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Estimation as Uncertainty Reduction

Darmstadt, Germany 2018

Making sense of estimation strategies and understanding why #noestimation is not as crazy as it sounds.

As important as estimation is to setting customer/stakeholder expectations and ultimately to paying the bills, there is surprisingly little discussion about what makes for a sound estimation strategy.

There’s an assumption that estimation is something that good developers should be good at, with the unspoken the corollary that failure to meet estimates is somehow the mark of an amateur. Once burned, developers push back that they lack specification. Backlog refinement meetings are scheduled. Time is set aside for technical planning, with expectations set, but often the cycle is repeated, leading to the question, what is this estimation thing?

Understanding the principle of information entropy as the basis for uncertainty reduction How to unbundle assumptions using range estimation How to qualify range estimates with confidence interval The array of measurement methods using Ration, Interval, Ordinal and Nominal scales Analytic, Analogous and Parametric techniques Story Decomposition Practices We’ll go through a number of techniques to verify your estimates.

• When does it take to make traditional time-against-task estimation effective? • What problems are we trying to resolve with Indirect estimation strategies, such as Planning poker, Story points, Fibonacci spreads or the Cherry-pit Mustang thing?

• What is “no estimation”, really? How would that work?

• we’ll review the practice of estimation calibration, which can help people improve their “sense of size”: useful when applied to any estimation strategy.

We hope to leave you with a better understanding of the various approaches to estimation, and to understand what they’re trying to achieve, to give you greater confidence in the choices you make in this critical area of software development.

pattern language

Let's agree to define productivity in terms of throughput. We can debate the meaning of productivity in terms of additional measurements of the business value of delivered work, but as Eliyahu Goldratt pointed out in his critique of the Balanced Scorecard, there is a virtue in simplicity. Throughput doesn’t answer all our questions about business value, but it is a sufficient metric for the context of evaluating the relationship of practices with productivity.