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“When Will This Be Done?”
A Practical Guide To Answering This
Question In An Agile Project
© 2015 Scott Ambler + Associate...
About Rod Bray
© Scott Ambler + Associates
2
• Senior Consultant, Scott Ambler + Associates
• 35+ years in IT
• CDAI, CDAP...
Before We Start
• That question is really based upon a “Waterfall” mindset
– Value is only delivered at the end; when all ...
Value Curve for a “Traditional” Project
Value
Time
© 2015 Scott Ambler + Associates johnrodbray 4
Learning Curve for a “Traditional” Project
Learning
Time
© 2015 Scott Ambler + Associates johnrodbray 5
Learning Curve for an Agile Project
© 2015 Scott Ambler + Associates johnrodbray 6
Learning
Time
Value Curve for an Agile Project
Value
Time
© 2015 Scott Ambler + Associates johnrodbray 7
Trim features
to deliver on a
d...
Our Discussion Today
• Reasons for the Question
• Planning Fallacy
• Realities of Estimation
• Strategies for Estimating
•...
Reasons for the Question
• Forecasts & estimates are used to choose between multiple options
– Planning, hiring and traini...
Really, It’s Two Questions
The question asked before (or just as) the project is started
The question asked after several ...
Why Plans Fail
• We don’t live in a deterministic world - especially in regards to software projects.
– Stochastic reality...
Realities of Estimation
• Estimates are guesses
– “guesstimate” is a more appropriate word than estimate”.
• Scope on IT p...
Realities of Estimation
• Guesstimates must reflect the quality of the inputs.
– If scope is fuzzy, guesstimate based on t...
Realities of Estimation
• It’s easier to guesstimate small things.
• It’s easier to guesstimate work you’re just about to ...
Realities of Estimation
• Someone who has done the work before will give a better
guesstimate than someone who hasn’t.
• G...
Realities of Estimation
• Guesstimates should be updated over time.
– As understanding of what stakeholders want improves
...
Realities of Estimation
• Guesstimation is far more art than science.
• Formal software guesstimation schemes are little m...
Realities of Estimation
• Past history isn’t as valuable as people hope.
– False foundation since context is always differ...
Summary of the Realities of Estimation
When you are required to provide estimates for
your software development efforts, y...
Strategies for Estimating
© Disciplined Agile Consortium 20
??
• Educated guess by an experienced
individual
• Educated gu...
Changing The Conversation
© 2015 Scott Ambler + Associates johnrodbray 21
Estimates Are Probability Distributions
© 2015 Scott Ambler + Associates johnrodbray 22
That are refined over time
© 2015 Scott Ambler + Associates johnrodbray 23
To become more accurate as learning increases and
timeline shortens
© 2015 Scott Ambler + Associates johnrodbray 24
Simple (and typical) Forecasting
© 2015 Scott Ambler + Associates johnrodbray 25
Net Velocity to Determine Real Progress
© Disciplined Agile Consortium 26
• Gross velocity does not account for added scop...
Estimating: Ranged Release Burndowns
• A ranged estimate of number of iterations required to complete work
• Range of unce...
A Different View
© 2015 Scott Ambler + Associates johnrodbray 28
Probabilistic Approach
• There is NO single forecast result
• Uncertainty In = Uncertainty Out
• There will always be many...
Monte Carlo Simulation
• The technique was first used by scientists working on the atom bomb.
• Monte Carlo simulation per...
Burn Up with Probability via Monte Carlo Simulation
© 2015 Scott Ambler + Associates johnrodbray 31
Embrace Probabilistic Realities
© 2015 Scott Ambler + Associates johnrodbray 32
Comparing Models
• Expert guess
• Ranged guess from multiple experts
• Regression forecast
• Probabilistic forecast
• “All...
Summary
1. Consider changing the question
– How will we spend money wisely?
– What do we need to know to plan?
2. Context ...
Thank You!
rod.bray@scottambler.com
Twitter: johnrodbray
DisciplinedAgileDelivery.com
ScottAmbler.com
© 2015 Scott Ambler ...
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When Will This Be Done?

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A Practical Guide to Answering This Question in an Agile Project. Software project estimation is hard. But our stakeholders need answers. In this presentation we seek to give our stakeholders the information that they need.

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When Will This Be Done?

  1. 1. “When Will This Be Done?” A Practical Guide To Answering This Question In An Agile Project © 2015 Scott Ambler + Associates scottwambler 1
  2. 2. About Rod Bray © Scott Ambler + Associates 2 • Senior Consultant, Scott Ambler + Associates • 35+ years in IT • CDAI, CDAP, PMI-ACP, CSP, CSM, ICP • Rod.Bray@scottambler.com • @johnrodbray • Helping to create Agile and Lean enterprises around the world
  3. 3. Before We Start • That question is really based upon a “Waterfall” mindset – Value is only delivered at the end; when all the activities are complete – Value is seen as binary; requirements (as specified) are complete • Agile projects deliver value in a different manner • Suggest a different question – Are we spending our time (and money) wisely? • What do we need to know to properly plan? © 2015 Scott Ambler + Associates johnrodbray 3
  4. 4. Value Curve for a “Traditional” Project Value Time © 2015 Scott Ambler + Associates johnrodbray 4
  5. 5. Learning Curve for a “Traditional” Project Learning Time © 2015 Scott Ambler + Associates johnrodbray 5
  6. 6. Learning Curve for an Agile Project © 2015 Scott Ambler + Associates johnrodbray 6 Learning Time
  7. 7. Value Curve for an Agile Project Value Time © 2015 Scott Ambler + Associates johnrodbray 7 Trim features to deliver on a date Delay release to get more features
  8. 8. Our Discussion Today • Reasons for the Question • Planning Fallacy • Realities of Estimation • Strategies for Estimating • Probabilistic Approaches • So How Do I Answer? © 2015 Scott Ambler + Associates johnrodbray 8
  9. 9. Reasons for the Question • Forecasts & estimates are used to choose between multiple options – Planning, hiring and training staff for the future – Portfolio Prioritization – Ruling out an option • Some contexts do NOT require an answer to this question – If there are no choices then there is no reason for estimates and forecasts – E.g. the project has been selected and the cost is fixed there is little reason to estimate, just start the work NOTE - Use the least precision that supports decision making i.e. We don’t measure distance between towns in feet © 2015 Scott Ambler + Associates johnrodbray 9
  10. 10. Really, It’s Two Questions The question asked before (or just as) the project is started The question asked after several Iterations (or weeks if using Lean/Kanban) Beware the Semmelweis Reflex; A professional (and general psychological) reflex to reject new evidence that threatens established norms or firmly held beliefs. – Named for a doctor preceding Louis Pasteur and his theories regarding germs An often established norm is the preference for wrong information rather than no information or delayed information. – “What do you mean that you can’t tell me when this will be finished?” © 2015 Scott Ambler + Associates johnrodbray 10
  11. 11. Why Plans Fail • We don’t live in a deterministic world - especially in regards to software projects. – Stochastic reality • We fall prey to a set of cognitive biases that make us believe that we can create a plan and use that to guide projects. – Wikipedia currently lists over 110 different cognitive biases • Hofstadter’s Law – It always takes longer than you thing; even when taking into account Hofstadter’s Law • Planning fallacy – We invite 3 of our friends to join us at a restaurant that is unfamiliar to all of us. We make plans to meet in front of the restaurant and get seated once everyone has arrived. – 16 possible outcomes, only 1 has everyone arriving at the same time. – 1 in 2 𝑛 © 2015 Scott Ambler + Associates johnrodbray 11
  12. 12. Realities of Estimation • Estimates are guesses – “guesstimate” is a more appropriate word than estimate”. • Scope on IT projects is a moving target. • Guesstimates are probability distributions. © 2015 Scott Ambler + Associates johnrodbray 12
  13. 13. Realities of Estimation • Guesstimates must reflect the quality of the inputs. – If scope is fuzzy, guesstimate based on that scope needs to be equally fuzzy. • Guesstimates anchor perception. – Tell them that it’s going to be between $750,000 and $1,750,000 and most people will fixate on the cost of $750,000. © 2015 Scott Ambler + Associates johnrodbray 13
  14. 14. Realities of Estimation • It’s easier to guesstimate small things. • It’s easier to guesstimate work you’re just about to do instead of work in the distant future – Temporal bias • The people doing the work will likely give a better guesstimate. – Motivated to get the guesstimate right when they must commit to it – Have a much better idea of their abilities. © 2015 Scott Ambler + Associates johnrodbray 14
  15. 15. Realities of Estimation • Someone who has done the work before will give a better guesstimate than someone who hasn’t. • Guesstimates reflect the situation that you face. – Geographic distribution, regulatory environment, etc. Context counts. • Multiple guesstimates are better than a single guesstimate – Insights from several points of view © 2015 Scott Ambler + Associates johnrodbray 15
  16. 16. Realities of Estimation • Guesstimates should be updated over time. – As understanding of what stakeholders want improves – As understanding of how well the team works together – As technical risks are addressed • It costs money to produce a guesstimate. – Greater precision requires greater cost. – Is the value of improved decision making capability from having the guesstimate greater than the cost of creating the guesstimate? – May consider even eliminating the guesstimation effort. © 2015 Scott Ambler + Associates johnrodbray 16
  17. 17. Realities of Estimation • Guesstimation is far more art than science. • Formal software guesstimation schemes are little more than a scientific façade. – Examples include function point counting, feature point counting, and COCOMO II – Expensive since they require detailed requirements and design work to be performed – Provide a false sense of security © 2015 Scott Ambler + Associates johnrodbray 17
  18. 18. Realities of Estimation • Past history isn’t as valuable as people hope. – False foundation since context is always different – people, technologies, teams change • Beware professional guesstimators. – Break many of the rules already described above. © 2015 Scott Ambler + Associates johnrodbray 18
  19. 19. Summary of the Realities of Estimation When you are required to provide estimates for your software development efforts, you should take a pragmatic, light-weight approach to doing so. Consider the cost and accuracy of such estimates to use the least precision that supports decision making. © 2015 Scott Ambler + Associates johnrodbray 19
  20. 20. Strategies for Estimating © Disciplined Agile Consortium 20 ?? • Educated guess by an experienced individual • Educated guess by the team • Similar sized items • Relative mass (grid) valuation • Planning poker (Wideband Delphi) • None • Function points • Cost/schedule set by the stakeholders
  21. 21. Changing The Conversation © 2015 Scott Ambler + Associates johnrodbray 21
  22. 22. Estimates Are Probability Distributions © 2015 Scott Ambler + Associates johnrodbray 22
  23. 23. That are refined over time © 2015 Scott Ambler + Associates johnrodbray 23
  24. 24. To become more accurate as learning increases and timeline shortens © 2015 Scott Ambler + Associates johnrodbray 24
  25. 25. Simple (and typical) Forecasting © 2015 Scott Ambler + Associates johnrodbray 25
  26. 26. Net Velocity to Determine Real Progress © Disciplined Agile Consortium 26 • Gross velocity does not account for added scope • Net velocity reduces the gross velocity by amount of added scope in an iteration
  27. 27. Estimating: Ranged Release Burndowns • A ranged estimate of number of iterations required to complete work • Range of uncertainty decreases as project progresses © Disciplined Agile Consortium 27
  28. 28. A Different View © 2015 Scott Ambler + Associates johnrodbray 28
  29. 29. Probabilistic Approach • There is NO single forecast result • Uncertainty In = Uncertainty Out • There will always be many possible results, some more likely that others • Strive for a bounded forecast – something like: – 85% likely to be sufficiently complete by August, 2017 – Need at least 2 teams – Definitely need at least $1,000,000 • Striving for a forecast with 85% certainty or more – Do not use medians or means – chance of a coin toss © 2015 Scott Ambler + Associates johnrodbray 29
  30. 30. Monte Carlo Simulation • The technique was first used by scientists working on the atom bomb. • Monte Carlo simulation performs risk analysis by building models of possible results by substituting a range of values—a probability distribution—for any factor that has inherent uncertainty. It then calculates results over and over, each time using a different set of random values from the probability functions. • A Monte Carlo simulation could involve thousands or tens of thousands of recalculations before it is complete. Monte Carlo simulation produces distributions of possible outcome values. • The result is a probability distribution of possible outcomes. In this way, Monte Carlo simulation provides a much more comprehensive view of what may happen. It tells you not only what could happen, but how likely it is to happen. © 2015 Scott Ambler + Associates johnrodbray 30
  31. 31. Burn Up with Probability via Monte Carlo Simulation © 2015 Scott Ambler + Associates johnrodbray 31
  32. 32. Embrace Probabilistic Realities © 2015 Scott Ambler + Associates johnrodbray 32
  33. 33. Comparing Models • Expert guess • Ranged guess from multiple experts • Regression forecast • Probabilistic forecast • “All models are wrong. Some are useful.” – George E. P. Box • Just has to be better than what is currently used and intuition alone – that’s a very low bar. © 2015 Scott Ambler + Associates johnrodbray 33
  34. 34. Summary 1. Consider changing the question – How will we spend money wisely? – What do we need to know to plan? 2. Context counts – Use the least precision to support decision making – What is known/unknown about scope and approach 3. Present the realities regarding estimates – We live in an uncertain world 4. Never give single values – Always use ranges 5. Present the probabilities – Not a normal distribution (Weibull most applicable) – Do not use means (or medians) © 2015 Scott Ambler + Associates johnrodbray 34
  35. 35. Thank You! rod.bray@scottambler.com Twitter: johnrodbray DisciplinedAgileDelivery.com ScottAmbler.com © 2015 Scott Ambler + Associates johnrodbray 35

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