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Measure and Manage Flow in Practice
 

Measure and Manage Flow in Practice

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    Measure and Manage Flow in Practice Measure and Manage Flow in Practice Presentation Transcript

    • Measure and Manage Flow in Practice kaizen WIP kaikaku flow value stream mapping visualize work flow cycle time lead time throughput TPS build failed CFDcreated byZsolt Fabók (me@zsoltfabok.com) August 30, 2011 @ Prezi HQ, Budapest
    • Before saying anything:"I promise not to exclude from consideration any idea based on its source,but to consider ideas across schools and heritages in order to find theones that best suit the current situation." [1]This means the end of statements like “That’s no good – it’s notagile / object-oriented / pure / etc…”, but rather a discussionabout whether an idea (agile or plan-driven or impure orwhatever) works well in the conditions of the moment.
    • Since you are quiteexperienced with visualize the workflow measure andKanban, well skip the manage flow improve collaborativelybasics... limit (using models & the scientific method) the work in progress (WIP) make process policies explicit ...and get right to point. Only a small CFD this time, because it was discussed several times before :-)
    • Given thefollowingKanban board: Guess what the chart on the left represents?
    • Answer:This is the lead time of A
    • A couple of reasonsto wait so long:hamster effect wrongprioritisation weekend rush defectsslow builds manual buildsdependencies late integration nocadence contextswitching changingrequirements missing deliverystrategy favour only the leftside of the boardA couple of ideas to reduce it:delivery cadence Littles law batching cost of delay prioritisation MMF taskoriented daily stand-up dynamic prioritisation mark ageing service levelagreement avatars explicit definition of done criteria
    • Measuring is veryeasy or Additionally, the dates and the strikes on the cards are very good indicators as well!
    • Favour periods over the whole flow (please, dont hold it against me) ... period n-1* period n* Flow* avg lead time 5 19 10 avg waiting time 78% 92% 95% estimation precision 51% 78% 65% throughput 3/12 0/10 42/60 back 3 13 26 * not real dataTheir data tell more about the progress, than the data of thewhole Flow!
    • There are traps out there, so be careful Sufficient planning requires knowing ● the lead time, and ● the throughputFor example (based on real data):Team1 has the following lead times for items of size L: 6, 6, 6, 22, 6, 3,4, 4, 13, 2, 2, 4, 8, 6, 9, 14, 14, 15, 16, 2, 5, 33, 8On the other handTeam2 has the following lead times for all kind of items: 4, 4, 4, 4, 3, 2, 5,5, 4, 4, 3, 4, 4, 3, 4, 4, 4, 3, 6, 3I wont even try to plan using the lead times of Team1, it isunhelpful, but Team2 is quite stable
    • There are traps out there, so be carefulThe throughput is a tricky one. Teams usually reporthow many work items they delivered during a period.Lets say it is 12 (remember the table 2 slides ago).But it doesnt say how many work items they closedduring the period. Closing an item means starting andfinishing it in the very same periodSo instead of 12, report 3 / 12. It says so much more: ● the team was able to close and deliver 3 items, or ● there are too many left overs from the previous period ● etc.
    • The measure the flow principle has ahuge potentialFor example I had the feeling that those work itemswhich are started near the weekend are being deliveredslower (longer lead times) than the others.
    • So, using the started and done dates from the work anda small script I got the following chart (a lower barmeans a better result): Note that I dont count weekends into the lead time, except for support organisations
    • For further reference: the theory behind Spent time + or Age waiting effective work cycle time (repetition!) lead time
    • Thank you very much for your attention!For more Kanban-related topics, check out my website: http://zsoltfabok.com/ or follow me on twitter: @ZsoltFabok