Insightly_Ep18
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Alyssa McGinn: [00:00:00] Welcome back everyone to another episode of the InSightly podcast. I was having a moment realizing that most statistics say that most podcasts don't make it

past episode

Jordan Walker: make

it

Alyssa McGinn: we have defeated I think like something crazy like

80 percent don't make it past episode 13.

Jordan Walker: This is wild, I was actually, um, looking at our stats earlier this week when I had that moment on Monday of oh my gosh what day is it and oh yeah we're recording again [00:01:00] later this week and so out of curiosity I was looking at our transistor

Analytics. Alyssa, we are getting subscribers,

subscribers We

are

getting regular, like, listens, so if you are one of our returning listeners, thank you. But we also want to hear from you, and we don't currently have Insightly podcast social media channels. Truthfully, Alyssa and I have enough issues managing our own business social media channels right now.

But you can email us at hello at insightlypodcast. com and we'd love to just hear what's interesting you currently, what sticks out as a good episode, you know, help us help you.

Alyssa McGinn: Please. But in

the sake of new listeners, I want to give them a little context. This podcast was created because Jordan and I were having conversations about data, data strategy and just the future of where data and analytics was heading for businesses behind closed doors.

And we wanted to [00:02:00] bring that to the world around us because we like talking about it. And I think it's just really, Gonna be a huge competitive advantage and a huge part of the future moving forward for

Jordan Walker: businesses And

Alyssa McGinn: And I think I've honestly even just the past like six months become More and more convinced of that and I've talked to more and more companies who

are

just realizing

The need for visibility and access to their data that's why we talk about all this stuff.

And so if you're new, thank you

And we hope that, you'll go back and listen to some of our previous episodes where we did a lot of groundwork and talked a lot about some basics and interviewed some really cool

Jordan Walker: going to

Alyssa McGinn: But today, we're going to talk about questions to ask your data, and I love this topic because

this feels like very foundational me. At a very much, a human level, are we curious about our businesses and our data and, where we want [00:03:00] to take our business that's really grounded in data, so and I think, we want to talk about how asking the right questions to your data unlocks valuable insights for better decision making.

Jordan Walker: yeah

unlocks

Alyssa McGinn: That's kind of where we're headed but I want to start with a

Jordan Walker: with Mmmm.

story.

Alyssa McGinn: because I'm gonna give a big shout out to Douglas Laney. If you, he's probably not listening to our

podcast, but

Jordan Walker: But if

you are, that'd be super cool.

Alyssa McGinn: wrote this awesome book called Data Juice 101 stories of how organizations are squeezing value from available data assets.

Jordan Walker: Show the camera. The book.

Alyssa McGinn: Literally an orange, just, and I think we've used this analogy before, like squeezing

juice, and he just goes through tons of short stories about companies in super cool ways that they're using data, but I feel like this highlights kind of the point here today. So

the

title of this one is Predictive Analytics Can Be Cool,

Jordan Walker: Yes, they Can.

Alyssa McGinn: and this is all about the hospitality, specifically the HVAC

[00:04:00] industry.

Jordan Walker: cool.

Alyssa McGinn: So here's the context. The company called Millennium Partners they had completed a major mixed use development in New York, Boston, Washington, D. C., San Francisco, and Miami, spending four billion dollars on

that

Jordan Walker: the development? Okay.

Alyssa McGinn: And they own and operate these offices, like super high end office buildings and they were planning to retrofit some of the buildings they had bought.

All their HVAC systems so that they could keep the systems control like

Jordan Walker: Centrally,

Alyssa McGinn: yeah

and so they hired a Company called Copper Tree Analytics to basically help them investigate Building out like an automation system So they're asking like how can we make sure that we are most efficiently using our heating and air systems so that we can save money

Jordan Walker: Yeah.

Alyssa McGinn: And so it says, CopperTree's analytics, CopperCube, which must be like their proprietary system, [00:05:00] extracted current and historical trend logs from the building automation system.

To investigate the building and establish a baseline, trend logs were then processed by CopperTree's system, and they used these tools to enable them to view energy trends in the building and customizable reports, so that they could pinpoint which equipment and systems could deliver the most energy savings impact.

So their question was, which systems could deliver the most energy savings impact? And can we look at the trends in the buildings and then to understand which of those would give us the most savings? So with that question, they were enabled to build a model predicting return on investment. And this is what's crazy.

So they kind of asked that question, they went through it, they built the reports, and after analyzing it, They saw a reduction in their electrical energy consumption of 64 percent per month.

Jordan Walker: Whoa!

Alyssa McGinn: to

dollars. Yeah. So

as

it turned [00:06:00] out, the projected savings from the study was within 1 percent of the actual values that were projected nearly $60,000 per year in electrical

Jordan Walker: awesome. And imagine what you can like reinvest that into

Alyssa McGinn: They said they're gonna put the ROI towards future renovations and other buildings. Literally combine, like, other, put that towards other buildings in their portfolio.

So I was just like, there's tons of other stories about this. So I just, like, pop open this book when I need some inspiration.

But, I was just thinking, like, this story probably started with some guy that worked for them saying, I wonder, how we could pinpoint the most, energy saving equipment that we use and use that. And how could we look at the trends to, like, figure that out?

Jordan Walker: I almost wonder through, if the question actually started out with Well we know we need to invest in these HVAC systems so how do we measure our ROI. Tell me why I should update these when you know it's going to have multiple like [00:07:00] zeros on that estimate and and all that sometimes changes within budget, so, like, that story reminds me of when I've had clients who are exploring, expanding a warehouse or, looking at additional property investments for, like, retail locations or something like that, and it usually starts with, okay, well, is the risk worth the return?

And so in this case, like, I'm wondering if that's where the question actually started and then the individuals that, you know, are really in charge of that started getting into, well, we have to prove that this HVAC system and the way that we manage it is a good investment. So here are the questions that we want to ask of this data to give us that validation for moving forward.

And they obviously won that argument with a 60, 000 annual return.

Alyssa McGinn: And

I wonder if part of it too was like, oh crap, like we have to do this. How can [00:08:00] we ensure that it's efficient?

Jordan Walker: Yeah, how can we maximize this step that we automatically

Alyssa McGinn: to take, right, because if they're doing like super nice office spaces, like their tenants are gonna have some level of expectation around heating and air, right?

I mean, that's just like mandatory that that's in good standing and working properly. So yeah, you're right. It's like, okay, well we have to do this.

And I think the physical asset side of businesses are, it's just expensive, right? To like manage that. And if they spent 4 billion on the property, like I just can't imagine like how much that that spend is.

So to say, yeah, okay, well we have to do this. Let's figure out how we can

model out,

to make sure that we're maximizing our savings. We're just not spending more than we have to

Jordan Walker: Yeah that's a good story to illustrate how there was an action that they're already having to take or exploring to take, but the multiple different [00:09:00] directions within the questions that you can ask your data.

Like how many different directions can you actually come at this problem and the solutions that you're trying to put on the table? Because I would imagine too if this story was expanded upon that there was probably some discussions before they even started talking about centralizing. Their HVAC system because like what started going through my mind is other efficiencies that were probably discovered is Okay, well if you are managing systems Individually across all of these locations that means that you have different vendors and partners for all of those locations which means that You have to have a team that's managing all these vendor and

partner situations and

so you're basically just like a, you know, constant property manager fielding complaints and requests and all of

that.

Alyssa McGinn: Which probably gets inefficient really

fast.

Jordan Walker: Yeah, so then you're looking at that as, well, we know that we have these bottlenecks and these issues. How do we address this? Okay, now here are some [00:10:00] solutions on the table that we can a look at.

Alyssa McGinn: And it reminds me of another story and then we can get into the content, which this is the content really. It's

stories

is the content of questions about your data.

But, There is a company, this is not in a book, this was an actual company that we know, that they were actually an HVAC repair company.

So that's what it reminded me. And they felt like their problem and the questions they were asking was that their leads and their marketing tactics just felt like stale. Like they didn't feel like they were meeting people at the right time, that the systems just like weren't ready to be like updated.

How would they know? You know, when a system needed to be updated or at the, like, how, how would they work back to like, okay, your system needs to be updated in November, or you need a new system in November. We need to be sending our salespeople to your door or calling you in

September.

Yeah.

So, they started getting curious around this because their salespeople were just like, we're calling on people, but they're like telling us that they don't need this for another year or six [00:11:00] months or whatever.

And they had worked, I think they had worked through the ICP, like they knew the type of company, all that stuff, but it just wasn't, the timing wasn't

right. So, they actually brought in third party data, not third party, external, it's, it's just not their own internal business data on

their customers.

It was market data about somehow they got, I guess it's public, basically like all the HVACs and when they needed to be

renewed. Yeah, and I don't know where they, like, sourced this from, they bought it, like, they bought a

list

of,

Jordan Walker: sure, like Experian or something like that. Transunion.

Alyssa McGinn: Yeah. something like that, Yeah.

So they integrated that into their lead list, and, then the salespeople just had a list of all the people who, in two months their HVAC system needs to be updated or, I guess, replaced or whatever. That marker is and then I think the sales people's success for even taking a lead Into proposal or to a next step was [00:12:00] up by 50 percent or something crazy.

Jordan Walker: Well, yeah, because at that point the, so that's like totally the world that I dip into all the time is one, how do you like hone in on the right target market and the right people that are in the right place at the right time. Yeah. In this case, it's your system's gonna need to be updated in the next couple of months or whatever.

Now you've got a leads list that is like ready to go. And so when you're focusing all your energy there, and you can, you know, these are probably the issues that you're experiencing with your current system, your warranty's already, you know, like three years out of date, like, here are the new energy standards that your current system probably

doesn't meet, like,

yeah, you can like actually start to develop a pitch that's Beyond just, hey, you need a new HVAC system or whatever.

Alyssa McGinn: we be your new HVAC

Jordan Walker: Yeah, but okay. So we've kind of like gone around in a couple of different ways with this story, but at the core of [00:13:00] it, I think something that stops teams, I won't even just say like businesses, because I think what stops teams from moving forward in exploring data avenues is not equating This curiosity to actual questions that you can get answers to.

Like sometimes I think like this natural curiosity where, you know, where we just gave an example of how we're bouncing different questions and ideas and whatnot off of a

scenario.

This happens all the time with teams in an office. But what ends up happening is what I end up seeing more often than not, I will just say that from my experience, is that rather than Breaking it down on, well, what data could we look at to support these hypotheses that we're making, or these questions that we're generating?

It usually goes to, well, these two things sound interesting, let's just go and test those things out. And there's nothing wrong with

[00:14:00] that, If

you don't have the data. You know, internally, or you're not sure like what to really pull, but what ends up happening there is like you go straight to implementing a tactic or a solution and then your data becomes just testing that without the validation that that was the right direction to begin with.

Alyssa McGinn: and that was my question, was what is holding companies back? Because to me, the data step seems very Clear, because it's like, you have these hypotheses, you go and test, but really like the data is very clear that A and B is not gonna work and you need to do C and D,

like go test those and then it goes back to the question of marketing and sales, ROI, like what's the best place to put our money, and it's like,

Jordan Walker: it's

Alyssa McGinn: going off of a hunch or a gut.

And just like going out there and saying, well, we think this because, you know, anecdotally one time we heard this story or something. But you know, to us, that's

clear.

Jordan Walker: Yeah.~ ~

Alyssa McGinn: ~But do you think there's anything else that is~

Jordan Walker: miss that step,

Alyssa McGinn: miss that step? I guess. Is [00:15:00] there anything

else?

Jordan Walker: Well, I mean, I think it's the Again, just in my experience, I think we get really enamored with wanting to have the solution, and activating some sort of direction.

Because That feels better than doing nothing. And depending on company size and, you know, current state of sales and whatnot, like if we kind of get into that scarcity mentality, we're going to skip a lot of those steps or make quick assumptions without a lot of analysis, right? Like sales are down. These are where the sales are down.

Go

and

make more sales where they're down.

Right.

makes sense, but if you're that I want an immediate solution kind of mindset, then puts us in that mentality where we might have some good ideas on how we can address that, but the metrics of success aren't against [00:16:00] indicators at that point.

They're against that ultimate, like sales are down, make sales go up. So if sales don't go up

and that's the only thing you are measuring against. Then, oh, it didn't work, do something else. And then you just see that cycle over and over again. So I think the biggest things that, in my experience, hold companies back from being curious and asking questions of their data is one, not tying that curiosity to, these are real questions that you can actually ask data.

Whether it's your data internally, industry or market level data The quantitative and qualitative, you

know, data, they're not tying that curiosity to those actual questions, and then the other is that time to implement. Are you willing to actually give the time, whether it's a couple of months or whatever, to truly source everything, analyze it, and see where the trends

are?

Alyssa McGinn: That's exactly what I was going to say, was that there's a component that you said of people just like wanting instant [00:17:00] results,

Jordan Walker: a component,

Alyssa McGinn: a component,

of the time to implement. That's what

I was, that's what we've seen, and just to put that in perspective, there is a

foundational time to implement where you need to get your data sources connected to whatever platform you're

Yeah going to use, you need to kind of get it cleaned up,

Jordan Walker: It depends on what your data looks like, too, in the beginning.

Alyssa McGinn: But I also want to encourage people that that is some, maybe some painful groundwork,

Jordan Walker: but

Alyssa McGinn: once that's done and you're connected and data is flowing,

No question is off limits. And that does, you don't have to go back and reinvent the wheel every single time.

Like, we have a client that we've been working with for, I think, three or four years.

You know, we went through that initial process. It was painful, honestly. Like, they were running QuickBooks Desktop, which is an on

Jordan Walker: I've dealt with

Alyssa McGinn: solution. And they also were

using HubSpot, I believe. And wanting to get some revenue [00:18:00] and sales.

Jordan Walker: I'm sorry you just like sparked this what scenario can I just ask a sidebar question

Sorry HubSpot and QuickBooks desktop how did they speak to one another?

They didn't. Okay well that answers

question number one because am I right in thinking that QuickBooks Desktop.

I mean, it's not like a real time, update to

Alyssa McGinn: No.

Jordan Walker: every 24 hours at best

kind

of

thing, right? Yeah. So the sales pipeline, sales and marketing, like, pipelines were not connected to the actual, okay. is groundwork that

has

Alyssa McGinn: Yeah. And I

think

it was probably, like, 6 to 12 months, of groundwork and still having to go through, a lot of technical hurdles, but what I'll say, now, today, currently, their CEO, a few weeks ago, was like, Hey, I'm really curious, like I want to see, Matrixes, we love Matrixes, he's like, [00:19:00] I want to see on a Matrix, like, our customers that are stars and those that are dogs, the stars were the ones that were, high revenue or high margin and growth

potential. And then the opposite of true was the dogs. It was like, they're low margin and they take

a

lot

of time,

or even

if they're high margin and they take a lot of time, he wanted to see that all in a matrix.

Because of the groundwork, his dashboard was done and spun up in, you know, a couple weeks. ~ ~And

so it's like, Once the groundwork is done, like, you can literally go to your development team or analyst or whoever does that and say, we want to know this, the time to implement is such a

hurdle

that it's like,

okay, we have to stop everything we're doing. Not really, but people think you have to stop everything we're doing. We have to go through all of our mess of data. We might have to start inputting new data points like it is just a process,

right? But Like, it's

one

of those things where once you do it, You can answer almost any

question.

Jordan Walker: Yeah, and I don't think it's really an option [00:20:00] anymore to not do it, you know, and going back to what you said at the top of this episode of how important data is in your competitive advantage, and I mean, it is the competitive advantage right now.

It will continue to be the competitive advantage. It's how you make sure that you're running an effective operation internally, externally. You know how your dollars and your capacity is being spent. You know, when we live in an era where we have to not only, obviously mind our budgets, but human capital and workforce development is a huge, challenge right now, getting more individuals and the right individuals into the roles.

Like, we've got a lot of factors at play within doing business today, because We're also not just local anymore. Like with the advance of technology, your, you know, hometown business can be a global business if you really want it to be. And that just introduces a whole lot of new variables to explore [00:21:00] on every ounce of scale in a business just means more variables to explore, to be able to ask good questions of how are we

doing?

Where should we go? Where should we improve? What are we doing awesome at? I mean, you can peel back that layer of the onion so many times once you have that foundation, but it's not an option anymore to just say we'll get to it. Like this should be an end of year goal to start at this

point.

point

Alyssa McGinn: I heard a podcast the other day that was like, you have 70 days left of this

year. enough time to take major action on whatever the

priority

is.

Jordan Walker: Yeah. What do you got?

Audit what you have currently. Write down every single question that you would want to be able to have answers to about business.

Dream

Alyssa McGinn: Yeah.

And start, start thinking about like, what are the KPI? We'll talk about KPIs. Like, what are the KPIs? What are the revenue drivers of our business? Start just brainstorming

that. But I also think too, back to what you were saying is like, People are jumping to the [00:22:00] shiny object, which I hate to burst the bubble, but data is the foundation of those shiny objects. AI.

Jordan Walker: Adding additional

Alyssa McGinn: revenue streams. Monetizing your data. Monetizing the

information you've

collected. Improving the customer experience. Like, if you ever want to sell your business, they look at your data.

Jordan Walker: the foundation Yeah.

Alyssa McGinn: That Is the foundation of it.

Jordan Walker: I Mean that's part of what they're

buying.

Alyssa McGinn: Yeah,

Jordan Walker: Really.

Alyssa McGinn: like who are your customers?

How good are they? Are they going to stay with you?

Jordan Walker: What's your brand equity. What? Yeah.

Alyssa McGinn: And that's all backed by data. So the shiny objects of, M& A activity or AI or monetization or machine learning, like all that stuff. You can't do any of that. You can't jump to that without good data foundations, which I know if you guys have been listening to this podcast for a long time, Wow, like we do harp on that, but it's like the fun, exciting stuff,

Jordan Walker: You can't do it until

you have that in place.

Alyssa McGinn: six months is a blip on the [00:23:00] radar,

Jordan Walker: I mean, if we're all being realistic, how many times do we, set these annual goals, at the beginning of the year, and we're like, by the end of Q1, we're gonna have this big, hairy rock accomplished, but then as you start getting into it, And you realize, oh, we actually can't do that yet because we've got all these other things that need to be addressed.

It was a great idea, but now it's a Q4 goal,

Alyssa McGinn: ~goal. Yeah.~ Yeah. because

you've

Jordan Walker: actually, like, roadmapped it out and you see what you need to do.

Alyssa McGinn: My pipeline represents that. Yeah. Like, literally, people that come to us and said, This is my goal for 2024, and I'm like, It's Q4. Yeah. Literally, like, I have multiple people that We're saying that exact same thing. It's like, okay, can we get this done by the end of the year? I'm like, no, no, we can't, but we can start, but we can't get that done. Well, I really wanted that, rock to be accomplished. Anyway,

before we end, I want to read some

questions that you can ask your data just to kind of bop through them. Just to give, get the wheels turning. So I kind of broke them down into

department.

Sales and marketing is obviously, I feel like, one where we have the most

[00:24:00] knowledge, potentially.

So here's some questions you can ask your data about your sales and marketing.

Which customer cohort is most profitable? Who are our most valuable customers based on lifetime value and

what attributes do they share?

What are the main reasons for customer churn in

the last year? How do seasonal factors affect our sales volume? How quickly do we respond to market trends and technological advancements and

product updates?

Jordan Walker: Ooh, that's a good one to ask?

Alyssa McGinn: What is the profit margin breakdown by product line or service offered? How do different marketing channels contribute to overall lead gen and customer acquisition?

Jordan Walker: and I think just sidebar, one day we probably should do a marketing focused data conversation, because that is one of the most elusive departments to tie directly to revenue and sales, and I think there needs to be a [00:25:00] conversation around what is a revenue attributed metric versus what is actually just customer experience and user experience.

Because those lines get, yeah, like, you know, we report in marketing and I'll just do this really quickly and then we'll move on. But in marketing, you know, a lot of marketers will report, okay, here's our website traffic, here's our social media engagement, here's what our top three posts were, whatever, that is all good information.

for the marketing team to have. That does not translate to an executive level on, okay, but how did that help us gain new leads, get new transactions, whatever the case may be. So there has to be a conversation around how do marketers actually get to measure return on investment against real sales data versus what is actually helping us understand how we can create.

a better customer experience, it does apply to this set of questions that we're [00:26:00] asking because there is a direct correlation to improved customer experience equals higher sales volume, longer lifetime value or greater lifetime

value,

so on and so forth. But that is still an elusive

bubble for marketers.

And that's all I will say about that for today.

Alyssa McGinn: Let's mark down for another episode because I think that is a really important topic to dive into. Like, basically offline, online to offline conversion, but that also requires sales and marketing being

seen as one.

Alyssa McGinn: Last one in the sales and marketing bucket, what stages in our sales cycle causes the most friction?

I think that's, you

could drill down real deep into that. I put a few operations type of questions, not as many, like a product based business, how effective. Are our inventory management strategies in reducing stockouts and overstock? If you're in a people business, like a service business, how many jobs are assigned to each staff member?

And what is the total number of jobs under each staff's management? So it's like a [00:27:00] capacity question.

What's the utilization and efficiency metrics for each staff member? You start to get into like, a lot of depth on capacity planning and people versus pipe, I mean, pipeline starts getting brought

into

Jordan Walker: into

that.

Yeah, absolutely. absolutely.

Alyssa McGinn: to fulfill our pipeline if we won 100 percent of it.

Jordan Walker: And I also, I've actually been a part of a sales team in my earlier career where some of those metrics within the service business that we were also looking at is are we assigning clients to the appropriate sales team member based on expertise? And I think you brought this up in one of our, previous podcasts about really aligning.

Customers with specialists within the organization. And so like when I first started in this, on the sales team, everyone was kind of like, I wouldn't say that they were generalists, but you were basically segmented based on, are you working with higher revenue? So you got the clout of like, we work on the big dollar accounts, and then everyone else was [00:28:00] smaller businesses.

So it was only segmented based off of revenue in that portfolio, but then the organization started to take a look at, well, what can actually create a better experience because this is a relationship type business, so then they started breaking some of those cohorts up and moving clients around to different account executives that had more experience or background or know how.

So instead of you only having maybe one of the automotive accounts, maybe you actually had three of them because you're super duper good at automotive versus this other person over here is awesome at retail

experiences. And that was actually a game changer to then use that insight as a way to deliver better experience, have a better sales pitch.

It was a lot more genuine in conversation because the reps didn't have to go out and talk about something. Now, sometimes they did, but you didn't

have to make it up or be like, I have no idea about your business. I'm [00:29:00] just

Alyssa McGinn: business. I'm just have

a package. Yeah, And

that

can be broken down so many ways by industry or by like

service type. So if it was a marketing agency and like, you're really good at,

or like you have an SEO sales team, I'm something up, but it could be by like the

specialization, which is, I think

what

Jordan Walker: are you a local SEO individual or are you more of like a regional expert?

Like

that,

oh gosh, local

SEO is a

Alyssa McGinn: Okay. but yeah, I mean, I think all these questions lead to more questions, basically, you know,

as you can tell. Oh, I put a few questions for manufacturing, cause that's been, that's something that's common in our local area. and I think across the world. how does production output compare to planned production

targets?

Alyssa McGinn: what are the bottlenecks in the production process and how frequently do they

occur?

Jordan Walker: That's good and that applies to if anyone is in manufacturing you've probably heard of lean manufacturing principles and so those questions definitely apply with [00:30:00] how to structure and format your manufacturing plant for greater outputs but you can only do that if you've got the data. foundation.

Alyssa McGinn: And the, the impact of that is big. Like, downtime. When you don't get these things right, that's like, oh crap, we have a project and we don't have the inventory to

fulfill. Right. Or, oh, we're down because You know, X, Y, Z.

So there's, there's a lot on the line there. Some questions for finance. What percentage of revenue is reinvested into the business for growth, and how does that impact profitability in the short term and long term? What service line, we talked about that, is most profitable? The magic of a lot of these questions is revenue.

True revenue from accounting systems married with sales and marketing data.

Alyssa McGinn: What's the percentage of revenue growth quarter over quarter and what are revenue drivers? I think revenue drivers is a huge piece of incorporating your financial data is to really understand what is driving revenue because I think that's also a lot of times assumed.

It's not just these [00:31:00] departments siloed, it's cross department and connecting the dots and asking the questions for how does this impact this? Like gone are the days where financial people just run financial reports and marketing people look at website traffic, And we don't ask the questions of how these things are impacting each

other.

Jordan Walker: Honestly, I feel like if there was anything that anyone took away from our podcast, I think that collaboration across departments around data is something that we mention whether we're trying to or not in any episode that regardless of data topic, the collaboration is always the piece that I want people to take away from that.

Putting your data in silos doesn't benefit anyone in the org or the organization. And Putting people in positions where they only operate data within a silo hinders their ability to ask good

questions.

Alyssa McGinn: Yeah. And don't be confused if you listen to the episode with Tariq about cybersecurity, it's okay to technically have your data [00:32:00] siloed for security.

Jordan Walker: Yes, that's not what we were talking about. That we are

okay

Alyssa McGinn: We are. good with

that.

Keep your data secure and safe. But we're talking about having it in a place or storage where it's separate from hackers, but you can use it to have an. Integrated collaborative data analysis experience.

Jordan Walker: And in our next episode actually with some of the terminology that we're going to get into we'll also kind of help break that down like the data, the data the raw formats, yes, secure them, silo them as you need to, but when you actually get it into analytics or business intelligence, that's where you need to at least be able to have the opportunity to bring it together, to then trendline it, project, see what, patterns and what not exist, What Alyssa and I are talking about breaking down silos and that collaboration is not the raw sets of data necessarily, it's make sure that you have the infrastructure to [00:33:00] where you can pull it together and that's part of that data foundation that we keep

talking

Alyssa McGinn: Yep, yep. And are you surprised that we went over on what

time we said we

Jordan Walker: at all. Not

at all.

Alyssa McGinn: I was like, oh, we're at the mark, and we haven't even read the

questions yet,

Jordan Walker: questions.

Alyssa McGinn: So here

we

are.

Jordan Walker: Well be fair, we're also kind of like, still waking up. So I think we needed chit

chat a

Alyssa McGinn: chat a

little

Jordan Walker: joining

Alyssa McGinn: So thanks for joining us for our chit chat, everyone who listened in. And we would love to hear from you guys, like, what questions have you asked your data? We know this is not a comprehensive list. We definitely have not even covered like all of the departments because we know businesses are very specific and so we would love to hear like any cool

stories

Jordan Walker: Yeah, what ahas have you

Alyssa McGinn: you uncovered?

Jordan Walker: what's like a question that you didn't think you needed to ask, and then you did, and it came back with something really cool. I want to know that.

Alyssa McGinn: Me too, we could do a whole like series on stories,

honestly.

Jordan Walker: predictive [00:34:00] analytics is cool.

Alyssa McGinn: is cool. Take that away. Data is cool.

This is the, it's, it's becoming less nerdy, less techie and more business.

Jordan Walker: yeah

Alyssa McGinn: Cool.

Jordan Walker: Yeah. I'm with it.

Alyssa McGinn: I'm here for it All right. Reach out to us at hello at insightlypodcast. com. We'd love to hear from you and we'll see you on the next episode.