How to measure your business performance and compare it to your predictions
A Beginner’s Guide to Variance Analysis – Part 2
Welcome to part 2 in this guide to variance analysis, in which I’ll explain how to perform actuals vs forecast variance analysis.
In brief, variance analysis in financial planning is the comparison of what was predicted to happen and what actually happened. It’s a retrospective on a financial forecast. From this analysis, you can learn how to improve the accuracy of financial forecasts and identify trends or anomalies in the business’ performance.
If I’ve already lost you, check out last week’s article, which introduces the concept of variance analysis, and why it provides such important metrics for startups and growing businesses!
Despite this being a heavily financial topic, ZERO accounting knowledge is required beyond this point. Everything I describe will include real-world examples so you can see just how to relate variance analysis to your business.
In this article, you’ll learn how to go about the actuals vs forecast process.
How to go about the actuals vs forecast process
First of all, you’ll need to have made a financial forecast – if you don’t have one already… well, you kinda need one to do actuals vs forecast analysis!
Beyond this, a financial forecast will help you plan more effectively, and it’s a great exercise in itself that will teach you a lot more about the business, or businesses you are involved with.
Choosing what kind of financial variance to analyse
A big choice that it’s useful to think about upfront is the kind of information you want to get from variance analysis. This will influence the sources you get your actual data from. Alternatively, you may have to just work with what’s most easily accessible, so knowing what kind of forecast information you need to compare your actual data is a necessity.
So, what do I mean by ‘kind’ of information? Business performance is typically measured by 3 reports, each of which describes the business’ financial transactions in a different light.
- Cash Flow – measures the actual cash that changes hands.
- Profit and Loss – measures what you owe and what is owed to you.
- Balance Sheet – measures the balance between assets (what the business owns), liabilities (what the business owes) and equity (money invested in the business, and any unspent profits).
For variance analysis, you should compare like-with-like. As a first step, choose the kind of variance analysis you want to achieve and ensure that you can get actual data that is formatted in this way.
Depending on the business, some kinds of financial data may be more easily accessible than others. Sole traders who run the business from a bank account will have easy access to cash-in and cash-out data for the month to hand, while larger organisations with prepared financial statements (form an accounting package for example) may find Profit and Loss an easier starting point as not all accounting packages provide a “direct method” cash flow.
How to collect and organise actual data
There are many ways you might collect actual data on your business’ financial activities. At the highest level, monitoring the end of month ingoing and outgoing cash from your business account is one way to do this.
Many spending apps now categorise spending according to the type of expense they are, and if you are a sole trader this may be particularly inviting. Alternatively, you could do this manually by keeping a record (in a spreadsheet or accounting system) of all of the business’ cash transactions each month.
For larger businesses, typically financial information will come from several places but ultimately affect one or more of the businesses’ bank accounts (and credit cards!).
The easiest way to collect data on your business is if you already have access to prepared financial statements. If your business uses an accounting system it ought to be able to produce financial reports on the business’ actual monthly performance.
A major issue you will come up against is how usefully your actual data is initially presented. For example, you might just have a lump of cash received in the month from “sales”. If you are selling several different products or services, just having information about a very broad category like “sales” will limit the usefulness of variance analysis.
Let’s look at an example, such a bike shop.
My bike shop is running a promotion of mountain bikes this summer and I expect to achieve higher than usual sales.
In August, I forecast total sales of £10,000.
Unfortunately, come the end of the month my actual data from August shows that I only achieved sales of £7,500.
But what can this information really tell me? Not a lot…
It doesn’t show which items sold successfully, or which items did not sell. It can’t even tell me if my mountain bike promotion was successful – it could be that I sold £7,500 of mountain bikes, but equally, I might have sold none.
Just comparing a top-line sales figure does not provide very useful information for variance analysis.
Categorisation is worth the time. If the way that you forecast and plan your business includes planning out revenue streams for different products or services, and their associated costs, then you to produce detailed variance you will need to achieve the same level of detail in your actual data each month.
Aligning actual data with forecast data
To reiterate, comparing like-with-like information is incredibly important in variance analysis. It’s the only way to get a valid comparison.
Comparing data from the same financial report, or at least with the same accounting treatment is the easiest way to achieve this. While financial reports are generally formatted in the same way, there can be subtle differences.
Here are two things to look out for:
Some Cash Flow reports include VAT or other taxes in the amounts they represent for sales and taxes, while others split these out. The important thing for variance analysis is to ensure that you are comparing two sets of the same data, either with tax or without tax.
Many financial reports include lines that present the totals of the rows above. A good example is Operating Profit on the Profit and Loss report.
In some systems, Operating Profit includes interest paid on loans and borrowing. In other versions of Profit and Loss reports, it doesn’t! These exceptions are usually minor, but it is worth checking that totals you compare are composed of the same information.
Once you have two sources of information, one for actual data and one for forecast data it’s time to match up this information, line-by-line. You’ll then be ready to move onto the next stage – calculating the variance.
Calculating and comparing actual vs forecast variance
Variance is usually expressed as a percentage. The percentage is calculated like this:
Percentage difference =
(numeric difference / forecast number) x 100.
Numeric difference: 200
(200 / 1,000) x 100 = 20
The variance is 20%.
Variance can also be expressed as the numeric difference between two values – which is even easier to calculate.
Next week in variance analysis…
In the next and final article in the Beginner’s Guide to Variance Analysis, I’ll look at the following:
- Interpreting variance analysis
- Budgeting, course correction and re-forecasting
- Balancing analysis and growing the business
See you in the next article where I’ll look at how to interpret the results of your variance analysis and how this data can be used in a re-forecast.