Syndicated from BeyeNetwork
The Evidence Based Management blog had a post on Why experts are so often wrong that discusses a book by Philip Tetlock (Expert Political Judgment: How Good Is It? How Can We Know?
In a world filled with expert predictions that are mostly incorrect, and filled with people who eagerly seek such predictions even though they are incorrect, Tetlock’s book explores why experts are so often wrong and why we listen to them anyway. There is no more evidence-based subject matter than forecasting. This book provides an excellent overview of the perils and pitfalls in making forecasts.
But if we can’t rely on experts to synthesize information and pass on judgments to us, can we make our own? Perhaps not, according to another post, this time from the Institute for the Future. In So much information, such limited ability to understand it all Vivian Distler quotes Stephan Dahl:
we make the assumption that they will be able to keep up with and synthesize the abundance of information that may be relevant to their health. 21% of adult Americans have only rudimentary skills, leaving them unable to extract even simple information from printed material. A further 25% can perform simple reading functions but “cannot integrate or synthesize several facts” from documents.
and she goes on to ask
Information will have to be made accessible and understandable. Are we ready to take on that obligation?
Personally I don’t think it is the information that needs to be made accessible and understandable, but the decisions that must be made with that information.We should not allow experts to make judgments without process (as I discussed here) and we cannot rely on consumers (or front line staff) to have the necessary analytic skills. Instead we should focus our experts on understanding how we might make a good decision and build that expertise (those rules) into a decison making system that also allows those impacted to add constraints or additional rules. These rules could take advantage of sophisticated analytics without just handing over decision-making power to the analytic models.
The end result could and should be a transparent system that makes decisions consistently based on the data and on robust analysis of that data using rules that come from regulations, policies, expertise and personal preference. An action support system not just a decision support system. Just a thought…
