Using Exemplars for baselining estimates



Stage 4

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Agile estimations introduce a new method for forecasting the delivery of work. It can take some influence to win over managers into accepting relative estimates rather than time-specific estimates. Building more accurate estimates both builds confidence and predictability in delivery.

Understanding Variation

Distinguishing the difference between variation, as well as understanding its causes and predicting behaviour, is key to management’s ability to properly remove problems or barriers. [1] Before we attempt to establish accurate estimations, we should first value the importance of variation in work systems.

A process that is in statistical control, stable, funishes a rational basis for prediction. [2] Advantages of processes that are in statistical control (stable) include:

  1. The process has an identity; its performance is predictable
  2. Costs are predictable
  3. The Kanban system of delivery follows naturally when a whole system is in statistical control
  4. Productivity is at a maximum (costs at a minimum)
  5. Relationships with vendors can be greatly simplified
  6. The effects of changes in the system can be measured with greater speed and reliability

Building a baseline

Building a baseline consists of various elements.

Measure and Capture Estimates – Teams should capture their estimates for work prior to commencing work on Product Backlog Items. Estimates may be captured prior or during Sprint Planning.

Measure Delivery Against Planned Work – At the end of the Sprint the team should review the completed work against the planned work. In most cases there will be some variance between planned and actual work. Metrics can be captured each Sprint to build a profile of velocity and throughput, as well as reliability of estimates.

Analyse Delivery – Teams should review delivery, such as in a Sprint Retrospective, to understand the root causes of any factors that resulted in any significant differences between estimate and actual delivery. Both effort and duration should be considered to better understand team velocity and throughput. Additional considerations such as staff unavailability should be taken into account.

clustering stories and size
Above: Baseline estimation grid aligning like cycle times

Planning Poker

Planning Poker is an activity for estimating work items, typically during Sprint Planning. The team selects a work item and each individual team member makes their own estimation. Estimations are then shared. Where there are different estimates, team members discuss their assumptions about the work. This helps to better understand factors in delivering the work. The team may then repeat the individual estimations until there is an agreement for the estimate.

When Do Estimates Become Reliable?

There is no accepted standard of statistical significance for past data sets become reliable for estimating team velocity. A common standard is six to eight Sprints. [3] However, this is assuming that both the Sprint velocity and individual work item estimations become more accurate over time.

Even with a stable team with a strong track record of estimations, there will always be variance if work is not uniform (e.g. manufacturing physical products).

Things to watch out for

  • Do not expect perfect alignment between estimate and actual effort. After all, they are still called estimates for a reason.
  • Ensure enough time to estimate work is given to teams. Rushed estimates may provide no value if you are attempting to produce reliable baseline estimates.
  • Consistently calculate velocity and throughput. If this is altered then it will skew estimates.

Actions to try

  • Facilitate planning poker with the team during Sprint Planning. Remember to discuss discrepencies in estimates.
  • Capture data in a consistent manner so that you can start to build a baseline over time.


1. The Deming Institute (2012) Knowledge of Variation.

2. Deming, W.E. (1982) Out of the Crisis.

3. Cohn, M. (2014) Velocity-Driven Sprint Planning.

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