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Humans are biased
Humans have personal and political pressures that pull at them. As such, humans are biased towards something, so as long as there are humans involved in making a forecast, the forecast will be biased. The key to making a forecast unbiased, is to find a method where humans have minimal influence on the outcome.
Everyone has been in the situation where the suggested forecast seems off. Finance has a gut feeling that the business is either too aggressive or sandbagging their forecast. But is the Finance gut feeling enough to revise a forecast? Normally not, and remember even though Finance is independent in its business advise, Finance is also bias. If Finance decides to submit a revised forecast, then Finance is on the hook as the owner of the forecast, which may or may not be aligned with the business.
There is only ONE forecast
The first rule of forecasting is to have alignment on what the official forecast is. There is one and only one official forecast and multiple forecasts is not an option. Alignment from dialogue between Finance and Business needs to take place to lock down one single forecast that is owned by both business and Finance.
But how does Business and Finance meet a forecast agreement if Finance think the business is either too aggressive or sandbagging their numbers? Finance gut feeling or relying on simple case examples like; last quarter this happened so it will probably happen again this quarter is not enough. Finance can reach alignment by convincing the business to adjust their position through the use of unbiased forecasting when Finance let the data talk and leave any bias out.
Unbiased Forecasting is a framework where Finance use multiple methods to forecast. Methods which cannot be manipulated and as such is independent of any personal opinions. Meaning, methods where historical data, market data, statistic or industry indexes are examined and often forecast algorithms are applied to predict future outcome.
Linear extrapolation is one of the simplest forms of an unbiased forecast methods. Smoothing and Leading Indicators are some of the more advanced techniques in this toolkit. Common for all of the methods are they make Finance capable at challenging the business by providing an independent evaluation of the business forecast a.k.a. unbiased foresting.
Unbiased Forecasting is a validation method
Unbiased forecasting should be used in concert with the business forecast to triangulate to yield higher forecast accuracy. Where multiple forecasts agree within a planning tolerance there is confidence of outcome, and where they do not there should follow deeper discussion to sort through the risks. The ability for Finance to provide unbiased recommendations both improves forecast accuracy and helps Finance become a strategic partner to the business. To achieve such, Finance will need to expand its toolbox beyond Excel to include advanced analytics systems and techniques that can challenge and influence the business position.
In the next article we will unlock the different methods that Finance can use to provide an unbiased forecast.
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Authors
This article is a collaboration between Robert J Zwerling and Jesper H Sorensen from the organization Finance Analytics Institute (www.fainstitute.com) and is an excerpt from their book, Implementing an Analytics Culture for Data Driven Decisions – A Manifesto for Next Generation Finance. Robert and Jesper are the content creators behind the Analytics Academy and will teaching at the Academy in September!
Copyright 2019 Finance Analytics Institute, Robert J Zwerling & Jesper H Sorensen. All rights reserved. No part of this document may be reproduced without this copyright notice.