Summary

In this conversation, Colin and Chris explore the dysfunctions caused by poorly designed dashboards in organizations. They discuss how metrics can mislead teams into believing they are successful while the reality is quite different. Through examples like the Royal Bank of Scotland, they illustrate the dangers of metric fixation and the importance of designing dashboards that reflect true performance. The discussion emphasizes the need for a cultural shift towards valuing truth and learning over mere numbers, and offers practical advice for revenue leaders on creating effective dashboards that drive meaningful outcomes.

Takeaways

1. Dashboards often misrepresent reality, leading to false success.
2. Metric fixation can create a culture of gaming the system.
3. Siloed dashboards can cost businesses over a trillion dollars annually.
4. Goodhart's Law highlights the dangers of tying metrics to compensation.
5. Effective dashboards should have counter metrics to prevent gaming.
6. Shared ownership of metrics can reduce departmental silos.
7. AI can help refine metrics but doesn't replace the need for good design.
8. Cultural change is necessary to prioritize learning over gaming.
9. Identifying toxic dashboards is crucial for organizational health.
10. A minimum viable dashboard should focus on a few key metrics.

Chapters

00:00 The Dashboard Dilemma

02:05 The Illusion of Success

06:36 The Cost of Metric Fixation

09:53 Goodhart's Law and Its Consequences

14:30 From Good Intentions to Dysfunction

21:00 Identifying Toxic Dashboards

23:55 The Dashboard Dilemma

27:36 Designing Effective Dashboards

33:00 Shared Metrics and Collaboration

35:00 The Role of AI in Metrics

38:15 Practical Advice for Revenue Leaders

43:52 Cultural Shifts in Metrics Management

Your dashboard is lying to you. Marketing's MQL graph is up 40%. Sales activity metrics are at record highs. Customer success scores are glowing. Every light's green. So why is revenue flat and churn creeping up?

Well Colin, it's because most dashboards don't actually measure reality. They measure gaming ability. You remember, I think maybe last season we talked about Wells Fargo. They created two million fake accounts to make their dashboard screen. UK police, as I was reading the other day, under-recorded 25 % of serious crimes to hit targets. When the dashboard becomes the goal, companies optimize for friction.

a good start. That's so completely the wrong word. Should we go again? Yeah it was so good too. Optimize for fiction not value. That's not that's not a sentence. Let me think about that will you?

Do you want to start again? Yeah, I hope to my house for fiction. It stopped in your tracks as well, so you couldn't quite, you couldn't quite stay.

I couldn't start. Once you've said optimizing for friction, I think there's no real coming back from that. Right, anyway, sorry Dominique, next, take two, yeah.

Right, we just start again.

Click,

Your dashboard is lying to you. Marketing's MQL graph is up 40%. Sales activity metrics are at record highs. Customer success scores are glowing. Every light's green. So why is revenue flat and why is churn creeping up?

Well, because Colin, most dashboards don't actually measure reality. They measure gaming ability. You remember Wells Fargo? We talked about it last season. They created two million fake accounts to make their dashboard screen. UK police, as I was reading about the other day, under reported 25 % of serious crimes, just so they could hit targets. When the dashboard becomes the goal,

and companies start optimizing for the green light, for the up and to the right, then they're not really measuring the right things. They're not measuring and optimizing for value.

So today on how to build a growth system, we're exposing how your metrics are actively destroying your growth. And more importantly, of course, as always, how to design dashboards that drive truth, not theatre.

So Chris, I want to start with something visceral. So paint me a picture of a typical Monday morning, as I like to say. We're going to do the pipeline review, and everyone's got a case of the Mondays. And actually, we're all looking at the dashboard, but the dashboard's driving the dysfunction.

Well, sadly, it's a pretty easy picture to paint because I think we've all been in this situation. know, we have the, and I've been sat on this particular side of the fence, marketing presents their dashboard. MQL's up, you 140%, 1,040%, doesn't matter. Content velocity is through the roof. Attribution models have showed that there's influence everywhere across the entire pipeline.

Then the lovely sales colleagues show their dashboard. Activity metrics are maxed out. Pipeline coverage looking really healthy. They've got demos booked at record rates. The customer success guys, CSAT's up in the 90s. Ticket resolution times are down. The executive teams there, everyone pats themselves on the back and they move on. So yeah, great stuff,

I mean, managers I've ever had, not you, would say that that sounds like a success.

you

Well, it does sound like a success, doesn't it? It's a convenient truth that everyone wants to believe, but it's theater. You know, the MQLs is, as we all know, as we bang on about on this podcast so often, you know, they're there because marketing is probably lowered the threshold. Yeah. Every, anyone that maybe they breathe near a form, you know, they become a qualified lead sales activities. Well, reps are, you know, logging the meetings that they're having with each other. And, know, someone in rev ops is not kind of fix that. And everyone's just enjoying the fact that's on the dashboard.

92 % CSAT or whatever they've hit. Well, as usual, they're surveying the happy customers or they are, you know, finishing their phone calls with it. If there's any reason you can't give me a nine or a 10, tell me now. We've all seen it. The dashboards are green, but the business is bleeding.

So I've been in this position, especially when I've been in, let's say, a junior position in a company and I can see all this going on and I'm just kind of sometimes just screaming into myself, how is no one seeing this? So why doesn't this get immediately noticed and brought to the fore?

Well, it's because most likely and most businesses create what Jerry Miller calls metric fixation. We've confused, or certainly they've confused measurement with reality. The dashboard isn't actually reflecting performance. It's creating its own reality. And it does create its own reality because dashboards are there to create behaviors, right? They're there to drive decision-making. So these things really do create reality. And here's the killer stat.

Siloed dashboards, disconnected dashboards, imaginary dashboards cost US businesses over a trillion dollars annually. That's 10 % of revenue lost to measurement dysfunction.

So just to qualify there, you're talking about a trillion dollars with a T, not a billion dollars,

Yeah, and isn't that the second time we've used a trillion dollars that's come out of the research? I mean, maybe it's a McKinsey thing, but ultimately...

These sort of issues, whether it's sales and marketing alignment, last time we talked about trial, whether it is dashboard dysfunction, these kind of issues, these disconnections, these fictions are costing the US economy and economies all around the world an absolute fortune. Fortune that could be measured in the GDP of small countries. But nevertheless, it is a McKinsey verified number.

When your dashboard incentivizes marketing to flood sales with rubbish leads, 79 % of them rather go nowhere. Sales, the stats suggest, ignore about half. In my experience, it's probably more like 90%. If you're doing that, you're not just wasting time. You're destroying trust inside the business. You're burning resources. You're creating cultural toxicity.

the dashboard becomes a kind of weapon for each department to of defend itself with against the other departments in the sort of value chain. And it just drives this kind of silo dysfunctional behavior. It drives dreadful decision-making and it's stagnating companies and it's happening everywhere.

All of what you just said resonates with my experience so much. think I'm having PTSD, to be quite honest. So let's look at a specific example of dashboard gaming gone wrong. And I guess since we've only got a couple of minutes on the podcast, let's go for a spectacular example. If you've got one.

Hahaha

Well, in honor of your Scottish heritage, I picked a Royal Bank of Scotland example. And this is a bit of a scary one. mean, this is, we've had a bit of a laugh here and it's all about MQLs, but this is actually a pretty serious example. Now, Royal Bank of Scotland were targeting a metric of revenue per client. And that was their kind of key North Star metric that they were using to drive performance across the entire team.

And within RBS, they had this group called the Restructuring Group. And that was supposedly there to help struggling businesses. So it was ultimately there to make sure the businesses that had got into arrears that were struggling with persistent debt or whatever, that they were supposed to be helping them out. But this memo got uncovered, and this is how this dreadful story has sort of come into the public eye because it became a court case.

There's a training memo that suggested that

For any company, irrespective of whether they were complete basket cases, they needed to focus on just hitting budget. This metric of revenue per client was just as much true in this restructuring group as it was anywhere else. And the result of this is that the dashboard, this metric essentially incentivized the people in this team to extract maximum fees from these failing businesses. The result?

A significant number of viable companies failed. They were destroyed. Their credit lines became unmanageable. They went into administration. And the reason this came to public domain is because RBS ended up with £400 million in fines and huge reputational damage, all from one metric on the dashboard.

Not for the first time in the last 15 years or so talking about Royal Bank of Scotland, historically at least, that just sounds criminal.

Well, I think it literally was criminal. think that's why they ended up with the fines. But a lot of good people, people that weren't criminals, people that were trying to do a good job, people that were trying to do what their managers had asked for them, they were trying to deliver a result for a company they probably believed in, ended up doing something which probably was criminal.

They were only following orders.

So, you know, that's dashboards. That's what dashboards can do when they're disconnected from real customer value, from real measurement of the actual system performance. When they get that sort of metric fixation and...

They don't just measure the wrong things, but they actively incentivize destruction. that case, they actively incentivize things which have serious negative systemic effects on the things that the business itself or the businesses that they are serving. It's what, something we've talked about before, it's called Goodhart's Law.

When a measure becomes a target, it ceases to become a good measure. Goodheart's law is actually using a slightly more complicated language than that. But in effect, the moment you put a KPI on a dashboard and tie it to compensation, you've created a game. Now, whether that compensation is a bonus or that compensation is the adulation of your senior management team.

you're creating something which is there to be gained that there is an incentive to artificially inflate, to artificially deflate, to artificially hit. And the question is really serious in the sense that, you know, whether or not that game ends in a, you know, a $400 million worth of fines, it is almost certainly destroying your ability to create strong business decisions and to create real value within your organization.

So, and my missus will hate me for this because she really loves building dashboards. So every dashboard's kind of basic, I don't mean to be reductive, but basically a game board and successes kind of hinges on how you design the game.

Yeah, I mean, who doesn't love a good dashboard? And as we will, I'm sure, get to by the end of the episode, you know, not all dashboards are bad. This is not an indictment of dashboards. This is really an indictment of poor dashboard construction of picking the wrong metrics and structuring your compensation and incentivization of them the wrong way. But, but yeah, most companies have designed a game where departments win by making other departments lose. Marketing wins by maximizing lead volume. Sales wins by cherry picking easy deals.

wins by placating complainers and you know ideally marginalizing them so they don't appear on the surveys at all. The customer, the business in that situation they lose.

So, I mean, we all know a lot of smart executives. Surely these people, I find it hard to believe that they're just not seeing right through this and yet the evidence says that that's what's happening.

Well, they're victims of something I hadn't heard about before actually, but when I was researching some of the background for the episode of something which is called the McNamara Fallacy, really interesting one.

Or from Bob McNamara in the Vietnam War, is that right?

Yeah, I knew you'd know who that was. It was a new one on me. But yeah, making decisions based solely on quantifiable metrics whilst ignoring qualitative reality. yeah, Bob McNamara, Robert McNamara, to the rest of us. He measured the success of the American, you know, forces within Vietnam during the war on the basis of things like body count and saute numbers and

Haha.

essentially things that could be reported back from the field as a number. And he completely ignored, and I'm sure you will know this far better than me Colin, but he completely ignored things like troop morale and frontline intelligence and a whole number of other things that were coming back from incredibly experienced officers that couldn't be reduced into a number that probably appeared in whatever a 1960s version of a dashboard looked like.

And today's executives optimize dashboard metrics, you know, in the same way that they can see everything's green and, you know, head off to the golf club happy whilst they could be bleeding customers and reputation and God knows what all around them. So ultimately the McNamara fallacy is replacing good judgment with numbers.

Yeah, a Robert Magna Mara dashboard is truly like mere fuel. mean, like looking at things like kill ratios and how many hills that you've captured. And by the way, once they've captured these hills and they go on the dashboard, they abandon them and they get recaptured. I mean, we could probably just do a whole episode on some of these kind of historical and political examples where the lessons that we learn on how to build a growth system apply to sort

running a country and McNamara would be one of the many episodes I tell you. Don't get me started!

As much as you'd love that, I think we might put that in the maybe pile.

I think it needs to be a side project podcast, that one. pulling me away from the Vietnam War and ranting about Robert McNamara, sort walk me through how a well-intentioned dashboard, because we don't obviously create these things in order to drive dysfunction, but how does it happen? How do we go from good intentions to dashboard hell?

accidentally, know, innocently in a well-intentioned series of unfortunate, you know, decisions. Ultimately, all companies want the same thing, more or less. They want accountability. They want to measure performance. They want to drive good decisions. They want to be data-driven, the phrase that we hear a lot, of course.

So each department gets KPIs and depending on the strength of those departments and the way that they set the sort of the process of setting metrics.

they probably just say, okay, marketing, you know, what metrics should we be tracking to check your performance? Smart people asking smart questions to equally smart people, but often getting slightly myopic answers, know, MQLs, great, lovely. Everyone loves an MQL, right? Well, we don't, but we've talked about that a lot, so I won't dive in there. But it's because ultimately that is what exists within the boundary of marketing as the ultimate end game that the business is asking for, you know, give me leads marketing.

Great, here's the measure of leads. Sales, okay, well, what are we gonna measure? Well, let's measure pipeline value and close rate and all that sort of good stuff, great. Success, satisfaction metrics, CSATs, response times, all good. Clean, measurable, logical metrics. And the dashboard will do a really good job of visualizing those. They'll visualize progress in inverted commas. But what they don't measure, of course, is

the actual system performance.

Yes, it all sounds reasonable until you say that last part. So how does it all start to break? When can you see the first signs of the train wheels coming off the track slowly?

Well, I guess where it breaks is when you start using targets within those metrics to become the barometer of company performance as we were talking about a second ago. So if marketing needs to hit a thousand MQLs a quarter, then well, either they can work harder and find more leads.

which they probably can't do because the nature of where most leads come from, particularly in a high MQL environment is ads and they probably can't have any more budget. If they probably already worked their, you know, minds off to optimize the conversion rates and click through rates and whatever else. So what can they do? Well, they can lower the bar of quality. They can change their lead scoring model. And funny enough, you know, what was 800 might become a thousand.

And, you know, green happens in the dashboard. They probably even have these conversations with people. Okay, well, actually, we can do this and we can do that and we can, you know, maybe the quality will erode a little bit, but, you know, sales are great. I'm sure they'll work it out. Happy days.

But then if you're dealing with sort of 1,000 leads and 700 are garbage and now the dashboard is showing you're all behind in your conversion rate, then if you're the salesperson, you start to pressure prospects harder, oversell. Maybe some salespeople, some people, not me of course, might make promises the product can't keep or, know, and some of these deals will close and...

Exactly. I marketing is doing their job,

The dashboard shows green and the general manager looks at the dashboard and says, yeah, all good.

Yep, good old end of month, of quarter heroics, you we got the job done. And then of course, you know,

those oversold customers land in success and then we start measuring satisfaction scores and they're not really where they should be because they weren't that well qualified in the first place and they got oversold and all the stuff that you were just saying. well for success to keep their you know metrics high then maybe they're offering some free services, they're over servicing, they're putting solutions consultants in where they should be you know they're sending them to help center articles.

they're bleeding profitability, they are conveniently skipping people from the post-interaction surveys, and you know, customers who bought the wrong product for the wrong reason, well, they churn, don't they? And then next quarter, we've got a different set of problems manifest on the same dashboard without really understanding that it's probably those metrics that have driven the systemic dysfunction.

So the dashboard, strangely, is a kind of disguise for the problem that the dashboard itself has created, it sounds like.

Yeah, absolutely. mean, the dashboard itself is amplifying the problem. I mentioned deming, I think, in the last episode. You know, one of the things that he talked about a lot was that when you optimize components separately,

you sub-optimize the entire system. So in effect, if you build a dashboard that is departmental, the department will optimize to the performance of the departmental objectives. And there is no incentive for anybody to optimize for overall system performance for business performance.

Wow, I mean that's from an organizational sort of holistic point of view that just sounds like insanity. at that, a gaping logical hole in how to run a business.

Yeah, I mean it...

Yeah, but it happens everywhere in every business and it happens innocently. It's pretty much predictable that it's going to happen, which is kind of crazy. And hopefully this podcast could be a, you know, at least a small voice in the rallying cry to not do it this way. There's something called Campbell's Law. The more any quantitative indicator is used for decision making, the more it will be corrupted. It's kind of a different

version of Goodheart's law. You have to remember that if you misconstruct your dashboard, it is not a neutral measure of performance. It is actually an active force in warping people's behavior and driving toxic behaviors that will actually actively harm your business.

Yeah, very important to have that health warning dashboards, right? So I guess as time's cracking on and I love talking about all these kind of negative examples, but we should sort of move on to diagnosing the problem for the listener. So I guess you start just how do you spot that you have a toxic dashboard?

So I think there are a few signs, but one of the top visible ones that's kind of out there is that if you've got departments, senior leaders, department heads celebrating hitting numbers while the business is struggling, that is probably your biggest signifier of an issue. And it's actually, it's easy want to miss that because whilst it seems blindingly obvious in the context of what we're talking about in this podcast,

humans are instinctively, I think, optimistic. They want to see that that one measure of marketing celebrating success might be a signifier of our change, a changing of the wind, that things might be going our way, where actually it's exactly the opposite. So that is one that's out there in the air, out there in the world, but it's easy to misdiagnose. I think also just below that surface,

I think that if we're really honest with ourselves, most departments know they're gaming the dashboard. It's a sort of unspoken truth. And I think that, you know, culturally changing that and making it clear that that's not acceptable. think that

that is something, you know, ultimately it's not difficult to spot because people really do know they're doing it. I also think that when dashboard discussions, you know, when the meeting, when the pipeline meeting, we painted a picture of at the start of the episode, focus on explaining the numbers, you know, that is a really big red flag. You know, when we're not talking about improving outcomes and making decisions, we are justifying how we came up, you know, with our math and

And that's right up there with the big warning signs. I think also dysfunctional, indeed toxic dashboards are probably characterized by metrics that haven't actually driven any positive decision making recently.

you know, when we're all just happy seeing them go up and to the right, but we all sort of know we don't kind of really want to make any decisions based on this and do any big changes because we're not really confident in the dashboard. I think that's a quiet signal. I don't know. think probably the final thought I have and one that, you know, sadly, I think we've probably all heard and experienced is, the sort of, well, I hit my number being used as a defense.

you where you have that sort of creeping adversarial relationship between the departments of, know, great, well, I've gained my dashboard better than you gained your dashboard. So it must be your problem. You know, that really is the breakdown of all things to come.

I'm pretty sure I've had all of these in the same meeting.

Yes, it would not surprise me in the least. think we probably all have got a reasonable bingo card on those over our careers.

Yeah, I was just going to say, Chris, when we've had this position, when we've been in this position working together, we just changed the dashboard or changed the scorecard or whatever it was that we were measuring. We changed how we were measuring it. You and I and other stakeholders would talk about it and we would change what we were measuring or how we were measuring so that it drove positive decision making. So why don't revenue leaders just change the dashboard in this situation?

And yeah.

That's a great question. I think it's probably the underlying kind of psychographic kind of route of why this is a problem in the first place. Because dashboards can become our political weapons, you know, with a small p. If you had to change the metrics,

you have to admit that the current ones were wrong, that you presided over a period in the company where you were all looking in the wrong direction, and willfully or otherwise. And that threatens people who have been succeeding at playing the game. If they've been winning the board game, there's not really a lot of individual incentive to go and make it much more difficult for themselves.

And that's why we see companies adding metrics rather than changing them, I would say. The dashboard gets more complicated, the game becomes more sophisticated, the dysfunction gets worse but harder to see. I think it's really down to individuals, individual behaviors and almost probably primal response.

It's kind of like dashboard inflation, isn't it? The dashboard keeps getting more complex and then the gaming gets more sophisticated and the dysfunction gets worse and then the dashboard gets more complex again.

Yeah, absolutely. I think we'll talk about Amazon a bit in a second, but you know, as a sort of prelude to what they do. If you look at the average enterprise dashboard, it has over 40 KPIs in it. Frankly, I've seen SME dashboards that have 40 KPIs in it and they've got 10 dashboards. you know, don't think that's, I think that's a reasonably conservative number. Amazon run their entire real retail operation on 12 metrics.

So if Amazon can run a trillion dollar business on 12 metrics, why does everyone else need 40? They don't. It is a signifier of dysfunction. They need to focus and they need to put honesty at the forefront of the dashboard and system effect as people like Amazon do because clearly that's working all right for them.

Yeah, we're going to have to crack on as I think we will overrun if we sort of as always, if we don't crack on, I think I'm convinced and hopefully the listeners are as well that our dashboards are driving this function. We can admit that we have a problem, but I can hear the pushback already before the comments start. But Chris, Colin, we need metrics.

As always, yeah.

It's the first step.

So how do we design dashboards that actually work?

Okay, well it's quite easy actually. It's almost formulaic, which is a good news, we like that. Very often the answer is it depends, in this case it actually isn't. Never put a single metric on a dashboard without its sort of antibody, you know, without its counterpoint. Every metric should have a counter metric that prevents gaming. It's a safety net that needs to be built into your dashboards.

So give me an example, I'm trying to sort of, the wheels and cogs are spinning in my head trying to think of an example of this antibody metric.

Okay, well, here's a good one that we use a lot. So demo booking rate, you know, we work with a lot of B2B SaaS companies, demo booking is obviously a big driver of ongoing performance. Good solid metric, right? Well, if you put it on the dashboard alone, then...

What does your team do? What does your SDR team do? Well, they book a demo with anybody that has a pulse. They tie up a load of time with solutions consultants and AEs, showing the system to people who realistically have no perspective of ever buying it. So what do we use as an antibody then? Well, we use things like...

qualified opportunity rate, or we do a more simple demo attendance rate as a good solid counterpoint metric. It really depends what kind of dysfunction we are trying to diagnose, but could be eventual close rate from demos specifically booked by a certain team. You have to think about what problem you're likely trying to fix, but ultimately,

If we think we're overbooking demos and people aren't turning up, put attendance rate. If we think we're booking demos and they're converting at the wrong rate, then actually put the qualified opportunity rate in. Whatever you do, make sure that you've got a metric pair or more that enforces truth and prevents gaming.

So in a way we sort of pay our metrics to create sort of, I guess what you might call in politics, checks and balances.

Yeah, exactly that, exactly that. I mentioned Amazon a minute ago. Their dashboard doesn't show stuff like MQLs. It shows controllable input metrics paired with output metrics. Controllable input metrics, I'll say that again, because controllable is the important word. So what they also have...

is an autonomous finance team. This only job in the whole company is to detect gaming. Really interesting. Probably not a luxury that most businesses can afford, but their only job is dashboard integrity. And

The purpose of this really is that not only do we have checks and balances on the dashboard, but we also have it in people's job role. People do what they're measured on to make sure that the anti-gaming control is working.

So it sounds like these, I'm just going to playfully characterize them as this dashboard police auditing definitions and investigating these anomalies and calling out gaming and making sure you can't game what they're actively monitoring. It all seems like kind of like an overhead essentially that a lot of businesses might kind of bulk at the idea of.

Yeah, and I think for most businesses having dashboard police as a job title probably is an overhead they can't afford. But I think if you wanted an analogy, you could probably call this an overhead much like a roll cage is in a racing car. It doesn't really serve a purpose until it does and then it stops you dying. So yes, you might even go faster without them. That bit of weight in the car might be slowing you down a bit.

But you really, really want it when you hit the wall. And when you think about companies that have actually implemented this kind of structure like Amazon, yeah.

If they tied 30 % of marketing comp to pipeline quality, not MQL volume, then what would the result have been? If they had added lead response times to sales dashboards, what would the behavior around those MQLs have been? If they'd created shared revenue dashboards everyone can see, then most likely we're going to increase pipeline velocity. We really need to think about that system effect and how we can work different metrics together to create behaviors that are

positive.

So you can literally change what the dashboard measures and effectively change the behavior, which is effectively like a positive example of what the problem is, right? If you create the wrong dashboard, you'll change behavior in a negative way. We could probably...

Yeah.

go on about this for a whole episode. But we should probably crack on. thought you might, while we're still on this part of the episode, it be good to talk about shared metrics across departments, because that really kind of gets to the heart of the problem and something we've talked about in this series around silos.

Yes, yes, yeah, yeah.

Yeah, absolutely. And it's a great question because your dashboard should show metrics that nobody owns alone. As much as I'm a big advocate of every metric having an owner,

Shared ownership is a really, really interesting concept because it means that you immediately, you know, cut the, well, I hit my number conversation off at the knees. You know, if you kind of think about things like revenue per lead,

then you can't just game that with volume. Sales can't game it with cherry picking. Customer success can't get to it purely through discounting. Everyone actually has to collaborate to move a number like revenue per lead. It's a really interesting one. Not necessarily one that fits everybody, but when you start creating some of these anti-silo metrics, as I'd call them, and you partner that up,

you know, with with symmetric pairs in the department, you can really start shaping behavior. Because as we've said a million times on this podcast, people do what they're measured on.

Indeed. Something that, again, I think everyone will be thinking about here, Chris, is that somehow AI, without really thinking about how, people are going to be thinking, well, can't AI fix this sort of problem with me? What about AI and dashboards? Everyone's talking about AI-powered analytics and so on. I wonder if we could say a bit about that before we can back on to the next section.

I mean, it is a massively growing...

know, sector within the market, there's a huge amount of investment going into kind of AI within business intelligence. There's some research for MIT actually here that's fascinating. know, companies using AI to refine metrics, not just track them, are three times more likely to see benefits. Now, I think you could remove the word AI from that and it would still stand up, you know, companies trying to refine metrics, not just track them, are three times more likely to see benefits. So don't think that's purely an AI thing, but AI

certainly an enabler because AI is pretty good at data crunching. It's quite cheap at doing that. And it can, if you tell it to think about system effect, it will. yeah, the good thing with AI is doesn't just visualize data. It can, if you tell it to detect gaming patterns and it can suggest better metrics. So if you use it as a tool,

to identify metrics that stop predicting success or indeed incentivize negative behaviors. That's great. And I think AI is an accelerator there, but the behaviors don't require AI. I think that's quite an important distinction.

AI, I mean sometimes AI as we know, especially LLMs can be the sort of ultimate yes man, but if you, with the right grubting and training, it can become the kind of anti-gaming mechanism effectively. Or certainly support the anti-gaming mechanism.

Yeah, absolutely. Yeah, absolutely. Don't misconstrued me as being sort of negative about AI. I think that's going to have a transformational role. And there are some examples where it is having a transformational role. think Wayfair have talked about how much success they have had with it because they have tried to, through their sort of data centralization efforts,

they have tried to bring contextual information into their reporting. So, you know, they've looked at things like, you know, deeper customer insight, like if a customer didn't buy that sofa, but they bought a different sofa, you know, that might be a lost sale or it might be category retention. And I think that when you kind of look at the

The dashboard, they've tried to make it smarter and try to look at that broader business context down to a customer level and use it to kind of surface insight around the metrics. I think that's quite interesting. It certainly made for a good case study. It'd be interesting to know how much performance that's driving, but certainly the intent is really interesting.

Yeah, that is really interesting and obviously a fast sort of evolving space as well. Before we completely run out of time, we should really get on to some practical advice for revenue leaders listening to this. We always spend a bit of time kind of on theory and examples and on diagnosis, but of course we also try to spend some time on giving some practical advice. I think a good way to start would just think.

What's the minimum viable dashboard? I was actually quite surprised by those stats where Amazon run the business on 12 KPIs. Quite complex business, that's been impressive. So what's like the minimum viable dashboard?

I think there's a few different levels to that and it's, you every business is different. So, I mean, this probably is a bit of an it depends, but I think structurally I love a North Star metric that everyone shares, particularly within the growth team. So yes, that can be stuff like revenue or customer lifetime value. It can be more activity-based, but you really need to make sure that it's

underpinned, know, we're leveled down by, I don't know, three, five input metrics that you can actually control, and a similar number, you know, three to five guardrail metrics that prevent gaming. I think that's it, you know, if we've got a unifying North Star that takes the silo out, then we're measuring people's inputs and outputs as a metric pair underneath that, and we're spreading that across the team.

and we're really, really thinking about what measures system effect and creates value within the business. I think if you've probably got more than 15 metrics on your dashboard, then you're not honestly driving performance from that. You're hiding, you're giving yourself good news stories. If we get down to the sort of brass tacks of what's actually...

impacting the business performance positively, that's probably not a lot of numbers and if you're pairing them up and unifying them up to a north star that's probably a pretty good start.

Yeah, agreed. So as I say, we're onto this part of the episode where we like to talk practical advice and like to keep it simple. I'm just going to make that even harder today by saying we could probably run to about five minutes for this section. And I know that you probably, especially with all the work with Rebspace that you're doing at the moment.

and we've had some interesting chats about that. You could probably talk for 45 minutes about this, but what do I do tomorrow if I'm a revenue leader and this all resonates with me?

Put your deerstalker on, become the revenue police, become the gaming detective and audit what's on the metric and reverse engineer it. Ask yourself, if I wanted to game this metric, how easy would it be?

you know, if we solely optimized for this, what would break elsewhere? And I think if you find that the answer is easy to come to and the answer is slightly scary, then you've got a problem and you either need to have a metric peg, you need to have the antibody, you need to have a counterweight, or you just need to get rid of the metric entirely.

Yeah, so what about political resistance? is the biggest source of inertia that I can think of as people whose very sizable bonuses and probably keeping their house depend on current metrics not changing. And of course they would want the metrics to change because, you know, I hit my number.

I think my instinctive reaction to that is, yeah, you've got to just tear things up and do what's right for the business. Politically, that can be difficult in itself, depending on your position. think as a, being the leader of a business without any shareholders, I can make decisions in a different way to if you're running a...

a Fortune 500 company which has a lot of vested interest, shall we say, within it. But if you want a slightly more moderate answer, then I think that experimentation, maybe run a shadow dashboard. Have a bit of a special ops dashboard and compare the two. Do what you think is right with the metric pairs in the North Star and track that.

see what your siloed dashboard that's in everyone's best interests is hiding. Data wins arguments and I think that what can, in this scenario, what has been seen cannot be unseen and I think you will come to the right decisions following that.

So seems to be Chris sort of cracking on a bit towards the end of the episode that what we're talking about here is a need for a complete sort of cultural flip in the organisation. Maybe we need to change the conversation, ban the phrase, but I hit my number as a defence and replace it with, here's what we learned, make dashboard reviews about insights and not...

interrogations or apologies or explanations of the numbers.

On that explanation of the numbers part, suppose we need to think of someone misses a metric, but learns something valuable. I they're typically I've seen a culture where we try to kind of save the best from that, but we're not really celebrating the learning that what we come away with is this horrible feeling that, we missed the metric, but we actually need a cultural flip to where we, where it's essentially about being a learning organization.

Yeah, it's such a good point. Such a good point. And I think, you know, we need to dive into this more in the next episode. But yes, absolutely.

A cultural reframe is what is required to change those behaviors. And that comes from acceptance. comes from, you know, instituting psychological safety across the organization and ultimately saying that, you know, we need to become a learning organization, not a gaming organization. We need to prioritize learnings as a win, as you say. You know, we need to stop using our dashboard to manage people and use it to manage system effect.

Yeah, I think that's a good point to kind of head to wrapping up really. As I said, there's and as you said, there's there's it's a rich topic. Once again, there are probably uncovered like three or four subtopics that will probably become episodes at some point. As usual, let's just kind of crystallize this. So companies, think, as we all know, are drowning in this dashboard dysfunction and they're

kind of hiding behind those very same dashboards to say, but I hit my number, look, the lights are green, it's up and to the right, everything's okay. But I think underneath we all really know that we're measuring the wrong things, we're incentivizing gaming the system, we're destroying value, and we're celebrating these green lights and up and to the right graphs. It seems that what you're seeing is the solution isn't more metrics, but just better designed.

pair metrics with counter metrics, create a sense of shared ownership. And something that you've talked to me about that I had never really thought of before, is of killing off the zombie KPIs. you know, if a measure hasn't been driving decision-making for a certain amount of time, then you should kill it, right?

Yeah, exactly. You know, for me, the crucial point and the crucial takeaway, I think, from this episode should be that your dashboard is to a degree a manifestation of the culture of your business.

And you need to be happy that not just as you're driving the right behaviors, but it's signifying that culturally your business is operating in the way that you want it to. Because it shapes behavior, it is part of the sort of the values of your organization. Are you prioritizing?

management of people, are you giving people incentives to, you know, mark their own homework or are you really about creating meaningful change within your organization and getting on towards

the things that you want to achieve and the growth that you want to achieve with your business. You have to understand and you have to decide culturally whether you want an organization that rewards truth and that you've culturally got truth and system performance and value creation in the heart of your organization. Or if actually you just want to feel good that, you know, the people are supposedly all contributing with, are we measuring the cogs in the machine or are we measuring the machine itself? And I think that's a cultural decision as

So basically you can design dashboards to actually reveal reality and not hide it. Which there'll be a few people listening that might be a bit of a scary prospect, right? But what do? I think with the trillion dollar figure there should perhaps be a bit of a wake up call and maybe one to pull out, a stat to pull out when you get some pushback in the meeting on Monday morning.

Indeed.

Absolutely, and I think it really does come back to those numbers because companies with aligned dashboards with metric systems that actually work 72 % more profitable. 72 %? I mean, that's nuts. They move 40 % faster, they retain customers for longer. And ultimately beyond those numbers, they are places to work.

that ultimately are more rewarding because they reward the right behaviors. So really, you know, why wouldn't you want to be doing that?

Indeed. Chris, I'm going to stop us there. As always, we have overrun, and I'm sure we've got lots more to say about the topic. For those listening, you've done this, you're mapping your metrics and you're becoming the dashboard police in your mind and you've found gaming behaviors that are destroying value, good time for an intervention. You could head to Rev.space and book a session to speak to Chris about growth system design.

really to help you identify which metrics are secretly sabotaging your growth and of course actually design ones that will drive value. That's all we've got time for this week. How to build a growth system is as always brought to you by RevSpace, a growth systems consultancy that connects B2B organizations with the future of growth. So RevSpace offers account-based growth managed services.

and go to market engineering projects. Please don't forget to follow and rate the podcast. It really helps us to bring the content to a wider audience. I'm the host Colin Shakespeare and as always joined by Chris Bayless. We'll be back next week. In the meantime, remember your dashboard is not neutral. It's either driving truth or it's driving theatre. Choose wisely. See you next week.

See you next week.