5 Reasons Why Business Analysts Like Decision Modeling with DMN

The purpose of business analysis is to accurately describe the requirements for an information system (more or less). Business Analysts use a variety of techniques to do this. They use techniques designed to help them find out what is required, to elicit the requirements, and they use techniques to describe and model those requirements in a way that is clear and implementable. In working with Business Analysts on a wide range of projects, I’ve drawn up my observations on why BA’s like decision modeling:

Decision Modeling  helps effectively use business rules.
For business analysts driving requirements for business rules analysis and business rules management system (BRMS) implementation, decision modeling provides a critical framework for success. Focusing only on the business rules themselves often results in a “big bucket o’rules” that are poorly coordinated and hard to manage. Decision modeling provides the needed principle to impose some business oriented structure on this complexity. Also, the separation of a declarative definition of these rules from the sequence-oriented business process improves both rules and processes.

Decision Modeling helps simplify processes and workflow.
Most systems involve some workflow and this is increasingly described by business analysts in terms of business process models. Experience shows that when these process models do not explicitly call out decisions, the process becomes over complex. Decision making modeled as business process is messy and hard to maintain. The local exceptions that can overwhelm process models are often all about decision-making. With decisions identified and modeled separately from the process these local exceptions don’t clutter up the process. Identifying and modeling decisions makes business processes simpler, smarter and more agile. The Decision Model and Notation (DMN) standard is a peer of the Business Process Model and Notation (BPMN) standard.

Decision Modeling clarifies analytic requirements.
The primary purpose of analytics, whether business intelligence, data mining or predictive analytics, is to improve decision making. With decision modeling, business analysts can identify and describe the decisions for which analytics will be required. How the data requirements support these decisions, and where these decisions fit, will be clarified and the use of analytics focused more precisely, delivering IT/Business/Analytics team collaboration and successful deployment.

Decision Modeling is the foundation for better data-driven decisions.
Everyone wants to make better data-driven decisions. Many companies are using reporting to support decision making but their ability to do so is bogged down. There are too many reports, resources are committed to existing reports and the link from reports to decision making is not well understood. Consolidating and streamlining reports is straightforward with decision management. A simple decision model, easily understandable to business and IT, makes it clear which reports are relevant, which are redundant and what is missing. The decision model also clarifies where analytics could be included to further improve decision making, what data is relevant and what data storage is appropriate (data warehouse,data lake, etc).

Decision Modeling is an Industry Standard and Best Practice
Decision modeling with the DMN standard is rapidly becoming a best practice for requirements across a range of projects, especially those looking to incorporate now or in the future BRMS or analytics capabilities. In addition to the DMN standard, software vendor support is rapidly growing and decision modeling is a new technique in the International Institute of Business Analysis (IIBA) Business Analyst Body of Knowledge or BABOK (R) version three.

Business Analysts have a pivotal role in the success of any systems project. They recognize the importance of tools and techniques to better describe the business requirements. Business Analysts want to use business rules most effectively, simplify complex business processes and focus analytics efforts. That’s why Business Analysts I’ve had the pleasure to work with like decision modeling.

An earlier version of this post first appeared on www.jtonedm.com.