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Associate Professor David Parsons
Massey University
David Parsons - Massey University
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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
 0, 1, 2, 3, 5, 8, 13, 20, 40 (in 5 „suits‟)
 + „fast forward/rewind‟ and „talk‟
David Parsons - Massey University
 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
 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
 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
 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
 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
 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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Planning Poker

  • 1. Associate Professor David Parsons Massey University David Parsons - Massey University
  • 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.  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.  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.  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.  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.  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.  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.  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.  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.  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.  0, 1, 2, 3, 5, 8, 13, 20, 40 (in 5 „suits‟)  + „fast forward/rewind‟ and „talk‟ David Parsons - Massey University
  • 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.  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.  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.  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.  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.  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