It’s that time of year again. Spring is in the air, the evenings are lengthening, and CIOs and CMOs are looking at their budgets and working out which projects they should invest in in 2016. There is a business case for every project. They know that these investments can improve their key performance metrics but these are tough choices. Every dollar or euro invested in “Project A” is a dollar or euro not available for other projects. You can’t do everything you want.
Why should they invest in predictive analytics?
The first reason is that predictive analytics is all about using your data to make better decisions, and the improvement in business results driven by predictive analytics is quantifiable and measurable. It is one of the few investments a CMO will make that is guaranteed to produce a return on investment (ROI). Even better, the ROI of predictive analytics compounds. The more you use it, the greater the return. There are opportunities to use it in every part of your business operations where there is data — which, in 2016, is everywhere.
So how does this work?
First you need a business question. The more central the business question to your profitability, the greater the return. So for a telecom provider, the key business questions may be connected to customer churn and penetration of multi-play offers. For another company it may mean improving the quote efficiency. For every business, it’s different. But once the business question has been identified, the data science team can go to work.
The data science team prepares the data and generate models. Once the models are completed they have an accurate measure of the ROI. They then embed the solution into the day-to-day operations so that the other employees can use the output to make better decisions. Once complete, they deploy the work into production.
Once in production, the model just works. As an example, the model manager in SAP Predictive Analytics monitors the performance of the model on a day-to-day basis and updates it when needed. If there is a problem the team is notified, but in general it just runs in the background optimizing the business. An ongoing ROI has been achieved and has been locked into the daily business operations of the company.
And ROI isn’t the only benefit…
But you still have your data science team. They can start working on another business question—and then another and another, until soon you have a business with thousands of models running in parallel helping answer thousands of business questions more efficiently across the entire company. An organization leveraging its data to maximum effect—all powered by predictive analytics.
So why should the CMO invest in predictive analytics? Because predictive analytics makes every other investment run better delivering clear and quantifiable margin improvement and ROI across the entire business.
To learn more about SAP Predictive Analytics, visit www.sap.com/predictive.