What are the odds? Transforming forecasts with probabilities

This is a more generic meetup version of the talk I've uploaded a few other times on probabilistic forecasting.

Transcript

1. @everydaykanban | @55degreesAB 1
   How well does
   
   
   your work
   fl
   ow
   
   
   fl
   ow?
   Julia Wester
   /in/juliawester/
   @everydaykanban
   Co-Founder, 55 Degrees AB
   What are the odds?
   Transform your forecasts
   with probabilities
   

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2. @everydaykanban | @55degreesAB
   Follow us on social media
   /company/55degrees
   @55degreesAB
   @55degreesAB
   /55degreesAB
   /c/ActionableAgileAnalytics
   Apps that make it easier
   to get work done
   🎉
   From re
   fi
   ning work, to bringing external data into Jira, to
   improving work
   fl
   ows and creating reliable forecasts, 55
   Degrees has apps to make your work less stressful.
   

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3. 3
   @everydaykanban | @55degreesAB
   Benjamin Franklin
   
   
   November 1789
   “…IN THIS WORLD,
   NOTHING IS CERTAIN
   EXCEPT DEATH AND
   TAXES.”
   

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4. Often forecasts are
   interpreted as
   certainties
   
   
   because we don’t tell
   them otherwise
   4
   @everydaykanban | @55degreesAB
   CC BY-SA 3.0, https://en.wikipedia.org/w/index.php?curid=3422341
   

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5. 5
   @everydaykanban | @55degreesAB
   The 3 Gaps
   Outcomes
   Plans
   Actions
   !
   Effects Gap
   Difference between what we
   expect our actions to achieve
   and what they actually achieve
   !
   Knowledge Gap
   Difference between what we
   would like to know and what we
   actually know
   !
   Alignment Gap
   Difference between what we want people
   to do and what they actually do
   

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6. 6
   @everydaykanban | @55degreesAB
   Used with permission from Jim Benson
   A predictable
   response
   

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7. 7
   @everydaykanban | @55degreesAB
   EE4: Building an SSV
   Timeline
   Total expected hours
   Total hours
   Sam Jansen
   Expected hours
   Total hours
   Alexander Meynen
   Expected hours
   Total hours
   Tinus Michiels
   Expected hours
   Total hours
   Jeroen van Aert
   Expected hours
   Total hours
   Jef Van Den Bergh
   Expected hours
   Total hours
   Bob Verschueren
   Expected hours
   Total hours
   1 2 3 4 5 6 7 8 9 10 11 12 13 14
   Tasks Subtasks wk h h h h h h h h h h h h h h
   Engineering
   a. Case SSV 1 i. Motor/ Solar panel analysis 7 4 3
   ii. Gear ratio 15 2,5 2,5 10 2,5 2,5 2,5 2,5
   iii. Choice of materials 10 5 1 1 1 1 1 5 1
   iv. Frame design 30 15 2 1 1 1 15 1 1
   v. Optimalisation (bisection method) 25 4 15 10 4
   vi. Sankey diagram 10 12 10
   vii. Production parts 20 10 12 10
   viii. Construction 60 10 10 10 10 10 10
   b. Case Simulink i. Simulation solar panel 24 4 4 4 4 5 4 4 10
   ii. Simulation DC-motor 7 4 3
   iii. Simulation race 6 1 1 1 1 1 1
   c. Case SSV 2 i. Slope run test 24 4 4 4 4 4 4
   ii. Simulation drive shaft 7 3 4
   iii. Technical drawings 40 10 30
   iv. Collision analysis 15 10 5
   d. Race day 30 5 5 5 5 5 5
   Enterprising
   e. Wikipage i. Company information 3 3 1
   ii. SSV information 5 5 1
   f. Name & Logo i. Design 2 1 2
   ii. Engraving 6 3 3
   g. Documents i. Plan of approach 4 2 2 2 2
   ii. Work breakdown structure 4 2 2 2 2
   iii. Gantt chart 10 1 5 3 5 3
   iv. Cooperation contract 2 2 2
   v. Case 1 document 45 5 5 15 5 5 15 5 5 15 5
   vi. Simulink document 15 5 10 5 10
   vii. Case 2 document 40 15 5 10 10
   h. Wikipage i. Upload documents 5 5 1
   ii. Blog 5 5 2 2
   iii. Design description 6 3 3
   iv. Final process report 5
   i. Evaluation i. Test 1 30 5,00 5 5 5 5 5
   ii. Test 2 30 5,00 5 5 5 5 5
   iii. Peer assessments 1
   total 548 0 92 27 92 25 92 21 88 22 91 25 90 25
   Legende milestone
   responsibillity
   Gantt chart 1
   Educating
   Weeks
   The workplace version of ruling it harder…
   CC BY-SA 3.0 - https://upload.wikimedia.org/wikipedia/commons/thumb/b/bf/AM4_Gantt.pdf
   

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8. Deterministic Forecast
   8
   @everydaykanban | @55degreesAB
   IT WILL BE
   
   
   DONE ON
   
   
   X DATE
   •Communicates a single
   possible outcome
   
   
   •Provides no probability of
   that outcome
   
   
   •Appropriate only when
   certainty is assured
   

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9. Probabilistic Forecast
   9
   @everydaykanban | @55degreesAB
   THERE’S AN
   
   
   85% CHANCE
   
   
   IT WILL BE DONE
   
   
   ON OR BEFORE
   

   X DATE
   •Two components:
   
   
   ‣ Range of outcomes
   
   
   ‣ Probability you’ll fall into
   that range
   
   
   •Appropriate whenever
   uncertainty is present
   

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10. 10
    Let’s create these probabilistic forecasts…
    @everydaykanban | @55degreesAB
    Single Item Forecasts
    Multiple Item Forecasts
    📆
    
    
    Fixed Date
    📑
    
    
    Fixed Scope
    2 Types
    

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11. For each, we can use the
    same simple data to
    calculate the probabilities
    11
    @everydaykanban | @55degreesAB
    

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12. Single Item Forecasts
    12
    @everydaykanban | @55degreesAB
    How long will it take?
    Finish
    Start
    Cycle Time: The total elapsed time it takes a work item
    to travel from start to
    fi
    nish
    

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13. 13
    @everydaykanban | @55degreesAB
    Finish
    Start
    Cycle Time: The total elapsed time it takes a work item
    to travel from start to
    fi
    nish
    Single Item Forecasts
    (Finish date - start date) + 1
    

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14. 85% of work took
    16 days or less
    Use a Cycle Time Scatterplot to
    calculate probabilities
    14
    @everydaykanban | @55degreesAB
    50% of work took
    
    
    7 days or less
    

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15. 15
    @everydaykanban | @55degreesAB
    Wrong as much
    as right…
    Contains too
    many outliers
    Just the right
    balance?
    Ask: What is the fallout if we fall
    outside of the probability?
    by understanding your risk tolerance
    Choose a probability
    

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16. 16
    @everydaykanban | @55degreesAB
    85% of the time we finish a
    

    work item in 16 days or less
    

    (from the day it starts)
    probabilistically
    Deliver your forecast
    

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17. 17
    @everydaykanban | @55degreesAB
    The underlying rule of thumb
    

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18. Multiple Item Forecasts
    18
    @everydaykanban | @55degreesAB
    Finish
    Start
    Throughput: The total count of items that pass the
    de
    fi
    ned
    fi
    nish point in a given unit of time
    When will
    they all be
    done?
    

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19. 19
    @everydaykanban | @55degreesAB
    A Throughput Run Chart will show you the data
    But you need a Monte Carlo Simulation
    to calculate the probabilities
    

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20. 20
    @everydaykanban | @55degreesAB
    For Fixed Scope, use Monte Carlo: When
    There’s an 85% chance that
    we will
    f
    inish these 45 items on
    or before May 25
    

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21. 21
    @everydaykanban | @55degreesAB
    For Fixed Date, use Monte Carlo: How Many
    There’s an 85% chance
    that we can
    f
    inish
    
    
    67 or more items by then
    

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22. 22
    @everydaykanban | @55degreesAB
    For an entire portfolio, use Portfolio Forecaster!
    

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23. 23
    @everydaykanban | @55degreesAB
    • When more than one outcome is possible,
    probabilistic forecasts are necessary.
    
    
    • Probabilistic forecasts show risk in 2 ways:
    

    a probability (%) and a range.
    
    
    • Choose a % that matches your risk tolerance
    
    
    • Tools like ActionableAgile and Portfolio Forecaster
    exist to help you create these forecasts in minutes.
    Summary
    

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24. @everydaykanban | @55degreesAB
    Thanks for
    listening!
    🎉
    Follow us on social media
    /company/55degrees
    @55degreesAB
    @55degreesAB
    /55degreesAB
    /c/ActionableAgileAnalytics
    

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