Make Data-Driven Decision-Making a Core Engineering Habit

This standard mandates the integration of data-driven decision-making into core engineering practices.

1. Make Data-Driven Decision-Making a Core Engineering Habit:

Engineers must be trained and empowered to use data in their decision-making process. This approach ensures informed and effective decision-making.

• 1.1 Championing a Data-First Mindset:
  • 1.1.1 Leadership Advocacy:
    • Encourage engineering leaders to champion a data-first mindset.
    • Promote the use of data in all decision-making processes.
  • 1.1.2 Data Literacy:
    • Provide training and resources to improve data literacy among engineering teams.
    • Foster a culture of data-driven problem-solving.
• 1.2 Data Training and Tooling:
  • 1.2.1 Data Analysis Tools:
    • Provide training and tools to help teams interpret and use data effectively.
    • Automate the setup and configuration of data analysis tools.
  • 1.2.2 Data Visualization Training:
    • Provide training on data visualization best practices.
    • Automate the generation of data visualizations.
• 1.3 Data-Driven Discussions:
  • 1.3.1 Sprint Planning Integration:
    • Integrate data-driven discussions into sprint planning sessions.
    • Use data to inform sprint goals and priorities.
  • 1.3.2 Retrospective Analysis:
    • Use data to analyze sprint performance and identify areas for improvement during retrospectives.
    • Automate the generation of retrospective reports.
  • 1.3.3 Incident Reviews:
    • Use data to analyze incidents and identify root causes.
    • Automate the generation of incident review reports.

By making data-driven decision-making a core engineering habit, organisations can ensure informed and effective decision-making.