Planning Poker

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An introduction the the agile estimation practice of Planning Poker

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Planning Poker

  1. 1. Associate Professor David Parsons Massey University David Parsons - Massey University
  2. 2.  First developed by James Grenning  “How to avoid analysis paralysis while release planning”  The aim of Planning Poker is to create estimates in a short time and involve the whole team David Parsons - Massey University
  3. 3.  Like the Planning Game, Planning Poker is not really a game ◦ Simply a way of using game-like activities to perform some of the tasks of agile planning  One significant difference is that in Planning Poker there are additional „pieces‟ – the „cards‟ used to estimate stories David Parsons - Massey University
  4. 4.  The customer reads a story ◦ There is a discussion clarifying the story as necessary  Each programmer selects their chosen estimate card ◦ (Or writes their estimate on a note card, if no pre- printed pack is available)  No discussion of estimates takes place at this stage  Once all programmers have written their estimate, all the cards are turned over David Parsons - Massey University
  5. 5.  If there is agreement, no discussion is necessary ◦ The estimate is recorded and we move on to the next story.  If there is disagreement in the estimates, the team can try to get a consensus  If there is no consensus, it doesn‟t matter ◦ It is only one story out of many  It can be deferred, split, or the lowest estimate can be taken David Parsons - Massey University
  6. 6.  Everyone in the team participates ◦ They have to make an estimate ◦ Everyone gains experience  Discussions are automatically triggered by the more problematic estimates  Where estimates are straightforward, the game enables consensus without unnecessary discussion David Parsons - Massey University
  7. 7.  Save time of manually writing estimates  Cards also only have a subset of possible estimated days  James Grenning‟s set: ◦ 1, 2, 3, 5, 7, 10 days and infinity  As the estimates get longer, the precision goes down David Parsons - Massey University
  8. 8.  Maximum story size is under 2 weeks  if you estimate that a story is longer than 2 weeks, play the infinity card and make the customer split the story David Parsons - Massey University
  9. 9.  Mountain Goat Software ◦ 0, 1, 2, 3, 5, 8, 13, 20, 40, and 100 ◦ online version also includes a .5 card ◦ The „zero‟ value might look odd but it does not mean it takes no time at all, rather that is closer to 0 than 1  Mike Cohn ◦ 1, 2, 3, 5, and 8 (Fibonacci sequence) ◦ or 1, 2, 4, and 8  StudioAlt ◦ ?, 0, ½, 1, 2, 3, 5, 8, 13, 20, 40, 100 David Parsons - Massey University
  10. 10.  If the number represents days, why do some card sets go up to 100?  Because not everyone sticks to „days‟ as their unit of estimation  “Planning Poker can be used with story points, ideal days, or any other estimating unit”  – Mountain Goat Software David Parsons - Massey University
  11. 11.  As well as the estimation number cards, some packs have additional cards ◦ „don‟t know‟ ◦ „discuss‟ ◦ „coffee time‟ ◦ etc.  You can make up cards that you find useful in your own processes David Parsons - Massey University
  12. 12.  0, 1, 2, 3, 5, 8, 13, 20, 40 (in 5 „suits‟)  + „fast forward/rewind‟ and „talk‟ David Parsons - Massey University
  13. 13.  One suggestion for maintaining the speed of the process is to use a 2-minute egg timer for each discussion  This may be turned over once more for more problematic estimates but then the next story should be estimated David Parsons - Massey University
  14. 14.  With large teams, where there are many stories to estimate, Planning Poker can be played separately by smaller teams  However they will need to have done some estimating as a whole team first, covering 10 to 20 stories ◦ This ensures that everyone is familiar with the technique ◦ Also ensures that subsequent estimates are consistent between groups David Parsons - Massey University
  15. 15.  A minor variation on Planning Poker is to use poker chips instead of estimation cards, 1 chip for each story point  Possible to use different coloured chips to indicate different estimation contexts ◦ “we had three team sizes we were considering for the release and we used white, blue and red chips to indicate the base story points and two levels of increment”  Yip, J. (2007) David Parsons - Massey University
  16. 16.  Another variation is to use an on-line version for distributed teams  You can also download versions for mobile phones planningpoker.com David Parsons - Massey University
  17. 17.  Moløkken-Østvold and Haugen (2007) identified some measurable and potential benefits  Haugen (2006) claimed that it improved estimation in most cases, but that it increased estimation error in the extreme cases David Parsons - Massey University
  18. 18.  Cohn, M. (2005). Agile Estimating and Planning, Addison-Wesley  Grenning, J. (2002). Planning Poker or How to avoid analysis paralysis while release planning https://sewiki.iai.uni- bonn.de/_media/teaching/labs/xp/2005a/doc.planningpoker- v1.pdf  Haugen, N. (2006). An Empirical Study of Using Planning Poker for User Story Estimation, AGILE 2006, 23-34  Moløkken-Østvold, K. & Haugen, N. (2007). Combining Estimates with Planning Poker – An Empirical Study, 18th Australian Software Engineering Conference (ASWEC 2007), 349–358  Yip, J. (2007). Hands-on release planning with poker chips. 14th Conference on Pattern Languages of Programs (PLOP 2007) David Parsons - Massey University

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