Benefits of Estimation

Group Estimation Benefits (1, pg 105)

• Research indicates group estimation is more accurate than individual estimation (Wisdom of Crowds by James Surowiecki)
• Authority must be decentralised within the group
• Anti-patterns = anchoring, analysis paralysis

Estimation Techniques

Product Backlog Estimation Techniques (1, pg 105)

• Story Points (1,2,3,5,8,13)
• T-shirt sizes (X-Small, Small, Medium, Large, X-Large)
• Animals, fruits etc (grape, satsuma, lemon, orange, grapefruit, cantaloupe, watermelon)
• ‘Same-size’ items (all PBIs are roughly the same size)
• ‘Right size’ items (at least one item can be delivered in a Sprint)

Probabilistic Estimating (page 110, Mastering Professional Scrum)

• Monte Carlo is an example of probabilistic estimating
• Uses historical data with a statistical sampling method
• Output is a range of possible future outcomes with a confidence level on that range
• Embraces uncertainty of predicting the future

Estimation Caution

Asymmetric nature of software estimation errors (2, pg 203) 

‘ There are known knowns. There are things we know we know. We also know there are known unknowns. That is to say. We know there are some things we do not know. But there are also unknown unknowns. The ones we don’t know we don’t know’ 

Former Secretary of Defence Donal Rumsfield

• Estimations are more likely to take longer than expected than they are to take a shorter amount of time than expected (i.e. they are asymmetric)
• Developers estimate based on known knowns, and sometimes known unknowns. 
  • Some error comes from misunderstanding these 
  • Most comes from unknown unknowns
• Larger tasks are more likely to have more unknown unknowns so the risk of rapidly increasing is much higher
• Cone of uncertainty shows that the likeliness of under as over-estimation is symmetric 

References

1. Mastering Professional Scrum by Stephanie Ockerman and Simon Reindl
2. Lean Product Playbook by Dan Olsen