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# 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 ā€Ø
NOT TO ESTIMATE
Is that the Question?
@mattphilip #bettersoftwarecon
HOFSTADTERā€™S LAW
ā€œIt always takes longer than you expect,
even when you take into account
Hofstadterā€™s Law.ā€
@mattphilip #bettersoftwarecon
PARKINSONā€™S LAW
Work expands so as to ļ¬ll the time
available for its completion.
@mattphilip #bettersoftwarecon
ā€œPOOR ESTIMATION SKILLSā€
@mattphilip #bettersoftwarecon
THE SPECTRUM OF ESTIMATING
NeverEstimateAnything
AlwaysEstimateEverything
Estimate Default Behavior Donā€™t estimate
Eļ¬€ort Factors All sources of variation
Intuition Approach Data
Deterministic Forecast Type Probabilistic
Tasks in hours Level of Detail Work items in days
High Eļ¬€ort Spent Low
Estimating better Improvement Aim Reducing variation
Commitment Management Service Expectations
@mattphilip #bettersoftwarecon
MANIFESTO RELEVANCE
@mattphilip #bettersoftwarecon
MANIFESTO RELEVANCE
@mattphilip #bettersoftwarecon
WHAT NOESTIMATES IS NOT SAYING
ā–«ļøŽ You are evil if you estimate
ā–«ļøŽ All estimates are totally useless
ā–«ļøŽ Stop doing your successful estimating practice
ā–«ļøŽ Stop having the conversations to understand/analyze/
break down work
ā–«ļøŽ Work items must be the same size
ā–«ļøŽ You must place your full faith and conļ¬dence in Monte
Carlo forecasts
@mattphilip #bettersoftwarecon
WHAT NOESTIMATES IS SAYING
ā–«ļøŽ Know why you are estimating
ā–«ļøŽ Discover for yourself how good you are at estimating
(measure)
ā–«ļøŽ Keep doing the things that help you understand the work
ā–«ļøŽ Upfront estimates need to be held loosely
ā–«ļøŽ If you focus on delivering value quickly, you obviate the
need for Iron Triangle considerations
@mattphilip #bettersoftwarecon
MY NOESTIMATES MANIFESTO
ā€¦ 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 ā€œempiricism over guessworkā€
REDUCING SOURCES
OF VARIATION
@mattphilip #bettersoftwarecon
DO YOU ASSUME CORRELATION?
Is the initial sizing a good predictor for when you can get your stuļ¬€?
In our case, the surprising truth was ā€no.ā€
ā€” Mattias Skarin, Real-World Kanban
@mattphilip #bettersoftwarecon
WHAT WE ESTIMATE
Code
@mattphilip #bettersoftwarecon
WHAT WE ESTIMATE
Analyze+Design+Code+Test+Deploy
@mattphilip #bettersoftwarecon
WHAT ACTUALLY HAPPENS
Analyze Code Test DeployDesign
Wait for approval
Wait for staļ¬€
availability
Wait for ā€Ø
rework
Wait for API
availability
Wait for ā€Ø
higher-priority work
to ļ¬nish
Wait for approval
Wait for ā€Ø
blocker ā€Ø
removal
@mattphilip #bettersoftwarecon
WHATā€™S GOING ON?
Value-added time
_________________________
Total elapsed delivery time
Flow eļ¬ƒciency =
@mattphilip #bettersoftwarecon
WHATā€™S GOING ON?
Low process eļ¬ƒciency (typically 5-15%
in software delivery) means that even if
we nailed the eļ¬€ort estimates ā€¦ we
would be accurately predicting 5-15% of
elapsed delivery time!ā€Ø
ā€” Troy Magennis
@mattphilip #bettersoftwarecon
SOURCES OF VARIATION
How many can you name?
@mattphilip #bettersoftwarecon
SOURCES OF VARIATION
Waiting for ā€Ø
availability
Rework
Team ā€Ø
dependencies
Stages in
team
development
(Tuckman)
Steps/ā€Ø
handoļ¬€s
Selection ā€Ø
policy
Essential ā€Ø
complication
Accidental ā€Ø
complication
System ā€Ø
dependencies
Work In ā€Ø
Progress
Technology/ā€Ø
domain/ā€Ø
product
Specialization
Team ā€Ø
composition
Multitasking/ā€Ø
context ā€Ø
switching
Collaborationā€Ø
policy
Blockers
@mattphilip #bettersoftwarecon
WHAT CAN YOU DO ABOUT VARIATION
How many remediesā€Ø
can you name?
@mattphilip #bettersoftwarecon
WHAT YOU CAN DO ABOUT VARIATION
ā–«ļøŽLower WIP
ā–«ļøŽConWIP/System WIP
ā–«ļøŽFive Focusing Steps
ā–«ļøŽBlocker clustering
ā–«ļøŽReduce workļ¬‚ow stages
ā–«ļøŽExplicit policies
ā–«ļøŽCost of Delay scheduling, sequencing and selection
ā–«ļøŽReduce ā€œexpeditesā€
Lean-Kanban
@mattphilip #bettersoftwarecon
WHAT YOU CAN DO ABOUT VARIATION
ā–«ļøŽā€œAgile 101ā€ (simple, decoupled design; thin vertical
slices; pairing)
ā–«ļøŽIdentify/make visible/measure dependencies
ā–«ļøŽCollaborate/Share work (Dimitar Bakardzhiev)
ā–«ļøŽSpike and stabilize (Dan North)
ā–«ļøŽReduce accidental complexity (Liz Keogh)
Team
Why?
@mattphilip #bettersoftwarecon
WHAT YOU CAN DO ABOUT VARIATION
ā–«ļøŽDetermine what actions would be diļ¬€erent based on
the estimate
ā–«ļøŽCustomer-based ļ¬tness criteria
ā–«ļøŽBudgeting: Team run rate
ā–«ļøŽFocus conversation on value, not cost
ā–«ļøŽMVP and product ownership
ā–«ļøŽCreate probabilistic forecast ASAP (as soon as you have
data) ā€“ together!
ā–«ļøŽService-Delivery Reviews
ā–«ļøŽTeams: Keep teams together, dedicated (reduces
context-switching, Tuckman stages)
Business
@mattphilip #bettersoftwarecon
POLICIES TO REDUCE VARIATION
ā–«ļøŽWe will only start new work at about the same rate that
we ļ¬nish old work.
ā–«ļøŽWe will make every reasonable eļ¬€ort to ļ¬nish all work
that is started and minimize wasted eļ¬€ort due to
discarded work items
ā–«ļøŽIf work becomes blocked, we will do everything we can
do unblock that work as expeditiously as possible.
ā–«ļøŽWe 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.
ā€” Daniel Vacanti, When Will It Be Done?
DATA OVER
INTUITION
@mattphilip #bettersoftwarecon
HUMAN BIAS
ā–«ļøŽRecency
ā–«ļøŽAvailability
ā–«ļøŽGamblerā€™s conceit
ā–«ļøŽAnchoring
ā–«ļøŽHalo eļ¬€ect
ā–«ļøŽMotivational
ā–«ļøŽConļ¬rmation
@mattphilip #bettersoftwarecon
FIRST, KNOW WHERE YOU ARE
@mattphilip #bettersoftwarecon
KEOGHā€™S ā€œSCALE OF IGNORANCEā€
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.
@mattphilip #bettersoftwarecon
DATA OVER INTUITION
@mattphilip #bettersoftwarecon
LETā€™S PRACTICE!
31
PROBABILISTIC OVER
DETERMINISTIC
@mattphilip #bettersoftwarecon
PROBABILISTIC OVER DETERMINISTIC
Dec 28
ā€” graphic courtesy of Larry Maccherone, (maccherone.com/lumenize)
@mattphilip #bettersoftwarecon
VACANTIā€™S VERITY
When making a forecast (predicting the future),
you have to accept that there is more than one
possible outcome. Thereforeā€¦ 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
@mattphilip #bettersoftwarecon
PROBABILISTIC OVER DETERMINISTIC
@mattphilip #bettersoftwarecon
PROBABILISTIC OVER DETERMINISTIC
@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
@mattphilip #bettersoftwarecon
PROBABILISTIC FORECASTING: ONE ITEM
@mattphilip #bettersoftwarecon
BACK TO YOUR SCATTERPLOT
@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 ā€Ø
expectancy
66% 100%
@mattphilip #bettersoftwarecon
EXPECTATIONS, NOT COMMITMENTS
@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
@mattphilip #bettersoftwarecon
TO ESTIMATE OR NOT TO ESTIMATE?
NeverEstimateAnything
AlwaysEstimateEverything
Estimate Default Behavior Donā€™t estimate
Eļ¬€ort Factors All sources of variation
Intuition Approach Data
Deterministic Forecast Type Probabilistic
Tasks in hours Level of Detail Work items in days
High Eļ¬€ort Spent Low
Estimating better Improvement Aim Reducing variation
Commitment Management Service Expectations
@mattphilip #bettersoftwarecon
BETTER QUESTIONS TO ASK
@mattphilip
ā–«ļøŽIn what context would estimates bring value, and what
are we willing to do about it when they donā€™t? ā€“ Woody
Zuill
ā–«ļøŽHow much time do we want to invest in this? ā€“ Matt
Wynne
ā–«ļøŽWhat can you do to maximize value and reduce risk in
planning and delivery? ā€“ Vasco Duarte
ā–«ļøŽCan we build a minimal set of functionality and then
learn what else we must build?
ā–«ļøŽWould we/you not invest in this work? If not, at what
order-of-magnitude estimate would we/you take that
action?
ā–«ļøŽWhat actions would be diļ¬€erent based on an estimate?
@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 ā€œWhenā€ 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 oļ¬€ estimating.
7. Focus improvement eļ¬€orts on reducing the sources of variation.
@mattphilip #bettersoftwarecon
HOW TO GET STARTED (NEW PROJECT)
1. Ask the ā€œbetter questionsā€ 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.
@mattphilip #bettersoftwarecon
REFERENCES AND FURTHER EXPLORATION
ā–«ļøŽ noestimatesbook.com (Vasco Duarte)
ā–«ļøŽ infoq.com/articles/noestimates-monte-carlo (Dimitar Bakardzhiev)
ā–«ļøŽ priceonomics.com/why-are-projects-always-behind-schedule
ā–«ļøŽ http://scrumandkanban.co.uk/estimation-meets-cyneļ¬n/
ā–«ļøŽ ronjeļ¬€ries.com
ā–«ļøŽ Lizkeogh.com
ā–«ļøŽ https://neilkillick.wordpress.com/
ā–«ļøŽ http://zuill.us/WoodyZuill/
ā–«ļøŽ mattphilip.wordpress.com/noestimates-game
ā–«ļøŽ When Will It Be Done? (Dan Vacanti)
ā–«ļøŽ focusedobjective.com (Troy Magennis)
ā–«ļøŽ actionableagile.com (Dan Vacanti)
ā–«ļøŽ kanbanize.com
ā–«ļøŽ scrum.org
@mattphilip #bettersoftwarecon
Questions?
THANK YOU

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