Wondering what NoEstimates means in practice, or why you would want to move toward NoEstimates? Perhaps you’ve heard the buzz or read Vasco Duarte’s book. Maybe you simply want to understand how you can spend less time estimating and more time delivering working software—all while providing your customers with some understanding of predictability. If so, Matthew Phillip will help you understand through lessons learned with NoEstimates what and to what degree different factors influence delivery time. Join Matthew to learn how to move from upfront intuition-based estimates to create a data-based probabilistic forecast that provides a more reliable way to talk about when stuff will be done—and expend less effort to do so. Learn to forecast when things will be done -- with less effort and more accuracy!

1. BT1
Concurrent Session
11/9/17 10:00 AM
The NoEstimates Game: Improve
Predictability with Less Effort
Presented by:
Matthew Phillip
ThoughtWorks
Brought to you by:
350 Corporate Way, Suite 400, Orange Park, FL 32073
888---268---8770 ·· 904---278---0524 - info@techwell.com - https://www.techwell.com/

2. Matthew Phillip
ThoughtWorks
Matthew Philip is the director of learning and development at ThoughtWorks. As
a coach, trainer, quality advocate, and facilitator, Matt helps organizations and
teams become fit for their purpose through continuous learning. He draws on
lean and agile values, principles, and practices (kanban method, XP, Scrum) to
offer experience, models, and options to customers and teammates. He tweets at
@mattphilip, blogs, and shares his presentations. Passionate about building
learning organizations, Matt has designed games for fun and learning, including
the NoEstimates game, which he has presented at conferences worldwide.

3. # b e t t e r s o f t w a r e c o n | @ m a t t p h i l i p
TO ESTIMATE OR
NOT TO ESTIMATE
Is that the Question?
@mattphilip #bettersoftwarecon
HOFSTADTER’S LAW
“It always takes longer than you expect,
even when you take into account
Hofstadter’s Law.”

4. @mattphilip #bettersoftwarecon
PARKINSON’S LAW
Work expands so as to fill the time
available for its completion.
@mattphilip #bettersoftwarecon
“POOR ESTIMATION SKILLS”

5. @mattphilip #bettersoftwarecon
THE SPECTRUM OF ESTIMATING
NeverEstimateAnything
AlwaysEstimateEverything
Estimate Default Behavior Don’t estimate
Effort Factors All sources of variation
Intuition Approach Data
Deterministic Forecast Type Probabilistic
Tasks in hours Level of Detail Work items in days
High Effort Spent Low
Estimating better Improvement Aim Reducing variation
Commitment Management Service Expectations
@mattphilip #bettersoftwarecon
MANIFESTO RELEVANCE

6. @mattphilip #bettersoftwarecon
MANIFESTO RELEVANCE
@mattphilip #bettersoftwarecon
WHAT NOESTIMATES IS NOT SAYING
▫︎ You are evil if you estimate
▫︎ All estimates are totally useless
▫︎ Stop doing your successful estimating practice
▫︎ Stop having the conversations to understand/analyze/
break down work
▫︎ Work items must be the same size
▫︎ You must place your full faith and confidence in Monte
Carlo forecasts

7. @mattphilip #bettersoftwarecon
WHAT NOESTIMATES IS SAYING
▫︎ Know why you are estimating
▫︎ Discover for yourself how good you are at estimating
(measure)
▫︎ Keep doing the things that help you understand the work
▫︎ Upfront estimates need to be held loosely
▫︎ If you focus on delivering value quickly, you obviate the
need for Iron Triangle considerations
@mattphilip #bettersoftwarecon
MY NOESTIMATES MANIFESTO
… We have come to value:
Reducing sources of variation over Improving estimating
Data over Intuition*
Probabilistic over Deterministic
MVP scope over Full scope
That is, while there is value in the items on the right, we value
the items on the left more.
*Neil Killick uses “empiricism over guesswork”

8. REDUCING SOURCES
OF VARIATION
@mattphilip #bettersoftwarecon
DO YOU ASSUME CORRELATION?
Is the initial sizing a good predictor for when you can get your stuff?
In our case, the surprising truth was ”no.”
— Mattias Skarin, Real-World Kanban

9. @mattphilip #bettersoftwarecon
WHAT WE ESTIMATE
Code
@mattphilip #bettersoftwarecon
WHAT WE ESTIMATE
Analyze+Design+Code+Test+Deploy

10. @mattphilip #bettersoftwarecon
WHAT ACTUALLY HAPPENS
Analyze Code Test DeployDesign
Wait for approval
Wait for staff
availability
Wait for
rework
Wait for API
availability
Wait for
higher-priority work
to finish
Wait for approval
Wait for
blocker
removal
@mattphilip #bettersoftwarecon
WHAT’S GOING ON?
Value-added time
_________________________
Total elapsed delivery time
Flow efficiency =

11. @mattphilip #bettersoftwarecon
WHAT’S GOING ON?
Low process efficiency (typically 5-15%
in software delivery) means that even if
we nailed the effort estimates … we
would be accurately predicting 5-15% of
elapsed delivery time!
— Troy Magennis
@mattphilip #bettersoftwarecon
SOURCES OF VARIATION
How many can you name?

12. @mattphilip #bettersoftwarecon
SOURCES OF VARIATION
Waiting for
availability
Rework
Team
dependencies
Stages in
team
development
(Tuckman)
Steps/
handoffs
Selection
policy
Essential
complication
Accidental
complication
System
dependencies
Work In
Progress
Technology/
domain/
product
Specialization
Team
composition
Multitasking/
context
switching
Collaboration
policy
Blockers
@mattphilip #bettersoftwarecon
WHAT CAN YOU DO ABOUT VARIATION
How many remedies
can you name?

13. @mattphilip #bettersoftwarecon
WHAT YOU CAN DO ABOUT VARIATION
▫︎Lower WIP
▫︎ConWIP/System WIP
▫︎Five Focusing Steps
▫︎Blocker clustering
▫︎Reduce workflow stages
▫︎Explicit policies
▫︎Cost of Delay scheduling, sequencing and selection
▫︎Reduce “expedites”
Lean-Kanban
@mattphilip #bettersoftwarecon
WHAT YOU CAN DO ABOUT VARIATION
▫︎“Agile 101” (simple, decoupled design; thin vertical
slices; pairing)
▫︎Identify/make visible/measure dependencies
▫︎Collaborate/Share work (Dimitar Bakardzhiev)
▫︎Spike and stabilize (Dan North)
▫︎Reduce accidental complexity (Liz Keogh)
Team
Why?

14. @mattphilip #bettersoftwarecon
WHAT YOU CAN DO ABOUT VARIATION
▫︎Determine what actions would be different based on
the estimate
▫︎Customer-based fitness criteria
▫︎Budgeting: Team run rate
▫︎Focus conversation on value, not cost
▫︎MVP and product ownership
▫︎Create probabilistic forecast ASAP (as soon as you have
data) – together!
▫︎Service-Delivery Reviews
▫︎Teams: Keep teams together, dedicated (reduces
context-switching, Tuckman stages)
Business
@mattphilip #bettersoftwarecon
POLICIES TO REDUCE VARIATION
▫︎We will only start new work at about the same rate that
we finish old work.
▫︎We will make every reasonable effort to finish all work
that is started and minimize wasted effort due to
discarded work items
▫︎If work becomes blocked, we will do everything we can
do unblock that work as expeditiously as possible.
▫︎We will closely monitor our policies around the order in
which we pull items through our system so that some
work items do not sit and age unnecessarily.
— Daniel Vacanti, When Will It Be Done?

15. DATA OVER
INTUITION
@mattphilip #bettersoftwarecon
HUMAN BIAS
▫︎Recency
▫︎Availability
▫︎Gambler’s conceit
▫︎Anchoring
▫︎Halo effect
▫︎Motivational
▫︎Confirmation

16. @mattphilip #bettersoftwarecon
FIRST, KNOW WHERE YOU ARE
@mattphilip #bettersoftwarecon
KEOGH’S “SCALE OF IGNORANCE”
1. Just about everyone in the world has done this.
2. Lots of people have done this, including someone on
our team.
3. Someone in our company has done this, or we have
access to expertise.
4. Someone in the world did this, but not in our
organization (and probably at a competitor).
5. Nobody in the world has ever done this before.

17. @mattphilip #bettersoftwarecon
DATA OVER INTUITION
@mattphilip #bettersoftwarecon
LET’S PRACTICE!

18. 31
PROBABILISTIC OVER
DETERMINISTIC
@mattphilip #bettersoftwarecon
PROBABILISTIC OVER DETERMINISTIC
Dec 28
— graphic courtesy of Larry Maccherone, (maccherone.com/lumenize)

19. @mattphilip #bettersoftwarecon
VACANTI’S VERITY
When making a forecast (predicting the future),
you have to accept that there is more than one
possible outcome. Therefore… A forecast is a
calculation about the future that includes both
a range and a probability of that range
occurring.
@mattphilip #bettersoftwarecon
PROBABILISTIC OVER DETERMINISTIC

20. @mattphilip #bettersoftwarecon
PROBABILISTIC OVER DETERMINISTIC
@mattphilip #bettersoftwarecon
PROBABILISTIC OVER DETERMINISTIC

21. @mattphilip #bettersoftwarecon
PROBABILISTIC OVER DETERMINISTIC
2%
20% 21%
3%
16% 16%
9%
7%
2% 2% 2%
Dec 28 Feb 17Nov 30 Jan 20
@mattphilip #bettersoftwarecon
PROBABILISTIC FORECASTING

22. @mattphilip #bettersoftwarecon
PROBABILISTIC FORECASTING: ONE ITEM
@mattphilip #bettersoftwarecon
BACK TO YOUR SCATTERPLOT

23. @mattphilip #bettersoftwarecon
STRAIGHT-LINE (AVERAGE) FORECASTS
Team A Team B
Work item #1 5 days 3 days
Work item #2 1 day 3 days
Work item #3 3 days 3 days
Average 3 days 3 days
3-day delivery time
expectancy
66% 100%
@mattphilip #bettersoftwarecon
EXPECTATIONS, NOT COMMITMENTS

24. @mattphilip #bettersoftwarecon
SERVICE-DELIVERY EXPECTATIONS
Expectation Performance
Expedite 90% 3 days or less
Standard Urgency 85% 10 days or less
Fixed-Date 90% On-time
44
IN SUMMARY

25. @mattphilip #bettersoftwarecon
TO ESTIMATE OR NOT TO ESTIMATE?
NeverEstimateAnything
AlwaysEstimateEverything
Estimate Default Behavior Don’t estimate
Effort Factors All sources of variation
Intuition Approach Data
Deterministic Forecast Type Probabilistic
Tasks in hours Level of Detail Work items in days
High Effort Spent Low
Estimating better Improvement Aim Reducing variation
Commitment Management Service Expectations
@mattphilip #bettersoftwarecon
BETTER QUESTIONS TO ASK
@mattphilip
▫︎In what context would estimates bring value, and what
are we willing to do about it when they don’t? – Woody
Zuill
▫︎How much time do we want to invest in this? – Matt
Wynne
▫︎What can you do to maximize value and reduce risk in
planning and delivery? – Vasco Duarte
▫︎Can we build a minimal set of functionality and then
learn what else we must build?
▫︎Would we/you not invest in this work? If not, at what
order-of-magnitude estimate would we/you take that
action?
▫︎What actions would be different based on an estimate?

26. @mattphilip #bettersoftwarecon
HOW TO GET STARTED (PROJECT IN PROGRESS)
1. Continue to discuss the work to analyze it and break it into thin
vertical slices.
2. Start tracking two pieces of data for each work item: commit
date and delivery date.
3. After accumulating 10 data points, run a Monte Carlo
simulation to provide a probabilistic forecast.
4. Begin answering the “When” question using data, either at the
project level or individual work-item level.
5. Validate whether the probabilistic forecasts match what actually
occurs.
6. If the forecasts are helpful, wean your team off estimating.
7. Focus improvement efforts on reducing the sources of variation.
@mattphilip #bettersoftwarecon
HOW TO GET STARTED (NEW PROJECT)
1. Ask the “better questions” above about the use and
importance of estimates.
2. Use reference-class data (similar delivery times from other
projects in similar tech stacks with similar teams) to provide an
initial probabilistic forecast
3. As soon as you accumulate 10 data points, run a Monte Carlo
simulation to provide an updated probabilistic forecast.
4. Continually reforecast when you get more information.

27. @mattphilip #bettersoftwarecon
REFERENCES AND FURTHER EXPLORATION
▫︎ noestimatesbook.com (Vasco Duarte)
▫︎ infoq.com/articles/noestimates-monte-carlo (Dimitar Bakardzhiev)
▫︎ priceonomics.com/why-are-projects-always-behind-schedule
▫︎ http://scrumandkanban.co.uk/estimation-meets-cynefin/
▫︎ ronjeffries.com
▫︎ Lizkeogh.com
▫︎ https://neilkillick.wordpress.com/
▫︎ http://zuill.us/WoodyZuill/
▫︎ mattphilip.wordpress.com/noestimates-game
▫︎ When Will It Be Done? (Dan Vacanti)
▫︎ focusedobjective.com (Troy Magennis)
▫︎ actionableagile.com (Dan Vacanti)
▫︎ kanbanize.com
▫︎ scrum.org
@mattphilip #bettersoftwarecon
Questions?
THANK YOU