Automating decisions has its own Return on Investment (ROI), but it is only the very beginning of a Decision Management transformation. The end goal should be to improve your decisions. Having the underlying decision logic out of the system code, gives you opportunities to analyze, understand and experiment; which was not really possible before.
It used to take time to ensure that your decision logic did what it was supposed to. Business Rules had to be implemented as code, then compiled, then tested in QA, then deployed, then eventually executed for real and the produced Production reports would tell you if there is a problem.
The sooner you actually see the effect of those business rules on your production data, the sooner your can correct the course of action, or feel safe about pushing those rules into Production.
What you can do… is to operationalize the gathering of data from your Production systems, and get them into your Decision Management systems to see how your business rules will be applied.
Measure early, measure often
Testing is good, and allows you to reduce the typos and logic errors in your business rules. You can see the raw impact of your decision logic before it gets out the door. What will make a key difference on your bottom-line though is how this new or update decision logic will behave in aggregate.
What you can do… is to measure Key Performance Indicators (KPIs) in your systems. KPIs are aggregated metrics that measure your business performance, your success. For example, you might care about the distribution of Approve, Decline and Refer decisions. but that datapoint alone is not sufficient: you want to make sure you decline the bad risk, keep the good risk, while at the same time do not undercut your revenue. In the Fraud case study I presented with eBay, we had a different set of key metrics that were critical to the fraud expert: Catch rate and Hit rate. Whatever those KPIs might be for your business, make sure you define them carefully, and that you measure continuously the progress you make towards them.
Look for more
There is what you see in the KPI reports, and there is what you don’t see… Why don’t you get an extra help from the super processing power of some analytics? they will likely not know better than you, but they can uncover some patterns in your historical data that you can refine and operationalize.
What you can do… is to crunch your data using analytic algorithms that help you ‘mine your business rules’. Once you obtain the data-driven rules, massage them
There might be more than one way to improve your bottom-line. If you are implementing compliance rules, then you may not have that many options to experiment on; but if you are looking to improve your profitability you might have to try things for real into multiple segments to see for yourself which one is most effective.
What you can do… is to start by setting up your simulation environment to run those business rules ‘comparisons’ at large-scale. It will give you a more realistic idea of your KPIs based on a larger sample. The next step is to start experimenting live. Marketers have done A-B testing for a long time. In the Decision Management space, we call that experimental design or champion-challenger.
You are the business expert, right? But how well do you know the contribution of your rules? The decisions we make in life do not always pan out exactly how we expected them to, sometimes for the better and sometimes not… It is the same for your business decisions. They generally work the way you expect but there could be surprises.
You could measure Key Performance Indicators (KPIs) in your systems and look at the reports on a regular basis. we recommend that of course.
What you could do too that is even more powerful, a greater learning experience… is to take the time to anticipate where you expect those KPIs to land and where you would like to take them. With clear objectives in mind, you will be more attuned to the outcome and, as a result, more effective in affecting those KPIs.
Learn more about Decision management and Sparkling Logic’s SMARTS™ Data-Powered Decision Manager