Decisions, complex and simple, are made throughout organizations every day. Many of these decisions are manual, but a growing number of them are automated.
Decisions are typically recognized through action words, such as ‘determine,’ ‘calculate’ or ‘estimate.’ For example, through a customer onboarding process, client details are collected and then decisions are made to: ‘determine due diligence,’ ‘determine suitable products’ within the client’s area of interest and associated risk determination, ‘determine risk level for this domain,’ ‘calculate product cost,’ as well as many more decisions throughout the KYC and AML processes. Once onboard, there may be other decisions such as ‘determine upsell products’ to add further value to the customer engagement.
We use the term business logic to represent how the decision conclusion is determined from a set of input data. Traditionally, there has been no robust and rigorous mechanism to extract business logic relating to decision making from process and data domains as well as various non-standard documents and spreadsheet formats. This results in the business logic being lost in a sea of domains, documents and formats. Change and automation becomes expensive and extremely high risk.
Decision management changes the game by creating a specific domain, separate from process and data, where decisions are determined, defined, tested, governed and analyzed. The advent of a robust and rigorous model (The Decision Model) provides the design principles and models that ensure decisions have integrity, and are unambiguous, accurate and consistent across an organization. The combination of intuitive graphics and intelligent tables drives common understanding of the decision business logic irrespective of role (BA, SME, Product Management, Audit, IT, Test, …).
The result is a set of reusable decision services that can be consumed across multiple processes and channels, driving improved omni-channel capability and customer experiences. Change management becomes greatly simplified as the user creates new versions of the decision model from the current model, with the ability to compare, test and release. Regulatory compliance also benefits greatly through the transparency and common understanding of the regulatory decisions interpreted and modeled from the appropriate regulation and/or policy.