Transcript Joel Semeniuk CEO, Imaginet Resources Microsoft Regional Director Microsoft MVP – Team System DPR205

Joel Semeniuk
CEO, Imaginet Resources
Microsoft Regional Director
Microsoft MVP – Team System
DPR205
What Is an Estimate?
Estimate <> Target or Commitment
Estimate
• Prediction
Target
• Desire
Commitment
• Promise
Estimate <> Planning
Estimation
• Analytical Unbiased
Process
• Goal = Accuracy
Planning
• Biased Goal-Seeking
Process
• Goal = Seek Result
Plans Need Good Estimates
Scheduling
Defining
Iterations
Identifying
Critical Path
Estimation
Prioritization
Breaking
Down Work
Common Scenario
How long do you think this project
should take? We need to have it
ready in 3 months with these
features….
My estimates say we can do this in
5 months
5 Months? Didn’t you hear me?
I need to have this in 3 months for
the trade show!
The manager wasn’t asking for an estimate but
a plan to solve a problem…
Tip: When asked for an estimate – determine if it should be an estimate or a plan to hit a target
Single Point Estimates
Rarely is a single point estimate an estimate
Estimates should include some level
of probability
Tip: When you see a single point estimate – question to see if this is really a target
Tip: When you see a single point estimate – you should question the probability
Tip: Don’t use a planning tool to make estimates (e.g., MS Project)
Using MS Project and Single Point Estimates
ID
Task Name
0
1
2
3
4
5
6
7
New Product
Work
14,272 hrs
Baseline
Really?
Variance
0 hrs 14,272 hrs
Actual
Remaining
0 hrs 14,272 hrs
New Product Development 14,272
Template
hrs
0 hrs 14,272 hrs
0 hrs
Initial NewProduct Screening
72 hrs
Stage
0 hrs
72 hrs
0 hrs
New product opportunity identified
0 hrs
0 hrs
0 hrs
0 hrs
Describe new product idea
16(1-page
hrs
written0 disclosure)
hrs
16 hrs
0 hrs
Gather information required
48 hrs
for go/no-go decision
0 hrs
48 hrs
0 hrs
Convene opportunity of screening
8 hrs committee
0 hrs
(decision to pursue
8 hrs idea or not)
0 hrs
Decision point - go/no-go to
0 hrs
preliminary investigation
0 hrs
0 hrs
0 hrs
14,272 hrs
72 hrs
0 hrs
16 hrs
48 hrs
8 hrs
0 hrs
% W. Comp.
0%
0%
0%
0%
0%
0%
0%
0%
Estimation Challenges
Provide a 90% Confident Estimate for the following:
How many people are at this conference?
What is the size of the largest whale ever discovered?
How many bugs will you have in your next software project?
What is the distance between Mars and the Sun?
What is the surface temperature of the sun?
What is the total volume of the Great Lakes?
Question: What makes you think you are 90% confident?
Question: Did you use an artificially narrow range?
Question: Where does the pressure to use a narrow range
come from?
Two Important Laws of Nature
Parkinson’s Law
If you give a person 5 days to deliver a task that could be
delivered in 4, the person will find something to do with
that extra day
The Student Syndrome
If given too much time, people procrastinate until late in the
project, at which point they rush to complete the work, and
likely won’t finish on time
These are two common arguments
against Overestimation
Uncertainty and Software Estimation
Not all requirements are known until
development time in most cases
Narrowing the Cone
Tip: The cone does not narrow itself;
it narrows when you continually make
decisions that narrow variability
Sources of Error
1. Chaotic Development Process
2. Unstable Requirements
3. Omitted Activities
4. Unfounded Optimism
5. Subjectivity
6. Off-the-Cuff Estimates
Things that Influence Estimates
Project Size
Type of Software Being Developed
Personnel Factors
Programming Languages
and LOTS of others such as:
•
•
•
•
•
•
Complexity
Constraints
Turnover
Experience
Tools
Ego
•
•
•
•
•
Team Cohesion
Process maturity
Architecture Risk
Technology Maturity
I’m sure you can name 10 more…
Estimation Practices
Count, Compute, Judge
Calibration and Historical Data
Expert Judgment
Decomposition and Recomposition
Estimation by Analogy
Proxy-Based Estimates
Expert Judgment in Groups
Use of Multiple Approaches
Count, Compute, Judge
Count, Compute, Judge
If you can count something – count it
Use “expert” judgment when there’s nothing
to count
What to count?
Something correlated with size of software
Something we can count sooner rather than later
Something that will produce a statistically
meaningful average
Something that you understand
Something you can count with minimal effort
Count, Compute, Judge
Examples of things you can count…
List of things
More things
Requirements
Web Pages
Features
Bugs
Use cases
Reports
Stories
Dialog boxes
Function Points
Database Tables
Change Requests
Classes
Tests
Cucumbers
Calibration and Historical Data
Helps to transform Count into Estimate
Best way to predict today’s weather is to look
at yesterday’s
Ways to calibrate:
Industry Data
Historical Data
Project Data
Industry Data
Historic Project Data Example
Team Size
Average Stories Delivered per Sprint
1
5
2–3
12
4–5
22
6–7
31
8
No Data
Tip: Using Time and “Actual Effort” as historical data is difficult
Current Project Data
Use Data from the Current Project to Predict
the Rest of the Project
Data for Sprint 1
Remainder of Project
27 story points (sp) delivered
Effort = 2.25 sp per staff week (spsw)
12 staff weeks (sw)
Schedule = 9 sp per calendar week (spcw)
3 calendar weeks (cw)
Project size = 180 sp
Preliminary Calibration
Preliminary Whole-Project Estimate
Effort = 27sp / 12sw = 2.25 sp per sw
Effort = 180sp/2.25 spsw = 80 staff weeks
Schedule = 27sp / 3w = 9 sp per cw
Schedule = 180sp / 9 spcw = 20 calendar weeks
Individual Expert Judgment
Two Types
Intuitive Expert Judgment (Spidey Senses) – not very accurate
Structured Expert Judgment – almost as accurate as
model-based estimates
Who Estimates?
People who are doing the work – most accurate
Granularity
End up with estimates that are around ¼–1 day large
Use Ranges
Best Case, Most Likely Case, Worst Case
Use Formulas
Optimistic PERT = [BestCase+(4XMostLikely)+WorstCase]/6
Pessimistic PERT = [BestCase+(3xMostLikely)+(2xWorstCase)]/6
Decomposition and Recomposition
AKA – Bottom Up
The Law of Large Numbers
Single Large Estimates are usually Largely wrong in a
single direction (+/-)
Breaking into smaller pieces – some are above, some are lower
The error at the detail level balances out the error on the whole
How Small to Break Things Down?
You need 5–10 smaller things to start seeing benefits
Use Common Work Breakdown to Avoid Missing Activities
Category
Create/Do
Plan
Integration
X
X
Documentation
X
X
Etc
X
Manage
Review
X
X
X
Rework
Defect
X
X
X
X
Big Problem with Bottom UP
Aggregating Estimates Doesn’t Work Well
Use complex standard deviation formulas to
aggregate when you have more than 10 tasks
This can get VERY complicated if you want
to be accurate
Take a statistics course for more information
Estimation by Analogy
Get details of previous project decomposed by feature area,
work breakdown or some other scheme
Compare size of new project piece by piece
Build up estimate of new project as a % of the old project size
Create an effort based on the size of the new project
compared to old
Check for congruent assumptions
Proxy-based Estimates
Find a Proxy that correlates to what you are estimating
that is easier to estimate/count
E.g., Estimation of # of Test Cases is correlated
to # of Requirements
Some use Proxies to estimate lines of code
What do lines of code really give you?
Some great techniques
Story Points
T-Shirt Sizing
Good for estimating test cases, defects,
documentation, etc.
Story Points
Assign a size to each story you are building
Story Point Scale
Specific Points to the Scale
Powers of 2
1, 2, 4, 8, 16, 32
Fibonacci
1, 2, 3, 5, 8, 13, 21
Story Points Example
Story
Points
Story 1
2
Story 2
1
Story 3
4
Story 4
8
…
Story 60
2
Total
180
Need to Calibrate an Iteration
Data for Iteration 1
27 Story Points Delivered
12 Staff weeks
3 Calendar Weeks
Calibration:
Effort = 27 story points / 12 staff weeks = 2.25 story points/staff week
Schedule = 27 story points / 3 calendar weeks = 9 story points/calendar week
Projecting Further
Assumptions from Calibration
Effort = 2.25 story points/staff week
Schedule = 9 story points/calendar week
Project size = 180 story points
Preliminary Whole-Project Estimate
Effort = 180 story points / 2.25 story points/staff week = 80 staff weeks
Schedule = 180 story points / 9 story points/calendar week = 20 calendar weeks
T-Shirt Sizing
How do Sales people and Delivery people
work together?
Sales people need to know relative size to help
determine priority
Estimator won’t estimate until further decomposed
Early in the Cone of Uncertainty
Remember – goal isn’t accuracy, but accurate
enough to support control and decisions
Can use T-shirt sizing to help
T-Shirt Sizing
Feature
Business Value
Dev Cost
Feature A
Large
Small
Feature B
Small
Large
Feature C
Large
Large
Feature D
Medium
Medium
Using for Prioritization
Business Value
Extra Large
Large
Medium
Small
Extra Large
0
4
6
7
Large
-4
0
2
3
Medium
-6
-2
0
1
Small
-7
-3
-1
-
Feature
Bus. Value
Dev Cost
Net Value
Feature A
L
S
3
Feature B
L
M
2
Feature C
L
L
0
Feature D
M
M
0
Expert Judgment in Groups
Group reviews can be fun
Have each team estimate pieces individually,
compare results
Don’t average estimates
Arrive at consensus
Techniques
Wideband Delphi Technique (quite formal)
Estimation Poker (quite fun)
Mixing Things Up
E.g., Expert Proxy Judgment in Groups
Quick Demos
Feature Prioritization Worksheet –
T-Shirt Sizing (kinda)
Feature Point Worksheet
Multi-Point Worksheet
Estimation Poker
Some Parting Thoughts
Keep Estimation Simple
Time Boxing is your friend
Do things that minimize uncertainty
Don’t be afraid to re-estimate and thus, re-plan
Estimation via consensus is harder than you think
Sometimes you have to commit; I’m sorry
Be careful when recording historic data – time-based
data is all a lie and lines of code are meaningless when
technology changes
Find a method that works for you – then
continually improve
Reference
[email protected]
Resources
www.microsoft.com/teched
www.microsoft.com/learning
Sessions On-Demand & Community
Microsoft Certification & Training Resources
http://microsoft.com/technet
http://microsoft.com/msdn
Resources for IT Professionals
Resources for Developers
www.microsoft.com/learning
Microsoft Certification and Training Resources
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