Improvement Led By Data
Improvement Led By Data
Inspection and adaptation is a key tenet of the adaptive mindset. Product teams seek to improve the quality of their backlog, the priorities in the backlog and their ways of working by using data to help make objective decisions. Data is obtained by measurement and by seeking feedback from customers and other stakeholders.
Considerations
Product Teams should constantly strive to improve what they are producing and how they are producing it. In the adaptive mindset, there is no concept of perfection - just an understanding that one option is better than another. All data - from measurement and from actively eliciting feedback - is considered when teams inspect their work. The conclusions drawn help teams to choose good options for improvement.
Even if the choice is not dear cut, teams will use experimentation to help it refine their decisions. Experimentation is used to provide new data that help clarify our choice. The adaptive mindset has a bias to action. When choices are not clear cut Product Teams avoid spending too long selecting an option. Rather an option is chosen, quickly as a basis for an experiment. The experiment is measured so future choices are guided by data
Levels
Green
Improvement Priorities Driven By Data
Product Teams consistently use data (from measurement and from feedback) to help inform their priorities for improvement.
Where data does not lead to clear not decisions, teams rapidly choose an option and then routinely frame an experiment. The experiment defines how additional data will be gathered to help refine or change the decision.
Experiments are performed consistently by the teams. Experiments are halted quickly once sufficient data is gathered to prove or disprove the experiments' hypothesis. The results of experiments are used as data to lead further decision making.
Amber
Improvement Priorities Set Inconsistently
Product Teams sometimes use data (from measurement and from feedback) to help inform their pricrelies for improvement where data is available. Decisions are made without recourse to data where the data is not available.
Experimentation is used only rarely to help obtain more data to influence the teams' decision making.
There is no consistent approach to experimentation and experiments sometimes fail because insufficient data is gathered to understand the outcome.
Red
Improvement Priorities Established Without Data
Product Teams routinely make choices about how to improve without recourse to data or to feedback because there is little or no data available to them.
Experiments are not used except in very exceptional circumstances.
Experiments fail regularly because the teams do not collect sufficient appropriate data.