Working in Data is Hard – Ep. 247

Working in data is hard—not because we can’t write DAX or build pipelines, but because analytics sits in the middle of changing business context, competing priorities, and ambiguous definitions. In Episode 247, Mike, Tommy, and Seth talk through why this work feels chaotic, and how to reduce the friction without pretending the problem is purely technical.

News & Announcements

• Power BI August 2023 feature summary — Scan what shipped that month to spot new features you can turn into quick wins (or avoid surprises in your tenant).

• Cursor — A modern, AI-assisted code editor that can speed up prototyping and documentation work around your data stack.

• Working in data is hard (LinkedIn) — The spark for this episode: a reminder that “hard” is often the environment, not the engineer.

• Subscribe to the Explicit Measures podcast — Follow the show and get new episodes as they drop.

• Tips+ Theme Generator — Build consistent Power BI themes fast so your team spends less time formatting and more time answering questions.

• Mike Carlo on LinkedIn — Follow Mike for Power BI/Fabric tips, demos, and episode updates.

• Seth Bauer on LinkedIn — Follow Seth for practical engineering and analytics perspective.

• Tommy Puglia on LinkedIn — Follow Tommy for leadership and delivery insights from the field.

Main Discussion

A lot of analytics pain comes from treating data work like it’s a simple “build the report” task. In reality, teams are constantly negotiating definitions, reconciling conflicting expectations, and working around incomplete context. The episode frames the problem clearly: the tools matter, but the bigger constraint is usually process.

Key takeaways:

• “Hard” often means unclear: when the question, grain, and success criteria aren’t explicit, rework is inevitable.
• Data teams do translation work all day—turning business intent into definitions, logic, and repeatable metrics.
• Ownership is a multiplier: projects move faster when it’s clear who can make the final call on definitions.
• Context switching is a delivery killer; limiting active workstreams can beat adding more headcount.
• Write the definitions down (and keep them visible): shared semantics reduces churn and rebuilds trust.
• Tight feedback loops (show, confirm, adjust) beat long “big reveal” cycles—especially when requirements are fuzzy.
• Sustainable delivery comes from a repeatable intake + decision process, not from heroics.

Looking Forward

Before building the next “simple report,” force clarity: document the decision it supports, define the metric, and name the owner—then ship the smallest version that answers the question.

Episode Transcript

0:00 [Music] foreign

0:30 good morning and welcome back to the explicit measures podcast with Tommy Seth and Mike hello everyone welcome back back we’re back baby it’s been a bit of a break we are now live again mistakes will happen matters will be made we are live again yes happy Tuesday gentlemen and it it is a very happy Tuesday in this household and I I think your household says well because in the next 25 minutes kids are back to school and what that

1:01 back to school and what that means for those of us who mostly work from home quiet just beautiful Blissful quiet it’s that time of year again I’m not excited about that at all at all right it’s not like you’ve just been around your family for way too long now well coming to coming from yeah like a two and a half week vacation we just got back from Europe so that was excellent fun trip I had to visited some family and

1:31 some family and got to see some see some sights see that’s that’s what that’s what Summer’s all about well the food what was the best thing it’s either food place you went or it’s probably gonna be one of those two right well I guess all right how many times about his food I have I have family extended family through by my wife in the Czech Republic so Cuisine wise like it’s very slow cooked recipes roast or porks whatever the most

2:02 porks whatever the most exciting Parts about what they do is one check water is beer oh that’s what it is really okay they have a fantastic I’m a gluten-free guy so like can’t have gluten but yeah have a local Ferdinand beer that is gluten-free fantastic but nice yes they they also they also may or may not know how to make fantastic slivovitsa in their backyard

2:32 in their backyard they’re family in Slovak is nice very very good at that so yes if I was gonna talk about the meals it was usually the precursors up to the the meal there are a few of my favorites but yeah awesome slovovitz and family amazing amazing well glad to have you back glad to get jumping back in here I think Tommy has been going through withdrawal the last two weeks just a little bit he’s been itching to get back onto the podcast and talk about some things

3:02 podcast and talk about some things coming out here so let’s just kick off some things with some openers Tommy you found one this thing called cursor cursor. seo it’s a some code it’s an AI feature Tommy’s all about the AI I’ll say this every time Tommy jump to a meeting there’s another AI thing showing up and he’s telling me something else new man that’s happening give us give us the rundown what is this thing you found so it’s really like vs code and for those who worked with vs code it’s basically that on steroids with AI not only like just like how

3:34 with AI not only like just like how vs code has blue cheese has copilot well this what you can actually do is go through your entire code base go through a certain code or even like say generate this for me anything and it works really well but what I wanted to try out because obviously this is when you’re thinking mostly developers you’re doing something python or Jupiter I’m like if I can integrate and index any documentation that was one of the things yes I wonder if I did Dax and I basically asked it something

4:05 and I basically asked it something pretty simple and I just said hey I have two tables that are like this based on daxed guide generate for me a rolling 60 days in the previous rolling wouldn’t it it was pretty much on point yeah and I’ve been testing that out a bunch too so I need to put some more up there but I’ll send a Twitter link because it’s incredible it’s really incredible so the the why is it why is this different than other AIS and based on your little demo

4:35 other AIS and based on your little demo Tommy that you you published here the idea here is when you run this AI you’re able to send it like a URL or or a documentation library and say hey here’s some information that you need to know before I talk to you and you basically sent them the Italians right here go to go to Dax dot guide know this information yeah and then use that to help you write formulas and it was you said it was pretty on point for finding code Snippets and examples in there which believe it or not

5:05 there which believe it or not between their website with blog articles and then all of the dax. guide information as well it’s pretty comprehensive if you could if you could pick in a couple more like interesting or useful sites around that you could enhance that even further you you could enhance that even further pick sqlbi. com know pick sqlbi. com pickax. guide and maybe a couple other really relevant areas as well so it’s this to me has been one of the more incredible honestly like things out there there again even especially now too with a

5:35 again even especially now too with a lot of people as we’re going into more python more and Engineering yeah where we start hey give me and again the documentation could be anything you choose just the LinkedIn index sure one of the cool last thing I’ll say is you can actually just say hey create a new project for me this is what I want to do it created for me I did you’re gonna love this love this it created for me both I have and now a python package and a Powershell module completely for PBI tools the command line line so which is great yeah that’s pretty

6:07 so which is great yeah that’s pretty cool cool so this is I think this is going to be continually the challenge here moving forward with anything AI related it’ll be the ability to say okay these things are going to provide immense amount of value because it has a wealth of knowledge behind it but will it work well will it just the discernment value of is this right did it what they I guess what they call when it lies it’s like is it hallucinating or not so like you’ll get a Dax statement out of it is it the right way to go about it is this the most efficient way to build a

6:37 this the most efficient way to build a deck statement it may get the job done so yeah I’m gonna I’ll have to play with it a little bit more and see where where it comes out and if it’s adding value for me as well pretty cool stuff nice find on that one Tommy Tommy the only other thing so since we’ve been gone for a while here a lot of things have been happening one other one I’ll throw down here will be is the power bi August feature summary has been released so there’s some new features so quickly want to run that by you guys and see if there’s

7:08 run that by you guys and see if there’s any features that stood out to you it seemed fairly light from a power bi perspective I know a lot of things are being developed and or created inside fabric at this point so I’ve been watching both the fabric blog and the power bi blog power bi just seems it’s okay but the fabric side of things it looks like a lot of things that have been been produced there but focusing just solely on the August update I think some of the new reporting features here they added

7:39 new reporting features here they added this well this well I I think this is this is funny to me they added a new layout switcher to switch between a desktop mode and a mobile mode so you can build reports in Mobile or desktop as if it was like a landscape landscape a report page and I’m like well that’s nice that you actually you actually added some buttons for that because likely no one knew they were there nor does anyone ever build reports for mobile so I think that’s probably the reason why they expose actual buttons

8:09 reason why they expose actual buttons for it that live on the page every day I don’t really love these buttons I’m like you’re just taking away more of my landscape space for the tabs on the page at the bottom of like this is where I’m like what is going on Microsoft put the icons on that left-hand nav bar that’s just sitting there totally empty not using a lot of space so I’m not sure if I really love the placement of these icons but oh yes it has been added

8:39 any other features you guys found and stuck out to you okay like I do like the enhancement around the power bi project file oh yes you publish directly from that yes that is a brand new thing ease of use feature I think that should be should be one that’s going to be useful as people start to integrate and use the pbip file yes a lot more it serves us well very well because we’ve been building scrims or or entire reports now with the theme generator

9:11 reports now with the theme generator the theme generator now supports the downloading of the pbap file format you can build your own Pages you can add background images to them as needed but now you don’t have to re-save it as a pbix you can literally download the entire project and then publish right from there right to the service which is awesome I was doing some testing of that this week as well that’s a great point out to be a huge Time Saver all right like using our totally you like for folks that don’t know we talk about it a lot but it’s not just the themes right we can create and manage every aspect of a

9:42 can create and manage every aspect of a theme but now with the wireframe background images all the actual visuals themselves download and then just add your data and your model and yeah a huge Time Saver but then this is just like another ease of use thing where it’s like downloaded here and then just publish it yeah edit those those small elements like the actual data exactly how was it in the article right was that an it’s towards the bottom after

10:13 it’s towards the bottom after after all the mobile updates it’s the developers area it’s your startup content developers yeah yeah second one under Developers publish a pbip file directly to the service yeah it’s interesting to me though that a lot of it is is user user visual formatting things you’re talking about this this recent

10:39 you’re talking about this this recent update updated yeah the whole update itself but it’s like a lot of focus on the third party tools and some of those are the third party visuals Zoom charts looks like some of those are those are always worthwhile I think to cycle through every once in a while just understand like how many how much time and effort is being put into some of those visualizations yes and I’m glad they’re calling them out I’m just a little disappointed that like I didn’t I don’t see any other intrinsic like in tool boxes some of the

11:09 like in tool boxes some of the visualizations that that we know are being worked on but you get a new you get a new bubble scale so new new bubble scale ranging because all those bubble charts you use so that’s a that’s incredibly helpful thanks for pointing that one out like I appreciate it not not on your top 10 list there you don’t use bubble charts every single day I may or may not have spent some dollars towards towards just saying amazing

11:40 amazing any other thoughts before we get into the topic for today just good to be back yeah it is gonna be back yeah I was talking with Tommy offline it’s like it feels like this is almost like my therapy session to some degree like I have some other people who understand the pains the the issues the challenges that go along with like reporting and working with it’s it’s a it’s the whole there’s people problems there’s process problems and there’s technology problems and all these things keep moving at the

12:11 and all these things keep moving at the same time so it’s nice having other people to understand how these three things integrate so well together I’m glad I can be here for you and and I’m glad I’m part of this group that we can hi I’m Mike I’m here hi I’m Mike I work with data data and guys data is hard which brings us into our topic today so that’s really a good lead-in so this is a post and the link is in the description of the video and we’ll also

12:41 description of the video and we’ll also grab the link the LinkedIn post here from Benjamin and and we’ll throw this down here in the chat window just in case people want to follow along and read it so this is a a chat thread and I’m talking about working in data is hard so just a really interesting topic here kind a really interesting topic here taking something from the interwebs of taking something from the interwebs and going through a a simple example here of here of maybe so for those who have been listening to the this is a US economy thing as well so there’s an

13:11 thing as well so there’s an example given in this that talks about svb Silicon Valley Bank I believe is the acronym there and they had some internal data I guess they were working on their analyst team or whatever they’re in their internal data or the model that was telling them where is the risk inside their company was highlighting the fact that when interest rates go up the bank will struggle right so this is a bit of talking through this and and

13:41 talking through this and and balancing the what do Executives want to see versus what does the data show and what are we actually being actionable on data data so let me pause right there it’s the introduction to the article Tommy you want to lead us in here any other additional thoughts around this blog post or things you want to call out here man if this didn’t ring like her almost reading it just from past experiences just right yeah it brought up some post-trauma and

14:13 yeah it brought up some post-trauma and just working in this industry where you just believe in the data you believe in like showcasing whatever it was right getting that insights unlocking and then people just don’t like what they see and everything like either a project dies or people move on and isn’t the isn’t the call isn’t there a phrase called like manifesting like when you like your sales are up 10 sales are up 10 you keep saying and like over and it becomes true just by like thinking positive thoughts is that is that what that that phrasing

14:43 is that is that what that that phrasing is is you’re running into the idea that people are trying to manifest their will on top of the data I want it to be I want our investments to go the right way thing thing I I’ll I’ll do one better again just even going along with this I was when I was a lowly data analysts I was doing finally a kpi dash previous from the targets I’m like hey where do the targets come from because we can project it they’re like oh we just add 15 every year it’s like like major targets like Revenue like no

15:16 like major targets like Revenue like no yeah like yeah yeah yeah thing and it’s like okay we could look at things and and begin to actually make this little thing no no this is what we want and well sales is actually different because they don’t want to do 15 so it’s five percent and we’re like What so the idea where you feel like you have all these insights that you can bring and you can have everyone to exactly see what they’re doing hey that the idea where yeah sometimes people will kill it because they don’t

15:46 people will kill it because they don’t like what that what the output is or they don’t believe in it or they just it’s different from expectation which is crazy crazy it’s interesting that you mentioned that because I feel like I’m YouTube is so smart I’ll say that just off the topic off there when I listen to I said I scroll a lot of YouTube shorts and things and watch a lot of Articles and I’ve been watching a lot of news or and or opinions about the economy in general and Tommy to your point there the ability to have

16:18 point there the ability to have this this concept of struggling with the data and working through these things this is a very real concept and I think that the data is difficult because there’s like you come into things and there could be noise in your data and I was watching a little article around or someone was making some fun of something it was along the idea of not every business always grows at 10 every year there has been some businesses that have been very like stagnant and they just maintain for

16:49 stagnant and they just maintain for numbers of years before something in the market changes someone leaves the market they get more market share whatever that is and then they’re able to grow again so I think there’s this misnomer or sometimes we think about hey why does why isn’t the business growing the same way every single year well that is not always going to happen there’s going to be times where it grows there’s comes and we’re not not going to grow yeah I I think I think there’s two two things I want to point out one is our conversation points are probably going to dovetail into some of some areas that

17:20 to dovetail into some of some areas that are not particularly applicable to to this scenario right but it drives it drives this conversation around what are what are the challenges that we face in in our day-to-day working with data and people or objectives within an organization because the one that that overrides and what I’m hearing you guys say under the covers right now are where there are there times where an objective or

17:51 there times where an objective or directive is completely superseding reality right where all like you may have these major initiatives and everybody throughout executive to management are are driving behind them and you’re you’re almost building a Culture of Fear behind that if if actual reality and data and typically it’s people who work with data all the time where you start to see things not aligning with where we want to be sure and and I think a lot of the conversation today is going to be around

18:22 conversation today is going to be around data culture and how do we how do we potentially work through situations and or not as as it pertains specifically to like SVP here I think there are some some areas that I I’ll want to talk about about like process but in this case in reading and Mike I think you might have the original link from Washington Post Yeah I do have the original language like there’s there’s a lot of this wasn’t just like a one person disagreed and a model

18:52 one person disagreed and a model changed right like there was process there was a risk management team there are there were so many things in place that were that were like tick yep check that box yep we’re gonna modify this we’re gonna do these things and I think that’s so it doesn’t this situation doesn’t fall in line that there was no process there was no regulation it was reported to federal and state that this was changing you and state that this was changing so there’s a lot of things involved know so there’s a lot of things involved in it’s not just one person that made the decision and then on the flip side articles like this are easy to write because

19:22 this are easy to write because hindsight’s 20 20. totally I said this I said that we this model change was going to break everything but in reality like even in the article they say like well this was also like there was precedence for this it’s not this was the first time this had ever happened it just there was The Sweet Spot of the Calamity of the economic change change and radical shift where interest rates had to you where interest rates had to increase and know increase and like the the things coming

19:54 like the the things coming out of that that story I think provide the full context where glibly we’re talking about this in in the scope of other areas or apparently Tommy’s traumatic experience today which we’ll we’ll give you hugs Tommy like that’s what thank you this is the therapy session you won’t walk through this with you we’re we’re there but ultimately in in the the LinkedIn post post there was a comment by Yuki kakagawa that I really loved and he just said

20:24 that I really loved and he just said this is all about company culture data-driven decisions are not the same as taking only what you like from data and I think that’s where a lot of conversation for me is going to go today we’re around like what what is that that stress point right where how do we make sure that we validate data how do we create you we validate data how do we create these value to the business know these value to the business but are there times where the business doesn’t want that because of these other

20:55 doesn’t want that because of these other initiatives so there’s a lot going on today we’ll see where we we mix out we flesh out yeah I agree I think this is a I think this is a great topic I think it’s super relevant I like how your summary there Seth pulled together a lot of key points around those areas I think this is yeah I think it’s a very good and then as I read through the article

21:16 and then as I read through the article here so going back to the Washington Post article that you pointed out I actually put that in the chat window as well so if you want to read along with there as well they’re they’re I’m looking I was reading through there and about halfway through I started highlighting a couple notes here a lot is that a lot of this comes from the top down right so a portion of it we’re saying a lot of the profit driven strategy of the entire banking or the bank was driven top down it was a very top-down driven look we’re

21:46 it was a very top-down driven look we’re we’re going to be profit basis is what we’re looking for so therefore aggressive moves were taken to be able to to make that profit that we want so that we can have that high growth rate that we that we need as a bank and so then on it says here in the article on March 8th they’re they’re forced to liquidate a bunch of things and take out a a loss of 1. 8 billion which is a huge amount of money to take a loss on when you’re talking about a bank but to your point something stuck out to me here Seth was this is a bank this is this is a very

22:17 this is a bank this is this is a very highly regulated market an area like this stuff happens like and and this is an area that where there’s a lot of scrutiny there’s a lot of eyes on it there’s a lot of Regulation around that industry so for them to even get wrapped around the axle around their data and make decisions based on their information to get themselves in trouble imagine how much more this is occurring in business units or other companies that are not as tightly regulated federally but it’s it’s a tricky topic yeah yeah and that’s where like one of

22:47 yeah yeah and that’s where like one of the if before I went super sleuthing in like back to the original article yeah one of the one of the things I was going to talk about like was a major breakdown in process or procedures right because if we think about like these the the key reports and we talk about like governance and making sure that there’s data quality that goes up through reporting there’s a reason why you build checks and balances up through things not just for Trust of data but it’s because in

23:20 for Trust of data but it’s because in certain scenarios like let’s say let’s say there is a key kpi metric that is part of your dashboard that says we are running a healthy business right and then we make a decision or the company makes a decision to radically put ourselves in a position where hey maybe there’s this massive growth opportunity and we’re going to pursue that that and the the ramifications of that decision start to be realized in the data and all of a sudden your kpis start

23:50 data and all of a sudden your kpis start turning red [Music] [Music] what do you do right like what do you fall back on well instantly everybody’s going to be like okay let’s validate that this is accurate 100 True like let’s do that but when you have those processes in place yep yep check check all the boxes we’re monitoring everything like the data’s coming through the same way these this ties back back this is a result of us as an organization understanding that we’re going down this route with the objectives

24:20 objectives then then it then it gets put on leadership right like okay do we shift course do we do things differently or in this case like let’s just say well do we modify how we calculate the healthiness of our business and what do you do in those situations where it’s like like I as an employee you’re trusting that the leadership team is is driving you in the right direction and that they they understand the Dynamics of in totality

24:51 understand the Dynamics of in totality of the business and making modifications to certain things with checks and balances in place should absolutely be able to happen now since like that falls off pretty quickly at the banking industry where it’s like okay well maybe not but you it’s like okay well maybe not but there there is that that know there there is that that there’s I think room for disagreement is what I’m saying yes versus where sounds like Tommy’s been where it’s just like yeah man like nothing you’re saying is making sense and we

25:23 you’re saying is making sense and we would never take this metric and pollute it because that would mean that you don’t know what you’re doing right because our there’s no doubt there’s no upside to that decision right outside of you wanting to manipulate something so you look good which is a playing field in here yeah so many topics here go ahead Tommy it’s it’s not even just the looking good what I’ve seen is continually be it’s it seems to always be about expectations and what people

25:54 be about expectations and what people expect the numbers to be which is kind expect the numbers to be which is the idea of we’ve dealt with the of the idea of we’ve dealt with the drivers of those expectations that’s what I was going with that’s what I look good right yeah because that that’s where data culture plays a huge role in this right because what drives bet it’s kids man what drives bad behavior like you you set an unattainable goal like my kids starting soccer again apparently like new head coach one of the things she said right off the bat is like if I

26:25 said right off the bat is like if I find out that grandparents or parents are paying their children for goals you’re off the team and I was like wait a minute what that’s a good thing you’re like I don’t know the goal for the kid is I don’t care about the team I’m gonna score a goal right yeah so in the same drive through a business like what are the what are the drivers for people’s motivation right and if Tommy if you’re reporting to somebody and their number their

26:55 to somebody and their number their number is 20 and your report is saying 17 but 20 gets a bonus what’s what’s the motivator for the for good behavior well you’re driving bad behavior in the business because they’re gonna start to do some individuals will choose choose that they they want to they want 20. Tommy make it make it 20. but how much do they pay per goal

27:26 that’s where that’s where you mean is this like five bucks a goal are we talking like 10 are these grandparents well off I need to know here right because this I might be able able this is exactly what I’m talking about exactly and how much money do these grandparents have I don’t understand like are they 100 per game or or if the kid another kid finds out hey hey yeah like I know I think that’s exactly right like you pay me the money ask me pass to me so I can I’ll give you a cut I’ll give you a cut

27:56 I’ll give you a cut I’ll give you a cut of the yeah I’ll give you a cut of the profits at the end here sorry I didn’t mean I didn’t I I’ve never even heard of that wow I but again but again sorry I didn’t mean to rip your tummy but I just was that just struck me as funny and go ahead Tommy jump in there it’s it’s like where how everyone already had a hunch in terms of like how they worked for years in Aeons before where they had some data but they felt this way or they wanted kind they felt this way or they wanted what not even they want the data to

28:28 of what not even they want the data to be something but they they had a project or they went on just like no don’t bother me with the the complete actuals where this is how we’ve been operating as an organization is because it’s usually not just one person and there’s probably also I’ve seen this too and not that I felt bad but a lot of times a good amount of times where it’s not necessarily the executive which is but that’s occurred where they someone’s on so much pressure to achieve a certain number or a certain rate and to show

28:58 number or a certain rate and to show anything that’s drasticably below that would either a mean that the last few years that they’ve been trying to look at the numbers is completely wrong this is not just a random no I don’t like that the reason why it’s often their expectations is because for however long they’ve been there or they the company’s been working they always assumed that they’re they have there’s a baseline error threshold and they kind baseline error threshold and they been operating off that so it’s kind of been operating off that so it’s kind of been operating off that so it’s like you’re you’re almost like of like you’re you’re almost like

29:30 like introducing a new reality there’s a there’s a question that keeps coming to my head here and I’ve been taking notes Here on the side one one of them keeps coming up with a little bit of data culture question around this topic this this to me this article feels a little bit around the data culture of the bank was in a place where profits before all else and it was so driven on that and again I think there’s a mindset here that they need to take aggression if they’re going to be able to play well there’s a lot of other people playing this game as well but to your point Tommy earlier you said

30:01 but to your point Tommy earlier you said the company says hey our goal is 10 more this year than last year and my question is do you really understand your business do you really understand what makes your business tick what do and I think this is what you were alluding to Seth a little while ago was was does do what drives more revenue or more sales in your company is it more phone calls is it more boots on the ground is it more marketing is it what what are the data points that you’re using to influence okay if I want

30:31 you’re using to influence okay if I want to get a 10 growth what actions can I take right now to make that work and I Tommy to your point there right when that number comes out of the thin air have we looked at the growth year over year for the last five years what does that look like were there any market conditions that were influencing things I was just talking with someone the other day around Ai and the idea of the pandemic has really messed with everyone’s forecasting because there’s this there’s this huge dip in certain

31:03 this there’s this huge dip in certain business markets that made a huge impact and and some people were buying things out of fear and so there’s these huge spikes in consumption and then other people were not and people were really cutting back for periods of time because things just got very nervous and so the whole the whole like you so the whole the whole like looking at know looking at the experience across the markets there’s a lot of influences here that can really tell your business if you’re up or down and I

31:33 your business if you’re up or down and I think to your point Tommy earlier that 10 up or down is so arbitrary they’re not even are we using data even to and do that analysis I think there’s a question here do you even understand your data your business I think you make a good point because in in banking here right especially if there was precedence okay say say say You’re Gonna lead lead at a high level of risk

31:55 lead at a high level of risk and you’re going to redefine your your models right yeah redefining the model shouldn’t be like we’re going to pretend we don’t have risk or maybe they redefine the model to like indic well there is no bank so obviously it wasn’t done right like where where what are what are the new indicators that tell you you’re in trouble right because it’s very the other thing I want to be aware of here it’s very easy for us to fall into this 2020 mindset of like oh I’m an

32:25 into this 2020 mindset of like oh I’m an employee and like I I know that the you employee and like I I know that the the CFO the chief the CEO they they know the CFO the chief the CEO they they LED this the wrong way yeah well leading is significantly different than following okay one and a perfect example of this in some scenarios there is no precedent yeah like Kodak as as a as a camera company yeah largest in the world yeah and and they had a guy they had a person come in and say like hey I developed digital cameras

32:55 say like hey I developed digital cameras and they were like no no way business is predicated on film We’re not gonna do that where are they bankrupt yeah there is no precedence for that there is no data indicator like unless you’re like oh hey let’s look out in the market for some leading indicator of our competitors doing something that we’re going to turn down right so interesting like that’s what I’m saying like it’s not as black and white and I guess maybe that’s where the lead into there’s a fine line between data that

33:25 between data that and the types of information right like the type of value that we bring are we just showing you like what what currently is happening right are we being predictive about things are we being prescriptive with the info like what are you doing with the data that is being provided from within the organization I think that’s also one of the main reasons why we as data people are like you better put all that together because it’s a extremely valuable resource for your executive team to understand

33:55 team to understand holistically how the business is doing and that’s why you go through these massive efforts to consolidate data to the point where you can report it in valuable metrics right but none of this to me is black and white and that’s like I guess the point between when we’re communicating about data versus people’s like objectives and what we need to do as a company because our leaders are saying that there is a fine line in here but I think the difference

34:25 line in here but I think the difference is is is is data should lead the conversation right if we’re seen if we’ve gotten to the point where we created all of these metrics to show indicators about the health of the business and the just then we have to be constantly reevaluating the business to ensure that our directives are our objectives are the right one and we’re being successful because if we’re not we have some difficult choices to make and I think what happens here is like you can’t the same way we build like a report or build

34:57 same way we build like a report or build out a try to build a data culture right a leader is trying to drive growth in the business continually okay but what does that take constant evaluation are we doing it right how do I know I’m doing it right here’s the data that says you’re doing it right right here’s the data says you’re doing it wrong whoa if we’re doing it wrong do we ride this if we ride it how long like and that’s I think the cycle that all of us especially as you drive into leadership position positions

35:28 leadership position positions have to re-evaluate everything we’re doing same way we do development right you’re constantly I’ll give you version one and I’m moving around to version two version three we’re constantly evaluating whether or not like our choice our Direction our build of something that’s larger and larger and larger is on the right tracks and sometimes it’s not right sometimes we need to reevaluate sometimes especially root related to like people right so it’s like hey what I’m trying here is not working but and the more indicators

35:58 not working but and the more indicators I have that tell me whether or not it’s working the better off we’re going to be but at the same time like this isn’t we’re definitely in the realm I think of people having to make hard choices and then those ramifications of the choices get larger and larger and larger depending on how high up in the organization how large that directive is because if you’re gonna you’re gonna say hey hey we’re gonna go launch the Strategic initiative you guys have both been part

36:28 initiative you guys have both been part of this right like we’re gonna launch this huge thing and I’m sure like Mike you’re passing Johnson Controls okay we’re gonna spend five million dollars and then at the end of three months we got nothing I I’ve seen projects that’s hard too right I’ve seen I’ve seen yeah I’ve seen mismanaged projects where things have spent a lot of money and all of a sudden the product just no longer exists we walked away it was it was invested heavily and the business decided to move away from them we’re thinking I’m thinking to myself there is so much

36:59 thinking to myself there is so much opportunity here and now there’s so much waste that has come out of it yes we have some IP around it yes there’s some things here that have been value-added but at the end of the day you’re looking at it going why does that product not exist now what happened so it to your to your point though there a lot of people I think are trying to very much meter and measure this this I believe I watched again the things that I consume I saw a YouTube short around somebody talking about a new employee talking to Satya Nadella and so I I

37:30 talking to Satya Nadella and so I I think Seth as MVPs we got the book from Satya hit refresh I believe was what it was yeah and I think you read that one but I think a very so if we think about Microsoft Microsoft has gone through a transformation as well they’ve gone through a very shift in how they do business from a very developer-centric area to more of like a business user-centric Arena I feel like and I’m very excited about whether their products is going and what they’re doing but but one of the this YouTube short was

38:00 one of the this YouTube short was emphasizing was Satya would sit and listen to people and and people who were new to the company brand new people to company tell me what’s going on what do you see happening what are the things that are good that are happening and what are things that are challenging they’re happening and trying to really as a leader yes you lead but I think to your point set this is I think dovetailing very well on this topic right as we look at these kpis and we look at the metrics the people who understand how the business is running are the people that are running the business are we listening to them are we

38:31 business are we listening to them are we hearing what they’re saying and not overriding our desire for the business above what my team and my people are saying saying and and there’s Nuance here too right because because in a healthy organization every worker all the way down understands what the objectives are of the company but unfortunately that’s not always the way right you want that to be that way right yeah so so there are cases where you may have an employee who’s like no the data is saying this right like this is what it’s showing because they only

39:01 is what it’s showing because they only understand 60 of the problem that their manager whoever above is trying to solve and then they get overwritten right no you’re you’re wrong because they’re not being told that there’s a whole other 40 where the request was you provide me this information provide me this metric I’m gonna go own this I’m gonna export it I’m gonna add my other 40 Secret Sauce that I’m not going to tell you about because I’m going to control the whole thing and that’s just not healthy right like

39:31 that’s just not healthy right like because then then you don’t open opportunities for everyone in the organization to make a difference right and I think that’s where a lot of the self-service bi a lot of the challenge like the things that we’re interested in promoting is access to data it’s everybody should have access to these things to ask questions because what happens when everybody’s asking questions well we come to an agreement right there’s a definition there’s a standard we start to create within our

40:02 standard we start to create within our organization everybody starts to understand how this works so your everybody is becoming more data literate and the more refinement we can make in an organization because more people have access to the right types of data and obviously there are certain aspects of data that require more security yeah but at the same time like it is a it is an open environment where the best ideas win as opposed to a controlling environment where only

40:33 controlling environment where only certain people win because they control the the messaging because ultimately it’s the message of what the data is giving us it’s not the data itself it’s hey what is this telling me and that is subjective to some degree yeah but but shouldn’t be subjective to every degree right true it should hey I’m interpreting this way this way I think this is why this is happening is this do you think the same thing here here’s this report here’s the day that we’re pulling blah blah blah right as opposed to give me the numbers here are the

41:04 to give me the numbers here are the numbers oh great job 20 again man that’s like that’s like six quarters in a row everybody else is failing and you’re not man great job it’s it’s the pressure that’s puts on from there yeah totally but that’s what yeah that that’s I think is a contributing factor so how do how do you so as I think through this one well a couple couple things come to mind and another another comment I wrote down here is how do when the business is in trouble is

41:34 the business is in trouble is like my first question how do we know when this is we’re not the culture isn’t aligned right to finding these in the tummy you’re saying very earlier experience has been I I have I I know exactly because I’ve been through I’ve been with a company yeah so I I I have a very strong opinion about this one you guys do you guys have any indicators like when for companies that you’ve you’ve worked with I can’t I want you to go you set

42:04 want you to go you set that up really well so so I will say I think I think there are some there are some signs of unhealthiness I would say as when I when I think about this in certain companies one of them is you over value or you over rate the skills on your teams in in in the organization so when you talk to people they are saying we’re

42:34 they are saying we’re experts in this area and when when experts show up and talk to people you find that there’s not the skills that we need so there’s a lot of there’s maybe that’s that’s something it is there is a very a little bit of smoke and mirrors that are occurring right you can tell everyone’s trying to make everything appear to be correct or the data culture is not there from a data standpoint so that that would be one indicator that I would find there you’re hearing things like the the operating system that makes the data doesn’t necessarily align to how you report on the data and make the

43:04 you report on the data and make the business run so whenever I hear the word reallocation or allocate it is a a signal to myself that says something in the design of the of the system to get data out of report out of the transactional system the system that makes you money into the reporting system to help you analyze your data when we start reallocating things it means there’s a disconnect to what the business wants to do to run the company versus how we’re capturing and catching data so there’s there’s that’s

43:34 catching data so there’s there’s that’s where sometimes you get a lot of the smoke and mirrors how we how we can make the numbers look correct so that’s one signal another signal I would say that I have found is when there’s too many pivoting directions so so I feel like sometimes it’s good to Pivot it’s good to change directions when market conditions are changing but if you see too many directional shifts on what you’re trying to accomplish or scope creep on projects keep getting larger and larger and larger these are the projects that fail and I’ve been into I’ve been

44:05 that fail and I’ve been into I’ve been around some IT projects that have been quite large moving an entire manufacturing company from the Legacy system into a new system right spent millions of dollars trying to transition from one system to another didn’t work well because there was a a resistance at the People level there was a culture shift that needed to happen and we the the teams were not brought along with that and and I think there’s a there’s a resistance to

44:36 a there’s a resistance to when you are doing large projects particularly in the I. T space I feel like there’s this idea of what is our process and what is the new technology that we’re bringing in and sometimes you have to negotiate on both of them sometimes you customize the technology and sometimes you customize the process and having that flexibility to really sit back and evaluate what do we switch what do we just can really help that business run one way or another so those may be my two main points that tell me there’s there’s some warning

45:06 tell me there’s there’s some warning signs in there not saying that that those are 100 true but they’re seeing they see they seem to be indicators and we’re not maybe the last part here I would say is maybe there’s not that success or wins of success with customers right if you’re not solving problems if you’re not meeting customers needs if you’re not producing satisfaction someone smaller more Nimble easier can come right along the way and and just repeat what you do but there’ll be those would be maybe a couple things that I would say

45:36 couple things that I would say indicators that would tell me potentially something’s wrong there Tom anything that you’ve observed I I think the biggest thing is it’s a culture thing is because it’s usually not just gonna be one person or a few group of people that have the same Tendencies because it really is truly a a cultural thing so I think it’s a habitual thing and I think part of it to be completely honest I think it starts with the types of requests that you’re actually getting

46:06 requests that you’re actually getting and truly like in terms of like what are people actually asking for in the first place and two what are they doing right now in a sense to like the back and forth with you is it a just hey show me the data show me a report we want to see everything integrated in one place or are they actually saying I want to see how my team’s doing because based on this and the type of action that they’re actually asking for I think even those who have the Excel

46:37 think even those who have the Excel sheets or those other systems I think there’s still that lack of trust so are they they asking you to actually in a sense dive in and then showcase to their team how everyone’s doing or how how projects doing or is that still in a sense kept head and we don’t want that actually in the portal and part of that too is also from the leadership too on how much are they pushing towards you and they pushing towards the team on team on we only want certain requests but honestly to me if you’re getting a lot of requests that are just we just need

47:08 of requests that are just we just need our data in power bi you can we just need to see the last 12 months I think anytime you start to introduce anything that would potentially show something potentially show a performance metric people are going to be a little hesitant and I I think the other part of that too is the other big indicator indicator is that communication like how much how well can you talk to them about what they want or I guess are they a little more intent and to turn like hesitant to try to and

47:38 and to turn like hesitant to try to and since like hey you’re just doing the data guy you’re not supposed to look at these things or we don’t want to see what’s under the Rock and that’s what I’ve always said is people just don’t want to know what’s really under the rock a lot because sometimes it’s hard to tell tell if people are going to trust it or not but the big indicator if you’re starting to build some of these reports and you’re just in the sandbox phase and people are freaking out and getting defensive because something’s not what they expected to be that’s a watch out for me that sounds like a that sounds

48:08 for me that sounds like a that sounds like a data culture challenge there that people aren’t able to communicate so this is what we’ve talked about in the podcast before right communicating with data is a thing like being able to communicate voice what’s going on with that and having people that understand it and are receptive to that that yeah without that without that capability you you lose the conversation yeah I like that one as well all right Seth we’ve given you some did we did we did we hit on any of the ones that you were observing during your time when you went through the company transition you did

48:40 through the company transition you did I think I think several of my points all revolve around when and how a company communicates with its employees but oh you guys drove I think in in the mix here in culture and in Civic areas I think from my experience are definite indicators right like one first and foremost so when is the company in trouble from Seth’s perspective wait when there’s no clear and or achievable goals for clients to achieve those goals right like yeah if if we

49:12 those goals right like yeah if if we aren’t on the same page in driving towards excellence in some Arena like what are what are we’re just keeping the lights on like what yeah what is what is the purpose for us all being here a second one are and I put in quotes the drivers are not happy and these are the key Playmakers everybody we work with in an organization who the people are that are going to get something done yes and who the people are who are not or it requires a

49:43 people are who are not or it requires a lot of effort to get them into a state of performance the vast Shocker the vast majority of people are more or less just there to collect a check and and there’s a laissez-faire attitude towards doing a job which is unfortunate I think just but is reality you have far less drivers or people who can influence the way a company succeeds that always exists in every company that’s an interesting

50:14 that’s an interesting and you start to lose they leave well the talent the town you get that brain drainage they lose their motivation to stay on top of everybody else to rise bring them up to achieve goals and when that happens like goals start to like output starts to go down so I think those those on a lower level right yeah you don’t know where we’re going and the people who can make a difference are either no longer

50:44 a difference are either no longer interested because they don’t have clear goals and there’s no real reason to go after them anymore and they’re in a state we’re probably looking because it’s a lot of work it’s a lot of work to pulling other people along for a ride or hit goals and and things like that that and then and then like I think it dovetails into like how a company talks to its employees transparency of company Health right like and these are typically in quarterly meetings if you’re if you’re lucky you have monthly right where the the business is engaging

51:14 right where the the business is engaging with the the employees on a regular basis the warning signs in there for me was there where especially as data people when there’s a disparity between our day-to-day and our understanding of the health of certain areas of the business yes and then what’s being told us in the quarterly data projection they’re like the that that alignment yes and so great is where you you start to go like I know they’re not pulling in from this you they’re not pulling in from this like well it’s also we as a data

51:44 know like well it’s also we as a data team there are a lot of smoke and mirrors that can happen there but on the data team you can you can go do your own analysis you can actually there’s there’s things that you see right you maybe have a little bit privy a little bit more privy to data that’s like telling you these these Direction things yeah and then the last two would be like that they’re just not talking about current state right everything is future everything is big wins it’s the interesting thing it’s the next big thing that we’re gonna sell it everything is predicated that’s a really

52:14 everything is predicated that’s a really good one without telling you like well what is what is our current state like what actions are we taking to if things aren’t great how are we fixing that like what what where are we missing what do we have to do what is our go to market strategy going to be like everything can’t be the next big win right and that’s where I’ve seen in the past where you have you have certain like leaders of sales teams guaranteeing yep like you guys build me this and

52:45 like you guys build me this and and yep they will sell it and they will come come and it never works even even at the macro level I would say that’s even in the report why are we getting no usage in this report well it’s just the colors aren’t right yes right yeah this is my fire drill I need it I need it I need it and then like two weeks later you’re like if you if everybody needed this why are five people looking at it wow same same deal right and that’s really good that’s where having that process as a bi developer is

53:11 that process as a bi developer is extremely important weighing the pros and all of us should be weighing the pros and cons of like somebody’s fire drill versus overall company objectives but if I don’t know what the company objectives are I can’t push back right I can’t say that what you’re asking for is a you thing right like I’ll put it on the back burner but I’m not gonna like this isn’t going to like uber critical where I’m gonna stay up all night to produce this for you because it doesn’t align with anything right yes and then and then the final one is

53:41 and then and then the final one is like we’re employees are more upset after company meetings than they were before the company that’s a good barometer right there it’s a good barometer wow so those those are from from Arenas where working for certain small companies and things that that didn’t fare so well are some indicators I’ve lived through that things aren’t so fantastic I found a maybe you want to keep the resume updated when people start polishing resumes when

54:12 when people start polishing resumes when you look at the number of minutes the company spent on LinkedIn or jobfinder. com when you watch The Rev the web traffic and those numbers start upticking there’s a potential problem there it’s interesting you mentioned this that point there Seth and I was literally scrolling through Linkedin the other day and I bookmarked a a that’s like a cheat sheet it’s kind it’s called setting priorities the ultimate cheat sheet and I’ll put the chat here in the window here for you to go jump on this one so I’d be curious if you guys hit that link check it out here

54:43 guys hit that link check it out here real quick but the idea is it’s a it’s a single one pager and talks about how can you set priorities for an individual for a team and for a leader and just very briefly summarizes different methods and I really liked the little the the Eisenhower Matrix method Matrix method which is one that stood out to me when you were saying that stuff Seth right on the onions it’s a x y coordinate coordinated chart it has four boxes on it is the task urgent and important

55:14 is the task urgent and important do it right away is the task not urgent but important decide and block time for it in the future right is the task urgent and unimportant you delegate it right we have to get something done but it’s not important that someone else can do it and then if the task is not urgent and unimportant delete it and just take it off the list so there’s a I liked this little infographic because it was like really neat for like these different methods about how do you evaluate what should we be working on and I think to

55:45 should we be working on and I think to your last point there are a couple of your points there towards the end there Seth Seth it sometimes we’re working on the wrong things sometimes we prioritize things in an incorrect way and having a method on how you can evaluate what do we work on where do we focus our time yeah and and but that’s constant too and that’s constant so important that agrees have okrs or ogsms or like alignment because that’s where teams collectively marry up right like okay more than happy

56:17 marry up right like okay more than happy to help you out business person a like what objective is this is this like helping you achieve in in this quarter yes well well it’s it’s not why are we doing it well then then I’m not serving my purpose which is to assist you in achieving all these other objectives like what what is the driver for this request are we going to make a special exception which can can be had but at the same time like I would say say rather than like taking on special

56:47 rather than like taking on special exceptions it’s more often than not that like work groups just find themselves like down in some rabbit hole without re-evaluating whether or not they should be there yeah and and that that is unfortunately the case where like this where that comment about constant reevaluation whether that’s at the very highest level with the highest level objectives are we going in the right direction what’s the litmus and to my comments to Mark who had a great question about like always talking about

57:17 about like always talking about what’s next well we should yes we should be talking about what’s next but we should also be talking about like hey that thing that was in the future how did we do did we do did we win did we lose yes like how are we progressing like what is the current state of these things because what we talked about should now be current state and if if it’s always future and we’re never talking about like win and loss and like making hard decisions or shifting goals or shifting then we’re not doing things right yes

57:48 we’re not doing things right yes what one thing that comes to mind here again this oh this is gonna we’re gonna winding down now we’re getting to the end here I’m gonna try and put a final thought here together and maybe this is just another random thought we were thinking about things here a lot of good items a lot of good topic items here around where we see challenges with doing data data things one of them I think is going to be this increasing excitement around AI I don’t think I’ve seen an art a news article yet but there’s going to be a news article

58:19 but there’s going to be a news article where someone relies on AI to produce a recommendation an outcome and someone uses it uses it trusting it wholeheartedly yeah and in reality it is totally the wrong thing to do in the business and and the business is going to burn down because of it yeah so so it’s not there yet I haven’t seen a news but I’m gonna put my my ear to the ground here and say if I’m if I’m looking at the landscape of where data and technology and AI is all coming together it’s getting more and

58:49 coming together it’s getting more and more difficult to discern from AI based things things what is really real what is truth what is what is something that I can actually go do versus what is not and so in all of this I’m I’m my mind my head goes goes prediction of things is very difficult and you have to have a good day to get there and you’ve got to have all these company culture pieces in place or at least working on them to try and improve them it’s like a living organism you got to keep working it and making it better and

59:19 working it and making it better and trying to improve as much as you can but then now the introduction of AI makes this I think even harder now and and now with companies executive level people and companies pushing we need AI we got to put it in place where do we put it it’s going to be very important to take those new recommendations in a very metered way anyway so that was just because of what my thought was I’m I’m waiting for the next article that comes out so mark my words I guess what episode whatever episode we’re on on this one so

59:49 whatever episode we’re on on this one so episode episode one a 247 I’m making a prediction there’s going to be a news article in the future around some company trusting AI that totally LED them astray and is now getting this totally wrong and and the dangers of AI is coming I have a story around this one we’ll have to save for the next episode I would I would say like final thought data is hard and it’s harder for for those of us that work with it because we need to ensure that data is

60:19 because we need to ensure that data is the driver for discussions not just I like that and if people have opinions that’s great goals fantastic but all of it should and can be measurable right because it’s honest it keeps everybody in the organization driving towards the same success factors the same goals the same everything and and I think it shines a light sometimes on hard conversations and hard pivots and that’s why sometimes you get people who ignore it and I think it’s okay to not make your

60:50 and I think it’s okay to not make your goals I think I think there’s there’s in this article particularly with svb there’s there’s a constant pressure to always win and and I think Simon sinek who doesn’t talk about the oh I always forget the name of the book The Never Ending game the yeah yep the business constantly has to reevaluate business is constantly it’s there there are rules in certain rules in business but the game is ever evolving the the game there is no and you don’t win at there’s no end gaming yeah there isn’t

61:21 there’s no end gaming yeah there isn’t the end game I guess it was his Simon’s next the end game but that’s another one that I’m like that that resonates with me and I was like oh my gosh business is like a Perpetual Risk game of Risk where you’re always shifting things and always adjusting and your competitors change and you change and you’re always adapting so yeah I I like the idea of being able to have a receptive learning educating heart as you do these things because I think the market conditions will change and you need to adapt to them as they come out tell me

61:51 adapt to them as they come out tell me any final thoughts for you as we wrap up here this is I this is I the big thing I think moving forward if you’re finding yourself in one of these situations if you are alone it’s probably the hardest thing to try to move mountains by yourself because like I said it really is a it’s no reporter technology is going to fix this this is about throwing people on board yeah and is this Begins the conversation to get actually get whether some more people involved in what you’re trying to do but you’ll find

62:21 what you’re trying to do but you’ll find out pretty soon whether people want to or not or not that’s true I agree with that one well with that we’ll wrap it up here thank you all very much for listening welcome to be back we’re very happy to be back in the podcast doing things for Real live again so thank you all for the chat has been amazing great ideas Chad thank you so much for participating we really appreciate you if if you like this podcast if you were challenged by it if you’ve had some things to think about if there were some links that we sent out that helped you out we’d love for you to share that with somebody else or only ask to our

62:51 somebody else or only ask to our listeners is just let somebody else know you found the topic interesting and had some value from this topic with that Tommy where else can you find the podcast you can find it anywhere it’s available Apple Spotify YouTube make sure to yeah apple Spotify YouTube If you want a question that you want us to talk about go to the power bi tips podcast finally join us live every Tuesday and Thursday Tommy’s a little bit Rusty there yeah it’s been a bit we gotta get you back into it anyways thank you all so much

63:22 into it anyways thank you all so much we’ll see you next time [Music] foreign

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