The #NoEstimates Debate
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Transcript of The #NoEstimates Debate
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Neil Killick, Agile Coach / Trainerneilkillick.com / iterative.com.au neil_killick
Copyright Neil Killick, Iterative, 2013
the #NoEstimates debate
Alternatives to Agile
Estimation and...
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WHAT IS
Like “Agile”, it has come to have many definitions and interpretations.
What is #NoEstimates?
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A conversation, started on Twitter, about ways in which software can be delivered with no estimates.
Birth of #NoEstimates
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A collection of opinions and practical advice from practitioners who deliver software with no estimates.
What drove the debate?
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A diverse and much needed debate about when it is appropriate to use estimates in software, and what form these should take.
It’s now become...
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Neil Killick Chris Chapman Henri Karhatsu
Woody Zuill Vasco Duarte
The #NoEstimates Crew
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WHAT ISEMBRACE AGILE PRINCIPLESFOCUS ON VALUEDELIVER SMALL SLICESDELIVER EARLY & FREQUENTLYCUSTOMER COLLABORATION
Common Ground
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thicsmpiricismmergence
3 E’s of #NoEstimates
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ETHICS - Cycle of Mistrust
Trust breaks down
Deliver the wrong thing, or late
Focus on schedule
Commitments of scope and time
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EMPIRICISM - Working software allows us to monitor progress and manage risk in a new way.
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EMERGENCEof cost and value aswe get feedback from users and market.
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Which is more predictable --A team that estimates or one that doesn’t ?
Predictability
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● DETERMINISTIC AND REACTIVE● FOCUS ON SCHEDULE / PLAN● SCOPE DRIVES DECISIONS● LOTS OF WIP IN ATTEMPT TO “GET IT ALL
DONE”● NO METRICS, OR INAPPROPRIATE ONES
Team #Estimates
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High variability12 days
1 Day
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● PROBABILISTIC AND PROACTIVE● FOCUS ON TIME AND CASH CONSTRAINTS● ITERATE DESIGN AND DECISIONS● DELIVER WITH FLOW / LIMIT WIP● ACTIONABLE METRICS (e.g. STORY CYCLE
TIME DISTRIBUTION) USING A “SLICING HEURISTIC”
Team #NoEstimates
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Better Predictability
3 days
1 Day
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● EXPLICIT POLICY FOR BREAKING DOWN WORK AND MEASURING HOW LONG IT TOOK (CYCLE TIME)
● STARTS AS A SHARED DEFINITION OF WORK TYPES (e.g. THEME, FEATURE, STORY, etc.)
● SLICE ALL UPCOMING WORK SIMPLY AND SYSTEMATICALLY FOR “SMALL-NESS”
What’s a“Slicing HeuristicTM”?
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● Given Bob is a registered user,
When Bob logs in
Then he should be logged in.
● Given Bob is logged in,
When Bob chooses Profile
Then he should see his profile.
Example -Max 1 User Scenario
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Slice into2 separate stories
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Slice those stories further
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● Agility relies on small chunks, so useful to have a consistent and explicit way of creating them
● Improve ready-ness and done-ness
● Focus on delivering more frequent slices of value
● No need to explicitly estimate or re-estimate
Why use aSlicing Heuristic?
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● Story points are ambiguous, time isn’t
● Explicit policy, so can be inspected and adapted to narrow control limits
● Outliers can be addressed at standup or retro
Why use aSlicing Heuristic?
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● Exposes goals from solutions and vice versa● Slices not necessarily “smaller” than thing we
sliced, but multiply our options
Slicing creates options
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● KEEP TEAMS TOGETHER● ENABLE CONTINUOUS DELIVERY● NO LONG PROJECTS / PROJECT THINKING● DRIP FUND (MULTIPLE OPTIONS)● BUILD THINGS ON DEMAND, DELIVER AS
SOON AS THEY ARE READY● FLEXIBLE CONTRACTS
Portfolio #NoEstimates
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Present a business case
Approved as viable option
Team assignedTimeboxed experiment
Is initiative still valuable
enough?
NO
Initiative prioritised
YES
+ Team(s) if required
Frequent delivery
& feedback loop
Stop
Choosing what to do
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Scaling up and down
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Questions
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What is and isn’t estimating, given people form and act on expectations of an uncertain future every day?
Question 1
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● Estimating = Giving ranges of actual or relative time based on past observation, WIP, team size, etc.
● Guessing = New teams, with competing priorities, asked to give single dates in unfamiliar domains
● There is nothing intrinsically wrong with estimating, so long as we:○ Understand its limitations○ Use it only in appropriate situations○ Don’t rely on it for big up front decision making○ Update our estimates (and everyone’s expectations)
based on real data frequently
Answer 1
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Why would we choose not to judge likely outcomes if worthwhile human endeavours necessarily carry risk?
Question 2
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● #NoEstimates is about alternatives to estimating the cost of delivering software, not the value it generates
● We must hypothesise (estimate) the value of things in order to decide if we will pursue them
● My argument is that rather than estimate cost we can control (fix) it in “drips” using fixed Agile teams
● Delivery of working software allows us to reassess value iteratively based on the reality of user / stakeholder feedback and market conditions
Answer 2
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If we elect not to take on the risk of predicting an uncertain future, who do we think should, and why?
Question 3
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● We should embrace the delicious uncertainty of software, be excellent in what we do and aim to delight rather than “meet requirements”
● Software products and services have ongoing value, so the final cost and value can never be known up front
● We can’t fix price and scope, but we can work collaboratively and continuously with our customers to build the best possible result for budget or time constraint
● We can provide flexible pricing and termination options to our customers based on similar past work
Answer 3
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Off the shelf library software costs $50k.We could try building our own at $2,500/day but might fail.What should we do?
Question 4
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● Answer depends on many things like whether we have an established team, are we capable of delivering features every few days, etc.
● Need to establish the problem rather than decide between solutions; Do we need the software at all?
● What are the consequences of spending more than the OTS product costs? Is the $50k a constraint?
● How would ongoing maintenance costs compare?
Answer 4
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● 4 weeks not far into the future, so probably have an instant sense of “Is it possible?” and“Can we build something better?”
○ Do we know enough about the domain?○ What are minimum features we need?○ How many people do we have? ○ Do we have any other WIP?
Answer 4 (contd)
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Neil Killick, Agile Coach / Trainerneilkillick.com / iterative.com.au neil_killick
Copyright Neil Killick, Iterative, 2013