All industry standards offer interchange. Successful standards offer skills interchange not just a technical interchange format.
The Decision Model and Notation (DMN) decision modeling standard has a published XML interchange format, of course, and several of the committee’s members are working really hard to iron out the remaining issues and make the XML interchange more robust. The ability to interchange decision models between vendors is a valuable one but the opportunity that DMN offers for skills interchange is, if anything, even more valuable.
DMN offers two critical kinds of skills interchange – it offers those working with business rules or decision logic a way to transfer their skills between products and it offers business analysts a way to transfer skills between different kinds of decisioning projects.
The vast majority of the business logic in a decisioning system can be defined using the two core DMN components:
- Decision Requirements Diagrams structure decision problems, break them into coherent pieces. They show where data is used and what knowledge assets (policies, regulations, best practices) are involved.
- Decision tables specify the logic for most of the decisions on the diagram using simple constructs.
You don’t get 100% of the execution defined using these two elements -you need to add “glue” of various kinds – but almost 100% of the business content is defined using these them. This means someone who knows DMN can transfer these skills between DMN tools. But it also means they can transfer these skills between business rules products too as the approach of decomposing a decision problem into a Decision Requirements Diagram before writing logic is totally transferable and frankly most decision tables look and work the same even if they don’t support DMN yet.
The second kind of skills interchange comes because decision modeling works for lots of different kinds of projects. We have used decision modeling and DMN to:
- Define business rules / decision logic for automation
- Frame requirements for predictive analytics and machine learning project
- Orchestrate a mix of packaged and custom decisioning components including business rules, predictive analytics, AI and optimization
- Model manual decision-making for consistency, mixing manual and automated decision making
- And more – see Decision Modeling has value across many projects
This means that business analysts who learn decision modeling can apply that skill across lots of projects.
Learn decision modeling and learn DMN. It’s a great skill that let’s you express business decision problems and one that is transferable -interchangable – across projects and products.
