[andyferris]

Hi Nilan - thanks for your words. It’s true, that as someone who is ultimately employed as a researcher in some role, I do wonder (a) when research is valuable and (b) whether the people controlling the decisions of when/how much research to undertake can justify this decision quantitatively. (But rather than think of “research” I’d prefer to back that out into a more fundamental concepts like “information”.)

I think your question 1 is partially answered by the inequality — it provides a upper bound for how much utility you could gain from the research. More practically, perhaps a decision maker could use gut feeling to break it down into quartiles — outcomes which are worst case (0th quartile), below average (1st quartile), average (2nd quartile), above average (3rd quartile) and best case (4th quartile). If the estimated cost of research is much less than ROI(3rd quartile) minus ROI(1st quartile), then the research seems worthwhile even for “typical” outcomes. If the estimated cost of research is greater than ROI(4th quartile) minus ROI(0th quartile) then the research is obviously not worthwhile (that’s the inequality).

I think your questions 2 and 3 are the questions I would also like to see answers to :) I think that given decision makers come from a variety of (often non-mathematical) backgrounds, tools should be simple and easy to use/remember, which is why I’m focusing on using things like “worst case scenario” and “above average scenario” and so on. That way we get to combine quantitative analysis and gut feeling to get good outcomes from typical decision makers.

And yes — I completely agree that the agile “release often, get feedback early” and the startup “move fast and break things” philosophies are designed for revealing information quickly so that you can make good decisions as early as possible (thus also maximizing the utility of that information). As a general work pattern, I put this under a kind-of “don’t be stupid” mentality — even if this maybe wasn’t obvious 25 years ago. I think the topic of the article is to be able to address specific, large decisions (like exercise 2).