A lot has been written about the use of predictive analytics; in sales and marketing to identify the basket of products the customers are most likely to buy based on their purchasing history;
in maintaining machinery and equipment by predicting when to schedule servicing and in crime prevention by ensuring geographic hot spots are adequately policed during critical hours. But other than forecasting which I wrote about last time, I guess most finance teams consider predictive analytics per se is something that has limited application in the fact-based world of accounting.
Well that’s certainly not the case according to Gary Cokins, whose forthcoming book, Predictive Business Analytics that he co-authored with Lawrence Maisel is due out this month. Gary has his feet firmly planted in the accounting and finance having started his career as a financial controller, before spending time in consultancy and in the software industry building for himself a considerable reputation in the world of cost management and budgeting along the way. So you can expect the content to be focused on real finance and business issues and highly practical. I was fortunate enough to get a preview of the type of content you can expect from an article Gary forwarded about how predictive analytics applies to finance. So here’s my brief resume of some of the main areas where predictive analytics applies to finance which you will find covered in considerably more detail in his book:-
Increasing profitability by targeting the more profitable customers
Having implemented customer profitability reporting using a solution such as SAP Profitability and Cost Management, it’s important to follow through with actions that improve the bottom line. That may mean encouraging poorly performing customers to use less costly self-service channels and reviewing any over-generous discounts they might have historically enjoyed. But it’s also vital to identify what characteristics the most profitable customers share so you can implement activities to retain those you have – and attract more like them.
By using analytic techniques such as discriminant analysis on all the variables we know about the customers, it is possible to identify discrete customer segments that can be acted on. It might be that customers from particular sectors or of a particular size are the most profitable, but once we know this we can identify others that could be targeted and use predictive analytics to model what it is worth investing in marketing in order to win their business.
Increasing product shelf opportunity
Again once you know the net margin of individual retail products, you can use predictive analytics to identify those that can generate the most profit taking into account the cost of carrying inventory and the likelihood of a stock out. Today when you can update sales forecasts in near real-time using fresh data from point-of-sale checkouts, business analytics can also be used to optimize the volume and routing of consignments of replenishment stock in the inbound supply chain and also dynamically adjust prices to maximize profits.
Increasing staff retention
The cost involved in recruiting and developing new staff is likely to out-weight the cost of applying predictive analytics to the challenge of employee retention – to say nothing of how losing a valuable team member disrupts the output and performance of a department. It therefore makes sense to understand the traits and characteristics of employees who have voluntarily left by considering factors such as their age, the timing and amount of previous salary awards and their duration of service to produce a ranking of those most likely to jump ship in the near future. This allows management to selectively intervene and make best use of their departmental salary pot when salary review time comes around.
These are just three simple examples of how finance can use predictive analytics to help their peers make better decisions that increase revenues, reduce costs and drive profitability. There are numerous other examples in Gary’s book. In fact whenever you find yourself using the words ‘maximize’ or ‘optimize’, you can be pretty sure that it’s time to put aside gut reaction and intuition and reach for a tool such as SAP Predictive Analytics or one of the solutions from the newly acquired KXEN.