episode 130
The I in “BI” Stands for Improvement
episode 130
The I in “BI” Stands for Improvement
We’re calling BS on lazy BI. For too long, dashboards and reports have glorified their ability to inform while taking zero ownership over actuating decisions or ensuring actions. Proof? How many times have you rotated from screen to screen like an overworked copy-paste minion?
In this episode, we expose reporting’s dirty little non-action secret and provide tips to evolve your analytics from passive to active. Learn to design for actionability, build automated assists around report insights, continually track business impact, and ultimately wring more value from data by moving from identification to improvement (while massively reducing operational suffering!).
If you’re tired of solutions that sound smart but barely lift a finger to drive results, this episode is for you. Let’s stop celebrating sexy viz and get serious about visibility leading to actionability. Real outcomes over pretty charts! Tune in now.
Episode Transcript
Rob Collie (00:00): Hello, friends. One of the themes that's emerged in my professional life over the years is that, going from A to B is often hard enough, but when you can't go directly from where you are to where you want to be and there's an intermediate step, when you need to go from A to B to C, there's often an inherent, insidious psychological danger. Which is that the middle step B in the A to B to C example, over time morphs into its own goal, its own end state in people's heads. Many years ago when I was working as a young product manager on the Excel Engineering Team at Microsoft, our vice president, during a presentation I was giving, it was a pitch about something we were going to do with the product. He told me, "Hey Rob, you're talking an awful lot about the oven and what people really want is steak."
(00:55): Now take a moment and reflect on how kind of crazy that example is. Like who cooks steaks and ovens, right? Rich people do apparently, and he was always doing things like this to remind us accidentally about how much wealthier he was than the rest of us. But anyway, set that part aside. We can use blenders and daiquiris if we want. The point is, you need to not forget about the end result, and this is particularly dangerous when that intermediate step, that intermediate goal is very difficult to achieve. In fact, it's so easy for this to happen that an entire multi, multi, multi, billion dollar industry, named itself incorrectly, business intelligence. And of course, who doesn't want to be intelligent, but intelligent is the middle state. It is the intermediate B state on the A to B to C journey, where C is actual improvement in your business's performance.
(01:55): Now, of course, in order to improve, you need to be informed, right? That's where the intelligence thing comes from. But again, the BI problem has been so difficult for so many years. Actually, for many decades, it has been so difficult that it's kind of become its own bullseye and it's a false bullseye. It's not where you should be pointing. It is a middle state and the two reasons why I think this is very important, number one is that, as you focus more and more of your attention on the false bullseye, you get worse and worse at hitting the true bullseye. Kind of hearkens back to that true North versus magnetic North thing in a podcast a few episodes back. And the other one is that, today BI has now become actually achievable, achievable enough in fact, that if we shift our attention back towards the true bullseye, the true target, which is improvement, we can even design our intelligence to be much, much, much more action and improvement oriented and we should.
(02:56): And just like our previous episode, this is one of those topics that has tremendous value, whether you're a business leader or a practitioner, because whether you're driving an improvement oriented philosophy from the top down or the bottom up, either way, it can make a tremendous difference and it's not just some frilly words. Justin and I talk about multiple, specific examples of how you can do this. All right, let's improve, shall we?
Announcer 1 (03:28): Ladies and gentlemen, may I have your attention, please.
Announcer 2 (03:32): 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 is data with the human element.
Rob Collie (03:58): All right, so kind of continuing our end of year, getting one's head on straight, thinking clearly for the new year, type of theme. We're going to talk about the action loop today or really why improvement is the goal, not just being informed, not just intelligence. The fact that it's BI, BI stands for business intelligence, in a way, almost gets us on the wrong foot.
Justin Mannhardt (04:18): Yes.
Rob Collie (04:19): It is completely possible to be well-informed or think you're well-informed anyway, right? The word, well, does a lot of work there. You can be informed and be unable to improve.
Justin Mannhardt (04:29): That's right.
Rob Collie (04:30): Which takes a moment to realize. I can tell you all kinds of things about your business that don't translate into improvement and the data can be used to provide that information.
Justin Mannhardt (04:38): That's right.
Rob Collie (04:39): So there's a big difference between shooting for the open net versus shooting around the goalie, sounds like the same thing, but it's not. And so the goal of today's conversation is to help remind people that improvement is the thing that they're after and not to get so distracted by the middleman of information.
Justin Mannhardt (04:58): I like it. Could you give us a Rob Collie definition of the term, action loop?
Rob Collie (05:06): To me, it's you identify a possible improvement. Possible improvement could be heading off a bad thing or amplifying a good thing.
Justin Mannhardt (05:15): That's right.
Rob Collie (05:16): Taking some sort of action to actually affect that improvement in the real world, measuring whether it worked and then wash, rinse, repeat, for infinite growth and improvement. But think about all the things that are involved in that loop? Being informed is only a part of it, it's just one stop in that cycle. But even within the being informed, I want to start this conversation saying, "Hey, ignore the taking action part for a moment. This philosophy will help you design better dashboards."
Justin Mannhardt (05:48): That's right.
Rob Collie (05:49): If that's all you're ever going to do is dashboards, and we're going to talk about the downstream stuff, the stuff that happens after the dashboard.
Justin Mannhardt (05:56): Right.
Rob Collie (05:56): But before we even go there, a dashboard that is designed to inform versus a dashboard that is designed to facilitate improvement.
Justin Mannhardt (06:04): Very different things.
Rob Collie (06:05): The temptation, and I think a lot of projects end up going this way, is to go from the data forward. "All right, let's go grab the data and let's see what we can tell people with it."
Justin Mannhardt (06:16): I'm not sure who to attribute this quote to. Many data or analytics initiatives fail because they focus on the data that someone has and not the data they need, and that's that idea of being data forward, like, "Let's just work with what we've got." Which is sort of adrift from, "What is it that we're trying to improve and are we anchored to that?"
Rob Collie (06:36): Yeah. This seems like a cousin in a parallel universe, to the faucets first versus plumbing first, right?
Justin Mannhardt (06:42): Yeah, for sure.
Rob Collie (06:43): They're kindred philosophies. One of the easiest ways to illustrate this, is just to give a couple of dumb counter examples that either I've encountered or that you've encountered or maybe we've even perpetrated, in past lives, I've been guilty. My favorite one was the report that I was asked many years ago to debug because it was running slowly. That was a, let's just call it, an SaaS tabular. It doesn't matter, it was a power pivot, Power BI, whatever. It's a model that resulted in a 100,000 row pivot table or matrix, that the report was 100,000 rows.
Justin Mannhardt (07:19): Yikes.
Rob Collie (07:19): It was running slowly.
Justin Mannhardt (07:21): I wonder why?
Rob Collie (07:21): My first reaction was, egads, who is using this thing, even if it runs quickly, who is taking a 100,000 row output and doing anything with it? It's like I need to take your 100,000 row report and run it through a data model to turn it-
Justin Mannhardt (07:39): Right. Like we came back to step one.
Rob Collie (07:42): ... this is raw data. This is not a report. It was basically a timecard report of every single employee they had in the entire. This is a very large organization. Every single employee they had in the entire nation, across hundreds of locations, the time they were scheduled in for that day, the time they were scheduled to be out for that day, whether they've clocked in, whether they haven't clocked in, it was a mess. The only thing that they were really using this for, was all these regional managers were scanning it every hour, which is why they needed to run fast. Every hour they were scanning it to see if they had a store somewhere that was empty because no one showed up.
(08:20): And I turned and looked at them and said, "Hey, no, no, we don't need the timecard report, that's data forward. You need the empty store detector, which will run incredibly fast by the way, and be super useful, and so think about it that way, the report's empty. By the way, we could make that report run really quickly. We don't have to worry about debugging whatever was going on with it."
Justin Mannhardt (08:39): Right.
Rob Collie (08:40): Not only that, but the new report, the empty store detector, could provide a lot of information about the employees that didn't show up, what their phone numbers are, do they have a history of not showing up and also other employees that might be persuaded to take their place. You just put on a completely different hat, just a totally different brain when you think of it that way. And so you can very much embody this approach to your job, even if your technology focus never leaves Power BI.
Justin Mannhardt (09:10): Yeah, never leave the dashboard. You can somewhat, I mean just to come from the other angle, it's okay to start with the main problem you're trying to improve, is that you don't know something. "I want this dashboard because I need to know X, Y, or Z." That's okay. You need to start there. Even simple thought exercises you put people through like, "Oh, Rob, once you know this, what would you want to know next?" And when the word know changes into the word do, and so even just putting yourself through those questions of like, "I want to know this because I want to know something else because I want to know something else, so I can do." Now you're at the catalyst of the action loop. The report has a form and a function and a purpose beyond just like, "Oh, I can explore stuff."
Rob Collie (09:58): I really like this. I like this for two reasons. Number one, I like the specific suggestion, so saying, "Hey, it's fine. You want to know something, we're not going to block you. Don't feel bad about your reason for creating this new report or whatever, is because you need to know something. Don't feel bad about that. Let's just make it an and, add the and. And these are the types of things that I might do differently if I did know." You don't have to be perfect. You might discover actions that you should take, you never would've thought of, but at least put your brain through the paces just for a few seconds, just to start strengthening those muscles of and then what, because that will make things better. You will get so much better, even if you're not building the reports, if you're asking someone else for the reports, you should be doing this.
Justin Mannhardt (10:45): Totally.
Rob Collie (10:46): Okay, so the second reason why I like this is because now it's starting to sound like we might actually be able to come up with a kit. We have to come up with some sort of fancy name for it, like the action loop empowerment kit.
Justin Mannhardt (10:56): Patent pending.
Rob Collie (10:58): The action loop empowerment, its acronym is ALE. We probably want to do better than that, right?
Justin Mannhardt (11:06): No, let's do better than ALE.
Rob Collie (11:07): Yeah. But anyway, the improvement mindset kit, that's one of them, is when you're either building or asking for some sort of new analysis or report, do the and, what are the types of things I might end up doing even? Just take a guess. I'm going to add another one to our kit. This one's a lot of fun, whether you're the person who needs reports and is asking for reports or whether you're the person building analysis and reports for someone else, either way, let's play the bat computer game.
Justin Mannhardt (11:41): The bat computer game?
Rob Collie (11:43): So in the bat computer game, you take your subject, who is the person who is going to be consuming information from the report. Again, this could be you, you could be the subject because you're the one that needs the report.
Justin Mannhardt (11:55): Right.
Rob Collie (11:56): You might be building something for someone else, in which case, now you need to think about them as the person sitting in front of the bat computer. So the person who's consuming a report, you're imagining them sitting in front of a bat computer, not the modern Dark Knight type of bat computer. I'm talking like the Adam West, 1960s, over the top, Andy Warhol style, big fat plastic buttons on this bat computer with big obnoxious labels on them. These buttons, these levers, these knobs that they have on this bat computer are all about the business. Those are the things that they will use to adjust the business to make changes, and that's what their job really is. Their job isn't to read reports. Their job is to move the buttons and the levers. Right?
Justin Mannhardt (12:41): Right.
Rob Collie (12:41): I don't know, if you're in charge of warehouses, you can say, "Increase inventory over here or transfer it over there." Or another example, if you're running a chain of convenience stores, you can change the hours of your convenience stores. You can change the product mix at these convenience stores. You can open new stores, you can close stores. Think about it that way. Okay, so you imagine this person, you sort of in your head, imagine what all the buttons and levers are in front of them, and there probably aren't that many.
Justin Mannhardt (13:11): Right.
Rob Collie (13:12): It's not 100.
Justin Mannhardt (13:13): No.
Rob Collie (13:13): It's not 100 levers and buttons on this bat computer. I suppose maybe the really long tail there might be, but if you're thinking backwards from that saying, "My dashboards, my reports, my analyses, are they helping me decide which control to touch and which direction to move it, and by how much?" So in the manager scenario that I was talking about before with the empty stores, I'm sure these managers had other jobs and their other buttons on their bat computer, but in those scenario we talked about, they had two buttons in front of them. One of them is, call the people who didn't show up, and the other one is, call the other people who work at that store to try to get them to take the place, right? Those are the buttons. When should they press that button? Well, they shouldn't press it, they shouldn't call the person if they're at work.
Justin Mannhardt (14:02): Right.
Rob Collie (14:02): Don't press the call the person who didn't show up, if they did show up. That's what you're ultimately trying to do, is to help them operate their bat computer.
Justin Mannhardt (14:10): Where I want to maybe emphasize something is, it's great to say, "Oh, I'd love an inventory reporter dashboard or I'd love a sales reporter dashboard." Or I'd love whatever it is, take an hour, 30 minutes, "What is the thing I think I'm interested in improving?" Give yourself some narrow focus. Bring in faucets first again, "Which faucet am I interested in, the kitchen faucet, the bathroom faucet?" No, it's very relatable.
Rob Collie (14:35): This bat computer trick is a very close relative of the and, that you were suggesting, right? It might be in the end that the kit just condenses down to one thing, to finish this and sort of really clarify it, let's give one more example and it's one that's come up before on this podcast and it's the crushinator. There was this large junkyard, acres and acres and acres of junked cars on their lot and the way junkyards work, and I didn't even really know this ahead of time, I just thought junkyards were the place where you just stacked things to the sky and they just sat there forever, never thought about what a junkyard's business model was.
Justin Mannhardt (15:11): Right.
Rob Collie (15:11): Of course, no one just pays to have cars sitting there. People come into junkyards and take parts off of old cars and then pay for them on their way out. So these old hulks of cars are a productive asset. It's almost like they're growing money, but they don't grow money forever. Eventually, a car on the lot has either been picked so clean of parts that it's not going to produce anymore or for whatever reason, that make, model, year of car, is no longer nearly in demand for parts as it used to be. And so those are two ways in which a car can become a less productive asset over time. Now, the junk yard is full, however much room and acreage they, they filled it up.
Justin Mannhardt (15:54): Resources are limited.
Rob Collie (15:56): Didn't take too long to fill it up, so they need to clear up space. If you've got something that's not producing money, it's just taking space and there are other things that could be coming in, other makes, models, years of cars, that could be coming in and taking its place. Okay, here we go, think about the bat computer again. They've got one button on their bat computer that they're just mashing every day and that button is labeled, Crush Cars.
Justin Mannhardt (16:21): Crush.
Rob Collie (16:23): When you determine that a car is no longer a productive asset or not productive enough, you send the big claw for it, pick it up, and you throw it in the compactor, you crush it down and you sell it for scrap metal, so you get one last hurrah of money out of this thing. Okay? So if you crush it too soon, you're crushing all of the good parts that were still in it and you're missing out on all that sweet, sweet, part selling revenue. Crush it too late though, and you've been occupying space on your lot that could have been used in a more optimized scenario, for a more productive car. This becomes such a problem that they're basically running the compactor, the crusher, 24/7, but which cars?
(17:05): So they asked us for the report and again, thinking data forward, which I don't blame them for. They asked us for a report with 50 columns in it and we've been to this rodeo. We go, "Oh, come on now, that's just going to become your next opponent. This 50 column thing, we know that you don't have those 50 columns today. That will be a huge upgrade for you, but we can do better." We said, "There's probably five columns that are the most impactful." And they said, "Yeah." "The reason why you're asking for 50 is because you're not sure in the future, whether you would need them or not. You feel like you get one shot at this asking us, so you've asked us for 50, but there's really five of the most important." They said, "Yeah, that's exactly what we're doing." I said, "Okay, so identify those five."
(17:45): And then we ranked all of the cars on the lot by those five, turned them into rank measurements, so rank X, if you want to use the DAX, and then we average those, we average those five and sorted by it. Very simple to understand and it put the likeliest crush candidates at the top of the list. Not necessarily 100% accurate, they might choose to crush the third one and not the first one, no big deal, but it's helping them. And by the way, we went ahead and gave them the other 45 columns, right?
Justin Mannhardt (18:13): Sure.
Rob Collie (18:14): But the report was centered around the sort of blended rank of those five. And they couldn't have loved this more, it was the most amazing thing.
Justin Mannhardt (18:25): There's something, I want to use the word special or magical, that kind of happens in a human's brain when the distance between looking at a report and the obvious nature of, "What should I do?" Just becomes so close, it's sort of elusive, I think too. I was thinking about one of my prior roles, my job was to manage this fleet of assets that were just all over the country, and if somebody needed one that wasn't nearby, the question was like, "Okay, which one do we move to be where it needs to be?"
(18:58): And this process when I got to this company was, "Oh, well, so-and-so makes phone calls and figures out what's where." Getting that process, similar, "Well, we need all 50 columns so we can sort and filter the requests." And it's like, "Well, there's a set of decision-making criteria that we're going to use here. We can make the report just say, 'Oh, the optimal asset to move for Rob is this one over in New Mexico.'" The reason I say it's elusive, it's not because we're foolish or anything, but it's sometimes hard to advance the thinking from your current state to like, "Oh, I can totally get this report to be closer to the action I need to take and just expedite this decision."
Rob Collie (19:34): So it's all about the bat computer in the end.
Justin Mannhardt (19:37): Yeah.
Rob Collie (19:37): So now that we've spent, I think sufficient time covering, when you're just focused on the dashboard, now let's zoom back. You're at the bat computer, it's like you're swiveling to your left and looking at the Power BI or the report computer that's telling you things. Then you have to swivel around back to your right and face the bat computer to take action. That's the reality. Even if you have the best, most action oriented dashboards reports in the world, and by the way, thank you Microsoft for every time I say the word dashboard, I have to say reports, in parentheses after it. That's really, really added to our syllable count over the years.
Justin Mannhardt (20:22): You mean a dashboard? No, a report.
Rob Collie (20:24): Wait, wait, wait, wait, lowercase D dashboard or capital D dashboard. Anyway.
Justin Mannhardt (20:28): The thing with the tiles?
Rob Collie (20:29): Yeah, the thing, the dashboard. Okay. If you really want to take the action loop mentality to that next level, you start to think about, "Why is the dashboard given a pass on helping me take the action?" Going back to the inventory and warehouse thing, let's say, I've got a report, a dashboard, it's so hard.
Justin Mannhardt (20:53): This should be like for the steering committee, could we just put this to rest everybody?
Rob Collie (20:59): We're going to do a super cut of all of this over the years on Raw Data and send it to Microsoft and say, "See, look at what you did." Right? It's like putting the dog's nose in it. And folks, if you're not in on the joke, Microsoft took a perfectly good industry term, dashboard, and decided it should mean something different, and the thing in Power BI that you think of as a dashboard is a report. Anyway, this is one of those mistakes made almost going on a decade ago now, it's getting close and it's with us forever. So all right, in the inventory and warehouse kind of thing, you've got something that's telling you, you've got an analysis that's telling you, that warehouse seven is low on product X and it's going to run out before the next scheduled replenishment. Now what?
(21:53): The report you're looking at can just sit there and just kind of fold its arms now and look at you and say, "Ooh, sucks to be you. I'm really looking forward to seeing how you solve this one." And that's sort of the standard that we've held BI to. It doesn't need to help. If it's a well-designed report though, it might also then tell you that warehouse three has an excess of supply of product X and is relatively close, geographically speaking, isn't that far away. That would be awesome. And that's already multiple steps beyond the standards we tend to hold things to, and I'm really saying, "Why have we given it such a pass?" This report is a piece of software and it is part of the action and improvement loop. Why does it get to be so lazy?
Justin Mannhardt (22:44): Right.
Rob Collie (22:45): If it helps me spot a problem, first of all, that's better than normal because normally it's just informing me, okay, it's gone to spotting a problem. Shouldn't it help me identify at least possible fixes?
Justin Mannhardt (22:58): Yeah.
Rob Collie (22:59): Okay, and let's say that it does. It tells me that warehouse three has an excess. So now even then, typically what I have to do is again, rotate my desk chair 90 degrees over to the bat computer, which is in this case, is logging into the whatever, warehouse management system, a completely different software, and I have to manually navigate to warehouse three and product X and, "How many could warehouse three afford to give up? I forget, now, I got to roll back over to the report." Right?
Justin Mannhardt (23:32): Yep.
Rob Collie (23:33): It was three and a half pallets or whatever and then transfer it to warehouse seven. "It was warehouse seven, right?" "Yeah, warehouse seven"
Justin Mannhardt (23:40): It can even be messier than that. It could be-
Rob Collie (23:43): No.
Justin Mannhardt (23:44): ... lots of people sending emails about the same and you're wondering-
Rob Collie (23:48): Oh, yeah, yeah, yeah. It's definitely emails.
Justin Mannhardt (23:52): ... Rob, I need some. And there's four people asking you for the same product and they're all looking at their reports wondering who won the lottery. It can get, blah.
Rob Collie (24:01): Okay. Yeah. All right, you got me? Yeah, I described the idealized-
Justin Mannhardt (24:07): Chaos. Chaos, Rob.
Rob Collie (24:10): ... all right, so this is where we're going to start leaning on you. Let's assume that the report has now been designed to spot problems and suggest potential solutions, which is amazing and can be done. It absolutely can be done. Okay?
Justin Mannhardt (24:23): Yeah, and should be.
Rob Collie (24:24): We have the technology. Once I've sort of picked a solution, what blows me away is that if I pick the solution, the report underneath the hood, it knows all of the context, it knows the quantity that I want to move. It knows the from warehouse, the to warehouse. It just seems like, what a shame, that information just kind of dead ends there. Now, there's a cheesy way which is still incredibly valuable, sort of not completely lose its context as I flip over to the bat computer, which is to have the report contain hyperlinks that are dynamically constructed based on what I'm looking at. So bare minimum in my idealized example where there aren't emails flying around and it's just logging into some system, constructing the URL, that takes me to warehouse three. Now, I mean in a really sophisticated world, maybe there's URL parameters that say, "Transfer from warehouse three to warehouse seven." Probably not because most systems aren't that cooperative from URLs, if they even accept URLs, but I think we can do better than that. Yeah?
Justin Mannhardt (25:31): We can do a lot better than that. That's a great start. Let's minimize the friction as much as possible. So where this can become more helpful, is when we start bringing some of Power BIS buddies and friends into the party. One example here is the idea that I can put a power app, which is a low-code application inside of my Power BI report, that can capture that context you're talking about, what was I looking at, what was the detail, and then go off and do something. So let's say for example, I do live in an email world. Our process is, if I need material, I got to email Rob at central dispatch. I could build something that I could just look and say, "Yeah, we need to do that." Click the button. It captures everything from the report, composes the message and instruction for you and sends it off and now you know.
Rob Collie (26:27): You can just cue it up as a draft, right?
Justin Mannhardt (26:29): Yeah.
Rob Collie (26:30): You can manually review it before you press send. Right?
Justin Mannhardt (26:33): Exactly.
Rob Collie (26:34): Just amazing.
Justin Mannhardt (26:35): Yeah. And we've done this type of thing, for example, even, so let's go to a different business context, maybe for a sales team, where you're trying to figure out maybe what types of products and services to recommend to a customer and just have that happen like, "Oh, based on variety of criteria and segmentation of customers, Rob, it might make sense for you to recommend these two or three things to your customer." And we just deliver that in a little message to you, little simple things. It's amazing how helpful it is. Just continue the maturity here for a second. So let's say we got these enhanced communication exercises we could do. Now we've introduced a scenario where we can also have some sort of tracking. We recommended products for Rob, we needed to move some inventory, and so now we've got this little maybe second page in our dashboard, here's the things we wanted to do. Are they done yet?
Rob Collie (27:26): Yeah. So I want to extend off of that, but I also want to rewind to your email example. Even something that auto composes the email, doesn't press send, you review it and then maybe you can even add a couple of notes at the top. "Hey Jimmy, I'm sorry to do this to you again." So the obvious advantage of it is speed. Right?
Justin Mannhardt (27:46): Yeah.
Rob Collie (27:47): If you've got lots of these things going on, you can achieve more of these improvements in a day or the rest of your job still fits in the day or this thing might not have happened until tomorrow, if it had fallen off the end of the day. So speed isn't just speed and it's not just capacity, it's also a performance thing. Sometimes it becomes a binary, it either got there in time or it didn't. Secondly, it reduces error.
Justin Mannhardt (28:13): Yeah, big time.
Rob Collie (28:14): You're going to have a manual error rate. Everybody's got an error rate on the things that they do manually.
Justin Mannhardt (28:20): Yeah. It's called being a human.
Rob Collie (28:21): Yeah. Imagine what happens when you transfer the inventory in the reverse direction?
Justin Mannhardt (28:27): Has happened.
Rob Collie (28:28): Right. Not a hard thing to do. So error rate is a big one. And then thirdly, you're taking down the human suffering cost of the job, and that is massive. You take something that on the one hand, used to feel like the most dehumanizing, draining and turn it into something that's actually like fun. It's actually fun to fix this problem.
Justin Mannhardt (28:53): Contact switching is really draining, even where you're describing like, "Oh, I swivel from this bat computer over to this one." When you get into that new system, I left my dashboard or report and I'm now in the WMS, now my brain is instantly flooded with all sorts of other stuff, and that's where this friction comes in. It's like, "Which warehouse?" And you were role-playing back and forth remembering, just get rid of that.
Rob Collie (29:24): And even when I'm doing well, I know that all I'm doing is being a perfect copy, paste monkey.
Justin Mannhardt (29:29): Yeah. That's not fun.
Rob Collie (29:30): That's my ceiling. When I used to teach classes, I forget what the context it was, I would say this in, but I basically say it every class at some point, which is like, "I think that all projects, if we want to look at them honestly, need to be measured in terms of three costs. We tend to measure them in time and money. Very hard to quantify this third one, but it's every bit as important as the first two, and that's quantity of suffering. How much psychic cost did we extract from ourselves, from our team, to achieve this?" You don't get an infinite amount of that.
Justin Mannhardt (30:02): Right.
Rob Collie (30:03): Even if everybody sticks around, no one leaves the company. You've still drained them and you're going to get less out of them over time, eventually some of them will leave. But it should appear on the accounting of the project, but you still in your head, as a business leader, absolutely should be thinking about that, is every bit as important as the other two costs.
Justin Mannhardt (30:25): 100%.
Rob Collie (30:26): Back to your fancy example.
Justin Mannhardt (30:28): We're tracking something.
Rob Collie (30:30): Circling back, the improvement you identified, you said, let's go with that improvement, so you can track whether the action was taken, that's part of the report. You can also tag the entities that were involved in this improvement, to track them to see if they improved?
Justin Mannhardt (30:44): That's right.
Rob Collie (30:44): Our warehouse example, it's a little weird, right? If it's more of a manufacturing example, we're like, "You know what? We're going to adjust the oxygen mixture on the flux capacitor." So you tag the flux capacitor, is something that recently received an improvement and on what date, so then you can compare its performance before and after.
Justin Mannhardt (31:04): Think about any level of highly optimized, highly specific situations. Let's use maybe, a more holistic example. Let's say, I'm looking at my 360 dashboard for my company and I can see revenues and costs and I can see all these different kinds of things and I realize something is off and I want to prescribe some action around that, that works too. "Sales are kind of falling flat. We should discuss with Rob what's going on in the Northeastern market and maybe run a campaign or a sale." And we can track that and we can know that, this is what we were looking at in our data when we made that decision and we can know that we did or didn't follow through on that action and what the outcomes were. It's just a much more holistic understanding of, "Why the hell do I have this dashboard in the first place?"
Rob Collie (31:54): Even if the action plan or the improvement is something that can't be systematized, it's more just like a conversation between two people. Where I've seen this is in scorecards, so a manager will meet with one of their direct reports and they'll discuss the things that are going well or not well, in their corner of the scorecard and they'll develop an action plan for how that goes or how they're going to change it. And then they write down the action plan, but they write down the action plan. Again, it's just human words, but they write it down on a notebook, maybe even in OneNote, but the thing is, it's not tied to the report. When you come back to the scorecard next month, you're meeting with the same direct report, you're looking at the number, maybe if it's a well-designed scorecard, you can see its history from a month ago.
(32:38): I think it's just gotten more fault tolerant about this stuff. It's become less stupid if you lose your host, you just keep going. That makes sense to me. Wouldn't it be great if the action plan that you discussed a month ago and agreed to, is now available in that context again within the report, within the scorecard, even that's an example of the action loop. Why does the scorecard get to take a pass on helping you record? It's the context in which you discover the problem. It's the context in which you discuss the solution. In fact, there are other parts of the scorecard that help you determine what the right answer should be, what the right action should be. The thing you record between the two of you, your notes should go there.
Justin Mannhardt (33:19): Yeah. That's such a great example because it's easy for me at least when we start talking about action loops, to just go straight to the hyper-specific problem, hyper optimized dashboard, and then this chain of automation that not only just sends emails to people but actually writes actions into other systems and triggers off a series of events. Just that simple like, "Hey, I noticed something. I had an idea of something we could do here." Living amongst the original moment, that's great. That's really great.
Rob Collie (33:55): Credit where it's due. That idea of the action plan, the human action plan being recorded in the context of the scorecard, talk about ahead of its time, a human being who was like a time traveler. One of my very first clients when I started this company, Mike Miskal at Command Industrial, and he was the one insisting that we go do this. We didn't have write-back, we didn't even have Power BI. All we had was Power Pivot and he was like, "We have to be able to do this." And he was even saying things like, "We're going to make BI, ReadWrite." Holy cow, what an absolute trailblazer. He's just one of my favorite people, and I mentioned him before on the podcast and it's so sad that he passed away. I wrote a blog post. I've actually had a couple of blog posts written about him. I'm still benefiting today from things I learned working with him like, "Hey, Mike, I'm the consultant here. What are you doing teaching me things?"
Justin Mannhardt (34:51): Those are great moments though, where you get into a situation with someone and they're kind of ahead of the curve and they want to push the envelope and for some reason they're not stuck on the currency. It's like, "No, we should totally be bringing all of this closer together." That's when some good stuff happens.
Rob Collie (35:07): This was sort of the nature of the earliest clients who would come to me because back then, this was like 2013, you had to be almost insane to bet on this thing that no one knew anything about, in a good way, right?
Justin Mannhardt (35:18): Yeah.
Rob Collie (35:19): Someone like that just clearly doesn't perceive boundaries, doesn't care, isn't thinking about, "Oh, you're cute little software limitations." "No, what I care about is the actual problem."
Justin Mannhardt (35:31): Right.
Rob Collie (35:32): We're all striving to be more like him. People like that are so rare, and the rest of us are just on this asymptotic approach.
Justin Mannhardt (35:43): There's so many ways and there's lots of different technology options now, to make that kind of ReadWrite opportunity that you were describing, but I think that should be, especially for what may be some of your core recurring issues are like, okay, you manage warehouses, you recurringly have an issue of moving material around and keeping things in stock. Thinking about those action loops is like, "Do my dashboards tell me what I actually need to know, in a way that allows me to know what to do about it? We've got the right knobs on the bat, computers." I love that.
Rob Collie (36:17): And I think that underlines, it's not every switch on the bat computer, it's the ones that people are using with some degree of regularity.
Justin Mannhardt (36:25): Or a sales team thing, for whatever reason, I do like working with customers on tried and true sales dashboard. "Okay, great. Yeah, we can show you what your sales numbers are. We can show you by rep or all these things." But okay, the person looking at this, what are you going to do about that? Forcing that conversation just a little bit further, we do some cool things like on that product recommendation side, where sales rep get a little email on their phone. It's like, "Hey, here's some things to be thinking about for this customer." That's awesome. It's really the framing for me. Don't just build a dashboard because you think you need a dashboard. Take the time to think about, "What are the things I'm trying to improve? What are the things I want to do because of it?" You get a much better result with your investment of time and money and a decrease in suffering.
Rob Collie (37:12): There's a dashboard or a report for that, I'm not sure which?
Justin Mannhardt (37:15): We'll work on that Monday.
Rob Collie (37:18): All right, well thanks Justin.
Announcer 2 (37:19): 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 day-to-day.
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