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What is Decision Management?

Modern-day business operations are centered around processes and data. However, when knowledge and expertise are forced into hard-coded, inflexible systems, bottlenecks occur. By adopting and scaling the capabilities of business rules, decision modeling, and machine learning, Digital Decisioning leverages data and expertise to create business value, improve results, and deliver a great user experience to effectively meet today’s operational requirements. For Digital Decisioning to deliver true value, it must initially focus on solving business problems that will, ultimately, contribute to positive and desirable business outcomes. Technology, automation, and methodologies are essential for Digital Decisioning, but they are always at the service of business decisions. 

The foundation for successful Digital Decisioning projects is applying a Decision Management approach. Decision Management models business decisions first. These decisions, for the most part, have to do with customers and how you engage with them, deliver services to them, or handle their transactions.Once you have a good grasp of what decisions your business needs to make and how these decisions will advance your business, Decision Management shows which technology and analytics tools you need to invest in and how to integrate them. Finally, Decision Management focuses on the processes and infrastructure needed to ensure continuous improvement and business engagement. To maximize success, adopt a proven approach such as the DecisionsFirst™ approach from Decision Management Solutions.

Decision Management operationalizes predictive analytics. Traditional approaches to analytics are hard to scale and hard to use in the real-time environment required in modern enterprise architectures.

Decision Management frames a predictive analytic effort, establishing a shared understanding across business, IT, and analytics teams. CRISP-DM and other methods stress the importance of business understanding but lack a repeatable, understandable format.  Decision modeling fills this gap. Decision modeling is a successful technique that develops a richer, more complete business understanding earlier. Decision modeling using the Decision Model and Notation (DMN) standard results in a clear business target, as well as an understanding of how the results will be used and deployed, and by whom.

With decision management you will:

  • Know where to get started
  • Know where and how the results will be deployed.
  • Reuse knowledge from project to project.
  • Value analytics in terms of business impact.

Predictive Analytics

We provide a complete set of consulting and training for Decision Management to help you build your decision management capability today. Our decisions-first comprehensive approach matches business drivers to decisions. Our approach is optionally supported by our collaborative decision modeling software, DecisionsFirst Modelerd for the implementation program.

Customer Next Best Action – Retail Banking

This major European retail bank’s Next Best Action initiative deployed multiple technologies, including predictive analytics and business rules, with significant organizational and process changes.

Decision Management Solutions:

  • Conducted a rapid review of the initiative, assessing technology, organization, modeling, and other capabilities.
  • Assessed multiple vendors’ analytic and business rule technology in the context of a complex technical architecture.
  • Delivered specific go-forward recommendations about the design and the critical boundaries between products.
  • Developed a decision model that described how predictive analytics, business rules, and other insight could be arbitrated to produce the best possible results while managing the trade-offs between batch and interactive deployments.

The results were foundational for gaining approval and for the implementation program.

Harness Data-driven Decision Making