What is Case Management?
Case management has different meanings. In healthcare, it is a collaborative process where healthcare professionals and patients work together to develop a plan to achieve certain goals. Typically, a case manager such as a nurse or social worker is assigned to monitor patient progress. In law, it is the systematic process for managing legal cases by legal professionals. This involves everything from scheduling court appearance to preparing legal documents. In technology systems, case management is a procedure for managing data, documents, and processes for unique cases. These cases can be incidents, investigations, or service requests. For this blog series, I’ll be focusing on the last, especially in the context of automated decisions.
Automated Decisions Involve Risk and Configuration
In general, automated decisions and decisions worth automating involve risk and configuration. For example, let’s look at a loan application.
- Risk: Every time you make a loan decision, your take on risk. Risk can come from approving an applicant that is unprofitable. Alternatively, risk can come from declining an applicant that would have been profitable. Not only is risk assessed at the individual level but also in aggregate, such as a particular loan product portfolio.
- Configuration: The loan product itself requires complex configurations that vary from applicant to applicant. Configurations include loan amount, interest and fees, term, and other ancillary services. These configurations are not only shaped by the applicant profile, but also by business objectives, consumer wants, the competitive landscape, and compliance.
Risk and configuration is not limited to automated decisions in Financial Services. Think about the automated decisions in Healthcare, Manufacturing, and Advertising. Regardless the industry, automated decisions will either mitigate risk and/or configure something.
3 Key Architecture Components in Automated Decisions
In order to effectively manage automated decisions, organizations need 3 key architecture components: decision management, decision analytics, and case management.
- Decision management enables business analysts and domain experts to capture, test, optimize, and manage the decisions.
- Decision analytics enables business analysts and domain experts to measure the business performance of the decisions.
- Case management enables IT to investigate when decisions fail to execute properly (investigative). In addition, it enables case workers to manage decisions that cannot be fully automated (operational). For example, there may be cases where you do not want to automatically approve or decline a loan applicant. Depending on the situation, you may want a fraud analyst or credit analyst to review the application and transaction data before making a decision.
We have already covered the importance of decision analytics in decision management (see From Decision Management to Prescriptive Analytics and Improve Your Automated Decisions with Decision Simulation). The previous generation of BRMS and analytics tools focused on capturing expertise from experts or data and not on improving business performance. The next generation of decision management tools, like SMARTS™ Decision Manager, has made decision analytics core to their capabilities.
What is less obvious is how next-gen decision management can enhance traditional case management approaches. Using decision management tools, case managers can efficiently capture expertise and apply that to decision-making. I cover how case managers can benefit from decision management in my next post.
Learn more about Decision Management and Sparkling Logic’s SMARTS™ Data-Powered Decision Manager