The Trend is your Friend - LAST Conference 2017

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Where we've gone wrong with agile estimation and forecasting How to measure and improve the predictability of delivery (without losing agility) How you can use historic data to generate powerful forecasts of your future progress. Practical tools and techniques to get you started.

The Trend is your Friend
Meaningful Forecasting for Agile Teams
Craig Drayton
@craigdrayton

think sharp elabor8
Agile
planning
has gone
horribly
wrong.

think sharp elabor8
Your customer does not care
how many Story Points
you deliver.

think sharp elabor8
But if forecasting delivery
dates is important to you…
… there are ways to
do it that don’t suck.

think sharp elabor8
What is forecasting?
Forecasting is using past data
to predict the likelihood of future outcomes
Agile forecasting is typically based on
Velocity (Average Story Points per Sprint)
(assuming that the future looks like the past)

think sharp elabor8
What’s wrong with using velocity to forecast?
Average October day in Melbourne:
Cloudy, light winds, high of 19.7°
October 8th, 2016 in Melbourne:

think sharp elabor8
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Frequency
Story one:
Completed in 16
days.
Story two:
Completed in 9
days
Story three:
Completed in 13
days.
How long would you
estimate the next
story will take?
Story fifteen:
How long do you estimate the
next story will take now?
System Lead Time
(days)
The average is not enough

think sharp elabor8
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 System Lead Time
(days)
Frequency
The SHAPE of data is more
important than individual data
points, or the average value
We can be ~75% (11/15) certain
that lead time will be between
5 and 9 days assuming that our
model remains stable
The average is not enough

think sharp elabor8
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Frequency
We can be ~75% (11/15) certain
that lead time will be between
6 and 8 days assuming that our
model remains stable
System Lead Time
(days)
The average is not enough

think sharp elabor8
Monte Carlo Simulation
Use past delivery data
to simulate future progress.
Do it lots of times
to see the likelihood
of different outcomes

think sharp elabor8
Monte Carlo Simulation
18 Days
15 Days
21 Days
18 Days
Sample randomly from
data on your past
progress…
...running through your
backlog to simulate your
future end date.
Do this thousands of times.
The proportion of
simulation runs that finish
by each date
= the likelihood of being
finished by that date
15 16 17 18 19 20 21 22 23
Lieklihood
Days to finish

think sharp elabor8
Monte Carlo Simulation
Now you can have better conversations.
15 16 17 18 19 20 21 22
Lieklihood
Days to finish backlog
There’s a 50/50 chance we’ll be
done within the next 18 days.
If you need more certainty,
there’s a 75% chance we’ll be
done within 19 days.
But if you want to be 95%
sure, better give it 22 days.

think sharp elabor8
But ONLY if your future
looks like your past!

think sharp elabor8
Many organisations that
seek certainty
behave in a way that
harms predictability.

think sharp elabor8
How do I get started?
1. Start by understanding your delivery patterns and
improving the stability/predictability of your delivery.
2. When you’re ready to try forecasting, there are some
great free spreadsheets available to help:
– https://goo.gl/EaJjFr
– http://bit.ly/SimResources
mazzlo.co
craig@mazzlo.co
And ask me about Mazzlo’s
simple but powerful
analytics for agile delivery.

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The Trend is your Friend - LAST Conference 2017

2. The Trend is your Friend Meaningful Forecasting for Agile Teams Craig Drayton @craigdrayton

3. think sharp elabor8

4. think sharp elabor8 Agile planning has gone horribly wrong.

5. think sharp elabor8 Your customer does not care how many Story Points you deliver.

6. think sharp elabor8 But if forecasting delivery dates is important to you… … there are ways to do it that don’t suck.

7. think sharp elabor8 What is forecasting? Forecasting is using past data to predict the likelihood of future outcomes Agile forecasting is typically based on Velocity (Average Story Points per Sprint) (assuming that the future looks like the past)

8. think sharp elabor8 What’s wrong with using velocity to forecast? Average October day in Melbourne: Cloudy, light winds, high of 19.7° October 8th, 2016 in Melbourne:

9. think sharp elabor8 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Frequency Story one: Completed in 16 days. Story two: Completed in 9 days Story three: Completed in 13 days. How long would you estimate the next story will take? Story fifteen: How long do you estimate the next story will take now? System Lead Time (days) The average is not enough

10. think sharp elabor8 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 System Lead Time (days) Frequency The SHAPE of data is more important than individual data points, or the average value We can be ~75% (11/15) certain that lead time will be between 5 and 9 days assuming that our model remains stable The average is not enough

11. think sharp elabor8 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Frequency We can be ~75% (11/15) certain that lead time will be between 6 and 8 days assuming that our model remains stable System Lead Time (days) The average is not enough

12. think sharp elabor8 Monte Carlo Simulation Use past delivery data to simulate future progress. Do it lots of times to see the likelihood of different outcomes

13. think sharp elabor8 Monte Carlo Simulation 18 Days 15 Days 21 Days 18 Days Sample randomly from data on your past progress… ...running through your backlog to simulate your future end date. Do this thousands of times. The proportion of simulation runs that finish by each date = the likelihood of being finished by that date 15 16 17 18 19 20 21 22 23 Lieklihood Days to finish

14. think sharp elabor8 Monte Carlo Simulation Now you can have better conversations. 15 16 17 18 19 20 21 22 Lieklihood Days to finish backlog There’s a 50/50 chance we’ll be done within the next 18 days. If you need more certainty, there’s a 75% chance we’ll be done within 19 days. But if you want to be 95% sure, better give it 22 days.

15. think sharp elabor8 But ONLY if your future looks like your past!

16. think sharp elabor8 Many organisations that seek certainty behave in a way that harms predictability.

17. think sharp elabor8

18. think sharp elabor8 How do I get started? 1. Start by understanding your delivery patterns and improving the stability/predictability of your delivery. 2. When you’re ready to try forecasting, there are some great free spreadsheets available to help: – https://goo.gl/EaJjFr – http://bit.ly/SimResources mazzlo.co craig@mazzlo.co And ask me about Mazzlo’s simple but powerful analytics for agile delivery.

19. Craig Drayton @craigdrayton

The Trend is your Friend - LAST Conference 2017

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