By Andy Burrows
[First published 21st April 2017]
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If you’ve seen the earlier articles in this series, you’ll know that I’ve been using what I’m calling a “purpose-driven” perspective to draw out useful insights into the work of the Finance function. My thesis is that being explicit about the reasons why we do things, not only boosts motivation and engagement within the team, but actually affects the way we do them. The introductory article that explains the thinking behind the approach.
This time round I want to take a look at why we do financial analysis.
What is ‘financial analysis’? As I thought about that question as a starting point, it occurred to me that it’s difficult to define financial analysis in general terms. If I think about any of the analysis I’ve done, or my teams have done, in the past, there’s such a wide variety of number work that qualifies as ‘financial analysis’. We could talk about “drilling down” or “slicing and dicing” or “getting behind the numbers”. But what would we mean by that? And what about modelling? I include that as ‘analysis’, but that’s not drilling down. That’s more like drilling up!
What we seem to be doing in financial analysis is looking at numbers in the accounts and seeing how they’re either made up or driven; or we’re using our understanding of how the accounts numbers are driven to derive accounting scenarios. We go both ways.
I could give a simplistic example: The ‘sales revenue’ figure in the P&L is something you would probably want to “drill into”. You’d break it down and see that it’s made up of revenue relating to different products. Or you could look at it a different way and see that it’s made up of sales to different customers, or in different regions, or sold through different distribution channels. In fact, you could look at more than one of these ‘dimensions’ at the same time.
Then you’d be interested in how that revenue is driven – prices, sales volumes, discounts, commission rates, etc – all of which could vary by product, customer, channel, region, currency, season. And in understanding drivers you’d have to find out which elements are fixed and which are variable. Are products priced differently for different customers, channels, regions, etc, or are the prices fixed? Can you get all that data from a system or database? Or do you have to look up a price list or refer to a contract or sales order? Or can you derive/calculate unknowns from what you know?
That’s “drilling down”. Modelling goes the other way. It takes the different drivers (prices, volumes, discounts, commissions, by customer, product, channel, region, etc) and calculates a theoretical top level sales revenue figure (sticking with this example) using assumed values for those variables.
Even that “simplistic example” above starts to sound potentially complex. And it turns out that it’s easier to define what financial analysis is by summarising why we do it. (That’s our purpose question.) So why do we do financial analysis?
My answer is this: We do financial analysis to answer questions about the financial performance of the business. And those questions can be traced back to two core ultimate questions: Why? And What If? I’ll come back to those ultimate questions later.
My main point at this stage is more basic: Understanding that the purpose of financial analysis is to answer questions helps us do the analysis more efficiently and present it more effectively.
It helps us to be more efficient, because having the question clear prevents us from going off at tangents or gathering data that isn’t required. For example, the MD asks you to give him an analysis of sales by customer. You would need to get some clarification – sales in what period? All products? Pre-discounts? Actuals? Forecast? Budget? All 2,000 customers or just the top 100 or 500? Imagine if you spent hours producing a 20-page spreadsheet listing sales for all 2,000 customers and giving actuals for the month and year to date, last full year, this year’s forecast and the budget… only to find that all he wanted to know was who the most influential customers were this year and what their sales figures were.
And the best clarification question is “what’s the question you’re trying to get an answer to?”
It also helps us to present analysis more effectively, because we all know that presentation matters. When senior executives ask questions, they don’t have time to look into stacks of data to get the answer. They normally want to be presented with something that shows them the answer in a way that clearly backs it up. It may mean including other data to provide context (for example, to show a customer is the biggest you may need to present the figures for other customers to show how much bigger), but the attention should be focused in on the insight that the analysis gives – the answer to the question(s).
It’s also helpful to know the question behind the question. I mentioned earlier that all analysis questions can be traced back to two ultimate questions – why and what if.
What I want to say about those two ultimate questions is two things.
Firstly, since there may be other questions that are asked, and require financial analysis, you can always trace back to the ultimate questions by asking “why are you asking that question?” (Constantly asking why is real purpose-consciousness.)
Let me try to illustrate what I mean:
Let’s go back to the example above. You’ve been asked for the sales revenue figures by customer, and you’ve asked what the question is that the MD is trying to answer.
If he says that he wants to see if any particular customers have ordered more or less than they did last year, then you still don’t know the ultimate reason he’s asking that question. So ask, “why do you want to know that?” If he says, “I want to know why overall sales revenue seem to be trending downwards,” then there’s your ultimate question. And there’s a lot more helpful stuff you can provide to help answer that.
“Why” is a question about a situation that exists in the present or the past. So, it’s a question about actual business performance.
If, on the other hand, when you ask why the MD is asking for sales by customer, he says that he wants to find out how dependent the business is on particular large customers, that’s a different focus. Ask, “why do you want to know that?” And he may say, “because I want to know what our exposure is if they took their business elsewhere”. That would be a “what if” question.
“What if” is a question about how future performance may look under certain conditions.
Secondly, the answers to those ultimate questions are meaningful statements, not just a set of numbers. And these statements can be assessed in terms of their strategic importance and insight. Like this:
Question: “Why…?”... Answer statement: “Sales revenue is down because customer x has started buying product y from competitor z, due to price considerations.”
Question: “What if…?” … Answer statement: “Under those assumptions sales revenue would decrease by $xk (y%), GP by $zk (p%) and net profit by $wk, leading to a forecast ROCE of c%. This is q% less than forecasts previously shared with investors.”
Hopefully you understand what I’m saying.
When I first moved into business Finance, after training as a public accountant/auditor, this was something that I quickly picked up on. I’d never been involved in monthly management reporting before, so the concept of doing a commentary for the executive committee was new. Even so, I immediately noticed that these commentaries were full of statements that didn’t say anything insightful – “sales are showing an adverse variance against budget because we sold less than expected”! So, I told the team to always do the analysis, and ask the questions (whether that be to the sales team or operations or whoever) to enable them to explain why the major variances had occurred. The aim was to ask as many questions in response to the analysis as possible, in order to understand everything about the situation. The result was more meaningful and helpful commentary, even when the analysis itself was never actually presented to the Exec.
The final thing to do after answering the “why” or “what if” questions is to ask what those answers imply in terms of actions. And then you should think about how strategically important are the actions implied? If you’re looking into big sales variances or modelling a new commercial contract then the results could have a big impact on strategy. If you’re looking very narrowly into “sundry expenses” the strategic importance is much lower.
There are two further insights I want to briefly mention, following on from the recognition that financial analysis is done to answer questions.
Firstly, just because it’s financial analysis doesn’t mean that every number in the analysis will have a $ or a £ sign in front of it. To understand the drivers for financial numbers (balance sheet, P&L, cashflow, ratios, etc) you often have to gather data that is even more basic. Sales volume isn’t a financial number, for instance. Number of deliveries isn’t a financial number either. But in both cases those things drive a financial number – sales revenue or distribution cost – if used in conjunction with something else (a price, an order volume, a per item postage and packing fee, etc).
Secondly, whilst I’m tempted to assume that you’ve all heard of the phrase, “analysis paralysis”, that may not be the case. And even if you have heard of it, the point is a good one to keep making.
It has been noted that some organisations suffer from “analysis paralysis”. This conveys two problems – having so much analysis that they can’t see the wood for the trees, and can’t see what the really important things are; and, spending so much time analysing that they don’t get round to actually doing anything.
The answer to “analysis paralysis” is not to stop analysing altogether. That would be both impossible and undesirable. To know what’s truly going on you need to do financial analysis.
The answer is to have a purpose-driven approach to financial analysis. That is, you recognise that financial analysis is all about answering questions. This can help you to avoid both aspects of “analysis paralysis”, and enable you to focus on the things that are important.
How do you avoid doing too much analysis? You examine the ultimate questions that sit behind each piece of analysis, and you ask what level of strategic importance those questions have. That’s the way to prioritise. Only do the work that is the most important to the strategy of the business, and the work that will best inform improvements to business performance. It’s not uncommon to find that some of the analysis you do is done just because you can. It doesn’t answer any questions. That’s pointless, it’s a distraction and should be stopped.
How do you avoid continually analysing without actually doing or changing anything because of it? You remind yourself that you only have one foundational purpose in asking the questions that require financial analysis. And that purpose is to identify actions and decisions that will maintain, protect and improve the performance of the business. Continually analysing without taking action is like reading lots of travel brochures without ever getting around to booking a holiday. It’s also a bit like carefully studying maps, but never leaving the house!
So, let’s summarise all that into a purpose statement. We do financial analysis to answer questions that enable actions to be taken to maintain, protect or improve business performance.
Being clear on the questions being asked will help us to do the analysis efficiently and present it effectively. And trying to draw out the ultimate “why” or “what if” question will help us to get meaningful insight out of the data. And that will help to inform decisions to drive business performance
To save you looking, here are the links to all the articles in this series:
Please let me know your thoughts, whether you agree or disagree, whether you think this is a helpful angle on things, and whether you can see any additional applications. Use the comments box below.
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