Why Research Decision Making?

29 Sep

It’s a common question when that is what you do. Researching decision making is fascinating, but you don’t do it just because you like the topic- although that helps. I research decision making because it yields so much valuable information about people, processes, cultures and organisations; and perhaps most interesting- it tells you a lot about innovation and insight.

Investigating the decision making process provides a window into how people, collectively and individually, make sense of common and unique situations. It provides data on how they reason, what do they notice, what do they ignore, how do they prioritise, what type of errors do they make, their problem solving strategies, how do they identify or explain away errors, and how do they utilise their environment and resources. And most significantly, how do people and organisations do all these things when plans go wrong.

This data gives you access to the most effective “shadow skills”, skills which don’t feature in a manual but are highly effective, the short cuts which out perform statistics, the errors which get explained away-bias, and cross links between disciplines which can be used in problem solving and innovation. It also provides data on how effective procedures, organisational structures and cultures are in dynamic, problem solving situations. Overall, it provides you with the deep structure of an individual or collective.

The results of decision making research are designed to take this product of deep structure and use it to drive insight- a new broader perspective, which kicks thinking and problem solving out of a spiral. We use it for all types of projects, but recently it’s having particular value in this direction -taking ideas which have reached a dead end, but have great commercial potential (an academic research project for example), and applying decision research to kick out this dead end and create a “product” of commercial value.

This is why it works in this example- academic research can get stuck in a spiral, an impasse of domain constraints, time and capacity. It’s easy to see commercial potential but there is a real gap between this potential and fulfilling the user requirements of the commercial world. The gap isn’t addressed by big ticket sales or constantly tweaking one pagers, it’s addressed by research which brings together the reasoning of the two domains. The structure of reasoning is identified in decision making research, the sense making, error types, problem solving etc. Stripping the commercial and academic domains down to structures allows the cross links to be more easily identified- it allows one domain to gain insight from the other in a way which solves a problem and adds genuine value.

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