you're matching against, what kinds of searches you're matching against, and what kind of messaging you're presenting to the user of Google. The only way to improve, most of the time, is to improve in the details.  (48:11): All right. For a while, we had this workflow where we'd identify an intersection of ads that we were running and what we were matching up with, in terms of people's searches. We'd identify a cluster of those that, I'll just keep it simple for the moment, where we'd say, "Look, right now we're providing the same message to a bunch of searches that aren't really the same search and we need to break this out, and provide a more custom, tailored message to each of these individual searches." We'd mark something for granularization.  (48:43): But originally, what we would do is we were looking at this report, we'd write down essentially this intersection and say, "Go split that out."  Justin Mannhardt (48:51): What did we do?  Rob Collie (48:52): Immediately, we'd lose all track of what did we even decide to do? Because then someone had to go over to totally Google AdWords system and enter new ads, and break this thing out. Even knowing whether that had happened, producing the work list of things that needed to happen, was very difficult because we were in the context of a Power BI dashboard that didn't do any communication elsewhere. We couldn't track what our to-do list was. Except again, completely offline. We built a Power App and embedded it into some of these reports. You'd click on the thing you'd want to break out, the Power App would pick up that context, and then we'd just use a little drop-down and say, "What do we want to do to this?" We're going to mark this for granularization.  (49:39): That did produce us a to-do list, that then could also be re-imported back into the report, so that we could se that we had marked that one to explode it out. We didn't have to look at it again, and we also in the reporting, could see whether that splitting up had been done because you'd come back to the Power App and say, "Done." Even better, you'd enter the IDs of the new groups, so that you can say, "Hey, this one is now superseded by these."  (50:07): Now we never got to the point of directly writing back to Google AdWords to make the changes. That still happened offline. We certainly could have imagined a world in which a Power App, a much more elaborate process was built that, then separately from the dashboard, would prompt you to write the new ad copy and things like that. You get to choose where the 80/20 is in your process. For us, the 80/20 was recording the list and tracking the lineage while we're in the context of the report. That was a big deal.  Justin Mannhardt (50:39): There are over 1000 pre-built and certified connectors available for the Power Platform. Rob Collie (50:46): That's it? Just kidding. Justin Mannhardt (50:48): They're adding things all the time. We live in a SaaS world. All these things, they're real. Rob Collie (50:53): Yeah. That's a really critical point about Microsoft, is that they have realized that they are the middleware company.  Justin Mannhardt (50:59): Satya is all about it.  Rob Collie (51:00): Yes. In the Bill and Steve era, this was not Microsoft's game. They wanted to own everything.  Justin Mannhardt (51:06): Yeah.  Rob Collie (51:07): In Satya era, it's more like, "No, we want to work with everything."  Justin Mannhardt (51:11): It's great, I love it.  Rob Collie (51:12): Just recently, as I've gone down this path myself, reverse engineering in my own little way what this term means and coming to the conclusions that we have, I've realized that we are a digital transformation company. It's not the only thing that we do. Is read only Power BI middleware, is that digital transformation? Well, probably. By the strictest definition, probably yes, but not by the spirit of the law. The spirit of the definition means a read/write workflow. I'd mentioned in this last example, Power BI can be part of a read/write workflow. There's no reason to sideline it. In the other episodes, where we talked about improvement and action is the goal, how a Power App can be added to a Power BI report to help you take action on what the report is telling you. But just the broader Power Platform, Power Apps and Power Automate in particular. We do have a handful of clients where, most of the work we're doing is digital transformation work. Justin Mannhardt (52:08): Right, this type of work.  Rob Collie (52:09): The adjacent in between that we're talking about. Even though we're mostly thought of as a Power BI company, as we're doing our next round of website rebuild, we've 100% put a digital transformation page on our sitemap. It'll probably use some of this language we're talking about here. Digital transformation, what does it mean? It is both not that special of a term, there's no rocket science to it, and at the same time, there's a lot of value to be realized from it.  Justin Mannhardt (52:36): Totally. Here's a fun little call back to our origin story as individuals and as a company. We spend a lot of our time helping, for example, like the Excel analyst move over to Power BI and we're trying to solve these middleware gaps. That's why I think, for us, it's just been quite natural to provide these types of services and capabilities to customers as we've grown because it's the same type of person that's spirited to solve these types of issues, and the technology, and the openness of it brought everything in range. It's fun to reflect back on how broad we can show up to a customer beyond just dashboards.  Rob Collie (53:22): Yeah. It's a miracle and a testament to what Microsoft has pulled off. You can certainly imagine a world in which they could enable that uptempo, highly efficient, what we call faucets first methodology for dashboards. Justin Mannhardt (53:22): Yeah.  Rob Collie (53:38): And stopping there. To extend it to something like workflow and applications, and have implementation of these solutions feel very, very, very similar. Justin Mannhardt (53:50): Yeah.  Rob Collie (53:50): It's completely compatible with our ethos. It's almost like I didn't even notice when we made that transition into doing both. It sneaked up on me. That's a good sign. I feel a little silly that it took me a while to digest it, but I love that it happened organically without us having to go- Justin Mannhardt (54:10): Right. Rob Collie (54:11): Pick up another toolset from another vendor, or change our hiring profile dramatically, or anything like that.  Justin Mannhardt (54:18): Yeah. Now, we've got some of these cool projects where you've got maybe someone that their expertise is more on the Power BI side, working right alongside someone whose expertise is more on the Power Apps, Power Automate side. They're just moving in lockstep with the same customer, closing these middleware gaps, building the reporting, and the action lives around it. It's that whole thing working together that makes it all really cool. Rob Collie (54:41): I'm also developing an intuition that AI, maybe not the only application of AI, but I think a lot of the surface area of where we will find AI to be useful, plugs into this digital transformation thing, the adjacent in between. In particular, in sub workflows within the overall workflow.  Justin Mannhardt (55:03): Yes.  Rob Collie (55:03): Did your reaction fit that?  Justin Mannhardt (55:06): Yes, totally. Totally, totally, totally. Yeah.  Rob Collie (55:09): Then, we're good. I think it's easy, with dashboards, with BI, to imagine the global. Going from a non-dashboard company to a dashboard company, it's very easy to imagine that as a global thing and it's probably the right thing. Any place where you're flying without the information you need in a convenient, easy to digest format, let's go and get that. Even there, with the transformation to a data oriented organization, a data driven culture, you still pick places to start.  Justin Mannhardt (55:39): You got to start somewhere.  Rob Collie (55:40): This other thing, digital transformation is a little harder to imagine is a global thing, and that's fine. I think AI's the same way. You should not be thinking about AI as a global transformation for your business. Just like digital transformation, it is a go find particular places where you can score these wins.  Speaker 4 (56:00): Thanks for listening to the Raw Data by P3 Adaptive Podcast. Let the experts at P3 Adaptive help your business. Just go to p3adaptive.com. Have a data day. 

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On this special episode, we welcome the legendary Matt Allington back to the podcast. As one of the original giants in the Power BI community, Matt is gearing up for retirement and has chosen to share his invaluable insights and experiences with us once more. From his groundbreaking work at Coca-Cola to becoming a trailblazer in the Power Platform space, Matt's journey is filled with lessons, challenges, and triumphs that have shaped the world of business intelligence. Today, Matt delves into the complexities of the Semantic Model, sharing stories from the trenches of solving data dilemmas that seemed insurmountable. He offers a peek into his transition from corporate life to a highly sought-after consultant, revealing the strategic thinking behind his success. But it's not just about the challenges; it's about the future too. Matt discusses the evolving landscape of the Power Platform and the exciting possibilities brought on by Microsoft's new Fabric rollout, providing listeners with a rare glimpse into the future of data analytics through the eyes of a seasoned expert. This isn't just another podcast episode; it's an opportunity to learn from a true pioneer in the field. Matt's reflections on his career, the evolution of Power BI, and his predictions for the future are more than just insights—they're a roadmap for anyone looking to make their mark in the world of business intelligence. As Matt prepares to bid farewell to his professional career, we invite you to join us in celebrating his incredible journey on "Raw Data by P3 Adaptive." It's a conversation filled with wisdom, inspiration, and a bit of nostalgia that you won't want to miss. Also in this episode: This aggression will not stand: The Big Lebowski The DAX Draft One of the world's most Amazing Humans, w/Matt Allington

In this week's episode of Raw Data, Rob takes the mic solo to dive into a riveting topic, sparked by Zach from our LinkedIn Steering Committee. The question at hand is a pivotal one in the rapidly evolving realms of analytics and AI: How essential is deep industry or domain knowledge in this tech-forward era? As we race through technological advancements, is there a shift in focus from the deep-rooted sector-specific expertise to a broader emphasis on adaptability and mastering new tech tools on the fly? Rob delves into this debate, weighing the traditional value of domain expertise against the rising tide of tech fluency and the concept of Just-In-Time (JIT) training. He suggests we may be on the cusp of a significant transformation in professional expectations, where the agility to learn and implement new technologies swiftly could eclipse the longstanding reliance on industry-specific knowledge. Further, Rob illuminates how platforms like Power BI are leveling the playing field, allowing professionals to transcend their industry silos and innovate in ways previously unimaginable. It's a discussion that not only broadens our understanding of the current tech landscape but also challenges our perceptions of what it means to be an expert in today's fast-paced world. But this is just the beginning. Dive into the full discussion in this week's episode, and then join us over at the Raw Data by P3 Adaptive LinkedIn Steering Committee to share your own insights. Are you experiencing this shift towards tech adaptability over industry knowledge in your career? Let's continue the conversation, pooling our experiences and insights as we face these exciting changes together. And if you enjoyed this episode, be sure to subscribe for new content delivered weekly! Also in this episode: I drink your milkshake – There Will Be Blood Environmental Engineering Meets the Data Gene w/ MS MVP Alice Drummond Timely Supply Chains and Double Data Genes, w/ Jon Perl