Agile Estimation for Fixed Price Model

1. Agile Estimation for
Fixed Price Model
Challenges & Possible Solutions
Jayanthi Srinivasan
Linkedin: Jayanthi S, PMP,ITIL,PMI-ACP,SAFe SA

2. 2
About Me
 PMP, ITIL, PMI-ACP, SAFE SA
Certified
 More than 16 years in IT Industry
 Specialized in
 Agile Coaching
 Assessment
 Transformation

3. 3
Key Highlights
Context – Agile & Upfront Estimation in Fixed Price Model at Proposal Stage
Fixed Cost instead of Fixed Scope As a Solution
Implementation Challenges
Change Management Process
Fixed Cost instead of Fixed Scope as a Solution
Estimation Barriers
Recommended Sizing Techniques
Requirement Clarity Levels
Story Point Computing Approach
Definition of Done
Story Point Computing Models
First Velocity Computation
Velocity Decelerators & Accelerators
How do we arrive at Schedules?
Overall Agile Story Point Estimation and Planning Framework
Sample Estimation
How do we track the budget during project execution?
Conclusion

4. 4
Context – Agile & Upfront Estimation in
Fixed Price Model at Proposal Stage
Agile
Estimation
Progressive
Requireme
nts
No Team
Clarity
Fixed time,
Cost, Scope
Implications if not
considered

5. 5
Fixed Cost instead of Fixed Scope As a Solution
Fixed Price Model Challenges
Change Management - Fixed Cost
instead of Fixed Scope
Story Sizing Techniques
Story Point Computation Models
First Velocity as a Magic Number
Team
Size
Total
Effort
Schedule
Arrival
Budget
Tracking

6. 6
Implementation Challenges
The Agile Triangle
Reference:
http://2.bp.blogspot.com/x_mffEtfUTg/UQAz2HidX3I/AAAAAAAAAPY/gvkVuRRRZLI/s1600/Figure3.jpg
Limited Scope
Control
Frequent
Prioritization
More
Adaptable
Collaborative
Continuous
Delivery

7. 7
Change Management Process
Scrum Change Management Process
Reference: http://www.gregmester.com/wp-
content/uploads/2015/08/IterationPlanningChange.jpg
 No changes during a sprint.
 However Scrum framework allows
the Product Owner to add Change
Requests in the product backlog.
 The Change Requests (story point
estimated) to be prioritized by
Product Owner.
 The equivalent Story point user
stories are replaced and re-
prioritized.

8. 8
Fixed Cost instead of Fixed Scope as a Solution
 Estimate by story points
with the initial set of
requirements.
 Identify an approach
to compute the story
points and share the
approach with
customer and arrive at
a common
understanding.
 Adapt for changes up
to the extent of
consumption of the
initially estimated story
points with some
buffer.
 Beyond the initial
estimate of story
points, it can be
considered as
additional cost.

9. 9
Estimation Barriers
Cost Effort
No Actual Team
players at
Proposal Phase
Identifying the Right
Sizing Technique to
arrive at Story points
Requirement
clarity
Management
Release is the
first of its kind
(No previous
velocity)

10. 10
Recommended Sizing Techniques
Spikes
Story
UI Changes
DB changes
Test cases
Automation Scripts
CM / packaging
Task Breakdown
Story
Story 1 Story 2 Story 3
Story Splitting
Spike sample stories and
stack other stories
relative to those stories
Sizing Scales
T- Shirt
Fibonacci Series Team Conscience
Expert
Opinion

11. 11
Requirement Clarity Levels
Theme •Low
Epic •Medium
Story •High
Task
Initial Requirements
RFP
BRD
User Cases
Workshops
Sources
Clarity levels

12. 12
Story Point Computing Approach
 Define Done criteria
 Define a Story Point Computing Model
 Compute total Story points
Never convert Story Points to Efforts. It would be a very big disaster!

13. 13
Definition of Done
Story 1
Story 2
Story 3
Software with all features
work as defined by the user
story
All QA testing for
completed features is done
with no pending defects
Regression tests pass
All documentation is
completed
Planned stories
demonstrated to the Product
Owner, Customer and other
stakeholders
Story 1
Story 2
Story 3
Sample DoD
DoD can evolve Sprint on Sprint
based on the requirements and past
learnings

14. 14
Story Point Computing Model 1- Story
Point – Task Matrix
http://www.slideshare.net:80/MarrajuBollapRagada/estimating-story-points-in-agile-
magic-approach-47345114
The guidelines for each
complexity factor can be
pre-defined considering
clarity, technical, data and
functional complexities.

15. 15
Story Point Computing Model 2 – Effort Matrix
Sample Base Effort in Person Hours based on
multiple Technologies
Java .Net Oracle
XS 8 8 10
S 12 16 16
M 20 24 24
X 24 32 30
XL 30 48 40
Story point mapping from an effort range
Story Point Effort Range
1 0-10
2 10-20
3 20-40
5 40-60
8 60-100
13 >100
Epic Feature Story
Technology
Mapping Classification Effort Story Point
Epic 1 Feature 1 Story 1 .NET XL 48 5
Epic 1 Feature 1 Story 2 Java S 12 2
Epic 2 Feature 1 Story 1 .NET X 32 3
Epic 2 Feature 1 Story 2 Java X 16 2
Epic 2 Feature 2 Story 2 Oracle XS 10 1
Map Story Points from Complexity –Sample Effort Matrix

16. 16
First Velocity Computation
When there is no velocity data and no clue on the how the first
velocity would be, consider the first few stories planned for iteration.
Perform task breakdown for one story and compute the effort in hours. Similarly, few
more stories can be taken up till the first iteration effort is achieved.
Different combinations of Team Size and Velocity may be worked out and analyzed

17. 17
Velocity Decelerators & Accelerators
Velocity Decelerators (VD) - Sample
Item Factor Level
Team Expertise High – 0.98
Medium – 0.80
Low – 0.5
Project
Tools Availability High – 0.98
Medium – 0.80
Low – 0.5
Project
Product Owner
Availability &
Participation
High – 0.98
Medium – 0.80
Low – 0.5
Project
Requirement Clarity High – 0.98
Medium – 0.80
Low – 0.5
User Story
Velocity Accelerators (VA) - Sample
Item Factor Level
Common Components High – 1.5
Medium – 1.3
Low – 1.1
Project
Common Test Cases High – 1.5
Medium – 1.3
Low – 1.1
Project
Repeat Releases of the same
kind
High – 1.5
Medium – 1.3
Low – 1.1
Project
Velocity = V * VD * VA
Set up your own Velocity Accelerators and Decelerators
based on your project based experience and past learning

18. 18
How do we arrive at Schedules?
•First Velocity from one
scrum team
•Number of Scrum Teams
•Project Start Date
•Sprint Duration
•Total Story Points
Input
•Story Sizing Techniques
•Story Point Computation
Model
•Velocity Accelerators &
Decelerators
Tools &
Techniques •End Date of the Project
•Total Engineering Efforts
Output

19. 19
Overall Agile Story Point Estimation and Planning
Framework – Part I
Step# Steps Inputs Tools and Techniques Output
1
Product Backlog
creation/refinement
Initial Requirements Customer Workshops
Product Backlog (Initial)
BRD Dialogs
Use Cases Interviews
RFP
Functional
Decomposition
Product Backlog (from Customer) DEEP
Sample Product Backlog from Past
Projects
2
User Stories
Creation/refinement
Product Backlog
INVEST
Product Backlog with user
stories
BRD
Requirements Document
Sample User Stories from Past projects
3 Definition of Done
RFP
Checklist
DOD (Sprint and Release
levels)
Customer Dialog
Sample DOD from past projects
Defined Delvierables
List of Engineering Activities
NFRs
4
Prioritization and
Sequencing
Product Backlog with User Stories MoSCOW
Product Backlog with
Prioritization and
Sequence
Functional Flow Kano
ROI
Priority
Sequencing
Risk

20. 20
Overall Agile Story Point Estimation and
Planning Framework – Part II
Step# Steps Inputs Tools and Techniques Output
5
Story Sizing and Total Story
points computing
Product Backlog with
Prioritization and
Sequence Story Point Matrix
Product Backlog with
Story points
DOD (Sprint and Release
levels) Effort Correlation Matrix
Task Break Down
Approach
Spikes
6 Define Sprint length RFP
Customer Preference
Fixed Length of Sprint
Team Preference
Team Comfort
Coordination with
external parties
User Story Clarity
7
Effort & Story point of Initial set
of Stories
Product Backlog with
Prioritization and
Sequence Spikes Effort of each Story
DOD (Sprint and Release
levels) Task Break down Story point of each Story
Story Splitting
Team Conscience
Initial Set of Stories Expert Opinion
8
First Velocity from 1st Scrum
team
Initial Scrum team size
Cumulative Story Effort
Match with Single Sprint
Effort
Velocity = Cumulative
Story point count
Single Sprint Effort (Initial
team Size * Sprint Length)
Cumulative Story Point
Effort

21. 21
Overall Agile Story Point Estimation and Planning Framework
– Part III
Step# Steps Inputs
Tools and
Techniques Output
9 Compute Number of Sprints
FirstVelocity
Agile Estimation
Template
No. of Sprints
Total Story points
Sprint length
Additional Rework, Buffer, Release
Sprints
10
Additional Full time Efforts
Computation
Pre-Engineering Sprints length
Agile Estimation
Template
Additional Efforts
(Sprint 0/ Framework
Sprint/Regression)
Pre-Engineering Team Size
Time Box for each
Scrum Ceremony
Scrum Master Efforts
Effort for Additional
Meetings
Scrum of Scrum master Efforts
11
Effort for Additonal Partime
roles
Part Time Role Players (Agile
Coach, Architect etc)
Agile Estimation
Template
Additional Effort
Duration
12
Pre-Engineering Efforts
(Before the Engineering
Sprint duration)
Sprint zero Activities
Agile Estimation
Template
Additonal Effort
Duration
Team Size

22. 22
Step# Steps Inputs Tools and Techniques Output Template Mapping
13
Post Engineering
Efforts(After the
Engineering Sprint
duration)
Post Engineering Activities
(Performance Testing, Security
Testing etc)
Agile Estimation
Template
Additional Effort
Release Plan (Post
Engineering Additional
Efforts (in case of big
bang approaches)) - Sec 9
Duration
Team Size
14 Project Start Date
Pre-Engineering Duration Agile Estimation
Template
Revised Project Start Date
15 Project End Date
First Velocity First Velocity * N
Nearest Agreed End Date
= Project End Date
Release Plan (Arrive at
Schedules) - Sec 11
Velocity Accelerators
Accelerators (Common
Components, Same
team and release,
common test cases, etc) N = No. of Scrum Teams Velocity-Accl-Decel
Velocity Decelerators
Decelerators
(Requirement Clarity,
Team Comfort, Product
Owner Availability etc)
No. of Scrum Teams
Agile Estimation
Template
Engineering Start Date
Projected Leaves of Team Members
Holidays
Post Engineering Duration
16 Sprint Planning
Product Backlog
Agile Estimation
Template
Stories in each Sprint Sizing-Planning (Sprint #)
Computed Velocity
Story points for each Story
Sequence
17
Scrum Team
planning
Product Backlog
Agile Estimation
Template
Feature Based Team
Sizing-Planning (Scrum
Team #)
Computed Velocity
Story points for each Story
Sequence
Feature Mapping
Stories in each Sprint
Overall Agile Story Point Estimation and Planning Framework – Part IV

23. 23
Sample Estimation
Form First Scrum Team (without Scrum Master)
Compute First Velocity from First Scrum team
Normal – Without applying Velocity Accelerators and Decelerators
Applied– After applying Velocity Accelerators and Decelerators
Normal Applied
Total Story Points 385 385
First Scrum Team Size 5 5
First Velocity 43 22
Number of Scrum Teams 2 2
Story point per sprint (Velocity of Sprint) 86 44
Estimated # of Sprints 4.48 8.92
Estimation Buffer Sprints @ 15% 0.67 1.34
Rework Buffer Sprints @ 10% 0.45 0.89
Additions Buffer Sprints @ 10% 0.45 0.89
Pre-Release Sprint 1 1
Total Number of Sprints 7.0 13.0
Dev
Tester
Manual
Tester
Automation
BA Configuration UI
Team Size 3 2 1 1 0 1
Total Team Size 8
Sprint Duration 10 Days
Effort per Sprint 80 PD
560 PH

24. 24
Sample Estimation
Arrival of End Date
First Sprint Start Date 1-Nov-2015 1-Nov-2015
Sprint Duration 10 10
Last Sprint End Date 5-Feb-2016 29-Apr-2016
Compute Engineering Efforts
Engineering Team Size 10 10
Scrum Masters 1 1
Additional Roles 0 0
Team Size 11 11
Total Effort (in PD) based on Engineering 774.80 1434.93
Project Start Date 1-Feb-2016 18-Jan-2016
Project End date 30-May-2016 21-Oct-2016
Project Expected Duration
(months)
4.0 9.2
Arrive at Schedules

25. 25
How do we track the budget during project
execution?
• The change management process is by Fixed Cost
instead of Fixed
• Once the initial estimated Story points are
consumed, the Story points beyond this can be
considered as additional.
• The sources of story points may not be user stories
from initial requirements only. As the Sprint
execution progresses, Product Backlog gets added
with defects, Technical Debt and Change
Requests which also carry story points.

26. 26
How do we track the budget during project
execution? – Contd….
A sample way of tracking can be done as
follows:
Total number of User stories
planned = 100
Initial Story Points Estimated =
350
Sprint Duration = 2 weeks
Planned Velocity = 50
Expected Number of Sprints = 7
Delivered: Without CRs, defects, technical debt
Actual: With CRs/ defects/ technical debt
Customized Burn-up Charts

27. 27
Conclusion
 Win-win solution of how Agile software development
projects can be executed in the fixed price model
proposed.
 Fixed Cost instead of Fixed Scope way of execution has
been the main highlight.
 To achieve this, the different hurdles like Requirement
clarity, Story Sizing, Story point computation models, First
time velocity and a customized Budget tracking
mechanisms have been shared.
 This overcomes the upfront Estimation challenges and
also an efficient method of arriving at Story points during
the proposal stage has been provided.

28. 28
 Head of Agile & DevOps Practice in a
Top BFSI company
 More than 20 years in IT Industry
 Agile Evangelist
 Agile Coaching, Transformation,
Implementation
KV Sharma
[LinkedIn: KV Sharma]
I Acknowledge…..
For reviewing, enabling and contributing ………….

29. 29
References
• http://www.nayima.be/html/fixedpriceprojects.pdf
• http://www.gregmester.com/agile-development-requirements-change/
• http://www.agilistapm.com/fixed-price-contracts/
• http://www.timecockpit.com/blog/2014/11/30/How-Fixed-Price-
Contracts-and-Agile-Can-Go-Together
• http://www.slideshare.net:80/MarrajuBollapRagada/estimating-story-
points-in-agile-magic-approach-47345114
• http://www.qaiglobalservices.com/conference/stc2013/pdfs/rashmi_pop
li.pdf
• https://www.scrumalliance.org/community/articles/2013/october/dealin
g-with-bugs-in-the-product-backlog
• https://www.scrumalliance.org/community/articles/2015/august/agile-
estimation-for-fixed-date-projects-and-fixed
• https://www.mountaingoatsoftware.com/blog/how-to-estimate-velocity-
as-an-agile-consultant
• http://www.agileforall.com/2009/10/patterns-for-splitting-user-stories/