Risk and Configuration at the Core of all Business Decisions
Most business decisions that are worth automating involve a combination of two key aspects, in various forms and under various names, but that boil down to risk and complex configuration. Take a loan application:
- The loan product is complex to configure, must take into account your business procedures, legal compliance requirements, customer desires, your competitive landscape, etc…
- You are also taking risks every time you originate a loan: a risk the loan is not paid back, the payment schedule is not respected, the interest rates vary significantly, etc… The risk is both on a per-loan, and on a per loan portfolio basis.
This is of course obvious, but most decisions actually do present the same two key aspects, be it in Financial Services, Healthcare, Marketing and Advertising, or other industries. It is thus not surprising that decision management solutions are applied to these problems.
Role of Decision Management, Decision Analytics, and Case Management
One important aspect of these decisions is that the systems that support them tend to combine a number of key architecture pieces: decision management, decision analytics and case management.
- Decision management is used to capture, test, optimize and manage the decisions to be rendered automatically,
- Decision analytics is used to measure the actual business performance of the decision being rendered automatically,
- and Case management is used to both take care of the case that the automated decision cannot take care of automatically (operational case management), and to investigate the reasons behind that failure (investigative case management).
Case management (operational and/or investigative) are present in one or another form, and they are particularly prevalent in systems that support decisions involving money transfer or healthcare impacting decisions.
The Importance of Decision Analytics
We have talked elsewhere in this blog (see From Decision Management to Prescriptive Analytics and Improve Your Automated Decisions with Decision Simulation) on how it is essential to have decision analytics included as part of any decision management solution. The previous generation of BRMS and predictive analytics tools fails at this by narrowly focusing on just the capture of expertise from experts or data, and (sometimes) its automation but not the management of its business quality. Next generation decision management tools, led by ours, SMARTS Decision Manager, make decision analytics core to the approach.
What is less obvious is that combining decision analytics and innovative expertise capture approaches, decision management can help provide a significant enhancement to traditional case management approaches by both assisting the case workers, and efficiently capturing the expertise applied by the case workers. That will be the subject of the next installment of our series.
Learn more about Decision Management and Sparkling Logic’s SMARTS™ Data-Powered Decision Manager
