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A. To serve as a blueprint for development

B. To gain insight into organizational efficiency

C. To prioritize the Program Backlog

D. To add or remove user segments based on business decisions

E. To understand how the flow of value can be improved

A. Total count of items on the Program Backlog

B. Team velocity

C. Cost of delay

D. Business value

E. Duration/job size

A. Continuous Exploration

B. Hypothesize

C. Collaborate and Research

D. Learn

A. Into Continuous Development, where they are implemented in small batches

B. Into Continuous Integration, where they are deployed with feature toggles

C. Into Continuous Integration, where they are then split into Stories

D. Into the Portfolio Backlog, where they are then prioritized

A. It helps operations teams know where to apply emergency fixes

B. It helps quickly create balanced scorecards for stakeholder review

C. It helps link objective production data to the hypothesis being tested

D. It helps define the minimum viable product (MVP)

A. Analyze regression testing results

B. Fix a broken build

C. Roll back a failed deployment

D. Capture usage metrics from a canary release

A. It enables a tolerance for low-risk, low-failure, and rapid recovery

B. It enables low-risk releases and fast recovery with fast fix-forward

C. It enables low-risk releases and fast recovery with no room for errors

D. It enables high-risk releases and fast recovery with fast fix-forward

A. Code commit and release

B. Code commit and user acceptance testing

C. Code commit and stage

D. Code commit and deploy

A. Business value

B. Hypothesize

C. Research and development

D. Alignment

A. Percent Complete and Accurate (%C&A)

B. Active Time

C. Code quality

D. Flow Efficiency