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Leveraging data: a CFO's perspective

CFO Sit-Down Series presentation 25 October 2022

When you don't know what you don't know

It’s no secret that transparency and visibility is the bread and butter of the CFO yet an astounding number of organisations are at the very beginning of achieving a 360 degree view. During this session we dive into where to start from in this journey and discuss the use of data assets to increase transparency as a CFO and effectively optimise resources across all business units.

Leveraging data

Join us as we get together with David Harreveld of Ascern Advisers to discuss:

  • The effective leveraging of data assets and business intelligence as a CFO

  • Increasing transparency and visibility business wide

  • Stepping towards effective optimising all efforts and resources across the business


I am going to start by letting you know that I will not make any jokes about standing between you and lunch - because I know that's what normally you have to do. I'm also going to start by by telling you a little bit about myself in the intro/

I’m a CFO, 20 years experience in corporate land. I'm a CPA, I'm a trained accountant. There is nothing I like more than a spreadsheet. I know we've had a few presentations earlier around replacing spreadsheets with with other systems. But I would, you know, if you give me a complex product costing model, or a budget or a forecast, I'll happily spend all weekend behind the computer working out where that spreadsheet doesn't work. So I tell you that only so you understand that I am actually your typical, cynical, introverted accountant. Which, if my face is going red, I'm not embarrassed, it's just that's what happens because I'm an introvert.

Personality Profiles

I also used to be a teacher before I was an accountant. So I do actually like to know a little bit about the audience that I'm talking to. And what I wanted to ask you today was, how many of you have I'm assuming a lot of you have done some personality profiling at work? How many of you have done the DISC profile? Okay, for those of you that haven't, there are there are four parts to a DISC profile. And this is the the profiling that, in essence, tells you what your natural tendency is. Dominance influence, conscientiousness and stability, stability and conscientiousness. So what I'm going to do is run through each of those four and get you to put your hand up for those of you that have done the DISC profile and you know, your profile. Just put your hand up. For those of you that can't remember or haven't done it. Put your hand up when when we hit the parts that you think you might be. It's quite common for people to have more than one so you might sit between S and C for example. Yeah. Any questions? All right. Who here thinks their natural natural tendency is dominance? You should be putting hands up higher. Who here is naturally an Influencer? Yeah, a few Dominance with Influence as well. It's me. Stability. Conscientiousness. Yeah, so most finance people tend to sit in the Stability and Conscientiousness bit. Some of us sit towards the Dominance bit. And I don't know for the other people that were Dominant and Influence. I might sit there because I'm not good at the details. I like spreadsheets. But I have people for details. Like they sort that out for me and I would do something with it. That's just how I work.

We're all different, CFOs in the room are all different styles of CFOs. I've also had possibly the longest title for a talk today, I don't know whether there's a prize. I'm here to talk to you about data. But data from my point of view as that cynical CFO.

Today’s Topic

I should probably also mention that a couple of years ago, I stopped working as a CFO for other people, and I started up for myself. So now I am an external CFO. And I go into businesses, small to medium businesses mostly. And I'll either work as their CFO on a permanent basis, going once a week, help them do whatever they need doing. Every business is different. Or on a project, they might bring me in for a while to work on a specific thing in their business or a short term replacement. While they while they replace a CFO or a financial controller.

A lot of what I do is going into business and working out: are we looking at the right data? Hence the 360 degree view that's a theme for today as well. So for me, getting the 360 degree view of a business means getting the right amount of visibility of the things that matter to the business. This is not always financial. So a lot of what I'm going to talk about today is non financial data that people need to run their business so that they get a good financial outcome. Does that sound familiar to some of you? Yep. A few nods. Or in other words, I want data that's not too hot and not too cold, but it’s just right. So, to explain that today I'm going to use a model. And it's a bit like putting on a pair of glasses, right? You apply a particular model when you're looking at something in your business. I've used this one, only because I do use it with some of my clients as well. We'll go in and talk to them about it might be helping them with their budgets. So we actually talk about a lot about their goals, what are they looking to achieve in their business?

As a whole over the next three to five years, before we start talking about this year's budgets, we actually spent mostly spend more time talking about the drivers of the business, because you would be surprised how many business owners and managers don't understand the levers that really drive their business. And that typically the CEOs, and management teams, who don't listen to their staff might have a follow on from the previous conversation as well. Once we know what drives their business, we talk about what things need to be measured, and what things people need to be accountable for. Most of you would be familiar with this model or something similar to it. Just putting it up there because I'm going to refer to it later on. When we go into a business, we call this the dartboard model. Because they're circles. And with a dartboard, you kind of throw stuff at it. So, throwing things at the dartboard is us trying to measure things. It's trying to understand their drivers, it's trying to measure the right things, it's trying to hold the right people accountable for things that will, will drive the business towards its goals.

In the real world, though, that is great. But if you're looking for a better real world analogy, you're better off looking at a football team or some kind of sporting team. I'm not a sports person. Not that I don't follow sports very well, but I can understand it. So instead of having a series of like a linear goal, driver measure accountability, you're actually working with a big team of people, some of them are in your business. Some of them are outside your business clients, suppliers, regulators, people who make decisions that can affect your business, and they're all moving randomly across that field, right. And if you think about, if you've heard, coaches talk about how they coach their teams, they go into a lot of detail around giving their people freedom, you train them up, and then you let them loose, you might have set plays for them in certain circumstances that they need to need to apply. It's a really good analogy. What it kind of highlights for me when we talk about data is the unknown unknowns.

What are the known knowns and unknown unknowns?

Have all of you seen this matrix before? We all know the known knowns, we all know that there are things that we know, but we don't really understand it. There are also some things with data that you might pull out of your business that you would understand it if you see it. But you don't always see it. And that might be because you're not measuring it. Or it might be because you just literally can't measure it in your business. So if you've ever worked in a business where people are unsatisfied, but you don't know what to do, you don't know what they're unsatisfied about. That's an unknown. The unknown unknowns, they might be sort of your black swan events, like a major a major risk event happening. Or they might be actually something to do with the running of your business that no one's ever taken the time to try and find out about.

All of that data is you're looking to sift through the known unknowns, the known unknowns, the unknowns, and the unknown unknowns, in order to get the right the right things measured for your business. So you could measure everything, but it's probably not a good idea to measure everything because you don't have time enough to interpret it. This is my attempt to explain what a football field might look like in terms of goals, and drivers and measures and things like that. I do know when I watch football on the TV, there are lots of statistics flowing down the side of the field. When coaches are watching their teams play, they're not particularly looking at those statistics. They're looking at the drivers, what's driving them along their way to the goal. So for example, if your possession of the ball in a soccer match or a football match is a major driver of whether you can score more than the other team. Passing accuracy, maybe that's that, that that's an accountability for the people that are on the field. Is it a driver of achieving that goal, it's a step towards it. But when you're looking at possession of the ball that encompasses passing accuracy and a whole bunch of other things. So you need to be targeted in what you measure.

It began with a mistake

I tell a lot of stories as well, and this is one of those times when I need to tell a story. So I worked at a business a number of years ago, I won't say which one, where we knew that we needed to get more information on our supply chain and on our inventory management, because it was a mixture of inventing, importing inventory, little bit of reworking the goods for sale. And it was just the business was growing really rapidly. We knew that there were things we didn't know, we knew there were unknown unknowns there. And we needed to turn them into well, first known unknowns, and then no knowns.

So, we had a business advisor to the business at that time, who said, You need to hire a data analyst, I have the perfect person for you … I can see you shaking your head! And the lady came into the business, and she was lovely. But she had a particular approach, which was she wanted to get a view on all of the business and pull it into one place and absorb the data before she could generate anything for us. And I would stand over here and say, well, I think I'd want to be able to measure this and this and this, because that's how you do it in an import business and a production business and manufacturing business. She would say no, no, no, no, you don't understand data. I will pull it all together into one big database. And then we can look at what emerges from the data. Like a giant sword or something coming out of a lake. I don't know what she wanted. But it didn't end well. And it didn't end well. It was all my fault. Sorry. It wasn't her fault. Because she told us when she started that that's how she worked. Because she worked at places where she had people to basically facilitate that and turn it into something useful. I had never worked with someone like that before. So I didn't know how to deal with them. So there was a lot of learning that goes on. And I make a lot of mistakes. And my job. I think if we're all honest with each other, we probably all do. We all learn from those mistakes. I learned from that to be very, very specific about what I want from a data analyst in future. But we also learned as part of that process in the back and forth, we actually did work out that some of the things that I wanted to measure wouldn't have helped. Because I forced her to pull that data out and show it to us. And we started changing things. And it got worse. So it wasn't useful data. I didn't have all the answers.

The importance of being honest with yourself

When you're dealing with uncertainty, you do need to be able to acknowledge for yourself that you don't have all the answers. Sometimes it's hard because people count on us for to provide all those answers. So this is what I went through. In that particular business with the data analyst. I went through my own stages of grief, and I call it this five stages of data grief. Yeah, feel free to take photos and use it. I actually said all these things, at one stage to this data analyst. And she just smiled very politely and said you don't understand. The truth was out there, we actually got to a stage where we could say we have measured what we think the drivers in our business are. But we have also uncovered these other things that we did not know. And these other things are actually driving your business as well. So that was an unknown known. And I always get confused between them as well. But what that meant, what that highlighted for me is when you're trying to build a structure, in your business, or any business that you go into, you should assume that there's stuff that you don't know. And you should focus on understanding the drivers within that particular business as much as you can. But you should revisit that over time. Because if you think about the businesses that you're in at the moment, and what you measure in those businesses, your KPIs or your you know, your Power BI reports and things like that, are they the same things that you were measuring three years ago pre COVID or not? Who's measuring the same stuff? Who's measuring different things now? Why?

Because your business has to change, right? Most businesses of people in this room will have changed over the last three years. So you need to consistently revisit not just the goals of your business, but also the things that drive your business. Because if you don't, you'll be measuring the wrong things. And if you measure the wrong things, then you end up with the wrong results. One thing, the third thing, their key measures only. People naturally have a tendency to measure everything they can. And that's why in that football analogy, where we talk about the accountabilities that get measured, the passing accuracy and things like that, you can measure everything, but it's not always really useful to throw five things that people.

Using data to improve processes can be surprising

So there is another business I currently work with. And they're on a fairly steep growth path at the moment. And we said to them, there are a number of things we need to do to manage your working capital better. One of those things, a lot of them revolves around inventory, and purchasing and costs and things like that, and then getting products to the warehouse quickly. Another major part of it was actually getting orders processed in time, which you would think would be a normal thing to do. But when we pulled the data out and measured it, and, and put it in people's faces every week, we worked out that they would quote for something and they would receive an order, within about three, four days, they get an actual confirmed order. It would take them on average at that time, 23 days to fulfil that order with stock they had in their warehouse. It's not a huge business, they've got maybe two to four warehouse people, depending on what time of year it is. But it was just really difficult for them. And everybody thought that they were fulfilling orders in about three days. The warehouse people thought they were fulfilling orders in three days. So when we put that data up and said they said that can't be correct. We said okay, we'll check it. Now, here's an order and we drill down into the data. Very cool system we had and said, here's an order. There's the order date, there's the shipment date, and went through the whole list. And they said, Ah, that's really interesting. Yeah. So why is that happening? And then you we got down into the accountabilities within that business and said, Okay, there's a process issue there with the warehouse people, there's a process issue with the customer service team, who is accountable for what part in that process like your normal process, review, improvement, business process optimization. But we kept measuring that. And then when we revisited that, in the next quarter, we kept that primary measure of shipment days for orders for not the warehouse, but the customer service manager.

Because in the process reorganisation, we worked out that the main problem with getting the orders out on time was that there were no requested dates on the orders. So nobody knew when the orders had to go out. So nobody knew when and if you don't know, when an order when an order is urgent, every single order becomes urgent. So they had this ginormous backlog of orders, some of them could have been shipped in four weeks time, because that's when the customer actually needed them. And some of them were actually urgent for the next day. So you're probably all familiar with that situation where salespeople are walking in and demanding that their order get pushed to the front of the queue. That's where they are at. So by going through that exercise, we're able to let them reorganise their own process, but put somebody in charge and responsible and accountable for those measures that actually counted. We actually ended up giving them some some other measurements of time in there. But they weren't a KPI. Note, nobody has been held accountable for those. The live measurements, that's a no brainer for anybody in this room. If you can get live data for how your business is running for what drives your business, then obviously, you should do that. If you can't get live data for what drives your business, then you should work out how to do that. And the Review bit to stay current, that is really to reiterate for everyone that you really need to go and revisit this regularly. The cycle that's appropriate will depend on the business. Whether it's a quarter whether it's more months, probably a bit short, but every year during a budget cycle, you'll know based on the rhythm of your business and the speed at which you need to operate, which one is appropriate.

What to take away from all this

So some things to take away just to reiterate, except that you don't know everything and you can't know everything when you walk into a business. So what you need to do when you go into a business or when you go and revisit this within your own business, you learn the drivers of the business. Go talk to people, get the managers to talk to people, set up a situation where you can get that data drawn up. And don't just rely on the CEO telling you that this is what's driving their business for the next quarter, because they also don't know everything. Trust but validate, I think someone said to me on stage, you might find that you've identified six major drivers for your business, for exam five or six. Some of them will be major drivers, and some of them will be minor drivers depending on their influence. Then you pick the ones that that matter. And then put them onto that live publishing of data. And then revisit them evolve, you should evolve the reporting as the business evolves. That's that whole discussion about business drivers. I think I've said it about five times today. Don't rely on your business drivers never changing because they can't. I can't think of any one business that maybe schools, maybe not that where the business drivers remain the same year on year, quarter on quarter week on week. And thank you very much.



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