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.
Business decision makers looking to add decision management, business rules management and predictive analytics capabilities to your competitive arsenal need an effective requirements framework. Use cases, process models, requirements documents and traditional waterfall approaches don’t work well for these iterative and decision-centric technologies. To work with analysts, developers and architects on these projects you need a common vocabulary and a shared perspective. This overview of decision management gives you what you need – an introduction to the core concepts and technologies and an outline of the best practice approach refined from years of real-world experience.
Building the requirements for decision management, business rules and predictive analytics requires new skills and approaches. Use cases, process models, requirements documents and traditional waterfall approaches don’t work well for these iterative and decision-centric technologies. Whether you are responsible for specifying requirements or integrating those requirements into an overall architecture, you need to add new techniques to your skill set. This pair of classes provides the critical context of the overall decision management approach, including an overview of the technologies, as well as introducing the most effective requirements approach for these systems – standards-based decision modeling using OMG’s Decision Model and Notation (DMN) standard.
Business Rules Analysts, Decision Service Developers
Decision management, decision services and other business rules-based implementations are great ways to build agile, adaptive and increasingly analytic systems. To be effective at developing these systems, especially if you are responsible for the business rules or decision-logic at their core, you need to connect high-level business concepts to detailed decision logic – and make sure that logic is unambiguous, precise, maintainable and transparent. These classes provide a framework and approach for iterative development, introduce the more effective approach to modeling requirements and teach you how to use the most widely used approach to specifying business rules – decision tables. And they do all this using decision modeling with DMN, a proven and standards-based approach.
Data Scientists, Analytics Modelers
Accurately framing the requirements for predictive analytics and embedding those analytics into real-time, prescriptive systems requires more than just data science skills. Applying proven approaches like CRISP-DM with their focus on business understanding, business value and iterative development requires more than just workflow thinking and the identification of success metrics. These classes provide an overview of decision management, a proven approach for developing and embedding predictive analytics and introduce the most effective requirements approach for predictive analytics – standards-based decision modeling using OMG’s Decision Model and Notation standard.
Learning Path Registration is now closed. Contact us for course package and group discounts.
Next sessions Fall 2016.
- Live Session: This is live training. Recorded sessions will be available to registrants on the day of each session.
- DecisionFirst Modeler: DecisionsFirst Modeler has a free basic version so participants can continue to use and develop their models in the software after the class.
- Cancellation Policy: Registrations may be canceled up to 48 hours in advance of the first class. A 15% administrative fee will be retained if you choose to cancel. To cancel, please contact us.
- Technology Check: The class will be conducted in Adobe Connect, a Flash-based environment. Please test your environment beforehand at https://admin.acrobat.com/common/help/en/support/meeting_test.htm. We will use chat and Q&A to communicate in the class but it is also helpful if we are able to have audio interactions. For audio interaction you need a microphone or headset connected to your computer and you need to have downloaded the Adobe Connect Add-in from the test URL above.
- Audio: Audio plays through your computer speakers. Please have a microphone or headset available for your computer so you can interact during the class. You will be able to type questions and comments, but a headset or microphone allows for more interactivity.
- If for any reason the class cannot take place as scheduled, you will be offered alternative training dates at the same price.