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What is decision automation?

The concept of decision automation (DA) is deceptively simple and intriguingly complex. DA refers to using information technologies to make decisions and implement programmed decision processes. Typically decision automation is considered most appropriate for well-structured, clearly defined, routine or programmed (cf., Simon, 1960) decision situations.

An automated decision process occurs without any "human" intervention. Decision making procedures are programmed and then the appropriate programs evaluate stored or "real time" data from sensors. Then using either algorithms based on quantitative models, logical or quantitative heuristics, statistical inference, or artificial intelligence technologies one or more actions are chosen to apply in the situation. The actions are taken by effectors including human or machine actors. An effector may change the value in a database, send a message or an alert, move an object or play a message.

Human decision makers determine the rules, models and methods used for making choices and completing decision tasks in programmed decision situations. Conceivably decision automation programs can "learn" from successes and failures and automatically improve and update the relevant stored procedures, rules or likelihoods.

Decision automation is a set of concepts, a related set of technologies, a set of methods and design tools, and an ambitious, general "goal". The range of decision tasks that can be automated has increased as technologies and design tools have imporoved. This technology evolution has also raised aspiration levels and created more challenging development goals. The overriding goal is to replace human decision makers in programmable decision situations where it can be demonstrated that the computered decision is at least as good as that of all or most human decision makers. The working assumption is that decision automation will be cost effective when compared to an equally skilled human decision maker in a programmed decision situation. The greatly expanded and evolving computing infrastructure makes it increasingly cost effective to apply decision automation in situations where that had been prohibitively costly.

Simon, H.A. (1960). The New Science of Management Decision. New York, NY: Harper and Row.