133 Emerging Standards in Decision Modeling—an Introduction to Decision Model & Notation James Taylor, Decision Management Solutions; Alan Fish, FI CO; Jan Vanthienen, KU Leuven; Paul Vincent, TI BCO 1. INTRODUCTION The BPM market has expanded and matured in recent years, driven in part by the growing acceptance and broad use of process standards and common modeling notations. As companies transition to intelligent BPM, however, there is a need to focus on decision-making as well as process execution and workflow. Decision-making is important in intelligent processes, making them simpler and more agile as well as increasing the rate of straight through processing. However existing standards and notations do not readily support the modeling and specification of decision making. To address this need a new standard is being developed at the OMG, the Decision Model and Notation (DMN) standard. The primary goal of DMN is to provide a common notation that is readily un- derstandable by all business users, from the business analysts needing to create initial decision requirements and then more detailed decision models, to the technical developers responsible for automating the decisions in pro- cesses, and finally, to the business people who will manage and monitor those decisions. DMN creates a standardized bridge for the gap between the business decision design and decision implementation. As many analysts designing and building business process models are also referring to or de- signing decisions, DMN notation is designed to be useable alongside the standard BPMN business process notation. In this paper four members of the submission team describe the importance and scope of decisions in intelligent BPM, introduce the basics of decision requirements modeling, discuss modeling decision logic in Decision Tables and provide an overall context for decisions in BPM more generally. 2. THE IMPORTANCE OF DECISIONS IN INTELLIGENT BPM A focus on decisions delivers on three critical elements of intelligent BPM— increased agility and capacity for business-led change; dramatic increases in Straight Through Processing / numbers of totally automated processes; and the ability to extract and operationalize value from Big Data analytics. Increased Business Agility Simpler and Therefore More Agile Processes Making decisions explicit and managing them in concert with processes en- sures an effective separation of concerns and a more streamlined design. Specifically, combining process management and decisioning decreases pro- cess complexity.