Insightly_Ep03_final
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[00:00:00]

Jordan Walker: Hello, Alyssa, welcome back.

Alyssa McGinn: Hello!

Jordan Walker: How are ya?

Alyssa McGinn: I'm doing good.

Jordan Walker: Good.

Alyssa McGinn: Which is a little rainy today, but besides that can't complain. March rains bring April flowers.

Jordan Walker: I think it's April flowers bring May flowers, but you know, global warming, things are shifting, like,

Alyssa McGinn: It's all changing.

Jordan Walker: Yeah I

want to start offf today's episode by giving a little shout out. Is that okay?

Alyssa McGinn: Go for it.

Jordan Walker: Well, for those who aren't aware, our local business journal recently hosted this [00:01:00] year's Innovation Awards. Those innovation awards really highlight companies in our region that are really making waves, not just driving innovation within their companies to, grow revenue and employee retention and, efficiency and things like that, but also developing tools and technologies that really benefit their consumers and we have two winners amongst us today. The first that I want to give a shout out to is our podcast partner, Brian Steele, with Forge Podcast Company. He was honored yesterday. Congratulations, Brian! And then, my beautiful co host Alyssa, and Infofluency was honored yesterday. Congratulations!

Alyssa McGinn: Thank you.

It was really awesome and a big privilege. I feel like for us to be among those honored and I will say, we were honored for innovating around revenue analytics, which is a lot of some of this stuff we're going to be talking about. So I feel like it's very fitting and we saw, a big need for revenue attribution and [00:02:00] customer based segmentation so we built an analytics tool that allows somewhat of a plug and play model for anyone's data to go in there to be able to have dashboards pretty much immediately without requiring any custom built from the ground up analytics to give people a, a jumping off point that is more attainable or easy start from.

So yeah, it was really awesome to be in that room.

Jordan Walker: Well, I think it was really cool because~ I, ~I feel like I've gotten to kind of see the evolution from the first launch of the revenue management dashboards to now and I know that's really how like our relationship really got developed is we started talking a little bit about like, okay, what do you do in data? What do you like? And then it was, can we demo? And I was mind blown because the thing that, and this is where a lot of our conversation started, is you have all of these different data points for revenue, for customer transactions, for product, but they're all in different areas, and maybe detached from the [00:03:00] financial aspect of the business as well, and I remember the first time that you walked me through those dashboards, very little context we were just kind of loosely talking about, okay, here's what it is capable of doing but then we immediately started launching into conversations about, well, here's what you could do with that. Here's how you could activate it and that, I feel like, was really that, ~like, ~spark moment for the two of us of, Oh my gosh, we should partner.

This is, one, a ton of fun, and two, highly beneficial, because it's not just about how can we, like, it's not just about measuring things, it's not just about bringing the data together so that you can view it, it's how are you going to use this to activate it moving forward and that, it's just really great that you guys were able to bring all of these, like, dashboards together and make it easy for companies to really leap into revenue management and seeing it from a different lens other than, okay, here's our transactional data over here, [00:04:00] here's what our customers look like over here.

Now it's mine through spreadsheets and spend hours pulling it all together to make some assumptions that might be old by the time you get to that point.

Alyssa McGinn: Yeah, and ~we~ we really did want to remove

barriers. We wanted to make it easier and we took a lot of what we had built for other clients and we were like, people keep asking for this. We should just put this together in a collection so that it's an easier place to start and you just kind of immediately move towards action and activating as opposed to some of what we'll talk about today, which is, well, I don't know what to measure or I don't know what metrics we should visualize or how we should visualize them or how we should look at them or how we should be able to filter them like, people get really caught up in a lot those questions and so our hope and what we've seen to be true so far is that this can just take you further, quicker.

Jordan Walker: yeah. And yeah, that's a great segue [00:05:00] to today's topic. One of the things that Alyssa and I really wanted to get into in this episode were, is more centered around what are the challenges with data in business and there are numerous, this episode will not cover all of them but we want to highlight a few that we tend to hear most frequently, at least at the start of a conversation and one that I hear a lot when I'm working with business development teams and marketing teams and sales teams is just the concept of we don't know what to measure.

We don't know what we should be looking at.

Do you get that a lot with your clients as well?

Alyssa McGinn: I would say we do some and then when we get into bigger companies a lot of times they are already measuring a lot and they just are kind of paralyzed and they don't know what to do with it.

Jordan Walker: I call that analysis paralysis.

We'll have a whole episode on that one later.

Alyssa McGinn: I think that is very real and a lot of times, they have a fully built out [00:06:00] CRM. They have a fully functioning accounting software with a whole team. They have even various other tools where they are, they're doing the things, they're capturing the data points.

But then I think it gets to a higher level issue of what matters. What are the KPIs? What does leadership care about? ~What, ~and I think a lot of that too can be organizational in the sense that what are our business objectives and how is that getting, dripped down into the whole company because

We could get all into that

but I think that's more what we see is not like, I think we hear sometimes what should we measure, but like.

Okay, we have

these systems, we've been tracking stuff in them for years. What do we

do?

Jordan Walker: That's actually the same kind of scenario that I bumped

into even

when I'm presented with the

question of what should we be measuring, we don't know what to measure.

A lot of times the data points are

already there. They're already housed

in some sort of system.

Even if we're just talking basic

Hey, I'm looking at just marketing programming at this point like, we [00:07:00] don't know what in our marketing works and doesn't work.

What should we be measuring? What matters? That sort of thing. The data is there, but it goes back to that kind of analysis paralysis of, okay, we have a lot of data points that we could be reporting on, but what is the most important?

And there are two thoughts that come up there for me and one, it's, the mentality that you just hit on of, well, what does leadership want to see?

And I'm not saying that that's the wrong perspective to have when you're trying to answer that question because we all have, leaders and stakeholders and whatnot that we need to be reporting to so that everybody understands, like, where are we heading? How are we performing? All of that kind of stuff but if we're purely basing our metrics around what does senior leadership team need to know. The problem that I have with that is that we're forgetting then how does that apply to the customers that we're serving and the business goals that we're trying to achieve and so, whenever I am approached [00:08:00] with that question, I'm usually starting off from the point of, okay, well, what are the tangible outcomes that the business wants to see in a particular time frame in the next year, next three years, whatever and then it becomes, okay, but what customers do you need in order to achieve those goals? We're all in business to serve customers. Without them, none of us are in business. Point blank, simple, pretty easy, right? If we are only looking at the key metric points that tell senior leadership, okay, we are moving the needle a little bit.

We're getting a return on our investment, things are working efficiently. That gives you operational. Are we doing our job?

It does not necessarily tell you, are you performing well for your customer? Are they growing with you in the ways that you want to grow? So even though that question can kind of bubble out into a lot of different areas, like to your point, usually there already are data points that are being captured.

It just boils down to [00:09:00] that mentality of what is it, what actually matters? And I always try to counsel clients, we got to go back to the goal and the customers that we're serving to reach that goal and then find the metrics that senior leadership needs to see.

Alyssa McGinn: Well, I want to delineate there because I feel like there's two problems at hand. One is that the people that are in the business development team or marketing or sales don't know what senior leadership's goals are, what the business overall objectives are. So that's one problem because there's super high level analytics and visualization that can be done at a high level.

So I think there's one problem when not everyone's on the same page, but I think there's another part of, a business development or marketing or sales team where they have general objectives to have high customer satisfaction or to cultivate strategy around the bigger objectives and there can still be analysis paralysis at that level, but then there's also can be other issues when

there isn't [00:10:00] higher business objectives being reached.

Jordan Walker: A lot of times when I'm seeing those kind of challenges collide. It's because our business objectives are not ~Excuse me, our business objectives are not ~aligned with the milestones that we have to achieve ~so I'm of that, ~I'm the kind of personality where I'm really great at planning long term and then breaking it down into milestones for other people.

Like, I can do it great for other people. When it's for my own life and my own business, I'm just like every other CEO out there, I want it now. I want immediate gratification. I need to know that we've launched, we're making moves, and tomorrow I'm going to start seeing some like progress on this, right?

But if we're developing milestones that are purely based on, ~like, ~maybe activities or, not really aligned with that tangible outcome, then it does kind of get difficult on identifying, okay, well, what are the metric points that we really need to be looking at? And at least in like the sales and marketing world, like let's take advertising, for [00:11:00] example, where I see analysis paralysis start playing out in that of, okay, we don't know what to measure, but we've got a report on something.

Then I see data points like, well, we reached a million impressions and got 3, 000 clicks off of it and that can be impressive if you're just going for ~like ~a big number to show, hey we got reach, hey we're getting notice, hey we're building awareness but that ~doesn't, again, that doesn't tell you if you're actually like That ~doesn't tell you the actions that people are creating, that doesn't tell you if you've reached the right audience within those impressions, that doesn't mean that those clicks translated into further engagement, and so sometimes,~ like, ~the other issue that kind of comes up is we don't necessarily, we know that we have things to, we have data points that we can pull, but in some cases it's not really understanding what those data points really mean.

We're going for the, this is what looks good to a senior leadership team, but if I were on that SLT and I was given impressions and clicks, I'd be like, so [00:12:00] what? That just tells me how we spend our money, if you know what those metrics actually mean.

Alyssa McGinn: I'll give an example on the flip side.

Jordan Walker: Okay.

Alyssa McGinn: So we have a client that is owned by a private equity. So they have a board that they report to, and their task for us was to basically overhaul their whole board reporting, make it interactive and visual

and so we started prying on, Hey, ~what are. ~What KPIs are you guys looking for? They wanted to do each department, every board meeting, they go through HR and sales and marketing operations. Come to find out the board wasn't satisfied with the KPIs that were being tracked and the story that was being told.

So the CEO comes back to us and says, so we're not tracking the right KPIs, apparently, what should we do? And so, we had to basically kind of 180 our strategy for helping them because we thought, Hey, we're just taking what you already have and making it better. And so I think that when we're working with that, because we're predominantly working [00:13:00] with the senior leadership team to have some of those higher level metrics.

So I was just kind of like shocked, I think, even at that high level, there's some differentiation on stakeholders

Jordan Walker: Yeah.

Alyssa McGinn: and all the stakeholders parties and who is looking at it and who cares about it. So that's just an example I think and we still haven't solved it. That probably six months ago.

Jordan Walker: That's super interesting though, because you know, if you hear something like that and it's like, okay, well the board isn't satisfied with the KPIs and the story that it's telling, is it because they aren't the right KPIs or is it because you just don't like the story that it's telling?

Because I've gotten into a lot of those kind of conversations where it's, well, what data points can we show to the board to appease them? And that goes back to the comment that I made earlier of, if you are purely looking for data just to satisfy a group of people that, and board, senior leadership team, your manager.

Dude down the street, doesn't matter who you're trying to satisfy. If it is purely just to win a [00:14:00] conversation or alleviate, I guess, the stress of getting more questions or whatever the case may be, this exists in corporations everywhere, by the way, like this is not an uncommon issue, but if we are only developing our data points based on what makes that group happy and satisfied, then we have to really ask ourselves, do we have the data culture that we should have? Or we need to do work there so that we do all have greater understanding on, okay, from a high level company perspective, ~what is, ~what are the points that we actually care about that will give us the right, the story that we need to know, good, bad, or ugly? Because, I've also had conversations with people where they're like, I don't want to know my data because I'm afraid of what it's going to tell me.

And that could be a whole conversation within itself and it's, sometimes the data may not give you the best story, but that is how you're supposed to take action. That's what you're supposed to start with. If you're identifying that it's not giving you, A, is it not giving you the insights that you [00:15:00] need in order to make informed decisions?

Then yeah, we need to solve that problem so that you can get the data you need to make informed decisions. Is it that the story is just not to your liking? Well, then why? That's an internal culture, operations, all the way down to sales and marketing and deployment, right? So I don't know, like that's just really interesting when you hear something like that, because I have to start to question of, okay, is it actually not the right data points and KPIs, or is it that we just don't like what they're telling us?

Alyssa McGinn: Yeah. And that kind of makes me I don't know if sad is the right word, but I'm like, we're not in business just to give you a report so you can report. Like, reporting isn't just for reporting, it's for strategic business decisions to be made and back to the top of our conversation around innovation, which I know we will get into more, when it's ugly and it doesn't tell you the right story, that's how you can innovate.

That's how the start of those ideas happen is,

it's like, what's the point of just looking at a report to look at it.

Jordan Walker: Right, well it's [00:16:00] the same thing when innovation and strategic planning. A lot of strategic plans, whether it's a business plan, a little league football plan, a military plan, it doesn't matter. A lot of strategic plans don't highlight this is our greatest challenge.

This is the challenge that we have to overcome in order to reach the goals that we're trying to get to and the data, and a lot of times is what helps you uncover what those challenges are. If you're trying like simple factor, let's say that you're trying to hit a certain revenue target within the next three years, but in order to hit that revenue target, you have to have an extension to a product line that satisfies~ a, ~a certain customer base, but that customer base hasn't been talked to, touched on, and a lot, they're stale. If you're not going to address how you're going to overcome the staleness with that group and then extend that product line, you can't immediately just say we're going to hit that revenue target [00:17:00] without you know breaking down those barriers that are ahead of you and so like if the story from the data that you're getting isn't good rather than looking at it as a well we don't like that and I'm totally making an assumption based off of what you said just from some of my experiences so maybe that's not where that comment was coming from but if you're gonna make ~a ~an assumption on what we don't like that these data points because we don't like the story that it's telling, again, maybe it's not the story's problem.

It's, okay, let's, let's actually look at this and take it as an opportunity. How do we address it? And again, what data points will help us understand how do we overcome this issue so that we can get to the next stage? That is how you develop strategic plans.

Alyssa McGinn: I totally agree and one more example before we move on is, we do a lot of profitability analysis, and sometimes that doesn't tell a very pretty story but a lot of companies are trying, and this is a positive example, a lot of them are trying to dig into that profitability to understand, what service line, [00:18:00] what combination of employee, service line, sales, whatever the combination factors are, that's not making it profitable and we had a client that it was showing,

like

majority of their services that these certain customers were buying was not profitable.

Of course, no board or senior leadership see that.

to know that either.

okay, but we're in the red and we need to figure out what is happening and how do we change that? And I just really appreciated their approach is they went service by service, broke down which of their customers ~were profitable. ~were buying that service.

And was it because of the customer? Was it because of the service or was it because of the cost ~of,~ to them? What were the factors at play that caused it to be unprofitable? And how do they need to make adjustments moving forward?

Jordan Walker: They really diagnosed the issue prior to just trying to take willy-nilly action on it. Yes.

Alyssa McGinn: I think that's, kind of the heart of what we're saying is, yeah. You know

that report didn't look pretty.

Jordan Walker: [00:19:00] Yeah.

Alyssa McGinn: I mean I think it looked visually pretty, but it

Jordan Walker: the story wasn't,

Alyssa McGinn: it did show a good story, but that's the start of a good story beginning, right? So all that to say reporting to report doesn't do anything for your business.

Jordan Walker: Yeah, so summarize so far if you find yourself in that boat where you're asking, okay, we don't know what to measure, Maybe you're at the point where you haven't collected the data in a way that it makes it feel really overwhelming or maybe you are collecting data but you're not sure if those are the right data points that you should be reporting on.

I think what we're, suggesting is start from the point of where is our business, where does our business want to go? Goal wise? What are the milestones that we are hoping to achieve?

Who are the audiences that we need to help us achieve those goals, internal, external, and then really take stock of what that journey looks like [00:20:00] from where you are now to where your end goal is and ask yourself, what points of data would we like to know more about so that we know, A, that we're heading in the right direction and that we can pivot when we note proactively.

We can pivot proactively. when we identify certain points.

Alyssa McGinn: And back to what you said earlier, is that most of the time the data is there. I think it is very rarely we're not measuring the right things. Maybe there's some inconsistencies in input, maybe there is one additional field that you want to look at but I feel like very rarely it's like we just aren't measuring anything. It's more of this next stage we're talking about of, yeah, the analysis paralysis or just like, okay, what now mentality.

Jordan Walker: yeah. So beyond having the question of, we don't know what to measure, or beyond having the Okay, we're measuring it, but how do we take action from [00:21:00] it? Something that we've highlighted in our first episodes is that we also know that there are technical complexities that are data challenges for a client and I think this is something that your company deals with a lot more than mine does and I would be interested to know from you, like, what are some of those, like, typical tech challenges in a high level? Like, I think we said in one of our early episodes, we're not going to try to get too technical, jargony in this and so we'll try to stay there, but yeah, what are some of the things that you hear?

Alyssa McGinn: I'll hit the technical things high level and, and not deep dive too deep into them but a couple of things that can cause technical challenges, one being that a company has such a specific use case that there's not an off the shelf software that meets their needs so they end up building out something custom, which is great but we have found technical challenges in connectivity and with just proper [00:22:00] data documentation around custom software. So a lot of times, That can be great to really have the data that this specific company needs, but it can cause more technical issues. I will say there are great, software developers out there that document it and have all the schemas and everything in line and in place, and it's really easy but there's also the flip side of that, and we've also run into that, where there's no documentation. We have no idea, what's going on inside the database of their custom softwares so I think high level back can be a challenge.

Jordan Walker: Yeah, I think that's a good point. I've worked with a couple of clients where they're in the middle of or they have built custom software and it's because of just as you said they either they started with it because they've been in business long enough that the perfect solution did not yet exist and now their business is completely operating off of like this ERP system that they've had to build ~You know,~ build on their own. They're not going to reverse course and go and get a stock solution when all of their [00:23:00] internal processes and whatnot are already running perfectly off of it just to start connecting things but having a data dictionary, from the teams that work with these programs, like, you don't necessarily even have to be, like, the developer to get that started. I've worked with teams where it's the analyst, so the platform's already there. The analyst is the one that's hands on it all day, every day. Maybe they're kind of the translator between the development team and other leaders but taking that time to really develop with that data dictionary, looks like

from how does this work, what is it, where's the data coming from, what other systems is it connected to, but what does it mean, I think also helps because then when you're trying to figure out, okay, well how do we build an API or whatever to connect this thing to this thing, you have to know where your sources are coming from and match them appropriately.

Alyssa McGinn: I think you hit on a huge point is what does this mean? Yeah. Because [00:24:00] in every industry and every type of business, even different companies, same industry, what the data means in connection to their business model and how they do business can be vastly different.

Jordan Walker: Like for example, one client that I've been working with for a while, like we've really had to do a lot of work to define what is a customer because in their industry they don't refer to them as customers or clients. In their industry, it's a member, and a customer has a different level ~of, like, ~the member is ~like, ~you're in our bunch, ~like, ~you are our go to people,~ like, ~we work together constantly. Customer has a very different definition for them.

It may not be the primary individual, maybe they're like a secondary individual on a particular account, and then you kind of funnel out from there on like, okay, well, what's a prospect? Is that how we refer to them? And so, at the end of the day, it may all kind of be similar from ~like, ~loose concept of we've got prospects, we've got leads, we've got qualified [00:25:00] leads, and then we've got customers, but if you name them a little bit differently and they have different specifications on what makes them a primary or a secondary even, that needs to be spelled out and frankly, you should be doing that anyway because if you have a customer service team that's operating against these indicators within a CRM system or something, like they should know what it means too, so that they're inputting the data correctly. So if you don't have that data dictionary to break that down, this is not only great for future connectivity situations, but it's also really great for internal ~like ~data culture building too.

Alyssa McGinn: And not to mention when you get into more highly regulated industries, asking what does this mean to you? Like, we worked with a, working with a health care company and so they're dealing with insurance providers. They're dealing with different types of patients with different codes for different diagnoses and so we had to spend months like, what does this mean? And how do we get to profit understand? They want to understand profitability.

What does [00:26:00] this data mean to you in relation to your business?

Jordan Walker: I think we're going to have to do a whole episode and bring one of our friends in on this because, and you know this person, and he might be surprised that I'm going to give him a shout out, but Ted Crewell from Moonbase. The first time I met Ted, he was giving a talk about just storytelling with data and when I first heard him speak, I was like, oh my gosh, you're my person because It was like speaking to me, and one of the things that he said in his talk was like, numbers are numbers, you can make these numbers say whatever you want them to say, but ~if you don't know the context behind,~ if you're not putting context behind what they mean for you and for your business, then all you're doing is reporting numbers. I'll give a very basic example of that. Google Analytics, one of the top or one of the most used website analytics tools, right? I get a lot of questions about things like page views and engagements and things like that. What, [00:27:00] you can measure, let's say, all of the different button clicks that you have on a website.

Not all of those hold the same weight. If somebody is clicking on a button to watch a video, that is a different level of intent than someone who is submitting a form that they had to spend time filling out. ~You can't, you're,~ if you're going to put like a weighted value or if you're going to put a value to both of those, think of it in the funnel, there are different places in the funnel, intent versus a purchase. Right? ~And so like, ~but if you report,~ well, ~we had 500 engagements on our site and only three of those were actually like more of a conversion based metric. All you did was report a total number of a thing. Each of those, they're reported the same and categorized the same in Google Analytics, but you have to be the one to know what the context is between it.

Alyssa McGinn: Well, that was a turn that I didn't

Jordan Walker: Yeah.

Alyssa McGinn: software to take, but here we are. The second more technically difficult, actually probably the most technically difficult problem is on premise servers and I won't deep dive into all the problems with that, but basically [00:28:00] all the analytics tools and visualization tools and the other data pipeline related tools are all online in the cloud. So to get the data flowing from on premise servers to the cloud environment is very challenging.

Jordan Walker: I imagine you have to like set or they're like I guess, are there gap fixes in that where it's like a 24 hour sync or, once every 24 hours or end of day sync or something like that that has to occur?

Alyssa McGinn: Yes, but that isn't as easy said as it is done. So a lot of times you have to be on site or like on some sort of remote desktop in their environment to be able to communicate extract the data or get the sync working, a lot of times it breaks. There's just a lot of

Jordan Walker: I had an issue with that in an e commerce situation where all of their inventory was on an on site server, but for e commerce they're using, like an online inventory tool.

I think it was WooCommerce on wordPress, right? [00:29:00] And, but all of their inventory being housed on site, which is how they built their company, and so it worked always for them, but it did not have a seamless sync because that inventory was not online and in the cloud. So it was actually really difficult from an e commerce perspective because if you're going to showcase how much you have in stock or try to keep track of how much is being purchased in an online platform versus your direct sales team that's hitting the road and meeting with people and submitting orders like all the time, there were ~You know,~ some scary moments where it's like, well, if we're getting low on inventory, let's say that we only have five of these things left over and somebody just bought all five of those things online, ~but so, ~but a salesperson also just sold five of those things at the same time or around the same time before the sink occurred.

Alyssa McGinn: So it's like a physical on

a physical on product?

Jordan Walker: Yeah.

Yeah, and so I mean like that's, that's kind of a more basic like version of that challenge, but that exists [00:30:00] quite a bit in, manufacturing companies that are now going into the e commerce or have been starting to make the wave into e commerce that ~That ~kind of is one of those scenarios where you really do have to kind of take stock of all of your tech stack and figure out for long term sustainability of this initiative, do we actually need to make process and tech changes now, which will alleviate the pain later?

Alyssa McGinn: And some of them have reasons why they want to be on premise, but also a lot of the initiatives and innovative new ways they want to approach strategy or efficiency, all is going to be in the cloud. So I've had a few conversations where it's like, you could do this, but I highly suggest you migrate to the cloud. first, if you're already planning on doing that at some point in the future, just because it will make everything a lot easier. you know, Another thing is QuickBooks Desktop,

Jordan Walker: Oh yeah. That's actually the e commerce scenario that I was just talking about.

Alyssa McGinn: So. apparently there are some functions and features [00:31:00] on QuickBooks Desktop that hasn't been translated online. So, there are reasons why people want to stay on that, but it just makes connectivity really difficult is basically the point.

The third is sometimes in the data, there's lack of joining fields between multiple systems. That's nothing really to elaborate on. It's just if you're migrating data from multiple sources. So, for example, like, let's say, QuickBooks IDs your customers as this, and then your CRM IDs your customers as this. If you're trying to understand revenue attribution, and the true revenue that's brought in by specific customers, and they have different, ways IDing them, it can be hard, and if there's not a joining field to connect those, like a lot of the ones off the shelf will make that a little bit easier.

~mm hmm ~but our team ~has had, ~has had trouble with lack of joining fields for sure.

Jordan Walker: Yeah, I have a client that is currently building their own customer data platform, and it's because of that scenario, they have a lot of different [00:32:00] avenues where they're like, different levels of customers and prospects come in, and they all have different IDs and it kind of depends on like, okay, what's the referral source and, and things like that but then in order for the CDP to work, they all have to have a unique identifier. So when it gets into that point, they have to have a different ID that does connect like, okay, this ID is this customer in these three different places.

And when I first started kind of understanding that issue, I was like, wow, this is kind of a rare situation but the more that I've come to understand it, ~that ~that is more common than I once thought it was.

Alyssa McGinn: Yes. I think it's probably 50 percent

Jordan Walker: Yaiks.

Alyssa McGinn: Situations that we've incorporated that into discovery like we want to get in there and see, or provide us documentation or something so we can understand because ~it's a, ~it can be a heavy lift to, I ~mean,~ manually do all of [00:33:00] that, or find some sort of alternative solution.

Jordan Walker: Goes back to the data dictionary document

Alyssa McGinn: Yes, 100%. And the last thing is just, especially with more high volume of data, a lot of times they're flowing from the origination, the input, to storage to , the analytics layer, and that's what a lot of people refer to as the data pipeline and there can be a lot of more steps into that but what happens is sometimes that pipeline breaks, and so there can be blockages and problems that happen at the, what I'll call the pass off stages between the pipeline.

So an example to make this more real, we had a prospect that their data is inputted by, ~inputted? Input. Yeah. By~ field text that are out in the field on iPads. It goes into a smart spreadsheet that then flows through to their database that then gets shutout to Azure storage. Got it. But what happened is that there was no sync. There had to be code basically [00:34:00] written to sync the smart spreadsheet to go into the database and back to all the things have to being aligned, the data points having to match and flow correctly and ~you have to,~ they had to hire like a custom software team to build out this SSIS code so that the data could flow properly.

Now there's more seamless ways to build the data pipeline. But, back to the custom situation, a lot of companies have these specific tech requirements or just things that have already been done a certain way they don't want to change that kind of requires some patchwork into a data pipeline scenario and that can make it really challenging to basically to get the data to the final destination of being able to see it and utilize it and make decisions.

Jordan Walker: Yeah, that's a tough situation to be in and I feel for companies that are in that because on the one front it's like you said okay well we already have this process we already have the way that we're doing it like our sales team already knows what they need to do let's not rock that [00:35:00] boat we'll figure out the in betweens but then it becomes like how much patchwork quilting do you really want to be doing just to make it work and to get the data to flow properly like, how much of that is actually worth the time and energy and budget to perform if there was just a different solution that then goes back to, okay, hey team in the field, here's actually what we need you to use. Like, is there a way that it could actually be patched from iPad, enter, it's already in Azure. Or like, database Azure, skip a step with the Smartsheet. ~But, ~I think that's where we get into and, maybe in a future episode we could actually talk to some companies that have gone through this and kind of hear their perspective and thinking, but, it's that kind of mentality of ~like, well,~ this is what we need right now.

We can't necessarily think about the future yet, but what happens when you get down the road and you've been doing what you're doing, but you have to change processes anyway [00:36:00] because security protocols change or

Alyssa McGinn: something forces you to

Jordan Walker: Yeah, and it's one of those where, you know, a lot of times we find ourselves in that woulda, coulda, shoulda moment, and it kind of is a callback to what we were talking about earlier.

In this case, if the mentality is coming from a, we don't want to rock the boat on a process that's already working, well, would it actually be a lot less painless if you just change the process? And I don't have an answer for that, but I definitely think that's something that companies have to ask at the beginning stages of these projects to really understand, like, what is the best outcome here?

Alyssa McGinn: Well, and in this case, they are so focused and have such urgency to give their customers real time data. So in this scenario, they are loading and unloading petrochemicals off ships. That's coming into, the channel dock and that's, I mean, and these are big companies like Exxon, ~Enron not Enron, they no longer. But~ Chevron, these people, they want to, they're very under the gun to give them real time information on their ships and what's been unloaded, what's been,

Jordan Walker: So they're not in a [00:37:00] situation where they can take a breath and, like,

Alyssa McGinn: well they don't feel like they can, but they're currently not giving them the customer facing data to know about their ships and so that, yeah, they feel very stressed and need to make this work. So I feel like, to be fair, we sit here on these chairs and say, Well, it'd just be better to redo your processess

Jordan Walker: yeah, better said than done, right?

Alyssa McGinn: There's always some sort of, other situations at play within companies that make that difficult and just stopping, the company ship, metaphorically, to redo everything is just very

Jordan Walker: Yeah, it's not in a lot of cases like that. It is not doable to slow down the process in order to do it differently.

Alyssa McGinn: But would you get to a point where you have to and then it is more painful?

Jordan Walker: I think like it's a conversation of just understanding that that is going to be a challenge and bake that into your plan. ~If you can't, if,~ if your business is really in that scenario where it's a, this is a dire need, we [00:38:00] can't slow this down, this has to happen, or like business fails tomorrow. Whether that's like true or not, if that is like really what you, where the mentality is coming from, then you have to bake into the plan of, okay, well then this is phase one, so that we get what we need, but know that you should actually start working on a phase two of, okay, but now how do we make this better, more seamless, because like if you have data flow blockages, and you have data that is like missing, how much, cleanup, are you going to have to do over a course of time?

At what point are you going to notice that data's missing? That's the thing that scares me in that scenario of~ like, ~ once you kind of get into your process and things are kind of coming through, maybe you have like a few things that you're like consistently looking at and you don't notice that maybe some data points that aren't like super duper important now aren't making it in because of some sort of like data flow problem and then when you need it, you're like, holy crap, we're missing two years worth of that metric point or [00:39:00] company profile never made it over like to this. We were just paying attention to customer name the whole time or whatever the case may be.

Like that's a big oopsie doopsie.

Alyssa McGinn: We had a client who had someone that shared the same sentiment as you and was scared, really scared that. So what happened is we ended up building them, ~like, ~a monitoring board.

So it's real time, it's like a, ~a ~visualization board built to monitor any nulls. If anything that doesn't get reported, it shows as null, and you can,~ like,~ click through and go back and

Jordan Walker: oh I wish so many platforms had that just automatically so that you can be proactive about whoa something's not coming through we need to address it oh that would be magical

Alyssa McGinn: yeah so we had to build that and, tack it on because ~the systems, ~the multiple systems didn't have that internally and now we use that off the shelf for people, like we have this monitoring board if you're worried about data quality or data consistency. We'll just, hook this up to your data sources that we've already connected, and that way you can go in, or whoever is, going to be watching over data quality to [00:40:00] make sure that you're not having huge gaps.

Jordan Walker: We should have a whole few episodes about data quality because I definitely want to hear more about that I actually think it's interesting and I feel like there might be others out there. If not, you can always email us at hello at insightlypodcast. com and tell us, yes, I like that topic or no, never talk about data quality to me ever again.

Alyssa McGinn: And on that note, if you have any other technical challenges that we did not touch on that you feel like are very prominent, we'd love to hear about those too. We feel like we covered pretty high level on most of the challenges, but we'd love to hear from you guys. Hello, at insightlypodcast. com.

Jordan Walker: Beautiful. We'll see you guys

Alyssa McGinn: See you next one.