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Elements of Decision Engineering

Decision making in many organizations has reached a complexity ceiling. Decision makers are inundated with information, constrained by ever-decreasing timeframes, and are swamped with complexity. In short, the needs of effective decision making have exceeded what can be achieved using informal approaches and improvised tools.

As in other disciplines that reached this watershed at some point during their histories (for example, construction and software engineering), a number of existing best practices are crystallizing into the emerging discipline of decision engineering. Following traditional engineering concepts, the essentials of decision engineering are outlined in the diagram below.

If the outcomes in other disciplines that adopted an engineering methodology are a guide, then the transition to decision engineering will have a dramatically positive effect on the timeframes, quality, and success of decision making.

Elements of Decision Engineering. Hover over rectangles in this diagram for explanations.

Hover your mouse over rectangles above for an explanation.

Planning is the phase of Decision Engineering during which decisions are made.  Planning is one of two primary phases of decision engineering, the other being Implementation of the decision. Implementation is the second of the two main Decision Engineering phases, the first of which is Planning. During Implementation, the decision that was made during Planning is executed within the organization, and its outcome is tracked. The decision engineering lifecycle consists of two phases: planning and implementation. Often, these phases alternate, as new information necessitates replanning, in a continuous cycle. Requirements capture and document what the decision is required to achieve, the choices available to decision makers, and the restrictions that constrain choices.  Unlike specifications, requirements are expressed in the language of the stakeholder in the decision, which is not precise. A decision specification starts with the requirements, and refines them into an implementable, testable language Design is the heart of the decision engineering process, and includes methodologies, tools, and processes for creating the decision itself.  As with an architect’s blueprint or software UML diagram, a structured visual language for expressing decision elements, their properties, and the relationships between them, is critical.  Such diagrams unambiguously both record and communicate assumptions, data sources, conclusions, and flow of reasoning. Decision quality assurance comprises processes that detect potential errors in a decision.  We can evaluate a decision for incorrect assumptions, flawed reasoning, statistical bias, and other errors. Alignment refers to the process by which multiple decisions throughout an organization, as well as the personnel responsible for making those decisions, are synchronized.  Alignment becomes especially critical in a rapidly changing environment. The core to the implementation phase is decision execution, which in all but the simplest of environments must be tightly coupled with monitoring key factors to ensure that they remain inside the bounds within which the decision model yields the desired outcomes.  If during monitoring, new information arises indicating the original decision should be adjusted, then the activities in the planning phase are restarted. Alternatively, specific changes may have been anticipated through multiple scenarios created at planning time, in which case execution is changed to reflect the appropriate new scenario, without requiring the extra time for replanning.
 
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