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Spreadsheet risk. How worried should we be?

spreadsheet risk

The risk of error in the misuse of Excel spreadsheets has been widely reported, with recent high profile mistakes hitting the headlines.

Many of us who rely on Excel to do our work are thinking, ‘there but for the grace of God go I…..’

So how worried should we be?

The good news is that major ‘business destroying’ errors are mercifully rare.

Things are no worse today than they have been for the last 15 – 20 years and we are not seeing long queues of Finance Directors outside job centres.

So let’s not panic just yet.

More good news is that once there is an appreciation of the risks, there are positive steps that we can take to mitigate them.

When assessing your Excel financial modelling risk, here are some of the key factors you should consider.

1. Is Excel the right tool for the job?

Excel is great, but it is not the answer to every problem. Excel has its limitations and they should be considered before using it in a business-critical application. The decision to use Excel should be an active one, rather than the default option.

2. Are you relying on Excel-based analysis to make business-critical decisions?

If your Excel modelling is limited to preparing shopping lists or tracking expenses, sleep easy. The impact of any errors will be small.

However, Excel is frequently used for business-critical reporting and decision making because of its flexibility. If this is the case in your business, you should be aware of the potential risks which come with the misuse of Excel.

3. Are your Excel models huge?

Excel models are frequently over 20MB in size, with upwards of 50 sheets and 1000s of rows of calculation per sheet. This equates to many millions of individual cells containing calculations. Each one of these calculations is an opportunity to make an error. As the number of calculations increases, so does the risk.

4. Are your models (over) complicated?

As well as the sheer quantity, the calculations themselves can also be impenetrable. It can be hard for anyone other than an experienced modeller, or the model builder themselves, to easily interpret what is going on.

Heavy use of complex formulae can impact the transparency of the model and hence increase the risk of error.

5. Do you understand what your Excel models are doing?

When it comes to modeling, there is often a disconnect between the modeller, and the decision-maker.

The modeller deals with detail, making thousands of small decisions hidden within the lines of Excel code, necessary to form a cohesive model to generate the big picture outputs.

The decision-maker then relies upon the big picture output of the model.

The problem arises when there is something of material commercial consequence buried in the detail of the thousands of small modelling decisions. Something about which the decision-maker is not aware.

If you do not understand the detail of what your model is doing, there is a risk you will be making flawed decisions.

6. Do you have appropriate review processes in place?

If you are using Excel for any business-critical application, you should have an appropriate review process in place.

The nature of the process should depend on the other risk factors discussed here. But, if you have no process, you are asking for trouble.

7. Do you have clarity of ownership?

If the unthinkable happens, and there is a big Excel error. Who’s to blame? Who should carry the can and be the one facing up to the board/shareholders?

We do not advocate a blame culture here. What we recommend is being clear at the outset who ‘owns’ the model. If it is clear who is responsible for the accuracy of the model it will help to focus minds on ensuring robust review processes.

Do you have clarity of ownership for your business-critical models?

8. Are your staff adequately trained?

Our training colleagues will give chapter and verse on this, so we won’t do it here. In short, asking an unqualified person to do a highly skilled professional job generally doesn’t end well.

9. Do you use financial modelling best practice?

In the financial modelling world, there are numerous versions of what constitutes ‘best practice’. These range from high-level principles as prescribed by the ICAEW to very prescriptive standards such as the FAST standard.

Applying best practice principles and a standardised approach can help to greatly reduce the risk of spreadsheet error.

A quick read through this list should give you an idea of where you are sitting on the Excel modelling risk spectrum.

Over the coming weeks we will expand on each of these areas as well as discussing strategies for better managing your modelling risk.

Oliver Durston


Oliver Durston

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