Decision engineering is applying relevant knowledge to design, build, maintain, and improve systems for making decisions.
Relevant knowledge can include knowledge of at least three kinds:
Theoretical knowledge from any relevant field of inquiry;
Practical knowledge (know-how, or tacit knowledge) of the decision engineer;
âLocalâ knowledge of the particular context and challenges of decision making, contributed by people already in or familiar with the context, such as the decision makers themselves.
In most cases, decision engineering means taking an existing system and considering to how improve it. A system can be better in various ways, including:
First and foremost, improving the decision hit rate, i.e. the proportion of decisions which are correct in the sense of choosing an optimal or at least satisfactory path of action;
More efficient in the sense of using less resources or producing decisions more quickly
More transparent or defensible.
Now, in order to improve a particular decision system, a decision engineer __might __use approaches such as:
Bringing standard engineering principles and techniques to bear on making decisions
Using more structured decision methods, including the application of decision analysis techniques
Basing decisions on âbig dataâ and âdata science,â such as predictive analytics
like this more general definition of decision engineering (in four words or less, building better decision systems) because it seems to get at the essence of what decision engineers do, allowing but not requiring that highly technical, quantitative approaches might be used.
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