Instead of each company, team, individual or toolset representing decision-making using their own brand of spreadsheet, word document or visio diagram, the Decision Model and Notation (DMN) defines a powerful, open standard for documenting decisions that means you are not tied in to a specific toolset, vendor or business analyst.

Decisions expressed in the Decision Model and Notation (DMN) are not only transparent but directly executable. This means that business analysts can test them with real data to see how they behave and explore multiple ‘what if?’ scenarios. It also means they can be deployed directly into a decision service that can be used from your business processes without any manual translation into code by IT teams. This avoids the errors and omissions that coding can introduce.

Using executable decisions models allows you to explain every behavior of your system after the fact. If the outcome of a decision is unexpected you can see exactly how it was reached by referring to the decision model. This accountability is generally useful, but vital in decision-making that supports regulatory compliance.

Because decision models capture all the sub-decisions, data and business knowledge that outcomes rely on, it is much easier to get a rapid impact assessment of any proposed change in decisions logic, input data or knowledge source. Armed with this, and the regression testing facility that most decision management stacks provide, you will never be surprised by the consequences of changes and can practice safe agility: the ability to alter your logic and check the consequences quickly and without error. Furthermore, decision modeling allows subject matter experts to explore the performance of alternate decision models. Both of these factors promote agility and innovation.

Using decision modeling rapidly drills down on your true data and knowledge requirements preventing the costly oversights that can lead to under or over provision of data.

Using the Decision Model and Notation (DMN) to express decision models has the added advantage that not only is it easy to understand by business subject matter experts, but models can be directly deployed into decision services providing a model driven development of business decisions, significantly decreasing the cost of change.

Decision modeling is a very effective means of integrating business rules, predictive analytics, optimization and cognitive aspects of decision-making into one coherent whole. Decision modeling can be used to consolidate BRMS, analytics, optimization and cognitive technologies.