The Manufacturing Industry is a Sweet Spot for Power BI and Power Apps, w/Madison Brooks

Rob Collie (00:00): Hello, friends. I'd like to start today's episode by asking you a question. How many physical objects, products, do you think you interact with in a single day? It's a lot. Take a moment and just think about it.

(00:13): I started counting a bit in my head, keeping score just for today alone, even just for a couple hours of today, and somewhere in the multiple dozens I got exhausted and I just stopped. Computers, shoes, phones, drinking glasses, eyeglasses, appliances, soaps. My car, which is itself assembled from thousands of separate products. My house, which is that again, but times 10. And of course right now I'm sitting in a chair in front of a desk, wearing headphones, speaking into a microphone that's attached to a computer. You get the idea.

(00:44): We spend so much time in the digital world that we forget that we actually spend all of our time in the physical world. And with the exception of let's say unprocessed foods, basically everything physical in our lives is manufactured. Yeah, the manufacturing industry makes the physical world. And the physical world is where we live 100% of our lives. And that's one of the reasons, but not the only reason, why we are excited to have P3 Adaptive Director of Client Services, Madison Brooks, as our guest for today's episode.

(01:18): She has a degree in chemical engineering and an MBA, but it was only about five minutes after graduation that her latent data gene went active and she's been a data person ever since really. Madison did work in the manufacturing industry before coming to P3, but she didn't leave it behind when she got here. We work with all industries at P3. And really no single industry makes up anything resembling a majority of our business, but manufacturing might be the one that we work with the most frequently.

(01:47): So we took the time to get Madison's origin story, as we always do with our guests on this show, and then we decided to focus basically the remainder of our time on what makes manufacturing such a hotbed for data-driven improvement. We talked about how manufacturing was probably the birthplace of BI long before it was even remotely called BI. We talked about how the rigors and complexities of dealing with the physical world make data disproportionately valuable.

(02:14): We talked about how the journey of a specific material ID through the manufacturing process and the ability to track it across all phases is like a superpower. And we also walked through a couple of relatively small recent case studies from our work in the manufacturing industry with our manufacturing clients. About how those small projects, quickly executed high ROI projects, can make such a big difference.

(02:39): And throughout it all, I think you will understand not only why we're so happy to have Madison on our team, but also why she is a director at our company. She's sharp, she's insightful, she's direct, and she's friendly. That makes her super effective with our clients and super effective as a leader on our team. But you'll see that for yourself. So let's get into it.

Speaker 2 (03:02): Ladies and gentlemen, may I have your attention, please?

Speaker 3 (03:06): This is the Raw Data by P3 Adaptive Podcast with your host Rob Collie and your co-host 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, down to Earth conversations about data, tech, and biz impact.

Rob Collie (03:37): Welcome to the show, Madison Brooks. How are you today?

Madison Brooks (03:40): I'm doing good. How are y'all doing?

Rob Collie (03:42): Fantastic. We've been backstage talking about our caffeine ingestion, getting geared up, important, makes for better podcasts and decreased sleep quality. These are the sacrifices that we make.

Madison Brooks (03:54): What a combo.

Justin Mannhardt (03:55): I don't know if I would make it through dinner time and chores and everything with the kids without the little early afternoon boost. I might crash and burn.

Rob Collie (04:05): So, Madison, tell the listeners a little bit about yourself. What's your role here at P3 and we'll go from there.

Madison Brooks (04:10): I'm one of the directors for Client Services at P3. Started back in early 2022, so very, very early on into the year, kicked off with P3. So much going on, so much growth since I started here, so it's really fun to see all of that.

(04:25): I work across a lot of different areas now in the director role. I get to work with my team pretty regularly all throughout the week. Working on making sure they're on assignments, what they're working on, being that support system, but I also really enjoy getting to work with the clients. So a lot of client facing time. Getting to work on how we can help them improve, what we can do to really work with them. And work better there and what they're working on, improve their processes and everything in between.

(04:50): So lots to do. But way back before coming over to P3, I actually came from a background in manufacturing and it was almost four years there with my degree being chemical engineering.

Rob Collie (05:02): Wow.

Madison Brooks (05:02): Started out with the chemical engineering degree at the University of Alabama, decided to stick around for at least one extra season there of some football. Wasn't quite ready to leave, so I did an MBA program there and that was kind of my first taste of data. I thought I'll add on that data analytics specialization since we have to choose one. And it was a whopping four classes in SaaS and I could say I specialized in data analytics.

(05:27): So that was coming out of college, having that chemical engineering background with the MBA. I was like, "What makes sense? What do I do from here?" And made my way into manufacturing where I spent a whole one month before being introduced to Power BI. And completely changed the progression of what I did with my career that first month.

(05:48): I didn't know what it was. I can remember the day I was placed in as manufacturing technology team because they had seen that specialization from those four classes. So I was put on this team and about a month in I was asked, "Hey, can you look at this Power BI tool and see if we could use this? What can we do with this?" And I don't think I ever really turned back from that moment.

(06:10): I dove in. I was really early on, so I was like, "I'm going to make a good impression. I want to learn everything I can, soak up all the information." That's where it led me. And all the way to the point where I had said, "Can I make this an entire career?" I want to do this with all of my time, and found P3 at that point.

Rob Collie (06:25): Chemical engineering is one of those degrees that I would expect that if you stayed with it as your primary career focus, you would be one of the few that would say, "Yes, I learned things in college that were valuable." But you're like, "Nah, no, I'm not going to do that."

(06:40): Also, chemical engineering, I got to salute it because that was not one of the blow off majors. Even within the engineering department, chemical engineering was known as a bit hardcore. Also, one of the more higher paying, but that means taking a lot more chemistry.

Madison Brooks (06:55): A lot of chemistry.

Rob Collie (06:56): Yeah.

Madison Brooks (06:56): I actually minored in chemistry. So I decided to torture myself a little bit more and do a couple extra labs so that I could minor in that. I have a degree in math alongside my chemical engineering and you had to minor in something and I was like, "Well, I already have to take enough chemistry, let's just add a couple more on here."

Rob Collie (07:12): Yeah, I mean you really took the easy path through. Chemical engineering, math, chemistry. I love that you said, "I decided to stick around." Not for an extra year.

Justin Mannhardt (07:21): For the football.

Rob Collie (07:23): An extra season.

Madison Brooks (07:23): Yeah.

Rob Collie (07:24): I was on the five-season plan.

Madison Brooks (07:28): Yeah. The MBA was just the extra bonus for that season.

Rob Collie (07:30): I grew up in Florida with SEC football and I understand it to be probably a bit more than what's healthy.

Madison Brooks (07:42): A little bit, yeah. But a lot of fun. The years that I was there, I think we had two national championships. I was there for some fun years.

Rob Collie (07:45): Good timing.

Madison Brooks (07:46): Great timing. Yeah.

Rob Collie (07:47): How did you go from chemical engineering to manufacturing? What was the tie in there?

Madison Brooks (07:52): Going to all the career fairs and everything like that, I remember they gave you a sheet and it would tell you what degrees people were hiring for. And the one that I walked up to, I think I saw someone I knew and I was like, "That guy's in my chemical engineering program." And I hadn't even seen it on the sheet and I was like, "I'll just talk to them."

(08:08): And ended up loving the person that I talked to, the company, things like that. At the time when I went and actually interviewed, I went on site and it's just this massive manufacturing facility. A lot of cool stuff there, a lot of process improvement. So a lot of chemical engineering is around improving processes, which is where I think almost all of the chemical engineers that I know, they didn't make their own way into manufacturing. It was something around process improvement.

(08:30): That happened to be one of the few companies that I went up to and talked to and they were like, "We're hiring chemical engineers." And gave me an offer, and so that's where I got started. But yeah, they had just started this manufacturing technology department at some point prior to me starting there and that just seemed like a fit with my data analytics there.

Justin Mannhardt (08:48): I'm learning things about Madison. Or I'm not learning anything, but it's just reinforcing. When I think about Madison, I always have this thought of Madison's just down for it. Oh, got my degree in chemical engineering. Oh, I like this person. This company seems cool. I'm down for it. Let's go. Let's do it. One month on the job, I'm down with Power BI, let's go.

Madison Brooks (09:09): You never know if you're going to like it. I could have picked up Power BI and been like, "This is horrible. What is this? We're not doing this." Luckily that was not the case. We're going to make a whole career out of it. This is what we're doing.

Rob Collie (09:17): How much actual quote/unquote chemical engineering did you do before Power BI forced you to take that left turn at Albuquerque?

Madison Brooks (09:25): I had one project that I kicked off while there. It was our wastewater treatment facility that we had on site because it was such a large site. And I got to do a couple of chemical in out processes of the water flow and all of that type of stuff. And I was like, "This is my degree. I did a class where I learned this."

(09:43): And then Power BI was like, "We're going to do something different." Because at that point I started learning Power BI. I was pretty self-taught. Teaching myself how to use Power BI and very quickly found myself over in the IT department where I got to actually interact at one point with every team on site. So anything from HR to sales to finance. To actually going to each of the plants that were on site and trying to see what they were doing with Power BI. If they were using Power BI, what users were actually using it and how can we improve the way we're working with it?

(10:14): So lots of opportunity in the manufacturing environment for things like that. We're always trying to improve processes, get rid of the manual processes we have. You couldn't imagine how many things were paper that would get passed from a desk to another desk and so on, so forth. So there were so many opportunities there to just grow across and practice Power BI.

Rob Collie (10:32): It's really interesting that Power BI, and this is completely valid I think, but it's really interesting to me that Power BI was considered one of the components of digital transformation.

(10:42): Little callback. We did do an episode specifically about digital transformation and so if this is interesting to y'all, listen in and you haven't heard that episode, look it up. All the places where paper gets passed around, let's digitize that process. What did we call it? It was the adjacent in between.

Justin Mannhardt (10:58): That's right. Adjacent and in between.

Rob Collie (11:01): Adjacent and in between. Those are the places where quote/unquote digital transformation lives. And Power BI itself oftentimes is a splice together between systems, the multiple fact tables, the semantic models, those are adjacent and in between. It's neat how we put a little bow on that.

(11:17): But obviously when we were talking about having you on the show, knowing your manufacturing background and also continued engagement with manufacturing clients here at P3. One of the things about P3 is that we have deliberately never chosen a specific industry focus. We've never said we are a company that works with just one vertical, just one category of company.

(11:42): Be just too limiting. There's too many people that need the sorts of services that we provide. We can really help so many different kinds of industries. It's still though kind of interesting to go look in the rear view mirror and see the clusters of clients that organically have happened. We didn't go out of our way to focus on manufacturing as an industry, but we've landed with manufacturing as a reasonable percentage of our clients.

(12:12): No industry makes up the majority of our clients. It's a long tail. But manufacturing might be certainly in the top three industry types of our clients for sure. And so it's not just a cool thing to talk about because we have Madison on the show. It's also cool to talk about because it seems to be a hotbed, one of the places where the Microsoft platform is really making a difference.

(12:35): And so you thought when you were transitioning to a full-time data career, that maybe you'd be kind of getting away from those manufacturing routes. But no, you've managed to stay very much in the game.

Madison Brooks (12:47): I moved away from manufacturing into this consulting world. I think the biggest difference there and something that's so exciting to me regardless of what industry it is that we work with, but even more exciting in manufacturing because I have that background, is that they're coming to us. They want the help. They want to see what we can do.

(13:05): They want to know what Power BI can do to help them, whether it's helping them get trained up on how to use it for themselves. On us trying to implement some projects that are going to increase their efficiency and help them see data and insights that they couldn't see before. That's just one of the most exciting parts about any industry that comes to us.

(13:23): But for me personally, especially in those manufacturing industries that I've interacted with since being at P3, it's really cool to see where they are, where we can take them. And then all of the possibilities that they have there that they can use our tools and really our expertise across the team that we have here.

(13:38): I loved the manufacturing environment, but at the time where I was, there wasn't the drive, right? There was only so much buy-in that I could keep trying to get. I remember reading some of the blogs that we had before I decided to accept my offer at P3 and a lot of them had that same story of I wanted to do more with that. I saw the potential of it and didn't have that buy-in behind me. Even though there were people all across using it, there was nothing kind of tying everyone together and pushing it forward.

Rob Collie (14:03): You can have buy-in from everyone that's immediately in your circle. You can be very much personally supported at distance zero, at distance one, but then the broader organization still has a lot of inertia to it. Even if it's not resistant to this revolutionary discovery, turning that ship takes a lot of time, a lot of effort.

(14:24): One of the beautiful things about working here is that we kind of get the wonderful, wonderful selection bias. That people really only come to us for help when they're sort of ready to absorb it. There are many, many, many organizations in the world that aren't ready just politically, bureaucratically, culturally. They're not really ready to absorb the change, completely positive change. They would be completely unhurt by it if they were open to it, but they're just not ready for it.

(14:49): Well, by definition we're not going to be working with them very often. And you're right, that's the 80% plus story of our consulting team. It feels like you discover fire for the first time, you're the first person ever. You look around and you say, "Look, fire." And everyone looks at you and goes, "Meh."

Justin Mannhardt (15:07): Right.

Rob Collie (15:07): You're like, "Well, so much for being here." You can't go back to sleep.

(15:14): Why do you think manufacturing does represent such a strong cluster for us? Industrial engineering, the entire discipline known as industrial engineering, came out of manufacturing. And I looked it up, it was like 1900 that the term industrial engineering was first used.

(15:34): So I could imagine from a historical perspective, I could imagine one of two things, and I'm sure the truth is neither of these. But imagine one answer is being that because they've always been a measurement and optimization type of industry. That they would be on the relatively front leading edge of adopting something like Power BI and doing more with data and modernizing their approach to data.

(15:58): The flip side might be that like the tortoise and the hare, sometimes if you're the leader in something, you can get complacent with it. You sort get locked into, it could be like a data-driven culture that's left over from the 1950s. And it's always worked and they've always been known as advanced relative to other industries, but then they wake up one day and realize that they're not.

(16:18): And so it's not bad news at that point. That's still like, "Oh, opportunity." But there's sort of a reawakening at that moment. Would you say that in your experience with the manufacturing industry that either of those narratives has any power? Is it completely different from either end point of that?

Madison Brooks (16:32): I would agree. So with one of those, going down that path of realizing that you're behind, which is just very common. We have so much Excel and so many manual processes that we do that I think ultimately came from the idea that there's so many data sources and so many silos that can happen in these massive manufacturing plants.

(16:52): One team, they start going and they pull everything and set it up in SAP, and then this other team starts getting things set up and they're like, :Oracle works great for our data." And before you know it, you have all these different sources and the immediate response is, "If I want to use this data, I got to export it. I need to get it into Excel, I need to get it somewhere where I can actually do something with it."

(17:12): And so I saw a lot of that lot of Excel usage and then people kind of step up and say, "Oh, I can use VBA. VBA can help me automate some things." And these slow steps until I would get to meet with them. I'd say, "Have you seen Power BI? Have you used this tool?" And we can connect to several data sources at the same time, pull them all in, and they can talk together. And that was just a huge revelation for people.

(17:34): And I think that's where we find a lot of our clients is that gap in their data integration. And luckily for us, we have people that can do both. We've got the data engineers, we've got people that can help them get their data cleaned up, how it needs to be. Help them with setting up models and things like that they might need, or we can jump into Power BI and we can start creating data models there. We can get ahold of that data and really make it work together to drive those business insights.

(17:59): One of our first slides that we do in foundations is you have all this time that's demanded of you and so much of that is the manual repetitive work. And you don't get to actually think. And we want to decrease that manual work and those steps that so many people do in their lives today and their work lives.

(18:15): I think that rings true so much in the manufacturing environment. And we're going to copy and paste this and we're going to email these reports back and forth and then no one has the most recent version. So trying to get those manual processes out and also optimize. There's so much room for optimization there in the manufacturing industry.

Justin Mannhardt (18:32): This isn't exclusive to manufacturing, but I think it has a tendency to feel very true. In a manufacturing organization, there's so much of that business that needs very constant monitoring. Materials coming in, work orders moving through a shop floor, orders going out, inventory moving around.

(18:55): There's so much to keep track of. That's why there's a spreadsheet with a template for this and it gets shared around. But sometimes the speed at which that can happen just conflicts with what really needs to happen. And I think that's a barrier to how could we actually make this better sometimes. We're just focused on we got to keep track of all this stuff because it's how we make money. We have to keep track of this.

Rob Collie (19:17): Yeah, I was thinking the same thing. Madison was talking about all the heavy usage of Excel and I'm like, "Well, that's par for the course. That's plug and play any industry." But there very well can be differences of degree.

(19:29): Reflecting on it, manufacturing is on a relatively short list of industries in which real world physical factors... Let's say you're running one of the world's largest law firms. By comparison, the complexity of that, I mean there's a lot more potentially people involved, blah, blah, blah, right? But from a systems' perspective, nah, that's Fisher-Price compared to a manufacturing operation.

(19:55): The real world is there front and center all the time in a million different ways, in a million different complexities. Even just the manufacturing machinery, like the shop floor industrial equipment, it might be very old. It works just fine. And the systems that you use, the quote/unquote electronics that run those systems, they can be extremely insular.

(20:20): You hear people talk about how they still have AS400 machines still running around and running their business. The proliferation of silos and the complexity of the business, I think both of those dials might be cranked a little higher for manufacturing relative to the average business.

Madison Brooks (20:34): Yeah, I fully agree with that because each of those processes then gets an entire department around it. So just to keep those things running and keep the processes going, you have someone that's constantly doing maintenance and then you have the actual manufacturing plant. And then you've got logistics.

(20:49): And every single team has their entire set of reporting. The things they need to see, the things they have to keep running, and everything's important. Because every part of that step has to happen in order for you to go from that raw material to the product that you can actually sell, all the way out to getting it to that customer. A lot of complexity, lots of data to work with, and lots of room for optimization in the manufacturing environment and others as well.

Justin Mannhardt (21:13): Madison, did you ever have any experiences when you felt like you could start to see the matrix? So it wasn't like, "Oh, I'm helping procurement, we're fixing procurement problems with data." But then you start to realize like, "Oh, my gosh, it's all interconnected." Have you had a moment like that?

Madison Brooks (21:29): Oh, so many. Even just background before P3, I was still very fresh into the world of manufacturing. I had learned about how everything worked, how the plant worked, all of the different departments. But as soon as you start pulling all those data sources in and you're like, "What's the one thing that ties all of this together?" And it's material ID.

(21:49): And being able to watch that material ID and figure out where it's going throughout the plant, you start to just have to take a step back and say, "Oh, wow, there's so much data around this one thing that, where do you even start?" Where do you actually start from when we purchase that item, when it went into this part of the plant, all the way through all the things it could do. Did it have a quality issue and it got kicked out to another department?

(22:13): That was really my first instance of seeing that amount of data and is Power BI the tool that can help us pull all this together? And getting people to see everything that they could pull in from those sources that were all over the place. Honestly, there was a lot of places where that hadn't been done yet.

(22:29): That people hadn't pulled the data from several sources to be able to see it yet, and that was a huge selling point for a lot of departments. Because they were like, "Oh, I can grab it from here and here. How do I do that? Who do I have to go to?" And I think the IT team probably still holds some grudges against me for telling them, "Oh, IT can grant you access to that. You can get access to this data."

(22:48): I definitely made some friends in the IT department that worked in SAP and things like that. To the point where I knew things to ask. And I was like, "All right, how do we find this data? Is it accessible?" But the light bulb that you saw go off in people's heads when they saw what they could do and the things that they could get ahold of and access and automate.

(23:06): And stop creating these reports where you drop in a number once a month. And at that point you're already looking at things in the past. There's no changing what's happened in the past. You've got to figure out what went wrong at that point. You have the ability to start being proactive if every single day that data is refreshing.

Rob Collie (23:21): The difference between finding out whether you made quota at the end of the month, ta-da good or ta-da bad. The difference between that and being able to see on day seven of the month, whether you're on track or not for making quota at the end of the month. And suddenly it's actionable versus unhelpful information. It's just a scoreboard that doesn't tell you how to get better at all.

(23:43): The thing about material ID, I got a really powerful visual journey in my head. The single physical material is as it works its way through the manufacturing process and maybe through exception processes like you mentioned, sometimes it's not a linear progression. Sometimes it has to go off to the side here for a second and be in limbo for a little while and then come back or whatever. And within any individual system, individual segment of the process, that material ID is visible from a data perspective, even an eyes-on perspective, within that little sub environment.

(24:18): But then as soon as it makes a transition into the next silo, poof, it's gone. It just disappears behind the curtain and now it's in someone else's little curtained off section of the floor. And then they say goodbye to it and it disappears again and there's absolutely no visibility.

(24:34): If you had a camera, it was riding along like a GoPro that was attached to this material, you'd be able to follow the day in the life or the workflow of it. And there might be 11 different systems that have data on that material ID that capture its journey, but that journey is fractured into 11 different places. So there's no visibility at all.

(24:55): And then we come along with something like Power BI and it just lights it up. All the curtains are gone almost effortlessly. You can see where the holdups are, where the waste is, which you'd never be able to see unless you can see the whole journey.

Justin Mannhardt (25:07): I had an experience like this. The material ID, it's amazing you picked that as the example here, Madison, because manufacturing, there's so much interconnectedness and it's the orchestration of so many activities, it never stops.

(25:22): I had an experience at a company I used to work for where a piece of equipment went down. So this piece of equipment was supposed to run so many jobs over the next several days or weeks. And because it was down now there's material that's stuck that's supposed to be moving through this machine, that's not getting out of the way for the material that's coming in on trucks.

(25:45): You would think, "Oh, yeah, we just need to worry about getting this machine back up." But when you think about managing your inventory, it's a physical problem. We have a log jam of pallet space. And to be able to see that and say like, "Oh, okay, we need to do something different here." If you're not communicating with your information and with your people, you're going to realize that too late. When there's a truck on your dock and you're like, "Well boss, where am I supposed to put all these pallets?"

Rob Collie (26:10): The physical world is demanding and unforgiving in a way that those of us who live in the digital world most of our lives can't really appreciate. After years at Microsoft, I never even got close to the facility that made the CDs that the software went on. Back when we still made CDs and DVDs, there was a location offsite in Seattle that did it. They eventually outsourced even that and then by now, I don't even know if they make physical media at all anymore, but I never went there.

(26:37): We were completely detached from the physical world at all times. And then years later I wrote my first book and because it was being printed relatively nearby, I got to go watch my book being, not printed. They'd already printed it, but I got to go watch the assembly process. The pages being folded and cut and bound, and it was insanely cool to see something physical like that.

(27:01): Even on the conveyor belt, there's this part in the conveyor belt after everything's been put together, they have a spiral corkscrew in the conveyor belt that just adds length to the conveyor belt. It's all it does, just adds length to it, so that the book glue has more time to cool before it gets to the packing station.

(27:19): The corkscrew conveyor belt is just the most compact in terms of using floor space to add length to the conveyor belt. It's like coming from a digital world, you would never expect the unforgiving. Seriously, you start packing that stuff before the glue's done, you're going to regret it.

Madison Brooks (27:36): Justin, you were talking about how you got to think all the way back to the beginning of the process. What are you going to back up? Where does the material that's coming in go when something goes down? Not only is there a team focusing on maintaining that machine and getting it back up, someone's got to focus on everything before it.

(27:50): And someone's got to focus on everything after it, all the way down to letting a customer know that they're not going to have that on time, that we're going to be behind and why. So the process from beginning to end is not only just very physical when you get out there into a manufacturing plant, but also so data-driven to be able to get that running and to keep everything aligned. So a tool like Power BI really digs in and allows you to see that whole process.

Rob Collie (28:17): One of the things that I'm always thinking about are the people and organizations, they're right there on the starting line. They're ripe for improvement, they're ready to go. They're ready to try this stuff out, but they're sort of not sure. They've heard stories, they hear all the pressure. Everyone's talking about data, data, data. So there's some FOMO building up. But that first step is so scary and I'm very sympathetic to it.

(28:42): People in the manufacturing industry, what would you say to them to sort of encourage them? And the reason I really want to ask you this is because you have authentically walked it. Yes, you work for a consulting industry that sells these sorts of services. Absolutely, that's the truth. But you came to that location in your career 100% honestly.

(29:03): You have chosen this career path because you saw what it could do at a manufacturing company. That was your one exposure to it. So you're a very authentic source. And what would you say to business leaders who are in exactly that spot? I think that that's still the majority in the world.

Madison Brooks (29:20): Just thinking about where you're going to be five years from now, if you don't start. If you keep waiting, you keep waiting for the right moment. I feel like it's so common to say, "Well, my data's not ready for it yet." Or, "My team's not ready for it yet because they're not trained to use it." Or, "We're not there yet. We are close, but we don't have everything in order. We want to have this all set up before we take that dive into the universe of Power BI and what it can bring to the table."

(29:48): For me, it's always just dive right in. You're not going to know what you can do fully with the tool until your data's there and you can grab it. And Power BI is meant to take raw data. One of the slides that we show again in our training is the ecosystem of Power BI.

(30:02): We emphasize that raw data can be messy. It can be nothing clean. It can be coming from CSV file. It could be coming from a database. Wherever it is, raw data can be extremely messy. It can be really clean. It can be anything in between. Power BI is meant to be able to handle that.

(30:17): Power Query goes and grabs that raw data. So if you don't make that leap, you'll keep waiting on that edge. You'll keep waiting until the data's there. Or until you know what you want to do with the tool instead of finding out what the tool can do for you. And what it's supposed to help you do with those business insights and getting your data out there.

Rob Collie (30:35): All the reasons why you think you might not be ready. That's awesome. I love that. And they're valid concerns. They really are. It's just how would you know that there is a way forward to make dramatically quick progress? That sidesteps those valid concerns. That mitigates them until you've seen it.

(30:57): For example, the thing you said about Power BI being made to meet that messy world where it is, it's almost like this perfect parallel to what we've been talking about with the manufacturing world. It's constrained and impacted by the unforgiving, noisy, messy real world. It's amazing to me. I still marvel at it, how well Power BI meets you where you're at.

(31:18): You don't need all of these elaborate prep steps. You don't need your organization brought up to a certain level before you can do it. In fact, Power BI becomes sort of like the forcing function and the clarifying function for one thing at a time, reaching the place you want to.

(31:34): Our whole faucets first, faucets drive the plumbing, not vice versa. That whole philosophy helps get your plumbing in order. Whereas you're right, if you feel like you're sitting around like all your data plumbing is a mess. Organizing that, taking that on, you're never going to finish that and you're right to be afraid of that. The thing is, we don't do it that way.

Justin Mannhardt (31:53): When Madison was talking about her experience, I wrote down, ready is a myth. It is so true. There's no such thing as ready in this context. So many efforts I've been a part of, I focus on how to get different data going into something. We're going to change our system and we're going to change the way we record something. You're ready when you have a problem that data can help you with.

(32:16): It's true, you might not have all of the right data. More often than not in my experience, you don't realize that you're missing something until you start and then you realize that's the thing we're missing. And so we want to build a process that's in that adjacent and in between idea, Rob. Let's build a process so we can get this data that's adjacent to what's already on our work order in our system because we need it.

Rob Collie (32:39): And the thing that's missing in that case ends up being focused, tactical. Not a boil the ocean, reinvent the world kind of thing that's missing. When you're sitting on the starting line thinking about why you're not ready, you're just sort of seeing the weight of everything all at once.

Madison Brooks (32:56): I think that alone is probably what holds back a large majority of people that haven't reached out to us yet. Is they're sitting there thinking, "I'm not ready for P3. I'm not ready for that leap." And like Justin said, that ready is a myth. And once we can wipe that away, more people need help. More people need this tool.

Rob Collie (33:14): Yeah, ready is not a pre-req.

Madison Brooks (33:14): There we go.

Rob Collie (33:14): Yeah.

Madison Brooks (33:18): Yeah. See Justin's over here coming up with ready is a myth. Meanwhile, I'm thinking about your mud comment and trying to come up with a cheesy joke in my head. Because I immediately went for the faucets first and I was like, "Your data can have mud." We go faucets first. Our goal is to wash away the mud. That's where we live. We live in washing away that mud using that faucet's first approach.

Rob Collie (33:37): We got filters. Yeah, you just slap a filter in that line and keep going.

Madison Brooks (33:41): Yep.

Rob Collie (33:41): So you mentioned the reasons not to start. They're good concerns. They're valid concerns, but they don't have to be obstacles. We specialize in helping you not get held up by those things. What about the payoff? On the one hand, the reasons why you're not starting. Okay, we can help you through that. My belief is that if you're on the starting line, you also have no idea yet how good it's going to be.

(34:06): One of the things that we always laugh about in our marketing and all that, is if we attempted to tell you the truth about how good things were going to be, you would never believe us. We have to almost lie to you and tell you it's going to be like 3X better than today when really it's going to be 25, 30X.

Madison Brooks (34:19): If I aim it straight towards the manufacturing environment, there's never that end point where you're going to say everything's optimized, everything's where it needs to be. But you can slowly chip away at all of the processes, all of the things that you have, and how you can optimize those. Whether you're going from raw material and trying to improve that process. And ordering materials and figuring out how to optimize their inventory. Trying to worry about the inventory management and how can we improve that process.

(34:49): So there's all these small processes. So I feel like when you take manufacturing as a whole, trying to get towards that, what is it going to look like? What's going to entice someone to step off the edge there and take that leap into Power BI? It's more saying you're going to take away some of that stress.

(35:05): Let this tool take away some of those stressors, those day-to-day stresses of are we running this correctly? Are we doing this process the right way? Is this as optimized as it can be? Can we save money here? That's a huge thing you hear in manufacturing is how can we save money? Which tends to lead some people towards FTE, trying to lower your head count, things like that. But I know honestly, the best place for that is in optimization.

(35:29): For me, the biggest point I would take to tell people what to look forward to when you do take that leap is just a sense of calm. A sense of being able to trust what you're doing is the optimized approach, is the right thing to do for different business processes that you're trying to improve.

(35:47): And reaching those goals. A lot of those are just never ending, never knowing if you're finally reaching that end state. For those processes, I'd want to know that I optimized it. I did what I needed to do and can walk away from that project feeling successful. Instead of wondering what the next project is after that one to do the next phase of success on that particular process.

Rob Collie (36:07): Madison, a while ago you were telling me a story about just one project. It's an ongoing relationship we have with this particular client. Just to kind of drive home for people how not big the project has to be in order to have a big impact.

(36:22): So at this client, there was one department that had a paper PO process with their vendors, even international vendors. And it's a paper-driven PO process because of course it's paper driven. That's how things have always been. If you've got digital PO process today, it's because you move to it from a paper PO process, because you're either post paper or not.

(36:43): You might think that again with a PO process that might do at max like 100 to a few hundred requests per week across an international vendor network, that might sound like this glacial move the Earth to a different orbit type of project. But in this particular instance, it was less than 20,000 of billable to the client. Between two and three weeks elapsed time to replace that paper process.

(37:11): Again with third party external secure, but external vendor access to the system. Stood up from scratch in a matter of weeks, small number of single digit weeks, low single digit weeks, and under a 20K price point. Perfect example of let's go tackle one thing that makes a difference in terms of the impact that it makes. I mean you can just imagine, right?

(37:34): Paper is slow, paper is error-prone, it can get lost in a stack. Paper is invisible, you don't know where it is. Whose desk is it on? There's no routing history of it. No clarity, no visibility. To fundamentally transform a paper process like that, not just an internal paper process, but a cross company boundary paper process, into a digital process that you know where everything's at. It's going to have a failure rate, an error rate that's basically zero and perfect visibility.

(38:08): That is a magic trick to pull that off really in any amount of time, at any price point, but especially with what we can do today. And by the way, this kind of execution time, this sort of execution price tag, was not possible five years ago. If you're sitting there on the starting line with a project like this going, "We can't do this because it's hard and it's going to be expensive and take forever."

(38:32): Yeah, it used to be. And technology has changed, but it takes a long time for that technology change to become culturally ubiquitous where everyone's just readily aware of how much faster things are. It's going to take maybe even a whole generation of workers to change out before we understand that, but it's real.

Justin Mannhardt (38:52): Stories like this are important in two contexts. One is we get to tell them on shows like this or in our case studies. And it helps people that are stuck on the starting line and go, "Oh, there was somebody else that got off the starting line and got a ton of benefit in a low risk, low cost, low time commitment type of a way."

(39:12): It's also important in the context of that company. Realize like, "Oh, we can actually make things better." And maybe some other teams saw like, "Oh, look what Madison and that team did over there. We could do something like that."

(39:24): And I think that's just a call back to our earlier part of our conversation around continuous improvement. The sheer quantity of projects and problems to solve. Getting started creates the momentum and other people can see Rob and Madison did that, we can do that. It's amazing. Rob, you said it like pick one and get it going.

Madison Brooks (39:42): This is definitely one of those pick ones. It was a really cool project. Really just down to that end result of changing the way that that team worked. The way that they interacted with this form that previously could show up on their desk with values that were not correct or the wrong GL account written down or just no GL account written down. And then they're having to contact someone, send an email, go to someone's desk, completely changes that.

(40:08): You take a power app, you can say, "We're going to automate the GL account based on this other field that was put in here earlier." Or we can go ahead and put some restraints. We can change the workflow on who it goes to based on the price that they put in here. All of these things that were these little pain points that were adding up for the way that someone works just quickly went away. Two to three weeks this new process goes in and those aren't even something you have to consider anymore. No one can do any of those anymore.

Rob Collie (40:36): I hadn't even thought about that angle of it. So something that jumps out at me out of that is that circling back to the manufacturing, having just so much more orders of magnitude greater exposure to real world complexity and physical machine and material complexity. Is that there's a lot more leverage to be had in terms of improvement out of data than there is in other industries.

(41:02): You mentioned FTE headcount. Compared to saving 1% on material cost, there's no headcount you can cut that's going to save you the dollars that a 1% savings, even maybe in one ingredient, one material category. There's just so much real world inertia, real world weight and mass and therefore expense. And then there's also the component of time.

Justin Mannhardt (41:27): Right.

Rob Collie (41:28): There's so many places where there's a lot of zeros on your costs. And therefore so many places where data can give you that confident visibility into where can you save?

(41:41): As another example, we were also talking recently about another one of these sort of short but super impactful projects in the manufacturing space. This one more in the kind of the quote/unquote traditional BI dashboard space. There was already an existing Excel report, as there so often is. Sometimes there isn't, but there often is an existing Excel report that's powering a workflow.

(42:03): It's a very, very important workflow for this manufacturing industry client. And the project was, again, I'm going to put the air quotes around it, just to convert it from Excel to Power BI.

Madison Brooks (42:14): Yeah. A lot of the projects that I've seen, and then they can be small projects, they can be large projects. They start in Excel. And it starts with, "Oh, we created some charts, we created some visuals, we calculated some things in Excel using our data." And then the idea is Power BI is going to automate that.

(42:31): I no longer have to refresh it, and that's huge for so many companies. That A CEO or a data analyst, anyone in between, doesn't have to go and click refresh and run something in Excel to get their data loading. That's a big driver for Power BI. Let's automate and that's awesome.

(42:46): But what people don't expect when they make their way into Power BI with this idea of automation is that it can drastically change their understanding of the impact of their data. You start to get these new capabilities that are not just automating your data. And getting it to refresh in an online service so you don't have to do it daily, but you start seeing new things.

(43:04): You start seeing trends. You start being able to drill into your data with two clicks of a button. And you get all these new capabilities that this project was just one of many examples that we've done that you see that outcome and you see it change the way people work and the way people see this tool. That would be one of the coolest outcomes I saw of this project, of so many different projects that start in a tool like Excel where people have already done amazing things.

(43:27): They've created these amazing reports that help them and they just amplify them even more. One of us gets in there and shows them what it can do and they're just amazed and they're super excited. So much so that it leads to, "Well, I showed this in a meeting and guess what? Two other departments now can't wait to get their hands on Power BI. They want to see what they can do with their data too." It just starts this kind of movement that flows throughout companies like this and really starts changing the way they see their data and what they can do with it.

Rob Collie (43:53): This is something that I often say, is that you can't replace an existing Excel workbook one for one with Power BI without vastly improving on the capabilities and the power that it brings. So in this particular case, the CEO of this organization was personally responsible for running this spreadsheet on a regular basis.

(44:16): Do you happen to remember how frequently they ran it? You simply can't run it frequently enough when someone, anyone, but especially someone of that leverage, that importance in the organization, is directly responsible for it. It's not going to get run all the time. It's not going to be real time.

Madison Brooks (44:32): Yeah, I think this was refreshing daily. I think the CEO had to go in daily. And I want to say it was at least a minimum of probably about 15 minutes or so of time, which we all know 15 minutes seems like a very short amount of our time. But to walk away from something else, get your head in that mindset, get something refreshing, walk back away, it can very much so add up.

(44:50): So one, getting the automation away, getting that step was amazing value. But being able to really dive into the data further, get more capabilities out of Power BI just took it up a whole nother level. And really took something that was already great, an Excel report that was created that was utilized to see all of these amazing KPIs to help run the business, and just elevate it using Power BI, was where that true value ended up lying in this entire project.

Rob Collie (45:17): You and I have talked about this particular engagement offline in detail, at a level of detail that we're not going to expose on this conversation, but there was some genius in this spreadsheet. The existing spreadsheet was really good, and that's why the CEO put his time into it every day.

(45:34): It was a big deal, a lot of intelligence in this, but you don't really perceive when you're there, all the places where the spreadsheet is limiting your idea. It's putting boundaries around the intelligence that you've had there. And helping them move it into Power BI really helped that core intelligence. That the inspiration that they had run to its full potential, and sometimes that's a really, really, really big deal.

(46:00): And as a side note, also, the CEO, I think kind of semi famously said like, "Okay, now that this is in place and running and it's doing all these things, if I ever want to retire now I can." But couldn't before because again, it was like his time, his baby that he had to push this through 15 minutes a day of the CEO's time. Imagine what that would accrue to in terms of other value.

(46:23): 15 minutes is never 15 minutes. It's 15 minutes plus all the context switching costs and all of that. And this was what like a two-week project?

Madison Brooks (46:30): It was two weeks and I think possibly just about a week and a half or two weeks after that added onto it. So in under a month, this massive report in Excel, all these KPIs are pulled in. We're getting drilled through into them. We start trending this data over time and seeing all this value in such a short project, which was really cool to see with that resource and with the stakeholders.

Rob Collie (46:52): Do you have any sense of how behaviors have changed as a result of all of this?

Madison Brooks (46:58): I don't know if that's as much of a behavior in the company, but this excitement around the data. Once the CEO was able to share this report, all of a sudden you start having these other team members and these other leaders in the company that are saying, "Well, what can I do with my report? Or what can I do to be able to visualize my data and get more insight out of it?" Several of those came out of just seeing those KPIs on a report that we've created.

Rob Collie (47:19): Yeah, I mean excitement is a really good, on the one hand you'd be like, "Who cares about excitement in business?" But excitement in a business context about data. This isn't like some ADHD distraction when you're excited about something as just mathematical as data.

(47:41): The excitement is a signal and a symptom of possibility and improvement. When people get excited in a business context, that means something, right? We're not riding a roller coaster here. We're not watching a great football game. We're just doing business and we're excited. That's a good KPI in itself.

Justin Mannhardt (47:59): There's a couple things that I would really want to emphasize for leaders at manufacturing companies. The first is the way Madison was describing the benefits. Continuous improvement has been ingrained in manufacturing organizations as a cultural pillar for so long.

(48:20): We're always trying to optimize everything. How can we minimize downtime, reduce waste, make things faster? It's a constant way of thinking. And so Power BI slips right into that idea just very naturally.

(48:34): And then I think one idea you just had there, Rob, which is the sheer quantity of potential problems and projects. Sometimes when we have so much that we could consider improving, we feel like we really need to take our time to prioritize and pick the right ones because we only have so many resources. But Power BI and other adjacent Microsoft tools are bringing the risk profile down so much that you can entertain more of those problems per period of time.

(49:06): You can really start to make compounding progress. And it's not unusual, maybe your first sets of dashboards, they're highlighting, yeah, maybe we have a process issue or we have data gaps. You can learn that faster and then you can solve the next problem faster.

(49:22): And so it's just sort of the right environment I think where there's this continuous improvement culture, more problems can get solved. There's a compounding effect to them. And so if you can get off the starting line and just give yourself the permission to focus on something, and that's when you really start to feel things moving, in my experience.

Rob Collie (49:43): Just pick one. Pick any question or uncertainty or place where you lack confidence in what you're able to see. Pick one, we'll go solve it. Then you're 1,000 times more informed about the contours of it, about what it can look like, about what possibilities look like.

(50:01): And then picking your second thing that you go after becomes like 1,000 times easier, 1,000 times clearer. The difference between being one step off of the starting line and being on the starting line is it's a massive difference in terms of clarity and empowerment and confidence.

(50:16): You mentioned continuous improvement. When you reach the point of a Fortune 500 manufacturing operation, if you're just one of the titans of manufacturing, you're going to have entire legions of continuous improvement specialists or Lean specialists and/or Six Sigma specialists, right? You're going to have whole departments of this.

(50:38): I do get the sense, this is purely anecdotal. I do get the sense that there is a scale at which people feel like they can't really afford that department. A lot of manufacturing isn't Fortune 500 level.

(50:50): Client of ours and former podcast guest, Matt Selig, Bar Keepers Friend. Bar Keepers Friend is a worldwide recognized brand and yet it's a family business. I've never heard mention of any of those terms while working with their organization. Continuous improvement, Lean Six Sigma, right? It didn't seem to me like they had that department. Justin, do you remember any such thing?

Justin Mannhardt (51:14): My own experience substantiates that where sometimes the best a company can afford to do is maybe send their line managers to a training, for example.

Rob Collie (51:23): Do a little toe dipping.

Justin Mannhardt (51:25): Yeah. Do a little toe dip. Very different.

Rob Collie (51:27): Yeah. That's not going to get you the cultural change, the impact, right? I mean, these other companies, again, at scale, they can afford and it's a good investment for them to have entire teams of referees essentially constantly looking at everything, which is completely separate from the day-to-day of getting the product manufactured. It's a luxury.

(51:46): It's like when I left Microsoft as a product manager, people said, "Oh, you can go anywhere once you've been to Microsoft." I'm like, "No, actually, my job only exists when a software company gets big enough." Because if you're going to have a 10 person software company, you're going to make sure all 10 of them write code. And I don't do that, right? So there's a certain scale, right?

(52:03): So one of the things I was thinking is that a lot of the benefits, these things like lean and Six Sigma, they were invented in a largely pre-digital context. And the whole notion of a control chart, for instance, which just fascinates me, is like you're literally drawing a chart by hand and seeing if it bounces above a certain line a certain number of times. I can write that in a formula now and just let me know. I don't even need to be looking at a chart. You can just alert me when something falls out of control.

(52:31): And so many of the benefits of continuous improvement, Lean Six Sigma, you can get those, and in fact, probably better in a lot of ways than the traditional approach without adding staff. We're talking about cutting FTE as a potential cost savings. The last thing you want to do is add FTE. Get the benefits of these disciplines with the staff you have.

Justin Mannhardt (52:54): Totally.

Rob Collie (52:55): Madison, you're a rockstar. I'm glad you're one of us.

Madison Brooks (52:57): Love being here. Could not imagine being anywhere else.

Speaker 3 (53:00): 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.