We recently released The Decision Management Manifesto. In previous posts I explained why we did this and why decisions are important. This week I want to talk about the technologies involved in Decision Management.
Most organizations will find that adopting Decision Management requires them to adopt some new technologies. Managing and automating business decisions is different from automating workflow or managing data. Business decisions have a lot of business content, decision logic, that must be visible and easy to change. They are often influenced by what has worked or not worked in the past, analytics. They often involve complex trade-offs and it is not always easy to tell immediately if a decision was a good one or not. These characteristics lead to four specific Decision Management technologies:
- Technology to manage decision logic.
Organizations typically adopt a Business Rules Management System to manage decision logic more effectively.
- Technology to develop and embed predictive analytics.
Organizations use data mining or predictive analytic workbenches, packaged analytic models, machine learning and other techniques to turn their historical data into usable analytic insight that can be embedded in systems.
- Technology to manage trade-offs and simulate results.
Some organizations adopt constraint-based optimization tools while others use trade-off matrices and other analysis techniques.
- Technology for monitoring and improving decision-making over time.
Often a mix of established performance management technologies and decision-specific simulation and impact analysis tools.
These technologies are often adopted separately or for specific purposes. Regardless they should not just be used by lumping them into traditional development efforts. Instead they should be used to develop Decision Services that provide decision-making to business processes, event-based systems and legacy or packaged applications. In parallel organizations should use add the infrastructure necessary to manage the logic and analytics in the decision over time and to link decision outcomes to the business impact of those decisions. This set – decision services, supporting infrastructure and decision analysis integration – is what we call a Decision Management System.
Decision Management Systems are different. They are agile because they use business rules to deliver transparency, business collaboration and rapid change when necessary. They are analytic because the analysis of historical data is used to adjust the way the system acts. They are adaptive because their performance is explicitly monitored and used to drive ongoing change and improvement.
The three steps of Decision Management – Decision Discovery, Decision Services and Decision Analysis – drive the construction and management of Decision Management Systems so you can transform your business.
You can always access the latest version of the Decision Management Manifesto at decisionmanagementsolutions.com/decision-management-manifesto and there’s an explanatory white paper too.
And/or join me for the upcoming webinar; The Decision Management Manifesto Explained, Wednesday, November 20, 2013, 9:00 AM PT.