This is the third of four articles in the Unbiased Forecast series. In this article we articulate how Finance can use the predictive methods, described in article two, to influence the forecast decisions by providing predictive analytics for ‘What might happen’. In addition we will reveal the concept of Systematic Intelligence which enable Finance to provide prescriptive analytics to also tell ‘How to make it happen’.
The information in the article and more will be covered at JPK Group’s 2020 Analytics Academy. Click here for more information.
Predictive Analytics – What might happen?
Finance often experience receiving a forecast from a business leader where Finance has the “gut feeling” that the business is either sandbagging or being too aggressive. The Predictive Methods for Unbiased Forecasting (described in article two) are the framework where Finance lets the data talk and leave human bias out of the discussion with the business. From the use of the multiple unbiased predictive methods, Finance can better influence business leader’s forecast decisions.
In the beginning the business normally doesn’t trust the Unbiased Forecasts from Finance, but as quarters pass and the business realizes the unbiased forecast from Finance is more accurate than the roll up forecast from the regional leaders, the business start to turn little by little.
After several quarters, business leaders “thrown in the towel” and turn to Finance for guidance. The business starts to ask the regional leaders why their forecasts are not aligned with the unbiased Finance forecast. As such, the unbiased forecast becomes the starting point of a decision process from which discussions follow to yield better forecasts and planning decisions.
Where Unbiased Forecast methods can influence the business forecast decision by telling ‘what might happen’ the methods don’t enable Finance to advise on ‘how to make it happen’. Finance can tell the business what number to forecast for the following quarter, but Finance cannot engage in a deep detail dialogue about customer level predictions; i.e. Finance cannot pin-point the new deals in pipeline that are going to close and which existing customers are going to renew their commitment. As such, a more sophisticated framework is needed – Systematic Intelligence…
Prescriptive Analytics – How to make it happen?
Systematic Intelligence is a method that allow Finance to get deep into the dialogue with the business, being able to tell things like; Which new deals have high propensity of closing, which existing customers have a high propensity of cancelling, etc. With Systematic Intelligence, Finance can advise the business where to focus to build new business and where to focus to better maintain existing business.
Systematic Intelligence is extremely powerful if Finance wants to step into the role of the Strategic Partner and impact the strategic direction for the business. If Finance wants to advise if a deal will close in a quarter, it develops a profile for similar historical deals from the use of Systematic Intelligence.
As an example, a sales rep forecasting a deal for a customer with high propensity of closing could have the following profile:
- The Sales Rep has sold a new deal every quarter for the past 3 years
- The Customer has bought a new product within the past 6 months
- The deal has a positive pipeline development
Conversely, a low propensity deal could have the following profile:
- The Sales Rep has never sold a new deal to a customer before
- The Customer hasn’t bought in the past 5 years
- The deal has been sitting in pipeline for 3 years without progressing
Understanding what profile each deal follows (Very High, High, Medium & Low propensity) enables Finance to provide unbiased and impactful guidance to the business for which deals to include in the forecast. But even more important, it enables Finance to provide guidance for which deals the business should focus its limited time to make its forecast.
Low Propensity deals will probably not close, so don’t waste time on them. Very High propensity deals are highly likely to close so minimize time on these deals to assure attention to the High and Medium deals. Especially focus on the Medium propensity deals as these are often the deals that will determine if a business makes its forecast or not.
With Systematic Intelligence, Finance is capable of getting into deep dialogues with the business by providing foresight that enables the business leaders to take data driven decisions.
Forecast as a Service (FaaS™)
New tools and techniques beyond Excel are required to get to this predictive and prescriptive level of analytics. Most Finance organizations will have limited resource to invest time, capital in new systems, training of current staff, or invest in new people to reach this level. Often budgets are constrained for Finance too. As such, FaaS is a groundbreaking new solution which will circumvents these investments/resource limitations. Our Next article will describe the concept of FaaS.
If you are interested in this topic, then join us at the next Analytics Academy!
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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.