Posts in the series:
- Benefits of Decision Modeling
- What is a decision model and what is DMN [this post]
- Decision Modeling: Decision Requirements
- Decision Modeling: Decision Logic
- Decision Modeling: Finding and modeling decisions
- Decision Modeling: Input Data and Knowledge Sources
- Building decision tables from decision models
- ML, AI and other forms of Data Analysis and Advanced Analytics
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In the first post in this series, I outlined the benefits of decision modeling. But what are decision models?
Decision Models – Visual Blueprints
A decision is the act of determining an output from a set of inputs – calculating, determining or selecting something – so you can take action. While mostly used to define decision-making that is going to be automated, so it can be executed repeatedly, decision models can define decisions that will be made manually and/or only once.
Decision models are visual blueprints for describing how a decision should be made. This visual blueprint shows how the decision-making can be broken down, and how the pieces of decision-making are orchestrated to make a coherent decision. It shows the data involved, the data output decisions, as well as the data sources.
This visual blueprint acts as a frame for capturing specific details about the decision-making. It is extended with detailed definitions of exactly how decisions are made – the logic, business rules, analytic insight or machine learning involved – to create a complete specification of the decision-making. It can be linked to metrics, processes, and organizational constructs.
DMN – the Industry Standard
While there are multiple ways to draw and manage decision models, there is only one industry standard – the Decision Model and Notation standard. DMN is managed by the Object Management Group (OMG) – the organization known for UML and BPMN among many other standards. DMN was first published in September 2015 and is an actively managed and constantly updated standard, now at release 1.5.
The DMN committee (Decision Management Solutions and IBM are both members) constantly reviews issues raised by the public, fixes errors found and extends the standard to cover new topics as new use cases and scenarios reveal limitations and issues. Each new release is backward compatible with previous ones and published documents are freely available – anyone can download them and build software that conforms.
One note on the specification, is that it is written for those who are developing software to support the standard, not for those who wish to build models using the standard. As such, reading the standard is not recommended as a way to learn how to apply it! Instead, find articles (like this one), books (like mine) or training classes instead!
DMN is the best way to build decision models – partly because it’s an industry standard (boosting your ability to transfer skills and interchange specifications) and partly because it’s just the best way to represent decisions: It’s simple to use yet it scales to incredibly complex problems, it allows non-technical people to specify things precisely, and it supports everything you need to define decision-making problems.
To do this, it has two layers – a decision requirements layer and a decision logic layer. I’ll cover those in the next two posts.
If you want more detail, you can get a text book on the approach (written by me and Jan Purchase): Real-World Decision Modeling with DMN 2nd Edition. If you or your company need help with decision modeling, drop me a line james@decisionmanagementsolutions.com and we can schedule a quick call to discuss. And if you’re excited about decision modeling and keen to do more, why not join DecisionAutomation.Org and participate?
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