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DecisionCamp 2017 Recap: DMN and Analytics

by | Aug 7, 2017 | DMN, Events, Predictive Analytics

I was pleased to be able to both attend and present at DecisionCamp 2017 in London on refinements to DMN and decision modeling for analytics. I want to thank my fellow members of the organizing committee and I would like to recognize the efforts of the conference Chair, Dr. Jacob Feldman, for making this important event possible.

Jan Purchase of LuxMagi and I presented on Refinements to DMN 1.1 Suggested by Real-World Experience, outlining three gaps in the Decision Model and Notation (DMN) that we see in the specification. Here’s our presentation and you can get more on our thinking in our book, Real-World Decision Modeling with DMN:

I also spoke on the role of decision modeling in defining business understanding and requirements for data science projects and in deployment.
Data science projects face common challenges:
  • Poor collaboration
  • Too many distractions and iterations from the business
  • A technically correct analytic model not delivering the business value.
  • Analytic models not getting deployed.

Decision models define the business understanding in a collaborative, graphical and business-friendly way. The process of decision modeling ties the analytic to the business result, shows how the analytic impacts the decision and clarifies the deployment context.

  • Decision modeling using the DMN industry standard gives you a clear sense of the business impact of your analytic, helping you and your business partners evaluate it and put it in context.
  • Decision models define what it will take to make your analytic actionable, making it clear exactly what needs to be deployed.
  • Decision models set up the framework you need to collect and analyze data about your model’s performance and its business impact.

To learn more, read our Briefs,


For more on DecisionCamp 2017, check out my blog series on JTonEDM for more details.


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