How Finance Helps Make the Future Happen

We’ve reached the highlight of our Analytics Series where we describe how Finance can drive more return on investment on our analytics efforts by building a new culture, creating insights, and now making the future happen through foresight. Foresight is described in business literature as… 

“…the ability to make a successful outcome happen…”

…hence while it does include forecasting and predictions through advanced analytics, it is just as much the ability to make the predicted outcomes happen or not. Good outcomes we want to maximize and bad ones we want to mitigate or eliminate. Foresight is what binds the WHAT MIGHT happen and the HOW to do it together.  

Let’s make the future happen! 

Through predictive analytics you can today, given all that you know, make predictions about how your business will develop should you take no actions to change it. On top of that you can build different scenarios and create models to predict WHAT MIGHT happen if you were to attempt making certain changes.  

However, just because something is predicted to happen and seems like the best outcome, you cannot allow yourself to autopilot all your decisions. There are more considerations to make like… 

• Do we have enough resources e.g. capital, people, etc.?
• Do we have the right capabilities e.g. people with experience of having done this before?
• Can our systems and processes deliver it?

All of this shouldn’t arrest you from becoming prescriptive about HOW to make the desired future happen. It’s simply a sanity check of the predicted outcomes.

What the future looks like 

The future of analytic decision-making is powerful and let us demonstrate with two examples. 

First, a Fortune 500 company, used advanced analytics to predict the propensity of sales deals to close in a quarter. Using sales history in the CRM system, analytic software built a profile of the characteristics that indicate when a deal will close, and when it will not. 

In a particular interesting example, the analytics revealed that while a specific customer was actively interested in buying, the salesman did not have the characteristics to close the deal with that profile of deal size. When the deal did not close in the quarter as predicted, the salesman on the account was changed the very next quarter and the very next month the sale closed. 

Now, the original salesman was not incompetent but simply didn’t have the skills to close a large deal. This was not seen by the salesman’s manager but was visible from the analytics. The salesman continued with the company and was successful to meet his quota from the deals whose profiles were a match for him. 

In a second example of a NYSE transportation company, it used AI to forecast revenue throughout its major and minor business units. This formed the base forecast that was then distributed to the business managers who adjusted the forecast based on their future knowledge. The combination of AI and humans produced 97% to 99% average monthly forecast accuracy over 18 months.  

This accuracy was significant and was then combined with correlations to economic indicators to determine those that lead demand. These indicators were used to test the adjusted forecast for reasonability to assure that adjustments were made on high confidence knowledge of specific future events. Salesmen optimism of a deal closing or a manager’s pessimism of a downturn in a region would be uncovered and rejected unless a firm factual foundation of the future existed. 

The ability to deliver high accuracy forecasts over 18 months led to better planning and control of operations. Consistent performance assured the company’s higher valuation as reflected in its PE multiple. The company received about an 18% higher multiple vs. a broad market basket of companies (excluding the tech sector).  

Leading finance functions make the future come true 

Of course, Finance is not alone in making the future happen and rarely does the finance function execute many of the actions that make the desired changes happen. However, Finance is participating end-to-end, from problem identification through scenario modeling to following up on actions and optimizing performance. 

As described above, predictions can be used to help sales operations put the right resources on the right accounts to maximize sales potential, or AI and leading economic indicators to deliver long range high forecast accuracy for better planning and control of operations.  

This is what leading finance functions can do! They’ve stopped reacting to what has happened around them and instead become proactive in making the changes happen. Finance can create a lot more value when decisions are based on data analytics, as opposed to, gut feeling. Are you ready to become a part of the leading pack!?

If you want to learn more about Analytics and our approach you should join the Implementing Analytics Academy in Chicago on 16-18 September. We hope to see you there! You can read previous articles in the series below.

Here's Why You Need A Culture Of Analytics

How To Build An Analytics Culture

The Art Of Turning Data To Insight Explained

Authors 

This article has been written in a collaboration between the Finance Analytics Institute led by Robert J Zwerling and Jesper H Sorensen and the Business Partnering Institute led by Michael Bülow and Anders Liu-Lindberg. The article will be part of a four-article series where we explain how to build a culture of analytics, how to build insights and foresights and sharing of some cases. Our aim with the series is to further push the finance function in its on-going transformation efforts towards being a strategist of the business.

Anders encourages you to take a tour of his past articles on finance transformation, finance business partnering and not least “Introducing The Finance Transformation Nine Box” which is really the starting point for the transformation. You should join our Finance Business Partner Forum which is part of the Business Partnering Institute's online community where we will continue to discuss this topic and you can click here to follow him on Twitter.

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Anders Liu-Lindberg is the Head of Global Finance Program Management Office at Maersk and I have more than 10 years of experience working with Finance at Maersk both in Denmark and abroad. I am also the co-founder of the Business Partnering Institute and owner of the largest group dedicated to Finance Business Partnering on LinkedIn with more than 5,000 members. My main goal at Maersk is to create a world-class finance function not least when it comes to Business Partnering. I am the co-author of the book “Skab Værdi Som Finansiel Forretningspartner” and a long-time Finance Blogger with 22.000+ followers.