Rationality of estimations

[sharovatov]

Details

Estimations (as pretty much any practice) comes at a cost.

There's proper math behind it, but the simple rule of thumb is: more time we spend on estimation, more accurate the estimation is.

The minimal estimation takes almost 0 time and has almost 0 value — we don't know the upcoming unknowns and uncertainty, and we have no clue of the task complexity.

And the ideal estimation can be done just measuring how much time it actually takes us to complete the task — all the unknowns are resolved, uncertainties became certainties, and the task complexity is not only known, but successfully dealt with.

Usually people choose some form of estimation from the range between ideal and minimal, paying some price for some prognosis accuracy.

But how do they determine the level of prognosis' accuracy they are willing to pay the estimation price for?

Why are they investing money in "buying the prognosis" in the first place?

I've asked managers a lot about this, here's a list of usual reasons they quoted for investing into estimation:

• to see team load/capacity
• public tender contract requires estimates
• ‘business’ needs to know ‘when’
• ‘business’ needs to understand how much the feature costs
• ‘business’ needs to be able to choose which feature to do first

In the talk I will go through each one of these and figure out when the investment in estimating is rational and when not.

And then I will also talk on the implications or negative 'side-effects' that estimation brings.

I will also talk on how to work without estimations, how to persuade your boss to try it

Target audience

Pretty much everyone I'd say

Speaker

Vitaly Sharovatov — github

20 years in IT, 13 years JS dev, 7 years teamlead, mentor, devrel. Passionate about teaching and just loves making people a bit happier :)

What the speaker would like to know

• Why do you need estimates?
• What purpose do they serve for your company and you?

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