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Don’t Explain Yesterday. Predict Tomorrow!

Don’t Explain Yesterday. Predict Tomorrow!

These days no one cares about the past because the present and the future is coming at you so fast and with so much change that dwelling on the past and making decisions based on historical insights can lead to disaster. All companies need to relate to this when they make decisions and when most want to make data-based decisions it means that the data provided to management also need to be forward-looking. Typically, companies have been driven by various KPIs depending on industry and the current state of the company. KPIs that tended to be backwards-looking rather than forward-looking. Companies, therefore, need to transform their analytics to be looking at Key Leading Indicators (KLIs) instead. Finance especially, having established itself as an analytical powerhouse, needs to be aboard with this paradigm change. Let’s then look at exactly what should be done.

Don’t record – predict

Finance functions need to be able to predict the future at least to a certain degree of certainty. While everyone knows that classic 5-year plans probably won’t turn out the way they were designed then it wouldn’t be too much to ask for instance to forecast how many goods or services are expected to be sold in the next 1-3 months. If you are a business that employs salespeople that make sales calls you should be able to predict your sales by following a certain formula.

Number of salespeople X number of sales calls X average addition to the pipeline per sales call X win ratio

Above might be a simplified formula, however, it does well to illustrate what you need to do. At any given time, you will know how many salespeople you have. You will also know how many sales calls you expect your sales force to make in the next 1-3 months either because of historical trends or because you’ve set targets for your sales force. You can also determine from historical data how much you add to your sales pipeline each time a sales rep performs a sales call. Then all you need to do is add your historical win ratio and you’re done. All four drivers will be changing constantly as you add more data to the pipeline and older data becomes obsolete. Variable costs typically follow your sales so they can be auto-predicted from your top-line and the rest (fixed costs, SG&A, depreciation etc.) you would know with a great degree of certainty. You can also go more granular on the cost side as some can be auto-predicted whereas others are driven by behaviours. Then you can track the KLIs related to your employee’s behaviour etc.

Can you predict the future?

Any of above variables could change significantly even within a short period hence predicting sales even 3 months out will require vast amounts of data at a very granular level as there could be a difference between face-to-face sales calls and phone calls. It could be that different segments will have a different addition to pipeline per sales call etc. However, all of it is driver based hence if you have set up your system so it has the needed granularity and is constantly fed with real-time data from your sales force then you shouldn’t be too far off in predicting the future. More likely than not you will at least be much closer to reality compared to taking your historical sales and applying a simple growth factor. This kind of forecasting might be sufficient for you but it has nothing to do with predicting the future!

Is your finance function using KLIs and driver based forecasting to predict in which direction the business is moving and where more pressure needs to be applied? Certainly, with more and more data being available you need to be in this space as the business has a need for it. Tell us how far are you on your journey?

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Want to talk?

If you would like a direct dialogue about how you can improve business partnering in your organisation, please contact us on:

Contact@businesspartneringinstitute.org

Telephone: +45 29170298.

 

 

 

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