This document outlines an agile process for developing data-driven solutions through iterative collaboration between business and data teams. It involves: 1) Understanding long-term goals and short-term sprints, then refining requirements; 2) Creating a roadmap from requirements to metrics to data elements to reports; and 3) Iterative development through sprints, with collaboration between teams to deliver working prototypes and refine requirements.

1. Agile Thinking Hat
Thoroughly understands
the big picture of what
are:
• The Long term
project goals, say
within current
financial year.
<Product Backlog>
• The short term
goals, say within
current quarter.
<Sprint Backlog>
Grey Requirements to
Actionable Specs
Deep dive into what are the key
ask of the project and create
formal requirement specs or
User Stories.
Brainstorm available
documents and artifacts,
collaboratively probe with
stakeholders, proactively listen
and assimilate.
Connect the dots with an eye
on End Goals.
Iterative Refinement
of Product Backlog
Iteratively and
continuously identify,
define and refine
incremental features to
align product
management, data
readiness and program
vision.
Integrated Solution
Roadmap
Requirements to
Metrics to Data
Element
Create an integrated
roadmap of:
Requirement 
Features  Metrics 
Data Elements 
Report Mockup 
Prototype  Pseudo
Code.
Feature Progression
Strategic Planning
Bring all stakeholders on
same page to
strategically plan and
execute the Feature
Progression to actualize
Program Vision.
Timebound Strategic
Collaboration with
Data team
At each stage make sure
the business side and
data side are aligned.
Help to make sure Data
team delivers the
desired data in right
time.
Dot Connecting | Agile Thinking | Business Problem Solving - Data Driven Consulting
Requirement
Prototyping
Collaboration
Delivering Incremental Benefits Across Each Project Touchpoint

2. Assure Build
Readiness for
Current Release
Identify, enumerate and
define the features
which are ready to be
pulled for build in
current release (Sprint)
Co-create an MVP
(Minimum Viable
Product)
• Provide release specific
specification of
Business Problem 
Metrics  Analytical
Reports Mockup.
• Assure the viability of
above in consultation
with the Data team and
other Stakeholders.
Data Extraction &
Analytics
Manipulations
• Identify the Data
elements desired for
Analytics and
Reporting.
• Provide the extraction
criteria for the above.
• Provide the key Data &
Analytical Manipulation
approach for report
build.
Test Conditions &
Expected Results
• Distill the underlying
logic of the business
solution into agreed
upon Test Conditions
and Expected
Results, TCER.
• Above TCER shall
provide the
framework for
accepting the
product release.
Test Execution & Release
Communication
• Liaise with the Data team to
execute the identified Test
Cases and Register the Pass and
Fail.
• Discuss with Data team and
finalize the desired fixes for the
Fails, get the ETA for the Fix.
• Communicate the Test Results,
desired fixes along with the ETA
across team. (Fixes to be taken
as a Delta Release as per the
ETA).
Co-create and Deliver
with Data Team
At each stage collaborate
with the Data team to
mitigate the Gaps.
Share desired input from
Reporting & Analytics
related information
delivery
Build Readiness Test Co-Create an MVP* Release Acceptance (UAT)
Build
Readiness
MVP
UAT
Dot Connecting | Agile Thinking | Business Problem Solving - Data Driven Consulting
Make Things Happen through Collaborative Execution of Sprints