statistical forecasting: estimation made easy
TRANSCRIPT
STATISTICAL FORECASTING
DON’T DO IT
T. DEMARCO, T. LISTER: WALTZING WITH BEARS
ACCURACY OF ESTIMATION
SOURCE: TSAI, KLAYMAN, HASTIE: EFFECTS OF AMOUNT OF INFORMATION ON JUDGMENT ACCURACY AND CONFIDENCE
ESTIMATION BIAS
LEA
WORK TIME
LEAD TIME FLOW EFFICIENCY =
LEAD TIME
WORK TIME
LEA WAIT TIME
LEA
LEA
THROUGHPUT VS STORY POINTS
UNIVERSE’S PLANS
source: DOGHOUSEDIARIES
BASED ON THE WORK OF TROY MAGENNIS, LARRY MACCHERONE AND DOUGLAS HUBBARD
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MONTE CARLO EXAMPLE
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AVERAGE PACE FORECAST - SIMPLE REGRESSION
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MONTE CARLO EXAMPLE: THROUGHPUT SAMPLES
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MONTE CARLO EXAMPLE: THROUPUT DISTRIBUTION
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MONTE CARLO EXAMPLE: UNLUCKY BRIAN
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MONTE CARLO EXAMPLE: WORST CASE SCENARIO
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MONTE CARLO EXAMPLE: BEST CASE SCENARIO
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MONTE CARLO EXAMPLE
MONTE CARLO EXAMPLE
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MONTE CARLO EXAMPLE
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MONTE CARLO EXAMPLE
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MONTE CARLO EXAMPLE
HISTORICAL DATA: COMPLETED STORIES
HISTORICAL DATA: TIMELINE
STATISTICAL MODEL: INPUT #1
WHY LEAD TIMES?
LEAD TIME
HISTORICAL DATA: LEAD TIMES
LEAD TIME DISTRIBUTION
LEAD TIME DISTRIBUTION
STATISTICAL MODEL: INPUT #2
HISTORICAL DATA: WORK IN PROGRESS
WORK IN PROGRESS DISTRIBUTION
READY…
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Iteration
SAMPLING LEAD TIME VALUES
SAMPLING LEAD TIME VALUES
SUM(LEAD TIME VALUES) = UNITS OF WORK
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87
SAMPLING WORK IN PROGRESS
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87
SAMPLING WORK IN PROGRESS
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90% CONFIDENCE INTERVAL?
UNCERTAINTY
BE BETTER
SOURCES & RESOURCES
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