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When You Have AI, Who Needs a Dashboard?
27 Plays1 month ago
Brendan & Brian open a pint with Allan Wille, co-founder & CEO of Klipfolio, to talk dashboards, data, & decision-making in the age of AI. From their shared roots in SaaS to a lively debate on whether dashboards are obsolete, this episode dives into what makes a dashboard actually useful—and why definitions matter more than ever. Plus, we explore the role of visualization and why dashboards deserve a spot on your screen. Bonus: the gang proposes the mysterious "Brendan Metric", Brian sips local suds in Sudbury, and Muskoka Brewery gets a cameo.
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Transcript
Introduction to 'Your B2B Marketing Pint'
00:00:00
Speaker
Your B2B Marketing Pint is the podcast for B2B technology marketers who want to sharpen their competitive edge. Joined by other marketing veterans, your hosts Brian O'Grady and Brendan Ziolo share expertise on what works today and why.
00:00:16
Speaker
Grab a cold pint of hot takes on branding, content marketing, demand generation and more served with a side of sarcasm.
Guest Introduction: Alan Ville from Clipfolio
00:00:27
Speaker
Hello, everyone, and welcome to the latest edition of the B2B Marketing Pint podcast.
00:00:33
Speaker
I'm super happy this episode to be joined by Alan Ville, who's a longtime friend, ironically, former boss of mine. He he put up with me for a while. And I think our first Brian client of both Zinc Marketing and Search search Warrant at one time.
00:00:51
Speaker
Alan's now the co-founder and CEO of Clipfolio, a business analytics platform that helps teams make faster, smarter decisions with data, which ironically is going to be our topic today as well.
00:01:02
Speaker
I guess that's the opposite of ironic. He's also, i know, a designer who's very, very talented. I've seen his work.
Beverage Break: Local Brews Discussion
00:01:10
Speaker
And a passionate cyclist who I just found out today does not cycle in the winter, outside anyway.
00:01:17
Speaker
I thought he did and was crazy because of it. No, it's a bad idea. Let's kick this off with our our standard opening. Brian, what are you drinking today? I'm glad you asked, Brendan.
00:01:30
Speaker
Long-time viewers may notice I'm in a different sh surrounding today. I'm coming to you live from northern Ontario. There's probably moose nearby. I'm up in Sudbury. And if I'm going to be up in Sudbury, where I found Trey Studios, that's where i'm sitting right now, in their podcast studio, 24-hour podcast studio in Sudbury, who knew?
00:01:48
Speaker
If I'm to be up in Sudbury, I got stop and get something local. So by coincidence, I was with friends on Panache Lake outside Sudbury. And what did I find? But a Panache Session IPA, which I know will be right up, right down Alan's alley because he's such a big fan of IPAs he discussed in the pre-show.
00:02:08
Speaker
That's what I'm cracking open today. My new friend Eric at Stack Brewery hooked me up with this. Shout out to Eric and Stack Brewery in Sudbury. What are you guys drinking? So I'm doing the non-alcohol as our regular viewers want. This time I'm doing a Muskoka Brewery Veer Hazy IPA.
00:02:29
Speaker
You know, fan of the IPAs. This one's quite good considering there's no alcohol in it. ah So big fan of that. And I'm also coming to you from our pub. So not the regular location, but our pub that we built, especially for this podcast.
00:02:42
Speaker
Hopefully ah that continues to work out for us. Alan, what are you drinking? Well, I mean, first of all, Brian and Brendan, thank you for having me on. I think this is great. I've known both of you for a very long time. So I'm i'm super happy to be here and and and happy to chat more about dashboards and analytics and everything in between. So I know we chatted earlier that I'm not a huge fan of IPAs, but every once in a blue moon, you sort of want something a little bit spicier. So I'm going for the detour. What?
00:03:18
Speaker
That's a full-on IPA. It's a full-on IPA. And I mean, as I said, every now and then you want to veer off the regular course and have a little bit more spice in the life, right? So that's what we're doing today.
00:03:29
Speaker
So I'm going to join you guys with that with this hoppy IPA. Fantastic. Unless I missed my guess, that's a Muskoka detour. I recognize the can. There you go. So maybe maybe we should drop the hint that two of us are drinking Muskoka now. So hint, hint, Muskoka Brewery.
00:03:46
Speaker
Sponsor us. Yeah, that's that's a sure shoe in. That's got to happen for next episode. That's how it works. All right. Cheers. Cheers, everyone. Now we can talk analytics and dashboards.
00:03:59
Speaker
Oh, there's a lot of hop in that.
00:04:05
Speaker
All right. are you Are you folks feeling analytical and expert and wise? ah Well, let's let's see where it takes us. Let's see where it takes us. Okay.
00:04:17
Speaker
ah Brendan, do you want me to start us off? It's all yours. The floor is yours, Brian, and then we'll get some great insights from Alan, I'm sure. Yeah, I've got so many things to ask, and I'm really glad we agreed to shared custody of Alan, who we've worked with, both of us in in the past. um We'll alternate weekends, I guess, to get Alan.
00:04:36
Speaker
Maybe he'll come back on the podcast, alternate weekends. But I have a lot of podcasts or rather dashboard questions Because basically ever since I was working with Alan and his team at Clipfolio, I fell in love with dashboards. I love measuring things that used to be we used not be able to measure in digital marketing.
00:04:54
Speaker
And it's close to my heart. I still don't think I've seen the perfect dashboard. um So I'm going to ask some of what some listeners, you do this all the time, might consider old school questions. But I know for a fact, there's a big chunk of people out there in the industry who don't have them, who don't use them, who wish they had them, who want to know more about them. So i'm going to start with some sort of oneon one on ones and we'll work our way up to the ah expert dashboard questions later.
00:05:18
Speaker
So let's start with a softball one.
Creating Effective Dashboards
00:05:21
Speaker
Alan, you've been doing this for a long time. You're an expert designer. You've made a lot of dashboards, 20 years, 20 years in dashboarding. How the hell do you make a dashboard that actually matters?
00:05:32
Speaker
And it gets used for its purpose, as opposed to a pretty dashboard that everyone agrees on and then gets ignored for the next year until it's turned off. What's the difference between the ones that actually matter and just the pretty ones that don't get used?
00:05:47
Speaker
Yeah, good good question, Brian. So you're right. I mean, we've worked with tens of thousands of customers um you know who use our our platform to to build dashboards and and have better decision-making tools in front of their teams.
00:06:02
Speaker
And the I think there's like there's a couple of things when you look at what are the dashboards or what are the tools that actually get used? So first of all, the very, very first thing is start small.
00:06:16
Speaker
And in particular, if you already have a metric that is being discussed in your Monday morning meetings, or if there's a manual process for a metric or a KPI that you're already looking at or manually updating on ah daily, weekly, or monthly basis, start there.
00:06:36
Speaker
See if you can automate that, maybe make it a little bit more robust, perhaps even include some segmentation. so So let's use an example. um Let's say you're an online retailer and you're looking at you know cart but abandonment.
00:06:54
Speaker
So how many people actually don't complete the the sale, right? This is a metric that is coming up all the time. But you don't have you don't have an automated way of looking at this. Maybe the data is coming through some system that needs to be copied and pasted into a spreadsheet.
00:07:08
Speaker
But every week, it's such an important metric that it gets talked about. So start with that. make sure that the thing that you're measuring is something that you're already doing and caring about. So that's probably the simplest way to start thinking about it. And then, as I said, make it more robust. So look at maybe this metric by returning a new customer, or maybe look at it by geo if the data supports it. So start there.
00:07:39
Speaker
The other thing is, start building out things that you then regularly revisit. So everybody's got grand plans and and we've had customers who've come to us and they said, you know, we've got, you know, 30 to 40 metrics that we want to start monitoring right off of the but right out of the gate.
00:07:55
Speaker
And that's great. They've they've done their research. But I bet you you'll start that process and maybe you'll get halfway there. You've got 20 metrics on dashboards. Revisit those dashboards, revisit those metrics because probably half of them will not get used.
00:08:12
Speaker
So then you've got a choice, either trim the ones that don't get used because clearly they're not as important or they're not intended or getting to the right audience or improve them.
00:08:23
Speaker
So Regularly come back, make sure that your dashboard, your cockpit is clean. It actually does spark discussion and it helps in decision making.
00:08:36
Speaker
And if it doesn't, keep keep maintaining it, keep updating it. I do this all the time. I mean, you could argue that we're one of the front runners in, you know, dashboard platforms, analytic platforms, and yet our internal dashboards are constantly, constantly being up updated.
00:08:54
Speaker
And I mean, you know, a little internal secret is we've got lots of metrics that are not being used. We should probably be deleting those. So there's no shame in having a plan, building it out, and then saying, you know what?
00:09:08
Speaker
These ones actually are not hitting the mark. Let's remove them or let's figure out why they're not hitting a mark and upgrading them. so So start with making sure that they get used. Start with something. If you can start with something that actually matters today and see if you can automate it in in an analytic dashboard that the team looks at every every week, every day, hopefully.
00:09:27
Speaker
Hopefully every day. I love that. And i I'm going to give a shout out. I'm not sure if it's you that taught me this or it was one of our previous guests. I can't remember the source. It wasn't me, although I'd love it if it were me. One of the measures we use in our business to do exactly what you just prescribed is ah the The example is, let's say you walk into the office in the morning and this KPI, KPI X, has either gone through the roof or it's fallen off a cliff overnight.
Building Role-Specific Dashboards
00:09:52
Speaker
Who do you call and what do you do next? And if the answer is nothing, get that thing off your dashboard. It doesn't matter. And then we try to use that all the time. Does that resonate? Yeah. I mean, so so it's interesting you mentioned that, right? So, I mean, immediately that sparks another sort of pitfall in my mind. so make sure that you're looking at the right timeframe, right? Because some metrics have got volatility that exists within a normal range.
00:10:21
Speaker
So if it's fallen off the ah cliff, maybe the first question you should be asking yourself is, hey, is this within the normal range? Is this expected?
00:10:32
Speaker
you know Do I need to freak out about this do Do I just need a larger date window, right? I mean, if you look at metrics on a minute by minute basis, it's gonna be all over the map.
00:10:43
Speaker
If you look at it on hourly basis, a daily basis, a weekly basis, and a quarterly basis, you're smoothing out those trends. So a lot of looking at metrics and dashboards, you have to look at the right time grain.
00:10:57
Speaker
And you know when do you make that decision? When do you want it smooth? And then the other thing, Also related to that is, well, it fell off it fell off the the edge of the world.
00:11:09
Speaker
Is there a particular segment that fell off? Or did something go up, but something else go down? like that ah The dashboard, the metric might have not done anything overnight, but you might have had tremendous change.
00:11:23
Speaker
Maybe Canada did a 300% increase and Germany did 300% decrease. and germany did a you know three hundred percent decrease But the average metric looks exactly the same.
00:11:34
Speaker
So I think be cautious about any kind of change. Make sure that you understand the time grain and then, you know, where you can dig in and see if there's movement underneath the hood.
00:11:47
Speaker
Makes sense to me. I could go on all day about that, but I know Brendan's chomping at the bit to get in here. What do you got, Brendan? Yeah, so I wanted to, Alan, you answered kind of part of my question, I think, already in what you were first talking about. You know, start small, make sure people are using the metric.
00:12:04
Speaker
If it's not being used, either improve or remove it because... definitely been at places where the dashboard was insanely complicated, tracked everything under the sun, and was then quickly ignored afterwards because people were just overwhelmed.
00:12:21
Speaker
And one of the things I always thought made sense, but want your take on it is, you know, different roles in the organization are going to have different data needs. So how do you you know, build out a dashboard for the CMO versus the CFO versus the CRO, et cetera, et cetera, without becoming it just overwhelming for the people who are building it out, customizing it and all that thing. So, you know, I definitely like your start small point and, you know, optimize, but there's also going to be various different needs by different people. What's kind of your recommendation to,
00:12:59
Speaker
make it work for the CEO and at the same time have a version that works for someone else or you know, yeahp that wants to get in the weeds. Yeah. And that' that's a huge, that's a huge question, Brendan.
00:13:11
Speaker
You know, it, it, on the one hand, it, it basically, if, if, if you build out the metrics that run your company, if you build out all of those metrics, you've basically defined the, the funnel or the strategy of your company.
00:13:27
Speaker
right So at the highest point is you know perhaps shareholder value. right The CFO, the CEO, they care about that. you know Then come all maybe the the profitability metrics and the revenue metrics and then the marketing metrics and then that the customer support and and engagement and and net promoter score, ah the HR metrics that sort of fuel all of that.
00:13:52
Speaker
If you build all of that stuff out, year you're easily in the realm of, you know, 100 metrics. That's not going to work for everybody, obviously, but the company as a whole is operating with all of those metrics in place.
00:14:10
Speaker
That structure is how the company basically operates from top of funnel to bottom of funnel and back again. So, You almost think about the metric system once you once you've built it out as sort of a living, breathing machine.
00:14:23
Speaker
And of course, there's going to be specialties inside of that that that machine where the CFO spends most of their time, the CEO or the head of support or the the the people manager.
00:14:35
Speaker
And I think it's, it's think of it as as a huge knowledge map or a knowledge graph or a business map, if you're not familiar with the term knowledge graph, where these things are actually interconnected.
00:14:47
Speaker
and And maybe a little a little example might help because you may you may have a ah support manager who is looking at the number of support tickets, just the the number or the close rate or something like that.
00:15:01
Speaker
They may ask a question, why did this metric go up or down? So the answering of that question traverses this whole knowledge graph. So to answer why did the metric go up or down, you may have to look at the other inputs.
00:15:19
Speaker
And other inputs may be explicit in that you know these two metrics are actually calculated together to make some other metric. So we know that there's a relationship there that if this goes up and that goes up, then it impacts this other metric.
00:15:33
Speaker
Other ones might be implicit. We know that net promoter score might not have a direct calculated relationship with number of support tickets, but it has a it has a loose and a relationship where if NPS score goes down, well, we're probably going to have more support tickets.
00:15:53
Speaker
So we know that those things are are key to the strategy. And then you may ask, well, why did NPS score go down? And you sort of unravel this thing. So if you want to have a ah real sense of the business, you are definitely focused on the things that your department can control and can take action on.
00:16:10
Speaker
But you also need to be familiar with the things that are influencing that or the things that you are influencing down the road. So I think, I mean, if you're familiar with kind of the OKR model of of managing ah objectives and and key results, it has a similar framework where there is these top level metrics that the business feeds into.
00:16:32
Speaker
You should be thinking about that as well. Every department, every team, even every person could be monitoring their own personal metrics if you if you go to that degree. So I think it really all has to do with, okay, what are the things that matter to my objectives? Do I do i know that they're actually feeding into the larger objectives?
00:16:53
Speaker
Can I take action on those objectives? And if I have to ask a question about why something happened, and i am i curious and familiar enough with the rest of the strategy so I can actually understand why something happened inside of this huge machine?
00:17:08
Speaker
So, I mean, that's a complicated and answer to that, but it It really is an organization. a company is a living, breathing organism and measurements are happening all over the place.
00:17:19
Speaker
But clearly you can't pay attention to everyone, but they're all explicitly or implicitly related to one another. Yeah, so I think it's really fascinating how you outlined all the interconnectedness and relatedness. But the key takeaway to me is, you know, how it relates to the business strategy, how it measures, how it can be used to improve or make changes.
00:17:42
Speaker
But where do you start in that? Because I think a lot of companies start with I have oodles of data. I'm going to build a dashboard that displays it nicely. Right. I like how you have flip that around and it's more about the business strategy. But how do you so where do you start then in terms of that? I think I think before you have these hundreds of metrics that are acting together as a unified machine, you start with your team.
00:18:11
Speaker
Again, like back to back to b Brian's question, you know like what's that advice? Start with something that you're already doing. What matters? every Every Monday morning meeting, what are the three metrics that you guys are discussing?
00:18:24
Speaker
Oh, I need to make sure that you know, our, our, our leads or the, the win rate or, you know, the, the ad spend, you know, these are the three things that I know are impacting my goals.
00:18:38
Speaker
Okay. If we're, if we're familiar with these goals and maybe furthermore, the other sort of key to success is that these metrics that you're starting with, they're,
00:18:51
Speaker
they're perfectly defined and perfect is a scary word because it sort of puts up barriers. But what I mean with that is they're, they're understood, they're familiar and understood by your team.
00:19:04
Speaker
So if somebody says, well, what's the win rate? Well, are they referring to the customer win rate or are they referring to an opportunity win rate or are they,
00:19:17
Speaker
looking at some other win rate. um So be very explicit about the the naming of your metric, the the definition, and that your team understands what that metric is.
00:19:29
Speaker
And I mean, there's there's certain metrics, especially like the the financial metrics, like EBITDA is a global metric. Everybody knows how EBITDA is calculated, ah how it's how defined.
00:19:41
Speaker
But inside of your team, you could have a you could have a Brendan metric. Totally fine. as long as that one As long as Brian knows, as long as Brian knows what the Brendan metric is, that's another reason why people stopped using dashboards. If, if, if, if there's confusion about what we're actually monitoring and measuring.
00:20:01
Speaker
Yeah. Then, then it's sort of all the trust element falls apart. So you can start as small as you want and you can and start as as unique as you want with metrics that only matter to you or your team.
00:20:14
Speaker
And then as you sort of start building out and start interfacing with the department, with the rest of the company, that's when those other connections, those strategic connections start taking shape.
00:20:26
Speaker
so So good luck, Brian, figuring out what the Brendan metric means. Oh, I've got some ideas.
00:20:34
Speaker
Yeah, that one that one may be a a lost cause right from the start. but Yeah. And we could have a whole other episode on why our terms in technology marketing this many years in still so nebulous and why do they change every company? yeah I don't think plumbers and electricians have that problem when they talk it. you know, so i i've I've given i've given a talk. i gave a talk on why BI has failed users. And it's it's ah it's a fun talk that I've i've given. I've given it a couple times now.
00:21:02
Speaker
But when I was researching this this topic, there was a ah quote from a Socrates, and I'm going to get it wrong, but it was something to the effect of,
00:21:13
Speaker
The definition of terms is the start to wisdom or something like that. And I thought it was like, it was perfect. I mean, if you're going to work in a team, you've got to be on the same page. And that's one of the big reasons why all of these dashboard and business intelligence projects fail.
00:21:31
Speaker
People just don't know what we're measuring. So let's be super clear that when I go into a meeting and I say, what was your sales this month? Well, is it net of returns?
00:21:43
Speaker
Is it inclusive of taxes? Is it you know, including these three states? Like, just be super clear about that. if If I want to get a bunch of marketers to fight, I'll just open the door of a meeting room and I'll yell engagement rate and I'll close the door and walk away and watch the fur fly.
00:21:59
Speaker
Absolutely. So that's, that those are the things that you've got it you've got to define early on so that everybody knows these are the, these are the metrics that matter. These are, these are how they're calculated and defined.
00:22:11
Speaker
Let's, let's go, let's go, you know, crush it. And everybody's on the same page. Okay, that was a perfect segue, that same page thing. You may be prejudicing your response. I don't know, but I'm going to find out.
00:22:23
Speaker
This is another one-on-one question, but it might only be like we forget. I think it's easy to forget. There's an 80-20 rule here, probably for our audience as well. There's a group of people who are already going, well, yeah, obviously, that all makes sense. Like I'm going to the next podcast. These guys are saying things that have been true for a long time.
00:22:40
Speaker
but there's another chunk of our audience who's probably going, because I've worked with a lot of these companies. Hey man, I've got a spreadsheet. I get some slides from my agency and I get an email once a week from my managers.
00:22:51
Speaker
I know the score. So my question is, let's say you do everything you just described right. You define the terms, you got your audience, you made the dashboard, everybody agrees on it.
00:23:02
Speaker
When this works, when it goes right. And by the way, you already acknowledged you'll probably have to change it next month. So it may not stay right for long, but when it's right, why should marketers care? Why should an organization care? What's the value of getting it right in inside an organization for a group of people. And that may seem obvious to you folks, but I bet you some of our listeners haven't had a dashboard project
Importance of Accurate Dashboards and AI
00:23:24
Speaker
yet.
00:23:24
Speaker
So let's do that. Yeah, I mean, I don't know if this is ah this is news to anybody, but the speed of being able to make decisions is one, a huge one. The confidence of being able to make decisions is probably the other one. So those two things really, really matter.
00:23:42
Speaker
So going from a spreadsheet model where either the data is manual, the problem is is that not everybody might have access to that spreadsheet. Or maybe they have a different version of the spreadsheet.
00:23:56
Speaker
Or maybe the data is three weeks old. So moving from that to an automated dashboard or analytics platform, the data is up to date.
00:24:08
Speaker
It's consistent. And because it's consistent and being distributed to everybody on the team, everybody's on the same page and they can make faster, better decisions.
00:24:18
Speaker
Now, I'll give you... so those are... those And that's not new the The BI world and the analytics world has for forever said, listen, you put a dashboard in front of but everybody and it focuses but the the decision-making speed and and the confidence on on better decisions.
00:24:38
Speaker
What's new today is that that data in a structured and consistent way, especially as you start building up more and more metrics, that data starts feeding into the AI systems that will be able to look at way more data than humans can. So as as ah as ah as a human, and you know you both are superhuman, you're probably able to look at 12 to 15 metrics and keep them all straight in your head and and and make decisions on that.
00:25:12
Speaker
and all the segmentations. you know so each think of that Think of that, right? like every Every metric will have X number of different permutations if you're looking at geo or customer type or whatever it is.
00:25:26
Speaker
An AI system, especially if it's well-defined and consistent over time, will understand the norms. They'll understand the relationships. They'll be able to inspect those segments.
00:25:38
Speaker
And they'll be able to then answer questions or make inferences based on that to the order of 10,000 to 100,000 times more than than humans can. So again, I'm advocating for a human in the loop always, but the AI is is going to supercharge that ability to run processes overnight and constantly, whereas you know humans can't do that.
00:26:03
Speaker
So that's another reason why to get your data house in order. not just in a spreadsheet, get it in order in something where we can find these relationships and an AI system can can make use of that stuff. So that's the other thing that is kind of changing in the world today. So you put it in an analytics tool and yes, your teams have got access to it. They can make faster, better, more confident decisions.
00:26:25
Speaker
But now an AI system can do the same thing. If we fast forward, everything you said about AI makes sense to me. Once you get the data lake, it can see it all. It can share it all. Keep some humans in the loop. Sure.
00:26:38
Speaker
But why do we need a dashboard ever again?
Will AI Replace Dashboards?
00:26:42
Speaker
If we've got the AI monitoring at all and it's going to alert us to what we need to know, does that not make a dashboard obsolete? Do I not need a dashboard anymore?
00:26:51
Speaker
Because I've got an AI agent. that'll tell me when I need to pay attention. yeah So this is, so but Brian, this is probably the best question yet. Like this one is super interesting, right? So humans are visual learners.
00:27:05
Speaker
We can, we can process trends and patterns a thousand times faster than we can by looking at a text output from a chat bot.
00:27:16
Speaker
So dashboards and data visualization and good communication in in a visual sense, I don't believe that's ever going to go away.
00:27:29
Speaker
what What is happening is that we're augmenting that with with insights or maybe look at it this way or look at it that way. So I believe it's the combination of making sure you're looking at the the right chart with the right frame of mind. So the AI can sort of help identify, hey, there's something weird going on here.
00:27:51
Speaker
I believe this is what's happening. Why don't you have a look at the at at the data here? So I think that visual ability to look at something is super, super important for humans.
00:28:03
Speaker
So, I mean, there's always two, there's, and so we have to sort of step back because there's often, there's often two tasks when you're looking at data. One is, one is a monitoring and a consistency task.
00:28:16
Speaker
So every single time I have my Monday morning meeting, I want to look at this chart and I want to have it up on the screen and and present it to the rest of the exec team in exactly the same way.
00:28:31
Speaker
I cannot present them with a chart that looks different because all of sudden the context, the history, the decision-making mode is off children. You start over every time. Yeah. Exactly. Exactly.
00:28:42
Speaker
And that's one of the other things that, you know, AI might get this right in the future, but right now, at least when you ask and an AI for a chart, it's gonna go off and present you with a chart that is probably gonna be different if you ask it for that same chart next week.
00:28:59
Speaker
It's gonna present to different different different axes. it So it doesn't have that contextual ability yet. Now, it'll probably improve on that and you can probably prompt it to to to be more precise and consistent.
00:29:10
Speaker
But again, I think there's a there's a there's a huge value in being very curated about certain types of of presentation data data, data presentation. So I think in certain cases, you always want to have this chart.
00:29:26
Speaker
You want to make sure that the axes are always the same. The colors are always the same. Everything that you're looking at and presenting to your teammates is familiar and you can make the right decision. So I think the visual ability to do that is is is not there yet. It might not ever be there with an AI system. So I think that's i think that's really, really important.
00:29:49
Speaker
And then I think the other thing that's, as I was just saying, the other thing that's really important is when you're doing this ad hoc ah question and answer kind of thing, I think the AI is actually really brilliant because you can have a dialogue And you can refine the questions that you're asking. And the the ai AI can do you know deep dives on things that you probably would not have time to do.
00:30:11
Speaker
But then you may want to say, well, show that to me as a trend line or show that meet to me with with normal bars. like I think that ability to take that textual feedback, that conversational feedback, and actually turn it into something visual, dashboard,
00:30:29
Speaker
I don't think that's ever going to weigh andnna go to go away. I think we're, we as humans, we need we need visuals to understand. We're wired that way. I think AI makes it much, much faster to zero in on what matters and maybe interpret what you're looking at.
00:30:44
Speaker
But I want to see it. And I think the rest of the world is is probably in that same mine mindset. They want to see it. They want it maybe explained in in ah in a more productive or more natural way.
00:30:57
Speaker
But yeah, I don't think, I don't think dashboards are are ever going to go away. I think people are visual learners. yeah that'ss That's built in, that's baked in. That is a fulsome defense of dashboards in the age of of AI. And Brendan, i'm going to throw you the mic in a second, but one follow up to share with your point there, Alan, is I lived that visual experience.
00:31:19
Speaker
I've lived it it frequently where a bunch of people are looking at a table on a big screen, a table of data and speculating as to what's happening. And then somebody turns it into a graph. Somebody puts it on a trend line and everybody goes, oh, that's what's happening. And suddenly everybody agrees because everybody can see it instantly. So I've lived that experience.
00:31:36
Speaker
Listen, table tables are awesome. i love I love tables as a way to organize and present data in a very, very consistent or very, very compressed manner. but it's, but you're missing things. You're missing the, that, that, that storytelling, that, that trend line, that analysis, that predictive ability, you know, that a visual gives you. So yeah, for sure. I think there's, and there's so many beautiful and and communicative visuals that there's, there's no shortage of, of different visual tools that you can use to, to tell the story and, and explain the data better.
00:32:10
Speaker
Agreed. Brendan, bring us home. I know we, uh, Could definitely go on the the AI topic for a while. And maybe that just means we need to have Alan back for a future episode. And we just focus on that, ah which you are always more than welcome to join us, Alan.
00:32:26
Speaker
but I did want to end or sort of start to wrap up with a question we've had fun with, with other guests that I want to now put you on the spot for. So, yeah sure you know, what's the biggest myth about dashboards and metrics and things like that, that basically just drives you nuts.
00:32:45
Speaker
Like everyone or a lot of people talk about it and you're like, please stop doing that. And then kind of give us the reality of, of behind that.
Clarifying Misconceptions on Metrics Monitoring
00:32:54
Speaker
I think the,
00:32:55
Speaker
My biggest issue, and this goes way back, and and again, I think it's just a human behavior. my my My biggest issue is that there's a group of people out there that believe that when you're monitoring metrics, you're monitoring them.
00:33:14
Speaker
they they feel They feel under the microscope by this. And i i get i get that, but it's also a it's a very defensive position to take. And I think if you can get your head around the fact that these are just numbers, understand them, you know look at how you can improve your decision-making, because this is ultimately a tool that should help make you into more of a superpower, a superhuman,
00:33:48
Speaker
you know Use that so that you can have a yeah have a discussion with your your peers or your boss about the data, not about you, about the data.
00:33:59
Speaker
And then you know it's it's it's a way to sort of say, okay, well, based on this, let's do this, this, and this, right? So I've definitely heard a little bit of that. And I mean, I i empathize with that. i mean, so...
00:34:12
Speaker
Let me sort of back up because our customers come to us mostly from a we dashboard forward, a data forward mindset. They want to put analytics in front. They want us to be more data driven.
00:34:26
Speaker
they They need this. I mean, the pace of business today almost requires it. So that comment or that that myth i've I've heard more from employees. you know there's There's a resistance um and and sort of a hesitation.
00:34:41
Speaker
Now, I think part of that also comes from the fact that the metrics that they're looking at are not trusted. So it might be a little bit of a, not only do I feel like I'm under the microscope, but I don't get it. I think it's a waste of time and therere these things are ill-defined and we can never agree on the the the right ah the right metric definition anyhow. So That's, that's up to, you know, the the folks that are putting these analytic tools in place, make sure you define the metrics, make sure everybody knows this is what it means. So I know I keep coming back to that, but that, that definition of terms is so, so important.
00:35:20
Speaker
And I honestly, I actually think it also helps all the employees feel more, feel safer about using the tools as well. So, so yeah, that's, that's definitely one that I hear, but you know, like it,
00:35:32
Speaker
for the most part, the world, the world, it's not optional anymore. yeah Like you need to understand data. You need to be data literate. You need to know how to use this as a tool and be faster and more confident at, uh, at the decision decisions that you're making.
00:35:48
Speaker
That's just the way it is.
00:35:52
Speaker
That's the bottom line, isn't it? Wow. but Maybe that's, maybe that's the right place to wrap up. Brendan, what do you think? Yeah, no, that that sounds good and I your insights today, Alan, your your help on this, both on the podcast and in as our paths continue to cross throughout both of our careers.
00:36:14
Speaker
It's great connecting with you again and having you on the podcast. And yeah, I think the the simplicity message was was front and center for me. And I can't agree enough with the clear defining of terms because I run into that more times than I can count. And I sure I would be a millionaire if I charged for each of those in some fashion.
00:36:37
Speaker
Absolutely. So yeah, really appreciate it, Alan. Any final words on your side? Anything you want to wrap us up with, Alan? No, I mean, even if you're measuring things in Excel, that's the right thing to do. But, you know, automate it, bring it out to more and more people.
00:36:56
Speaker
and your business will reward you. So just get moving on that stuff. Fantastic. and That's a great way to wrap up. And my closer will be twofold. It's two-part close.
00:37:07
Speaker
One is i want I feel smart today because you're the second guest on this podcast to reference ancient Greek philosophy in a technology marketing discussion. I think episode one, John Blackmore might have referenced.
00:37:19
Speaker
one of the big three ah philosophers in in Greece. So that makes me feel smart. Like we're we're resting on foundations that matter. The other thing I'm really going to encourage every listener to comment on when that when they finish this episode is I want to know what their definition, their common term for the Brendan metric would be. What would we be measuring and and how would it be described?
00:37:38
Speaker
um The Brendan metric. Absolutely. You know, I'd be interested in that one too. For sure. I'm interested in that one. Yeah. but Yeah, our thanks, Alan. It's always ah a great pleasure to work with you and to talk to you and to share beer with you.
00:37:53
Speaker
And I appreciate your insights today. I have a funny notion we'll be inviting you back. That's great. I really appreciate it, Brian, Brendan. Thank you so much. Cheers.
00:38:04
Speaker
Cheers. Hey folks, if you liked that episode, you won't believe the next one. So don't forget to subscribe on your favorite platform and you won't miss out. Or if you've got an idea we haven't thought of yet, hit us up in the comments.
00:38:17
Speaker
We'll cover that too.