Colin (00:03.331)

Last time on how to build a growth system, we talked about dashboards, the big shiny dials that everyone stares at and kind of measures their success by in many cases. But here's the thing, the dashboards aren't actually what moves the business. They just really just report the news.

Chris (00:23.714)

Yeah, exactly. You know, we all love dashboard, right? And a great dashboard, you know, can be a really, really powerful tool in a business. So we're not knocking them, but this episode, it felt like the natural extension of what we were talking about last week to really think about the signals underneath the dashboard. You know, whether that is simple stuff like click or customer apply or a system alert or, you know, a churn figure.

They're the levers that we can actually use to understand behaviors and to pull in certain directions to actually change the behaviors that drive performance within the business. So we're going to dig into that.

Colin (01:08.015)

So we always like to define these problems from a systems thinking point of view and those who have been listening closely over the months will probably have guessed what we're talking about here and that's feedback loops. So for those that don't know, what are we actually talking about when we say feedback loops?

Chris (01:29.762)

Well, a feedback loop in really simple terms is a raw signal within the business that we turn into action. And ideally, when we turn action into learning. And you know.

Today's about how we build loops that can honestly make your business faster, smarter, harder to knock off course. So, yeah, they're a really important thing that's happening all the time and people don't necessarily think of as a sort of force or an entity within their business.

Colin (02:06.619)

I guess it's important to point out that feedback loops basically exist whether or not we actually choose to act on them. But what we're talking about today is kind of about how to harness feedback loops essentially to drive growth around.

Chris (02:23.564)

Yeah, that's exactly it. So you've got a feedback loop when an output feeds an input in simple terms. you could think of them as the of the control wiring of the business. And yeah, as you say, feedback loops exist whether or not we choose to act on them.

Feedback loops are working on your business right now while you're listening to this. They are a sort of pervasive, multi-layered entity which is acting everywhere, positively and negatively. And in a system thinking sense, feedback is simply information about the system's past behavior influencing its future behavior.

So if we think about that in sort of biological terms, your body is sweating. That's a feedback loop. Because it's hot. You know, that's the data point.

We also have that and we talk about in insistent and we love using the example of a thermostat in a room. The thermostat is there to switch the boiler on when the room gets too cold, it drops below a certain level, the thermostat feeds back to the boiler that it's dropped below a threshold and then we're going to turn the boiler on, turn the furnace on, turn the heat up and when it gets back there, we're gonna switch it back off again. That's a sort of mechanical feedback loop in action.

But in business, you know, we talk about feedback loops, things, really simple things like customer reviews. You know, the more good customer reviews you get, the more future sales you're going to get. The more future sales you get, the more reviews you're going to get. And if you keep doing a good job, you know, that's going to be what we call a compounding feedback loop. It's going to keep doing good things that's going to accelerate away.

Chris (04:13.518)

And when we think about things like customer churn or employee morale or word of mouth referrals, the business is full of latent loops. And all of these are feedback mechanisms that operate continuously, whether you're paying attention to them or not.

Colin (04:29.357)

Yes, can already hear those who haven't thought about this too hard in the past thinking, wait, I need to be collecting like even more data points now and putting them on a dashboard. Is that what they're going to tell me?

Chris (04:44.406)

Yeah, I mean, it's a tempting way to think about it, isn't it? But a metric only really becomes a loop.

when it reliably triggers a decision or an action. Otherwise, it's just another number on the dashboard. And we talked about trying to limit those last week. But actually, some ways, a metric is really just the sort of, I think about like we talked about central heating system. It's kind of like the gauge that's on the pipe that's measuring the pressure or whatever. It's really just there to measure the loop, to measure the strength of the loop. And that's a good way, I think, to think about constructing dashboards as being a mechanism

measuring positive and negative loops within the organization.

Colin (05:29.273)

So thinking about, obviously there's an almost, not quite, but an almost sort of infinite amount of things that we could potentially measure that may or may not sort of, we could maybe use to sort of trigger a decision or an action or influence how we run the business. But so where do we kind of plant the flag? What should we be looking at?

Chris (05:54.446)

Well, I think if you want the evidence really for why listening to feedback loops and trying to harness them as a good idea, you know, I briefly touched on kind of customer churn. And I think churn is a really, really important, interesting, pervasive loop.

Colin (05:55.117)

metric wise in order to.

Chris (06:15.982)

that's visible in most organizations, and particularly if you're in the SaaS industry or something where you probably have quite a high customer count, churn is a really, really big deal. And when you look at churn, then you've got a loop when that churn figure creates action.

And indeed, you also have another kind of a loop, which I guess we'll talk about in a second, that might actually be creating the churn in the first place. So when you actually keyed into that, when you really start seeing that for what it is, then seeing double digit lifts in retention is not uncommon. If you start seeing the problem through the view, through the paradigm of it's a loop, balancing loop or a reinforcing loop,

then you can really start to create really powerful impact within the organization because you start to understand cause and effect. And that's a really, really key thing that, of course, we all strive for as business people, as leaders, as operators. We really want to understand what inputs create what outputs. And a feedback loop is really just a mechanism for talking about and measuring that.

Colin (07:33.999)

Yeah, so I'm going to jump in here on behalf of the lay person. you've we've introduced the idea of feedback loops, but then already a few minutes in you've mentioned that there's different kinds of loops reinforcing and balancing. So it would be good if we could sort of put a bit of definition on that for those who are for the uninitiated.

Chris (07:52.974)

So a good way to think about.

A reinforcing loop is something that amplifies change. So the more it happens, the more it continues to happen. Like the referrals and kind of word of mouth and often the sort of example I used earlier, some people might call it a networking effect. A balancing loop counteracts change. So it pushes the system back towards stability or to equilibrium. So a thermostat is a really good example of

a balancing loop. know, it's job is to always keep the system in its kind of equilibrium state of, you know, just the right temperature. And, you know, we can think about that in terms of kind of rate limiting or capacity constraints. as growth teams, know, really what we want to be doing is accelerating the right reinforcing loops and preventing the negative side effects.

that can be created by not having the right to balancing loops if that's not too much of a sort of double negative. know balancing loops can be really really positive you know just because it's pulling something back I think that's easy to perceive that as negative but actually balancing loops also have a really strong role in stability.

within the organization, they stop things running away with us. the important thing, I think, to note with both kind of loops is that both can be positive and negative. You can have reinforcing negative effects. A really good one within the sort of field of growth, of course, that we love to talk about is things like reducing marketing budgets.

Chris (09:42.422)

If you reduce marketing budgets and assume your marketing team is effective, which I'm sure everyone's that are listening to the growth systems are, then you are probably going to have less leads and less sales. And if there are less sales, there is less revenue. And if there's less revenue, there's less marketing budget. And so the spiral continues. So that is a reinforcing loop, but a negative reinforcing loop. And when you talk about runaway claps, actually, that is often a negative reinforcing loop at work.

Colin (10:12.431)

Yeah, that's what I was thinking. Like I'm really interested in stuff like sorry to diverge from the sort B2B chat for a second, but things like natural history, like the natural history of the earth, where we have these sort of balancing loops where, say for example, the world has incredibly high carbon dioxide in the atmosphere and therefore we get lots and lots more plants which then lock up loads of carbon and then balance out the temperature and stop us going into a runaway process. And of course there's now

Part of what the arguments are about in climate science is are we now entering a of runaway process like a negative reinforcing loop? So that's what it sort of puts me in mind of immediately is that there's a lot of examples from life, not just from the B2B world.

Chris (11:06.915)

Mm-hmm.

Yeah, exactly. Often I think in business, it's been popular in the last couple of years to talk about the sort of flywheel effect. know, HubSpot spent quite a lot of time talking about, you know, the flywheel. A couple of years ago, I'm not sure it's something they say so much now, but really that...

Colin (11:29.695)

Rather than, as opposed to a funnel, say for example, talking about sales process, they don't imagine it as a funnel, imagine it as a flywheel. Basically what they're describing is a positive reinforcing loop, right, for anyone who's familiar with that, they'll know what we're talking about.

Chris (11:43.17)

Yeah.

Exactly that. Yeah, exactly that. But I think what that sort of view of the world perhaps misses is that you have in a business lots of different feedback loops working at the same time. So, know, loops interact with each other. And actually, flywheel effects are a really interesting one because if, for instance, you...

know, more money on marketing, means you get more customers.

which means you push more volume into your onboarding team, which might slow down their capacity to onboard people, which might make customers unhappy, which might promote earlier churn, which might then slow down your overall ability to accelerate revenue. So you have a, you know, a reinforcing loop, creating a balancing loop in that scenario. So we're talking about a lot of concepts that are very everyday in business.

but when you relate them to this of thought of the feedback loop, then you can start to sort of harness where that system effect might impact you later on and use it as a predictive indicator.

Colin (13:01.953)

Yeah, and that's a good point that we are sort of at that stage of the episode where we're always speaking in quite conceptual terms. What might be good is just to move on to sort of how we can sort of run a diagnostic, a sort of audit of the loops within our businesses and sort of, I guess, kind of stress test our loops and really map out what's happening in the system. I guess we would need to

do that before being able to really harness feedback loops for what we want, for the outcomes we want.

Chris (13:43.724)

Yeah, absolutely. mean, I think that it's, there is a truism in, in the fact that, you know, to really see something you need to be able to measure it. And what we know we have these loops acting in the business 24 hours a day, you know, that in positively and negatively and all across the different departments and activities that we do.

So if we start relating that back into sort of the practicality and perhaps even back towards the dashboard, our ability to really harness this information is to be able to capture it. And what we need to be thinking about is the sort of latency that we have within the system in our ability to capture it. So...

If we think about the sort of various stages that we have within this process, you know, we need to be able to measure the signal. So there's going to be in a time between the event happening and the signal reaching us. And as we talked about at the start, lots of loops go unnoticed, you know, they go unmeasured. So actually that's the time to signal is almost infinite because we don't actually detect it at all.

So one of the first things I think is really then starting to go, well, what is my ability to detect the signals in my business? You know, they're really, really noisy, you know, businesses. There's lots of signals going on. We talked about getting down to 12 metrics or, you know, there or thereabouts, but what should I be listening to and how quickly can I measure that and, you know, and learn from it? And I think that learning piece is, is key because actually if we can turn signals into actions, then we've got a

go through sort of insight and decision making first. what is my mechanism within the organization? Not just to hear the signal, but to interpret it, to turn it into insight and then to turn that insight into decision making and then that decision making into action. You've got sort of a four-stage process and of course in every business you have a degree of kind of latency between all of these stages and the trick is

Chris (16:02.318)

to understand what the right amount of latency is. So if we've got, we're talking about churn numbers and we're in a fast-moving SaaS business, if we're only measuring churn once every three months, then you know that is really historical.

know, the amount of customers we might have lost before we realized that the churn signal, you know, was heard by the business. Because then, of course, once we've known that there's churn, well, okay, well, what's the insight from that? What other loops were acting on that? We need to go do the systems analysis.

to make a decision to take action, you know, could have a really long lag on that and you could be losing hundreds if not thousands of customers during your time, your sort of your process of going through those four levels. know, with things like Churn, we want to hear about that every week, probably, if not every day. I mean, it depends on the scale and sort of throughput of your business.

So, you know, it will always depend what the right kind of level of latency is, but, and it will adapt and it will sort of, you know, be right size to your organization. But ultimately, if we can see it and we can measure it at the right speed, then we can act at the right speed. so I think when we kind of get into the practicalities of it, what we think, okay, well, what are my kind of critical metrics I've got on the dashboard? Yeah. What do I really want to know about the health of the business? Then we can think about, okay, well, what, what are the sort of feedback loops that are.

empowering that, are constraining us within that process of driving understanding and driving change. And once we have that understanding, then we can start putting in the diagnostic tools underneath it to make sure we're listening to the right stuff.

Colin (17:53.421)

Now, on that listening to the right stuff point, it strikes me that your churn example is quite an interesting one, because of course, even if we're reporting on churn or looking at churn on a daily basis or whatever, I will immediately go to the you don't have churn every minute, it's always going to be this sort of lagging historical indicator and what we really need to think about in the case of churn.

is what leading indicators might help us to trigger actions which might prevent churn. So it got me thinking, I don't want to go down that rabbit hole and make it all about churn, but it got me thinking about the signals that we miss on dashboards. So like the loud stuff like churn turns up on charts, right? But a lot of the useful stuff.

like in the churn example where what leading indicators might we look at, qualitative data might we look at to figure out when churn is going to happen and therefore take action to prevent it. I want to dive into where do we look for those sorts of signals if that's not divergent from the main topic too much.

Chris (19:09.536)

No, it's a great question because dashboards are almost by default numeric in nature. You know, they are calculated fields, are percentages, they are absolute numbers, they are the change in state from one month to the next and therefore they are sort of inherently quantitative.

and the quiet signals are almost always qualitative. So, if we're looking at that churn example, then we can see churn, probably see MPS, we CSAT as a score, that's all in the sort CS dashboard. And those might be good predictors of churn. mean, in my experience, MPS is a really bad predictor of churn, but we can save that for another episode. But what is probably...

Colin (19:57.594)

Hmph.

Chris (20:04.012)

the hidden gold, the quiet signals that really will move the needle in understanding and taking insight from the signal might be transcripts from support calls. They might be the categories that you get around support calls.

They might even be things like sales call information. Are we hearing in our sales cause all the time, do you have this feature or that feature? well actually, competitor A has got that. Well, that's probably a signal that we've got out there that's...

you know, that's kind of telling us that perhaps there's been a change in the market dynamics, you know, suddenly something that's really important to people. We've missed the boat on, you know, we haven't been listening to our customers well enough and using that to inform our development pipeline. it could be stuff like product reviews. could be just sort of, you know, community chatter, whether that's in a forum or at our conference or at a wherever.

They're pretty weak signals by themselves. One review, one support call transcript might not tell you much, or it might not be very reliable as an indicator. But if you can listen to those en masse and you can interpret them...

then really they can be very strong heuristics which drive us towards better decision making and almost always those sort of things don't appear on the dashboard. So it's a really good question and a really important point to make sure that we've got keyed into as organizational change agents.

Colin (21:41.711)

Otherwise these weak signals end up becoming sort secondhand anecdotes from the one person who's got a view on a particular weak signal or soft signal. We maybe need a place to kind of aggregate those weak signals or at least a place for them to live where somebody can kind of read them or perhaps we train, I'm nervous about this, but AI tools to do that analysis at scale for us.

Chris (22:06.742)

Yeah, mean, dashboards are sort of inherently past tense. know, yes, you can put some leading indicators on them, but often they are very lagging.

in nature, you if you can interpret some of these signals correctly, then they can be good leading indicators. You know, we can start to see a groundswell of a problem happening in the quiet signals. So it's not an easy thing, but absolutely AI, I think, does offer us the ability, maybe not easily, but certainly plausibly, to start interpreting that amount of information at scale. And

Yeah, we've increasingly seen that happen in the sort of CS world with things like sentiment analysis live through AI. That's predominantly being used for core routing and how we then sort of triage. But also it can be used as a reportable metric. But actually...

AI is pretty good at picking up instances of certain words and algorithmically you can definitely train it to kind of think about are we hearing about competitors, are we hearing about certain brands, are we hearing negative sentiment, are we hearing whatever it might be that might be an indicator that we can start to pick up on and start to report on. So yeah, these things are more possible now than they've ever been.

Colin (23:37.569)

Yeah, I'm still nervous about these sorts of things. I'm not going to start uploading my call transcripts a chat GPT-5 or something like that to look for signals. I'm not sure we're quite there in terms of the maturity of this technology, but I feel like particularly when we're speaking about, like recently I've done some work with large enterprises that have like 11,000

sales people and incredibly complex sales cycles and things and customer journeys and I'm thinking there needs to be that probably a place for weak signals to live where that person reads them and advises on action is probably not a scalable design there.

Chris (24:27.116)

Yeah, I think what's interesting about when you have that kind of scale, the feedback loop actually needs to be listening to the people on the ground, you know, and it's probably tempting to do a complex AI project, but

But actually, know, the artificial intelligence tends to be, you know, pretty expensive and not always that reliable in those kinds of things. But human beings are actually pretty intelligent themselves. And actually, if you speak to some sellers and they'll say, oh yeah, well actually, you know, the last 15 calls I've been on, well, 10 of them kind of mentioned this thing. And then you put that into a forum and then you aggregate that across, you know, your selling community or your CS community, then, you know, then you can really take some insights

from the quiet signals and actually that is an instance where you need to create a feedback loop. Often that information can just stick, it can stick in one part of the business or perhaps it's discussed by the water cooler or between the particular management layer but it's not actually fed into different parts of the business that can act on that signal because if we're hearing about a feature then

good seller you'd like to think if they hear that enough is going to report that to someone but it's not necessarily going to be the case and someone's not necessarily going to listen to them but actually if we put this kind of you know operational retro process in we put this kind of you know

360 kind of view of the problem in place and we implement that through some sort of a traditional feedback process, then you can start to kind of build on those signals and really hear them more clearly.

Colin (26:16.927)

Yeah, it seems to me that though these sort of weak signals or soft signals that we're talking about tend to get, although they're kind of seen as useful and nice to have, they tend to get downgraded compared to those big loud metrics like, you know, annual contract value or churn or something like that on a dashboard. And we don't really, a lot of organizations aren't really aware of sort

frameworks and concepts that they can deploy to make sure that they're integrating all of that, all of those signals and knowing where to act on feedback loops and things like that. What might be quite good at this stage is if we start to connect all this that we're talking about to how companies can actually use this understanding to beat their competitors effectively.

what they can actually do about it and why I guess.

Chris (27:20.866)

I think that whether we're talking about, you know, signals that you can detect with data or ones that you have to listen carefully to, we still have to create the operational processes within the business that are going to enable us to not just hear them, but to act upon them.

And I think that's why that kind of has talking about the sort of, you know, levels of latency between hearing the signal and dividing insight from it and, you know, deciding on action and then implementing that action. You know, we can kind of express that through things like build, measure, learn or

observe, orientate, decide and act or, you know, sort of the IDS process. You know, whatever you're doing, we really need to do it in a way which is repeatable and scalable and has the authority and ownership inherent within the people operating that process to ensure that it that we do get value from it.

And I think for me, the, the competitive advantage only really occurs when your teams are enabled and given the ability and the authority to not just listen better, but to act faster and to

Colin (28:51.181)

Yeah.

Chris (28:56.13)

you know, have the time to sort of diagnose issues and to act upon them. And, you know, there are lots of ways that you can do that, but ultimately, the smaller we make the loops, the more we can act on them in a way which is concerted and kind of committed and logical, the better.

I would put a slight health warning on that without wishing to go too deep into kind of systems theory basics that there is in feedback loops a concept we haven't talked about and I don't think we should probably talk about in this episode too much of delays and oscillations that sometimes acting too fast is just as bad as acting too slow, which is a funny thing.

But the example that's often used with that is in retail. It's like an average order over a week. If we normally sell one widget a day and suddenly one day we sell five widgets, well, our order rate has increased fivefold. So if I then normally order seven widgets for next week and then I

order 50 widgets, then I'm going to have an overstocking issue, which might mean then I have to balancing loop kicks in where I'm going to start then discounting my widgets and overall over the month because I listened and acted too fast, I'm going to sell the same but make less money from them. So a two second example, but I do think that the way that we act and the speed at which we act has to be

balanced against our capacity to create oscillation within the system.

Colin (30:48.803)

Yes, it's all about that sort of calibration. It's not all just about moving as fast as possible.

Chris (30:57.228)

Yeah, yeah, exactly that. mean, I think it's great to measure fast, but we shouldn't doesn't mean we should always act fast.

Colin (31:05.775)

Yeah, that's a really important point in our industry of move fast and break things. Perhaps this might seem initially like a sort of counter-intuitive concept, but I think your retail example is a really good one. think everyone should be able to understand that pretty simply. I will try it out on my six-year-old and see if he gets it. And then we know it's spill-proof.

Before we run out of time, as we usually do, it would be great if we could dive into some practical advice. think everyone listening can kind of see the value in what we're saying. But then again, I think there's a bit of a gap in terms of sort of practical advice out there into how to put some of this understanding that we're helping people with.

to good use.

Chris (32:06.412)

Yeah. I I think if you want to start harnessing the power of feedback loops, then, and I don't just mean, you know, feedback from the team as we use an example there, but, but it could be, you know, an order rate or a churn rate. then what I would be looking at is, particularly in a growth team context is thinking about the customer journey.

I'm really starting to isolate parts of our customer journey where we're going to have feedback loops at work. And I would start to drill down into those and initially just start thinking about cause and effect. So, you know, if we have got leads, say really simple example as being a part of that journey right at the start.

then we should be able to start defining what the balancing loops and what the reinforcing loops are acting upon our leads pipeline. And then I'd start mapping those out. So, you know, budget could be a reinforcing loop, seasonality could be a balancing loop maybe. And then I would really start looking at how to measure what those loops are telling us.

and I would start thinking about our sort of, you know, signal to insight, the decision to action kind of latencies, how quickly should we be acting upon those, know, how quickly are we doing it now? And then I'd be thinking about, you know, which of those feels like it's having the biggest unmanaged impact on the problem at hand? You know,

in a media budget, then, you know, sorry, in a sort of media driven leads example, then turning the budget up should probably turn the leads up. You know, that's a, you know, that's a simple reinforcing loop. But if we are

Chris (34:19.57)

in certain industries maybe in B2B, you know, what might be holding us back in there, you know, are there certain market characteristics, there certain market dynamics? You know, if we start thinking about what is impacting those and what we can change, then if you pick somewhere that you can then start thinking about making an impact, then we can start creating some kind of guardrails around that.

we can start measuring the inputs and the outputs, much like we talked about in dashboards. And then we can start experimenting for, you know, what made it go up? You know, what accelerated the positive reinforcement? You know, what perhaps slowed it down? And that's something where we can then start thinking, okay, well then suddenly we've moved from having a metric, how many leads do we have, to understanding the loop that is powering the leads.

And then the sub, you know, the levers we can pull to accelerate or break that force, whether it's a positive or a negative. And if we start unpacking the problem like that and unpacking the customer journey, then, you know, I would start doing that in sprints. You know, I would put that into a sprint process. I would build a hypothesis of things that are going to be impacting those balancing and reinforcing loops. And I would start experimenting and, you know, sort of testing, measuring and learning.

Colin (35:43.405)

Yeah, it's funny when you're talking about creating the right guardrails there, it kind of cast me back to last week's episode about the dashboards and thinking about sort of pairing those make it go up metrics with the with don't break it metrics as it to create your own sort of checks and balances if you like.

Chris (36:09.004)

Yeah, absolutely. So I imagine we are probably getting to the point where we need to start wrapping up.

Colin (36:20.583)

We are actually we have a few minutes to go, but yeah, we should probably start wrapping up. So. Do you have any? Anything I guess that we've not covered so far that you would want to dive into? We've kept it fairly fairly concise for us today.

Chris (36:42.734)

Chris (36:46.806)

Yeah, I think let's talk very briefly about some diagnosis because I think we've talked about kind of what loops are and maybe how we can start harnessing them. But let's talk about some sort of failure modes maybe.

Colin (37:04.604)

So when stuff breaks, if you like.

Chris (37:07.65)

Yeah, exactly. And I think when stuff breaks in terms of how we're harnessing feedback, it's normally for one of, you know, a couple of reasons. And one of those is around latency. You know, we talked about that a little bit, is that we're listening too slowly. You know, we're kind of fighting last quarter's battle because the, you know, the time to signal

is just too long. So if we can increase management frequency in that kind of scenario, then we're kind of managing that kind of latency in a way that's going to give us more relevant information to kind of take forward. Another kind of failure mode that we see a lot is that the loop is just too noisy and dashboards can be a of agitation.

Colin (38:04.975)

higher hose of metrics.

Chris (38:07.254)

Exactly, you if we've got too many metrics and none of them are really decisive, then ultimately we are going to not hear the signal clearly enough. We're not going to know what to add on because we have too much signal noise in there. And then I think kind of the final failure mode that we often see is just that we're listening to something which is just not really relevant anymore.

Maybe there's a signal that does exist and just no one's there. We kind of haven't got an owner to act on it, but more often than not, it's just because we're listening to something that's not really a relevant signal. It's kind of a dead loop. So I think when we're trying to diagnose what is going on and how we can really start harnessing the power of loops, then we really need to be looking for latency. We need to be looking for noise and we need to be looking for ownership.

Colin (38:56.601)

So the sort dead loops piece is interesting to me because it gets me thinking as well because part of the problem there is that no owner can really act on these loops. And it gets me thinking about, who should own this? We're talking about these feedback loops and how we can sort of utilize these signals to kind of optimize what we're doing.

You know, how should we put governance around the ownership of this? If I can just throw that at you before we close it off. Why am I being so boring this week? Like last week I'm talking about governance all the time. What's happened to me?

Chris (39:30.59)

Chris (39:36.716)

I know you're loving some governance the last couple of weeks. mean, governance is an important thing, but ultimately, I wouldn't be too worried about it at the start of the journey. I think that as long as we are applying the data fundamentals that we discussed last week that metrics have an owner.

Colin (39:39.939)

Doesn't sound like me.

Chris (39:59.63)

and we are applying the logic that metric should be the gauge on the side of the feedback loop, that then inherently the loop has an owner if the metric has an owner, and it should be within that person's authority and remit to act upon the data and therefore act upon what the loop is, the signal is telling them.

And I think if we keep things simple and we have that association between loop and metric and ownership, then they become to a degree self-governing.

Colin (40:35.087)

Yeah, you know, this is all very valuable stuff that I think we should sort of put together some materials for this for the show notes that people might be able to help people to take action as well. I'm going to hand that over as an action to you right now, because before you get a chance to give it to me. As you were saying, we are kind of hurtling towards that.

Chris (40:57.912)

Sounds good, let's do it.

Colin (41:04.249)

point in the show where we have to start wrapping up. You've succinctly quashed my governance concerns very efficiently. Any final thoughts you want to share before we wrap up?

Chris (41:20.43)

I think that my takeaway from this episode would be that loops are everywhere.

We need to tune into them as business owners, as operators, and we need to understand that there are relationships. Loops don't act in isolation. A reinforcing loop can create a balancing loop that we have this sort of interrelationship between feedback that's existing all the way across our organization.

All of that is creating a lot of data, it's creating a lot of noise. And I think the more we can really tune into the loops, which are really important.

the more we can really dig into what the cause and effect is within those data points. The more we can tune our dashboards in to really be listening to the right things relating back to the episode last week. And as long as we create a strong framework of ownership between all of these things, then we can really move the needle in terms of creating positive change within our businesses.

Colin (42:28.431)

You know, that's what I'm all about, as well, the good governance. Apparently that's my thing now. No, that was fantastic. It is a really good, a really good follow on from, if anyone hasn't listened to the previous episode about dashboards driving dysfunction, that would be a good next step to tune into that. I think those two episodes go together really nicely.

is unfortunately all we've got time for today. We overran less than usual. Well done, Chris. We will attempt to keep honing that. All that remains is to just remind you that how to build a growth system is brought to you, as always, by RevSpace. RevSpace is a growth systems consultancy that connects B2B organizations like yours with the future of growth.

RevSpace will offer things like account-based growth managed services, go-to-market engineering projects and more. Please also don't forget to follow and rate the podcast. It really helps us to bring the content to wider audience. And of course, we would always really appreciate a moment of your time to tell us what you think. That's all we've got time for this week. Thanks very much. See you next time.

Chris (43:47.855)

Thanks for listening.