Why Quick Wins Are So Important – Ep. 317

This episode is a reality check on quick wins: why they matter for stakeholder trust and adoption, and how to deliver them without creating long-term technical debt.

News & Announcements

• Data Factory Spotlight: Semantic model refresh activity | Microsoft Fabric Blog | Microsoft Fabric — Overview  Data Factory empowers you to ingest, prepare and transform data across your data estate with a modern data integration experience. Whether you are a citizen or professional developer, Data Factory is…
• PowerBI.tips Podcast — Subscribe and listen to the Explicit Measures podcast episodes and related content.
• Power BI Theme Generator — Create and download Power BI report themes using the PowerBI.tips theme generator.

Main Discussion

The main theme is that quick wins aren’t “small work”—they’re strategic delivery that builds confidence and creates room for larger initiatives.

Key points from the conversation:

• Momentum + trust: early wins prove value and help stakeholders buy into the next phase of the roadmap.
• Choosing the right win: pick something visible and valuable, but avoid a shortcut that you’ll have to rebuild later.
• Iterate in public: show progress (demos), get feedback, and keep scope tight so you can actually ship.
• Avoiding tech-debt traps: quick doesn’t mean sloppy—keep the semantic model and governance in mind even for small deliverables.
• Use wins to fund the bigger work: once you’ve earned trust, it becomes easier to get time for foundational improvements.

Looking Forward

Identify one high-impact deliverable you can ship in 1–2 weeks, demo it, then use the feedback to shape the next milestone on the longer roadmap.

What changes are you seeing in your organization around this topic? Share your thoughts and we may cover them in a future episode.

Episode Transcript

0:34 good morning and welcome back to the explicit measures podcast with Tommy Seth and Seth and Mike good morning everybody good morning good morning gentlemen and nowy Tuesday it’s that was a good one that was a good one some someday maybe it’s not going to be so good yeah maybe some there’ll be a little trepidation with one of those PHR recording that’s coming up never missed one yet we have not missed one yet yet all right jumping in today for our a couple introductions but before we go to

1:05 couple introductions but before we go to that let’s just quickly talk about what our main topic is going to be today main topic today is going to be around talking or delivering what those quick wins are what does a quick win mean when you start a project with PBI what would Define a quick win and why is this impactful why do we care about doing these things initially in the roll out of powerbi and we’ll talk about our our observations around why that may be a good thing or what we’ve seen and how this helps communicate this story of powerb powerb organization with that let’s jump into the news I feel like I really need like

1:35 the news I feel like I really need like a little audio bite for some news stuff like like that yeah that yeah like radio that’s like more of a radio show if we were are we not really a radio show though really yeah small steps who knows someone podcasts are the new radio show aren’t they I would agree it’s say that I like that I’m totally down from doing a 4 to7 powerbi in the morning oh oh boy Whoa

2:06 powerbi in the morning oh oh boy Whoa you’re never going to want to sleep again are you you just you just want to punish yourself all the time with you guys it’s never punishment it’s a reward oh every moment around South I feel like I’m getting [Applause] [Laughter] punished feel like I did something wrong wow that’s like that’s a good that’s a good point Mich [Laughter] the Seth’s got good Seth’s got really good ideas I always feel like I’m like oh man he thought about things way better than I did so I’m wrong again so not true we we did we were

2:39 again so not true we we did we were recording yesterday I’m totally this is totally in justest I’m totally teasing Seth Seth doesn’t make me feel like I’m a bad stepchild my mother-in-law is in town the amount of laughing we were doing yesterday I came up I’m like all the laughter you heard all genuine genuine thing good just like just so I feel like Life’s Too Short not to laugh and have some enjoyment with things there’s isn’t there some like there’s some like endorphins release when you laugh and things it just makes things better yeah but you can’t force it there’s a very natural thing here where thank goodness how many other people can you really laugh with

3:09 other people can you really laugh with powerbi I don’t know I really don’t know that number how many data jokes can you really get your hands around not that chat GPT about 37 thank you chat GPT scouring the internet for funny jokes yeah awesome oh so let’s jump into a couple of our main news items here so one of the news items that we saw just come out recently is the mic this is in the description below I will also throw the link here as well into the chat there is now a data Factory

3:39 the chat there is now a data Factory Spotlight that has just come out they’re trying to highlight a new feature here of data Factory a new activity has recently appeared and it’s the pipeline activity so you can now refresh your semantic models using the pipeline at the end of a a data loading process which this is it should have been there for a while but it it never to aure data Factory so this is a really good feature any comments from your guys’s perspective on using this or thinking this is a needed feature yeah I

4:10 thinking this is a needed feature yeah I thinking this is a needed feature yeah this was there’s a ton of mean this was there’s a ton of Articles out there about how to do this with power automate it’s already available in power automate to refresh the semantic model Yes again to your point this is one of those now it’s great thank goodness but it took it should have been there day one thing I me this is a big win in my opinion yeah I agree it’s one of those those what do they call them ease of life you ease of life no ease of use that’s thing better my life thank

4:40 use that’s thing better my life thank you yeah obviously it’s your you can use apis and you can refresh from AF right now nice that they’re adding it in the fabric ecosystem but yeah ex a little task that let you easily do something is always better than having to figure out the configurations and set it up and have have all the taxs right like weit wait weight on completion right so so that’s one yeah that’s one where that that’s

5:11 one yeah that’s one where that that’s nice because you can fire off like yep the refresh completed versus just what it what it by nature is right now where you’re just like yeah go go run it and then I’m moving on through the ADF pipe so if it fails for any reason it’s harder to track that but yeah in this way it’s easy to see so there’s actually two API calls that actually need to be made to make this work properly because we’ve built some more elaborate call wait response because the the refresh activity is actually an asynchronous response meaning send it

5:42 asynchronous response meaning send it and then it it it just gets kicked off there’s nothing that comes back and says oh it’s complete or doesn’t leave the refresh open because that port or that call could be open for hours at a time your refresh could take a long time so this one I believe is click off the refresh and will there’s another API call that says okay now that I’ve started the refresh what’s the refresh ID keep calling that every so often until it’s completed now there’s probably something smart behind the scenes but the idea here is that you’re able to then wait until that

6:12 you’re able to then wait until that refresh is complete which makes a ton more sense what we would do previously there’s two ways you solve this previously either you have a whole bunch of other actions like three or four calls get a toen make a call make the web call wait and continually calling something over and over again until it like returns back success or failure or you kick it off and just move on or you go into the service and just say okay my data loaded should be done by about you data loaded should be done by about 7 a. and you just fat know 7 a. and you just fat finger in okay well we’ll just give it an hour to rest and then we’ll kick off

6:43 an hour to rest and then we’ll kick off the refresh work by you just schedule it independently which can come with all kinds of problems and that’s yeah that’s the significant part is probably the waiting till success because in power automate you can get the success signal but it doesn’t wait so you have to do a lot of looping to actually check and that was the only API I feel like a lot of apis are just a user interface waiting to happen that’s what a web app is built on top of though you’re right that’s why you build a web application because all

7:14 you build a web application because all the web application just sits on top of apis that talk to something else in the back ends yeah that’s that’s what they’re there for anyways good new feature I believe this is from Mark chromer no Alex Powers even better even better better I hope Alex is out there listening to this one because we’re talking about your feature Alex and you wrote a good blog article on it so we’re very pleased around that one all right moving on let’s jump over to another topic that we thought was relevant here there is another announcement here

7:44 there is another announcement here for the autom ml is beginning to be deprecated Tommy give us a little bit more details on this one I think you had some topic items around this particular area when Microsoft giveth Microsoft taketh away so I’m not sure if they really gave us the beginning I don’t know maybe maybea something no one used so in case you didn’t know which I’m actually a surprise always when people don’t know a feature existed in data flows gen one was actually the ability on an existing data flow to run an auto

8:15 on an existing data flow to run an auto machine learning model they were about five models I think at at one point and if you wanted to know more well too late it’s gone it’s now officially deprecated but it was a cool it was a pretty neat feature but obviously not a ton of use it’s gone it’s not available in another in another Tooling in a data flow they didn’t move it they simply have removed the ability to take an existing data flow or query and running Auto ml model across it

8:48 and running Auto ml model across it now I I I don’t so let’s just be clear around some of this stuff I think this is another one of these like hey we weren’t getting a lot of usage on it originally people were probably just trying it and honestly I’ve tried it a couple times and it was a very clunky experience it just didn’t really smoothly execute the way I thought it should and I think it also uses i’ have to double check on this one I don’t know don’t quote me on this one but I believe it uses some azure compute in order to do its job well you don’t need Azure you don’t need any license key or subscription to do it for

9:19 license key or subscription to do it for this one autoo I thought it was there was a license something that came from Azure side to make you do something on a desktop the cognitive load oh maybe that’s what I’m thinking of okay yeah but regardless though like okay cool we had autom ml but I believe autom ml is now already in notebooks so the data science yeah so you’re getting it in fabric now but that may maybe if we look at this a little differently instead of saying maybe there was no usage maybe now that there’s a more

9:51 usage maybe now that there’s a more complete solution in fabric there it’s no longer needed that’s that’s where I was weing where it is for a better experience to pay more money for C multiple I didn’t I didn’t say it who said that I didn’t say didn’t say that you do you really you should

10:12 that you do you really you should be paying money for things you want to use like it’s not none of this stuff’s free like someone you should be and I and I did I I say that in just like it’s it’s a good feature if you find some value from it this is this is also where I’m thinking like autom ml is a really interesting feature I need to spend more time with it personally and again I like the idea of it I think it’s going to be a great move but if I think about like the growup story I keep saying the growup story but it’s the growup story of powerbi this is the stuff that we’re going to want to be bringing to our I’m going to say it like this business users turned data

10:42 this business users turned data Engineers turned lightweight data scientists in the space there’s a lot of lwh hanging fruit and value in your data that you could probably throw through autom ML and get some correlation between some things a customer turn analysis some linear regression stuff I me there’s probably some things you could throw at the automl that it can figure out stuff for your business and it’s pretty straightforward to use so I think that’s really helpful because we’re now exposing this really neat technology to people who could actually have find real benefit from it because if the business

11:13 benefit from it because if the business understands the need tie that into using this autom ml in inside notebook so I think it’s a really great opportunity here it’s the genius too I think of fact without pandering but honestly The Genius of how Fabrics really situated in terms of it’s a centralized product but I think without the Clutter because again in order to use the previous feature in gen one you had to do it on an existing data flow a data flow that you’re probably using not for ML or not the intended purpose what was occurring was you had to then create

11:43 occurring was you had to then create another query and then you’re cluttering that existing data flow now we already have a space for that and I think to your point Seth we have a dedicated space for data science for these types of features we’re not like oh it’s ml it’s data science too it’s like no no now we actually have that dedicated space so it it does make a lot of sense to actually have that and it with the data science and fabric it doesn’t have to be a data flow yeah and I’m throwing this in also in the chat when into as well so another opportunity that I think makes sense here is I like your point

12:14 makes sense here is I like your point there Tommy it doesn’t have to be stuck in data flows and to be maybe clear here maybe data flows weren’t the most efficient way to run autom ml either right so if I look at like when I look at comparisons I’ve seen some blog posts come out about this if I write a pipeline if I run a data flow and I run a notebook they all have different amounts of compute usage that do different consumptions based on the plat the the compute you’re using spark seems to be pretty dogon efficient compared to comparatively to the other on so some teams I have seen on blog

12:46 on so some teams I have seen on blog articles have made the decision to say look we are only going to write data Engineering in notebooks because it is so much more efficient from a cuu consumption standpoint meaning I can do more with notebooks I can do more more data engineering with this with less compute than I could if I was using pipelines or data flows is that the origin of Jupiter notebooks was for data science I believe so oh I don’t know the whole history of everything there I think so I think it came out of spark

13:17 think so I think it came out of spark and this whole experience around spark I and this whole experience around spark spark has been this really mean spark has been this really interesting I have a lot of data and I need to do something very fast and I need a lot of compute power but need memory so it spark is an evolution of Hadoop which is storage of lots of data on dis spark is storage of lots of data in memory and then once you had things in memory stuff could happen really fast and I think that’s where it leveraging the advantage of this stuff and and from there the use case maybe was more born around machine learning and ML and all kinds of other stuff yeah I think the

13:48 kinds of other stuff yeah I think the acceleration of that really came came out when you didn’t have to stay you out when you didn’t have to stay spend all day precons learning know spend all day precons learning about chocolate clouds whatever the new thing thing setting up your own environment all just became a service right yeah so did I it was a pain what’s what’s striking me and I don’t know why it’s the removal of the autom ml feature that is like giving me this aha moment but it almost to to Sidetrack slightly if you think about how the

14:20 slightly if you think about how the evolution of fabric right whether this was how it evolved I have no idea but it it strikes me by removing this feature that a at some point when Microsoft kept adding all of these additional features like data flows and then we’re going to add autom ML and all these things we need for our our powerbi solution right which is data and Reporting we’ve already got great ETL we’ve got the great semantic model we need all these other things

14:51 model we need all these other things that they were building new technologies into powerbi that they already had really well established products for and like I as I’m thinking about this I’m like did somebody just go why are we rebuilding everything let’s just consolidate all of our things the same way we did with powerbi right where what was the strength of powerbi right out of the gate and what gave us so much confidence in it it was power query and it was tabular models like the backend bones

15:21 tabular models like the backend bones were things that have been around for a a long time were wellestablished tools and it was really just the front end that needed some love and figuring out and thank goodness Miguel’s still giving it love and figuring it out it’s come a long way but at the same time the power of what we were able to do and the quick wins that we were able to provide were solid because of that like hardcore infrastructure that was there and now if you look at it Fabric’s the same thing it’s the same type of idea where hey

15:55 it’s the same type of idea where hey we’ve got these amazing tools let’s just bring them together into the seam of experience and everybody understands the tool sets and they’re very robust in their own ways so that all of a sudden you I I would expect we see more deprecated features of things that were built just specifically the prefer the powerbi service or for a particular use case because not everybody could plug into all these different services and now you can and now now the experience overall is going to be much better across that ecosystem as it knits

16:26 across that ecosystem as it knits together Tighter and Tighter one challenge that a lot of businesses face especially so to your point Seth I really want to hang on that note just a little bit longer one of the major challenges when going from Azure to powerbi and back and forth and there’s a lot of configuration things and especially when we’re talking like virtual networks and making sure everything talks together and it’s all secure a lot of that is now just being handled in the powerbi ecosystem so before everything that we’re talking about now already existed in either synaps blob storage a

16:58 existed in either synaps blob storage a your data Factory a lot of the other pieces were already there but they weren’t as quite tightly as coupled together as we’re seeing inside Fabric and to me one of the things that I I’m finding very valuable right now is the amount of friction that is being reduced every single month by them building better features more Integrations like activities refresh pipeline great like that’s what I want that’s that’s one more piece of friction that you’ve removed away from me I’m like I’m more apt to use pipelines and notebooks now because I can easily move things around

17:28 because I can easily move things around wait till we get wait till we get pipelines that can send parameters into a data flow holy cow I’m really going to be looking forward to that one because that’s going to be exciting for me I why is that not already exist like it’s again it’s one of those little areas of like can I get a little bit more friction removed every single month and now this is what we said I think back in like November last year wait six months eight months you’re going to have a very compelling story because they’re continually refining and sanding the idea so it’s getting much easier to use I have to change my

17:58 easier to use I have to change my analogy for for the last nine years I’ve said that I believe that powerbi is the iPod for data the way that the iPod transformed the music industry well if that’s the case then Fabric’s probably the iPhone for communication in terms of like really what it’s done I think that that friction part can’t be understated and what friction I have Tommy you keep bringing Apple into this conversation it has nothing to do fantastic products yeah it’s like the Windows phone how wait The Zo

18:29 Windows phone how wait The Zo I’m not bringing up Zoom it’s like when they bought no key no that’s not a good idea either I’m talking about two re maybe we should stay away from the phone analogies okay yeah yeah for for Micosoft Micosoft you guys are doing great haven’t haven’t bowed so well for Microsoft at this point maybe we’ll get a flipping phone that will have power by the way have you seen anyone sorry totally random side phones have you seen anyone using one of those phones that like literally fold in half where you like open it up and it’s like

18:59 where you like open it up and it’s like a bigger screen because it like opens on a commercial that’s what I’ve seen I’ve seen I’ve never ever seen anyone like does anyone ever sell these things I don’t know where they go anyways do I want with that I feel like if I see anyone doing that I’m like I’m not going to talk to that person well I feel like there was a Windows phone that was supposed to like fold in half or fold open and had a bigger screen it was like this now you can have your full Outlook like as if I couldn’t use it before my phone previously it’s here’s more screen to clutter up with buttons that I don’t understand Inside Out look anyways moving on bring back the keyboard

19:30 keyboard for that was a very large Rabbit Trail let’s move on all right anyways apparently I got up earlier up today and my coffee is kicking in let’s jump into our main topic for today so main topic for today there’s not actually an article we’re just going to just generally discuss things let’s talk about why quick wins are so important and maybe let’s we probably need to Define when we say what is a quick win what does that mean so Tommy give us a little kickoff here what does a quick win mean to you and where we going with the topic today our the origin of this actually came from our implementation

20:00 actually came from our implementation series our 11p part series and one of the big things we talked about was there’s a lot of planning and prepping usually with powerbi projects whether you’re adoption implementation or just shifting gears in some space and I’ll Define quick wins as it’s the early loow hanging fruit that you can do that people can actually see a definite and

20:22 people can actually see a definite and manifested impact of whatever the Project’s going to be it’s something they can touch something they can see something they can interact with and I think our conversation that we previously had was man we should really focus on these shouldn’t we and I think that’s what I’ll start with in terms of they are integral I have thousands of examples but let me start there and see what you guys think when your description includes manifested impact wow that was off that’s

20:52 impact wow that was off that’s impressive I Google that I have to Google those entire words together like what does that even mean I think unfortunately I’m on cup four created your own impact yeah you manifest the impact that you want to have manifest manifestation is like I I want it to happen there for it happen will it into existence so willing the impact into into existence that’s not bad I feel pretty I’m pretty i’mna I’m gonna sign off now nice job that’s a t-shirt yep yep that’s a

21:25 t-shirt that’s a little long yeah I think I think the T-shirt should be I manifest impact yeah it’s a lot of ink it’s a lot of ink but I think it’s worth it okay I’ll buy it all right going to a store near you manifesting impact so quick winds so quick winds so I I have a lot of thoughts on quick win so I I like what you’re you’re defining there I think for me defining a quick win is really around taking a business problem and boiling

21:55 taking a business problem and boiling it down or distilling it down into something that we can and then solve right so let’s to me a quick win would be hey we have this process people are being thrown at some data stuff it takes us two hours 3 hours you stuff it takes us two hours 3 hours half a day to compute the know half a day to compute the information let’s build a processor around that and shorten that down to like a refresh every night and in the morning I show up and the data is ready for me like so it’s it’s gone from like something that took a a long time to produce and I’m now producing like a an

22:27 produce and I’m now producing like a an a regular output of that same information I’ll give you a blatant example from one of the Consulting clients I went through they had a a manufact they distributor of stuff and so they weren’t they weren’t a huge company but what they were able to do is they were doing a lot of things inside Excel their Excel files were getting slower there’s a lot of big things we’re pulling a lot of things from different data sources but they had pretty much a central data Store where all the transaction data was coming from so what we were able to do is we were able to

22:58 we were able to do is we were able to build an entire powerbi data model that housed all of their transactions for their entire company’s history into one data model so it was incredibly impactful because instead of trying to Define in the Excel document every single cell or format or visual or Charter like having to all the data come in because again that the file would get very bloated by a by using the Coler store by able to Cur pressing the data we were able to shove all the comy data into one large semantic model and from there we had n number of

23:29 model and from there we had n number of peoples hitting it accessing it trying to absorb that data and try to produce what they needed to impact their job so it was more of a a data access issue because it was a bottleneck one person made this Excel file and then that was shared without the company now we had a central data model which we could then distribute to multiple people produce some can reports but we’d let people discover and do some self-discovery on top of it now this was maybe a a weird use case CU not every company has all their transactional data in one data set but but that was hugely

23:59 in one data set but but that was hugely impactful for them because that process had traditionally been fractured across many different files and it was on SharePoint it was on drives and so now we have this portal that we can go to to find the information so I feel to me that is a good definition of like a quick win right something was hard we’ve made it simpler we give you a new process that’s actually more efficient than the old one so that’s how I would Define it anything Seth for you or that you would want to Define differently well I think that’s that’s an example of a quick win for sure right creating creating

24:29 creating efficiencies and and even on a simplified version of that right where folks are just in Excel doing copy and paste doing some formulas like how how many times have you walked in where you many times have you walked in where folks aren’t using power quy in know folks aren’t using power quy in Excel which is also an option for creating an efficiency right start start using this thing that will automate all the things that you do every time and this this is what virtuous waste right in an organization where people are literally just like yep I I have to go

25:00 literally just like yep I I have to go run this report I extract the data I put the data in in my Excel spreadsheet I review and I have to like make sure the formulas are right and I’m copying this into the next Tab and the next Tab and the next tab in six or eight hours or multiple days later you get a report so this is an example of like hey what what parts of that can we peel out and automate right away and some of those are larger projects but like what’s the quick win Time Savings right in ter terms of is it a quick win if

25:30 terms of is it a quick win if you can spend two weeks and save you you can spend two weeks and save overall a month of time yeah I know overall a month of time yeah I think some other quick win exam like I examples we could probably talk about are like providing insights that otherwise are are difficult for the organization to consolidate together or just in general generating data sets that otherwise are inaccessible right as a good quick win so yeah the one thing I

26:00 a good quick win so yeah the one thing I I don’t think I’m disagreeing with but for me either the most impactful quick wins or really how I would really Define it it’s always an impact towards a goal a bigger goal it’s a small solution towards a bigger problem I don’t see quick wins really existing siloed in terms of we’re just randomly doing a quick win it’s we’re going to work on this project whether it’s adoption or adopting powerbi and what along that Journey can we display or show that’s going to have an immediate impact

26:32 going to have an immediate impact towards the actual intended audience and to me it always has to be on that Journey towards whatever the bigger problem or bigger project is at least for to me to see the the most net impact yeah I would agree with that I impact yeah I would agree with that but you’re you’re also driving I mean but you’re you’re also driving I mean but you’re you’re also driving a lot of this convers we’re talking mean a lot of this convers we’re talking about reporting and powerbi and what we can do within an organization but more often than not quick wins are discussed in the the realm of you’re just joining an organization you’re trying to like

27:05 organization you’re trying to like provide some value right out of the gate you want to show your value but in reality like we’re we have the opportunity to do that a lot within the organization right because you’re you’re working with potentially many different teams and the value of the quick win I think goes beyond just the delivery of something because the outcome is hopefully a visible success for the organization right or for somebody so like ultimately what is that

27:36 somebody so like ultimately what is that doing to spur on like more powerbi or hey and I suppose this is even applicable to ramping up powerbi in the organization right because what does what do those activities do for those people those early successes it generates excitement right like holy crap you just saved me four hours you crap you just saved me four hours a week in my like a half a day a know a week in my like a half a day a week in just stuff I was doing and you

28:06 week in just stuff I was doing and you showed me how I can do that in the future or how I can improve the efficiency of my job or you just gave me the Insight I needed to go make this decision with confidence instead of every week being super stressed out and kind like giving my best guess but that’s the final answer and ultimately I think where this ticks in really big imp impactful things for an organization and this mindset of quick wins albeit I

28:36 this mindset of quick wins albeit I agree with you it’s not the the the stopping point is it increases the morale or has the potential to of the areas that you influence yeah there’s a song I would actually equate with quick wins and it’s the Willy Wonka song because to me it’s that like I knew we were gonna go chocolate and you will be yeah we’re doing the chocolate thing in a world of Pure Imagination and I think to me like when I think of quick wins it really is it’s it’s to your exact point and it’s what can we accelerate I

29:07 and it’s what can we accelerate I identify in any project that I’m doing Med what quick wins can we display in the upcoming few weeks even if it’s a longer project because I think there’s I think you said the magic word said it’s the morale it’s people getting that excitement out there and you have to do that if you want people on board with attention spans with we’re spending money how long is this project going to take because a lot of times our other conversations there’s always complications that will arise and they will arise what can we do to show what

29:38 will arise what can we do to show what what can this be or let’s get a little taste of what are we actually working towards and to me I I consider quick wins as crucial as the final project well I don’t know if I’d yes I suppose for for for buyin right yeah I I like Andrew borer in the in the chat says quick wi should open your audience’s eyes to the potential of the tool and that is something we hav we didn’t we didn’t discuss yet right if you think about the

30:09 you think about the capabilities brought together in powerbi right especially for the business user and now and to an extension now fabric but it’s more the ecosystem I think or the next steps that that was mind-blowing like when you’re introducing these capabilities and it’s easy enough for business to be like wait a minute I just have to click this

30:32 a minute I just have to click this button I know where my Excel file is the data is in there and you just did a transformation and you’re modifi your wife had this like what I I can change data yes you can you can massively change every value in the for and and it blows people’s mind especially when you’re trying to develop a data culture or have people understand data to a better degree and how can manipulate it those those are the things that I think generate excitement

31:06 right I would agree with that one I think I like the I like the idea of excitement here because I think a lot of the excitement of this initial builds of projects carries on throughout the rest of the parb deployment right so there is some things that are just not fun when it comes to parbi there’s just some like long running we have data problems There’s issues we got to sniff out what the the challenge of things are but like you need some quick wins to like get people excited about yes this does make sense if we spend the hard time the effort the money to spend

31:36 hard time the effort the money to spend people to do this there is a brighter side on the other side of this that lets us do more than we did before I really do think that those quick wins are kind do think that those quick wins are you got to tee up a of you got to tee up a couple here or in the beginning of a project and then once people buy into yes this is valuable now you have the capability to say okay now we’re going to take on a hard project now we’re going to do some real data engineering we’re going to build some bigger things and one thing that I find a lot of is I don’t think I think a lot of organizations don’t understand how bad

32:06 organizations don’t understand how bad their data is until you’re able to see it like this is one of these things like you can’t really know how your powerbi tenant is being used until you actually start having monitoring in place to actually see what it’s doing a lot of people run their powerb tenant and think they know what’s going on but in reality they don’t there’s not a data backing up what they’re doing so where are those compute units being spent what are they being spent on is there a business unit that’s really abusing one of your workspaces with a lot of stuff in there we don’t know so until you start looking or monitoring what’s

32:36 start looking or monitoring what’s happening you don’t have any ability to push it forward that what that that’s making me think of a few good points but I think the biggest one is yeah these quick wins they’re not a demo or preview they’re something that’s actually usable tangible that can that be implemented or inte ated with the business today right it’s not we’re going to show you a demo now you can’t use it for another three months this is something that we can push out I had a transformed something that looked like a

33:07 transformed something that looked like a loss into a quick win we were working with a a client and they realized they had no definitions around any of their metrics therefore very difficult to create any type of reporting and we had to figure out where we had some frustration there was some like well what that that first idea Mike to in so many words to put to light that oh we have no data governance and therefore we’ve been doing everything with head knowledge where do we go from

33:37 with head knowledge where do we go from here and how do we actually transform that to hey let’s actually create one of our quick ones was a process we put in place not necessarily the report just something to say into light like you want to scale this you don’t want to do 15 hours of excel I’m not showing a power query I’m saying do you have a definition of your kpis and where do we centralize that and to them that was a huge quick win or it was very enlightening it wasn’t a product it wasn’t a technology but it was something that they immediately integrated and

34:09 that they immediately integrated and adopted what do do you guys do you guys find that well let me let me let me pose this in a different way okay I’ve found that over time here I liked it better the other way you were going to lead us you were going to Le I knowa there was no the first way there there was no trap there was no trap this is I no this is the thing you like think of the answer you’re like I

34:39 like think of the answer you’re like I know what the answer is I’m GNA ask them a question to see if their answer alignance with what I’m thinking sorry I didn’t mean to interrupt your question this is this is not one of those times so he says I love it I I guess do you feel the same because recently I’ve been thinking about about what what are the impacts myself or the business intelligence team can make within an organization a lot of time we talk we talk about data we talk about reporting because these are the key cornerstones of of what we do but to

35:11 cornerstones of of what we do but to Tommy’s point I found that in a in so many areas I don’t know if it’s the data thing or being keyed into the business and solving some of the problems through reporting that a lot of a lot of the value my team is bringing and myself is in seeing deficiencies in process oh yeah and I don’t by Nature because of like all of these things together but it doesn’t matter whether or not it’s

35:42 doesn’t matter whether or not it’s specific to like me going and building something it’s anything it’s it’s wh why are we doing that do we understand the the time wasted when we’re making that decision or do we understand like where we’re just shifting responsibilities from one part of the organization to the other and and many people don’t think in that in those terms so like I often find myself probably annoying people way out of my my league going well what was the basis for that like why would we do that

36:12 basis for that like why would we do that what this is that process looks like this if we kept it this way it would be this and that would be much more simple for the organization to do it like you I do this all the time and I wonder if it’s a bu product and you guys do that as well or if it’s just I’m a oh no I’ll double down with you feel like it’s almost like cheating to get quick wins that way because yeah I’m completely on on line with you and I think the same way where it’s like oh did that man you how how how long does it take to do that they go oh this like we could do that in X

36:42 this like we could do that in X Y and Z it’s almost cheating in terms of quick wins because it’s so easy for us in terms of I think having the business and the technical side to go we can solve this in X Y and Z in a week and people to people blows their mind that that’s possible yeah us and that’s your that’s the technical knowhow that you have like what what I’m suggesting is a little bit yes it applies to Quick wins but I I was making applications outside of quick win okay honestly I think if

37:14 of quick win okay honestly I think if you do those if you do those quick little and I don’t mean to use the word quick but if you’re finding those deficiencies or you’re finding those those slogs in the in the organization and process to me those equate exactly to a quick WI to be someone that’s usually not something that’s going to take you three months that you find it’s something that you immediately know the answer to when you see those deficiencies and how to solve it that to me it almost equates so quick when I I know exactly what you’re saying but tell me the difference

37:45 but tell me the difference in all actuality and and this is completely un unended which the audience will never believe but that example I think also highlights one of the most important things about a quick win it and what separates it from Just identifying a process breakdown or a better way to do things is a successful quick win is a collective quick win your your working with somebody and solving

38:15 your working with somebody and solving somebody’s problem multiple Solutions are being solved and they want you they want you want you to the other in the other scenario it’s like yeah great you could have a quick win you could solve it with your stuff but if it’s not going to get used or adopted or nobody wants to use it then it’s it’s not a quick win because the quick win is a is a visible success to the organization right yes or a people and that Collective part I think is is really key before you move on I want to just answer your question one more

38:45 to just answer your question one more time because I I really liked your point there and I think I think there’s a really interesting note here around okay when you have a more integrated solution other challenges present themselves as potential like opportunities present themselves as ways to solve things right so you were saying like hey why are we doing these things when we start talking about like the powerbi ecosystem as a integrated solution where I start with data and I use a pipeline and I

39:15 with data and I use a pipeline and I copy it down and I do notebooks and all these things because it’s all in one bucket you can see where the friction lies in a process so I I think Integrated Solutions potentially expose weaknesses in our process and I think you’re asking the right questions here around these quick wins and pushing back a little bit because if you don’t know there’s an integrated solution like I’ve seen this happen in other places you buy a tool online and the tool does like 80% of what you want so you have to go buy a second tool or build a process

39:46 go buy a second tool or build a process to meet that Gap to what you actually need the data to do nothing wrong with that it’s just now a more complicated process so I think every time there’s this there’s a there’s a I don’t know it’s a power automate thing or some kind it’s a power automate thing or some power AO where it’s like it’s called of power AO where it’s like it’s called process is it process mapping or process oh mining process mining is what it’s called maybe yes I know exactly what you mean what I’m talking about so there’s this concept of like things are happening inside a process but what does that process how do you mine that process out and and can you

40:17 mine that process out and and can you take the holistic step back and say okay what are we trying to accomplish with this I think you’re right asking the right question Seth the value to back to the business is why are we doing what we’re doing that should continually be a question and if the answer of why we’re doing this is a legit reason cool we move on the legit reason get happens we’re we’re fine with it everything moves forward we’re good to go but if it’s if we can’t answer that question correctly it’s not a quick win we’re

40:44 correctly it’s not a quick win we’re just adding process to add process and we might even understand what that process means anyways I just I thought that was a really good point in really good observation you had there yeah I want to touch on one real I think integral part of a quick win is for whom right if if you’re like hey we reduced the number of tables in our database from 500 to 400 the stakeholder doesn’t care they’re going to go cool but I think the the audience or the intended target of that quick win is really going to be a make or break to me because you can do a you can do a thousand quick

41:14 can do a you can do a thousand quick runs around the technicalities and you runs around the technicalities and for your data scientists or the know for your data scientists or the data engineers and solve a lot of problems but to me I think when you focus on where should we or what quick win should we do where should we focus on finding them find them where the audience is a stakeholder find them where the audience is someone who is a decision maker or at least that they may not be directly impacted it’s not necessarily going to be their process but it’s something that impacts their team or their department so at the end

41:44 team or their department so at the end of the quarter you can say hey here’s what bi did here’s what we did or here’s what I did we worked on this this and this and they can directly see where that impact is because yeah you can have a ton of quick wins but audience is so important here in terms of who is impacted or who sees the impact more importantly yeah and I think this is where it dovetails into a different part of the conversation where I’m I’m a huge okr guy or gsms like if your organiz if

42:14 okr guy or gsms like if your organiz if you don’t know where your organization is going you don’t know how to make the big wins right and I think quick wins are valuable as long as you have a clear direction of why you’re implementing it right and that could be many various things if if there’s an organizational wide effort to drive efficiencies in the business like it could very well be that you’re just hopping around doing efficiency things but that’s significantly different than hopping around doing efficiency things because you think that adds value to the

42:44 you think that adds value to the business does it yes but is it recognized or is it an initiative or is it is there something else that you should be should be or is there something else that you’re driving towards as as opposed to it just being busy work or ultimately somebody says hey man I heard you do this thing come in spend a week and you’re like great how much time did I save you five minutes right right like well maybe that wasn’t time time well spent yeah and I think I think clear goals right at a

43:18 think I think clear goals right at a higher level allow us to start solving these problems and quick wins are part of that path they shouldn’t be the end goal in and of themselves I don’t think because whenever I’m engaging with the business I’m looking for how I can provide value right like e sooner right and that’s the quick win but that’s a stepping stone for me and the next the follow on are in to jur world or whatever stories right the additional

43:48 or whatever stories right the additional work that has to be done because typically typically you’re moving in a direction that there’s value that you’re adding to the business and either it’s that quick win has deficiencies right that you want to solve permanently or you’re solving a problem that you could solve for The Wider Wider organization by building it into a data model or the next steps of evolution of a repeatable artifact for the organization to reuse in a much

44:19 the organization to reuse in a much quicker fashion and that’s where I think it extends past that and having that Vision past just this little quick win is really important because the difference between a small Pro there is a difference in my mind between a very small project that is helpful versus quick win terminology because in my mind a quick win is the first step in a larger effort so if I’m if I’m picking up what you’re putting down here you would you’re basically saying too that

44:49 would you’re basically saying too that anytime you’re doing a quick win you’re communicating to the business we’re doing this quick win because of Project X YZ or because of initiative XYZ they don’t exist is that what I’m here okay absolutely and that can be driven by the business the business can say hey I want this really big thing you’re like okay well you don’t understand what you’re asking for because that’s like a five six seven week project right so what I’m going to do is I’m going to like figure out how do I give you a good value and and keep you on for

45:22 you a good value and and keep you on for the hook which is like and I think the quick win is drives the excitement you’re solving some problems but it also it also resonates more in the story of hey we’re gonna we’re going to produce this for you and then you give them it resonates or makes sense to the business that you’re you’re providing value in time frames that’s acceptable to them because they don’t understand why it’s going to take seven weeks right that so they’re they’re

45:52 weeks right that so they’re they’re always like typically you have to prove the value right if you’re going to do this you’re going to spend all this time and somehow what I won’t I won’t go go too off the rabit trail but it’s like if you’re it helps with the story of we’re going to build you a full complete solution but you’re going to have something in your hands that you can analyze that you can get value of that you can test in two weeks then we’re going to increment and we’re going to give you these these features right in four weeks and you’re you’re building that story of like the complete solution

46:23 that story of like the complete solution but you’re still giving them business value right out of the gate because like we have to remember business doesn’t move at the speed of development and Technology right they need answers fast all the time and you could have an argument about whether or not that’s a planning problem or or you have customer concerns you have you have to solve this thing and you need an answer in two days and that’s where this rapid cycle of fire drills you can find yourself in if you don’t like you have

46:55 yourself in if you don’t like you have to address those right you have to those problems but you have to also be thinking about the future so you’re removing those those problems and distractions and giving business the insights and the data that they need so those fire drills don’t hit your front door I I totally agree with these things I I really am aligning with my observations are very similar to Seth to what you’re saying like it’s these things happen and this is this is

47:25 things happen and this is this is a in my mind here I’m going and I’m I’m thinking about how do I transition away from Quick wins into more strategic longer term positions so yes quick wins are good initially getting some people on board getting an apartment leveraged and figuring out they like what they’re doing here but then there’s a TR to me there’s like a transition that needs to occur between okay we’ve had some like for example another good example I think might be a quick win is we built a model someone did it not really efficient not performant things are starting to fail right a quick win for that team would be come in and help

47:56 for that team would be come in and help them op optimize the model give them some better horsepower there so that way they can load more data it’s faster it’s incremental refresh teach the team something new you’ve created a quick win their data now is refreshing okay now let’s talk about what does that what knowledge did we gain from that quick win and what can we do to either repeat it with other teams or provide it for documentation back to the broad organization and now we start chipping away with these bigger initiatives which is everyone in the company Needs A Better Effort around data culture

48:26 Better Effort around data culture everyone in the company need some more capabilities around what’s going on here so I think there’s in my mind is I’m trying to transition away from a couple of those quick wins and then turning into more of a long-term support okay let’s establish a center of excellence let’s establish a Community Practice let’s start really taking these these processes that we have found as good best practices and quick wins turn them into company policies and then start leveraging them to really impact the business moving forward I think that’s the heart of it this is what I

48:56 that’s the heart of it this is what I love is because I think without the longer scope or followup of a quick win it’s just a fix we’re really talking about either it’s a fix or it’s a quick win and I think one thing as I’m hearing both of you I feel like what could really derail or honestly harm what you’re trying to do or what you’ve just achieved if that quick win has no followup if that quick win has no additional communication to your point on the longer term pitcher then you’re just doing fixes then you’re just solving fires to the business you’re not

49:27 solving fires to the business you’re not actually working on something that’s going to be a bigger impact so yeah I’m really seeing here this quick win as to your point it’s one of the initial stages of a project but it has to be one of the initial stages of some type of project or initiative and to me it’s not just doing it I to me I’m I’m I don’t want to focus here but I want to just really iterate that you have to communicate this you have to say why you’re doing this to the stakeholders and what L what little paintbrush does

49:59 and what L what little paintbrush does this play in the larger picture or else you’re not going to get the buy into to the business you’re just doing a fix you’re just doing your job not getting so and I think we did this quick win hey can we get more money can we get more resources or because of this we could do so much more and really utilizing the quick wi and and that’s the key and and that’s where I think to your point you you need to do Opera operational things things that keep the business running and those are sometimes

50:30 business running and those are sometimes the the fire drills or data access but there there’s a lot in that nugget of things that you could extrapolate and solve longer term I I think just just for examples sake when I I I I want to walk through a specific scenario so because a quick win as I’ve been saying is a a part of a process so to walk

50:53 is a a part of a process so to walk people through if I if you don’t if you’re not thinking in those terms an example of like how I would think about a report build and a good example of like a quick win it’s a brand new area brand new business we don’t have access to the data quite yet we’ve got to figure out what that ETL pattern looks like yes this belongs in our model like this Central data Mark Etc how would I produce a quick win a quick win to me would be okay I’m going to look in totality of

51:23 okay I’m going to look in totality of the things we want to build they want a report that has four pages we go through the requirements Gathering we figure out all the things that that they need from there we determine okay can we pull out two of these Pages because a lot of this data is is very straightforward we’re just doing Simple sums EGS Etc a quick win is let’s use this opportunity to directly connect with powerbi we’re going to rough out the ETL and power query right figure that out with the business what are all the transforms

51:53 business what are all the transforms we’re going to connect to the data sources this is our this is our ongoing effort of discovery of data right working with the business to validate the data outputs and we’re going to give them two pages and we’re going to accomplish that in two weeks right something to that effect yep but that’s not where I stop and the problem is is like a lot of places do stop because we connected the data we got the transforms and we gave the business when business intelligence teams engage here which is typically like what we’re talking about the next step is how do I

52:25 talking about the next step is how do I refine and pull that Ed ETL into our Enterprise systems like I need to connect this to AER data Factory I’m going to take the learnings that I had from my quick win and apply them to my pipeline which now I have my the same things on the output in the same processing times and now I can develop report page three and four this is now four or five weeks in right so the business now has everything that they need to need and now I have like a tech de item which is does this data

52:56 tech de item which is does this data belong in my data Mark for this area of the business yes it does I need to build this into that make all these adjustments on the back end to make sure that I’m in like pulling this data in and then I can shift the report front end over into pulling from the data Mark and now I have my full complete solution where this report is now just part of the ecosystem but the difference between me going I need 8 weeks to finish that project because it’s got to come out of the data mark because we built this for your business

53:27 because we built this for your business area is the quick win correct gave I gave the business value and then I gave them more value and then behind the scenes I’m doing other stuff that I’m going to bake into other estimates right hey yep somebody who’s got 40 hours of time I’m only going to I’m only going to book out 34 or 30 because 10 hours in the next Sprints are to solve this other problem because now I’ve got that data in my data Mark and now next time somebody body else from the business

53:57 somebody body else from the business goes hey can you add pages five and six because I really want that yes boom yep absolutely you can it’s already pulled in here’s the here’s the data it’s part of my data Mark we’ve already got that all together it’s Stow ball and that’s that’s the value right because but I’m thinking long term about the infrastructure how these things are pieces so is quick WIS applicable in this scenario all the time no I’m thinking of it from like business intelligence team engaging the business but I think what my final point would be is like you there’s always value

54:29 is like you there’s always value in Opportunities where a project is going to take a really long time to look for these streamlined ways in which to provide visible progress progress yeah and successes age along the Journey of a project and that’s where you’re going to get byy in with big huge projects of power VI implementation or just smaller areas where you’re building out a report is looking for these opportunities to incrementally add value

54:59 opportunities to incrementally add value and then behind the scenes you don’t really need to talk about the tech that stuff like it’s just your building for the future of the organization or you’re building for the future of reusable things within your business unit and and that’s work that just tacks in on a on a different work stream I like that a lot that’s a really interesting I I I think I agree with a lot of that Seth and I definitely one thing I would say that works well for I think organizations is especially after you’ve gotten through a couple quick wins with powerbi really starting to focus on

55:30 powerbi really starting to focus on centralizing that so what you’re talking about Seth is there’s a there’s a need here around you have some quick wins but you’re talking about longer term bigger initiatives more strategic moves of data and things longer term I really think that’s very impactful but that comes out of that what I would call the governing body of that Center of Excellence like where okay Seth you’re the one taking the initiative you’re you’re doing these things from Central bi they’re really does need to be some substantial conversation around what is our

56:00 conversation around what is our long-term objectives how does these quick wins apply towards those bigger needs of the organization and I think strategically if nothing else you should be thinking about like a quarterly plan of like hey this quarter we’re going to try and do X and so that way you can take these bigger initiatives and Define them as okay in the beginning of the quarter we’re going to do a couple quick wins here’s one or two quick wins we’re going to try and do this quarter but then there’s also some longer running multiple quarter exercises we have to clean this back end we’re going to switch out a a CRM system

56:31 we’re going to switch out a a CRM system like there’s going to be bigger things that are occurring across the organization that needs to span multiple quarters so just giving some context to like here are the quick wins we’re going to produce now here are some things we’re going to push towards a bigger initiative and that comes out of that Center of Excellence I think really is impactful and it really helps organizations see the value shortterm but also more value long term no Mike I I am th% with you because you’re just talking out of the the big book of data governance right because you have the committee who’s saying what are our biggest problems or initiatives we need

57:02 biggest problems or initiatives we need to do then that puts together a task force yeah I and because I think the one thing I’ve seen with myself and I’ve seen with teams I’ve worked on where we worked on a lot of what I thought were great projects but the stakeholders the people who were who made the decisions didn’t necessarily see the impact so even though they were valuable to the business like how like how much do you get Buy in from the people ultimately going to spend the dough or provide the resources in an ideal world yeah you have the data

57:32 ideal world yeah you have the data governance team to say hey we really need work on X Y and Z or better consumption of our our data or it’s too low it’s too slow let’s put together this task force and that’s where the quick wins can originate from so I if you could have a team that can do that man you are setting yourself up for almost immediate success I like it so said you gave your final thoughts Tommy any final thoughts for you as you wrap here see the previous 15 seconds right okay good that was Tommy’s

58:02 right okay good that was Tommy’s final so I would I would Echo your final thoughts there Tommy I think this is a balance between delivering value now focus on quick wins today and then also incorpor that into a more strategic things moving forward and again I think this quick win scenario really plays very well if you look at the powerbi adoption Ro map so if you haven’t seen that if you need to go Google that one go Google the powerbi adoption road map really impactful and I have used it multiple times on multiple different companies and found great success with us this is Microsoft doing

58:33 success with us this is Microsoft doing this stuff for 20 years this is really smart people that they’re saying here are the here are the things you need to consider when you talk about this and so I think that’s very valuable it feels very overwhelming but just Implement a little bit identify where you’re at there’s Melissa coat did a great job and and Matthew roach did a great job writing that up saying in that quick wins wins those quick wins maybe level 100 level 200 type activities inside your organization just try and move up a level just try and identify where you’re

59:04 level just try and identify where you’re at where you’re weak where you’re strong and just trying to do a little bit better I just heard a speaker James Clear from Atomic habits was talking about be 1% better tomorrow than you were today and I can’t he was talking about it personally like if you’re going to lift weights you do 10 reps today do 11 tomorrow right just do a little bit more each day and then you the phrase that came out of that was you underestimate well sorry you overestimate how much you can do in a year you underestimate what how much you

59:34 year you underestimate what how much you can do in 10 years so there’s there’s an interesting balance there of if you just keep improving a little bit each time do a little bit better do a little bit more documentation do a little bit more each time you do it when you look back and it’s six months down the road you’re like wow we made a lot of progress by just doing a little bit better each time so anyways I think that’s the value of quick wins you’re saying our podcast and should be be an hour 10 yeah next time next next episode not this too long as it is awesome well that thank you all very

60:06 is awesome well that thank you all very much for listening we we appreciate your ears on the podcast I hope you found some value from learning about quick wins and how we see them hopefully you can Implement a couple quick wins in your organization as well and if you have some we’d love to hear about it chat us on Twitter let us know in LinkedIn if you hear about get us some comments going let us know what quick wins you have found and we’ll wrap it up here Tommy where else can you find the podcast you can find us in apple and Spotify wherever you at your podcast make sure to subscribe and leave a rating it helps us out a ton do you have a question an idea or a topic that you

60:36 a question an idea or a topic that you want us to talk about in a future episode head over to powerbi. com thought we wer G Miss there yeah almost we gear off return back we got it we got it recover recover got it thank you all very much and we’ll see you next

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