Digital transformation is not just about implementing technology or changing the way technology is used. It is about a more evolved business experience; from operations to strategic decisions, companies are collaborating more with goals to improve workflows and increase the bottom line. Through automation, enhanced connectivity and more sophisticated decision making, organizations can change the way they work to improve customer interactions, day to day processes, and ultimately achieve their business objectives.
With FICO DMN Modeler, decision makers can understand exactly what goes into the decision making process. DMN Modeler takes a top down approach by understanding what inputs are necessary for the decision, rather than determining decisions based on the data that’s available. Because DMN follows an industry standard, Decision Model and Notation, all members of an organization can follow the decision process and understand key elements to the logic. This increases collaboration between teams and eliminates any confusion or lack of clarity stemmed by decisions made in silos. When analytic models or other inputs change, DMN Modeler easily shows how these changes effect the final decision, helping build collaboration between data scientists, LOB managers, and executives that are all following the same decision requirements diagrams.
For example, let’s say I want to buy a car. With Decision Model and Notation, there are 4 simple components involved in creating a Decision Requirements Diagram (DRD) to outline all necessary data and decisions to understand the decision process behind my purchase.
Deciding what car to buy involves several decisions and data points.
- Decision element – the business concept of an operational decision. In buying a car, the key decisions I need to make are the actual purchase of the car, deciding what my preferences are, and determining how much I can afford.
- Input data element – the data structure whose component values describe the case about which decisions are to be made. When deciding what my car preferences are, some of the inputs that I would consider are the quality of the car, or the color and style of the vehicle.
- Business knowledge model – business concepts such as policies, which could be an analytic model or an algorithm. In my car preferences, I would apply a set of rules or ranking. For example, I would have a scorecard ranking certain features such as a technology package, safety, and size of the car.
- Knowledge Source – this is where the knowledge or information to make a decision comes from. If I think about how I can better understand the quality of the car, I would consider my own personal experiences (with that particular make and model), as well as consumer ratings.
You can build a Decision Requirement Diagram (DRD) to capture everything in one place.
By using a DRD, it’s very easy to see how changes affect different parts of the decision making process. If one day I decided that my scorecard for car preferences changed, it would impact the entire decision. Because “car preferences” is one of the main decisions in the actual purchase of the car, changing the way I prioritize different features could change my ultimate decision.
Making decisions can be difficult and risky. Let DMN Modeler simplify the complexity of decisions through a clear industry standard. With DMN Modeler’s simplified decision-first approach, your organization will disrupt its existing processes and become more collaborative and efficient.