In my earlier post I talked about Wide Band Delphi. WBD stands of its own when the requirements are clear and there are no possible hindrances. But, how often do you make software in ideal conditions? As Murphy’s Law states, if something can go wrong, it will go wrong.So it’s better to make a range estimate when compared to a point estimate. These are highly useful in cases where the requirements would become gradually clear and not initially.

Here, just like WBD, estimators whose have expertise in the particular field assemble. But unlike earlier, here they provide 3 estimates for each task.

a) Best Case

b) Worst Case

c) Most likely

But we are not done yet. The next step is to assign probability to each of these cases. Let’s say we assign

a) P(Best Case) = 0.2

b) P(Most Likely) = 0.6

c) P(Worst Case) = 0.2

Next step would obviously be calculate the estimated value and of course the Standard deviation as we are mentioning the range.

Expected Value = μ = Sum ( x ) * P ( x)

Standard Deviation = σ = Worst Case * P (Worst Case ) – Best Case * P( Best Case)

You would do this for each of the estimators and take their average to find the cumulative Expected Value and Standard Deviation. We now proceed to calculate (μ-3 σ) and (μ+3 σ) values, which would in-effect, give us a better estimate than the usual WBD method.

We could also calculate (μ-6 σ) and (μ+6 σ) values or (μ-1 σ) and (μ+1 σ) values depending on whether want 68% CI or 95 CI or 99% CI. Now doesn’t this sounds more analytical than the default Wide Band Delphi method ??

Manoj ++, making of a Global Citizen…!

1 year ago