How to estimate uncertain data

Data Estimator is a tool that helps answer questions about uncertain quantities, eg. “What will our company’s sales be next year?”

It is designed to be used as part of an interview process, where expert judgements are drawn out and quantified.

It’s a reminder that in this world of big data, some things remain hard to measure, especially when it comes to the future.

You will be asked a handful of questions, using “probability wheels” like this to visualise the uncertainties:

probability wheel

When you’re done, you will be able to see and export the resulting probability distribution. For example, the result could be “there is a 60% chance this market will more than double in five years, a 20% chance it will more than treble, but a 10% chance it will shrink.”

probability density

It will also show some alternatives for you how you could place the uncertainty in a decision tree, eg.

decision tree node

Try it out here: http://racingtadpole.com/more/estimator/

  

One thought on “How to estimate uncertain data”

  1. Arthur,
    Your blog reminds me of what John Maynard Keynes wrote in the 1930s about investment appraisal:
    “The outstanding fact is the extreme precariousness of the basis of knowledge on which our estimates of prospective yield have to be made. Our knowledge of the factors which will govern the yield of an investment some years hence is usually very slight and often negligible. If we speak frankly, we have to admit that our basis of knowledge for estimating the yield ten years hence of a railway, a copper mine, a textile factory, the goodwill of a patent medicine, an Atlantic liner, a building in the City of London amounts to little and sometimes to nothing; or even five years hence.”
    Hence there is a valuable role for Data Estimator tool to elicit the tacit knowledge of experts in a well-structured process.
    Best regards,
    Jay

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