Data @ the core of Enterprise Agile

Mathew AniyanProgram Manager, Microsoft

Abstract

• Agile adopts an empirical approach to software development. One of the key aspects of a successful Agile Implementation is how quickly we can react to change. For this, we need to ensure that data flows seamlessly from customer to the Agile team. This data should form a critical part of our decision making.• Is the customer successful in using our product or service?• Which features are customer most interested in?• Where are the friction points in usage?• Where are the failures happening in our product?• How is the customer engaging with our product over time?• and many more similar questions.

• In this talk, I discuss best practices in data collection, analysis and visualization and how data can make your Agile process and thereby your business more effective.

Agile Manifesto - http://www.agilemanifesto.org/

Principles behind the Agile Manifesto• Welcome changing requirements, even late in development. Agile

processes harness change for the customer's competitive advantage.

• At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly.

Data as the lifeblood of Agile

• Helps understand changing requirements• Measures progress against goals

Before we start: Privacy

• Classify your data• Seek customer permission• Security• Who can access?• How to secure?

• Err on the side of caution

Design your data

Start with the Business Questions

How will you visualize the data?

What decision will you make?

A Sample Business QuestionDemo

Data Collection Infrastructure

Hot PathDemo

Warm PathDemo

Cold PathDemo

SurveysA sample questionnaire

Analysis – Per Incident

• Root Cause Analysis• 5 Whys

Analysis – Per Day

• Daily trends• Operational

Analysis – Per Week

• Operational• Learning focused

September 7

Monday Tuesday Wednesday Thursday Friday Saturday Sunday

8 9 10 11 12 13

14 15 16 17 18 19 20

9/8/2015 - 9/15/2015

Mean Time

• To Detect• To Fix• Between Failures

Analysis – Per Month

• Business focused• Experiments

Machine Learning

• K-Means clustering

Visualization Samples

Availability

Usage Funnels

Map Visualizations

Cohorts

Flow Diagrams

TreeMap

Animated Bubble ChartsDemo

Tables with Sparklines

Summary

• Use data to drive your decisions• Plan your data• Develop the right data collection infrastructure• Analyze at needed• Use visualizations to communicate with data effectively