Benefits of Estimation

Group Estimation Benefits (1, page 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

Fibonacci Sequence for Story Points

Fibonacci in Nature (3, page 123)

• Shell of a nautilus
• Branches of a tree
• Cauliflower
• Curves of human brain
• Shape of a galaxy
• Called the ‘Golden Mean’ or ‘Golden Ratio’ 

Product Backlog Estimation Techniques (1, page 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 (1, page 110)

• 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

Planning Poker

HOW (3, page 130)

1. Each person had a deck of cards with the fibonacci numbers on them 
2. Item to be estimated is brought to the table
3. Everyone pulls the card they think represents the right amount of effort
4. If everyone is within 2 cards of each other, add them all up, take the average and move on
5. If people are more than 3 cards apart, the low and high ends talk through their reasons, then everyone does another round

Benefits

• ‘take a broad array of opinions, attempts to remove as much biais as possible, and with informed, yet anonymous, statements, narrows down opinions into a generally accepted estimate’ (3, page 129)
• Avoids bandwagon effect (everyone jumping on an idea because they thought everyone else was on board) (3, page 125)
• Avoids halo-effect (when one characteristic of something influences how people perceive other unrelated characteristics (3, page 126)

Estimation Caution

Asymmetric nature of software estimation errors (2, page 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 

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References

1. Mastering Professional Scrum by Stephanie Ockerman and Simon Reindl
2. Lean Product Playbook by Dan Olsen
3. Scrum: The Art of Doing Twice the Work in Half the Time by Jeff Sutherland

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