Adopting EEBO Metrics

Stage 1: Model your metrics

In this stage, the focus is on modeling the EEBO Metrics for of your program. You will utilize the concept of Fully Modeled Metrics to establish Engineering Excellence Metrics. Then you will to identify Business Outcome Metrics based on the key outcome expectations from various stakeholders, including Customers, Users, Partners, and Organizational Leadership. These expectations play a crucial role in determining which metrics are most suitable for tracking alignment between product outcomes and stakeholder expectations. Among the identified metrics, Fitness Metrics will be singled out, and a voting process will be employed to prioritize the Business Outcome Metrics. Lastly, Business Outcome Metrics will be further developed using the Fully Modeled Metrics concept.

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Stage 2: Establish Correlation

This stage highlights the importance of EEBO Metrics in assessing team performance holistically. The methods used underscore the significance of measuring performance against team-agreed goals and tracking deviations over time for meaningful correlation analysis.

EEBO Metrics promote the evaluation of teams as a whole rather than focusing on individual performances. However, assessing a team's effectiveness or comparing one team to another can be complex, particularly when dealing with seven different metrics, each with its own unique calculation method.

The EEBO framework emphasizes the importance of measuring performance against team-agreed goals rather than fixed numerical targets. This approach aligns with the concept of a fully modeled metric and allows for flexibility as goals may vary among teams depending on the specific product being developed.

To implement this, teams should calculate the deviation of each metric from its respective success marker. Ideally, these deviations should trend towards zero, indicating that teams are making progress towards their goals.

Teams can use any suitable method to standardize these deviations and calculate the average across the deviations of the seven key metrics for Engineering Excellence. This will provide a score indicating where the team stands at present. As the team continues to improve, this deviation score should approach zero.

Similarly, teams can apply the same method to normalize deviations and calculate the average across the deviations of key metrics across the four categories of business outcomes to assess how closely the product aligns with business expectations. Again, as the team makes progress, this deviation score should trend towards zero.

Monitoring these two scores over time can reveal trends that can be analyzed for correlation and provide valuable insights for improvement.

Stage 3: Dashboard Your EEBO Metrics

We've noticed the use of various tools, including simple options like Excel or Google Sheets for quick starts, as well as more advanced integrated dashboards like PowerBI or Tableau. Additionally, we've come across customized versions of Hygieia. Consulting assets like Thoughtworks Polaris have proven to be valuable resources for Thoughtworks in their client engagements.

Stage 4: Monitor & Remediate

Effectively Addressing Underperformance in Slow-Moving Metrics

Unlike stock tickers, these metrics change slowly, typically during the end of sprints, product releases, or transformation programs. Therefore, monitoring should account for these longer timeframes.

Metrics may sometimes underperform. Reacting hastily with ad hoc solutions often proves ineffective and can exacerbate problems. To address underperforming metrics effectively, it is crucial to establish clear remediation plans. These plans should detail specific steps and strategies for implementation when metrics dip below acceptable levels. A systematic approach to remediation enables organizations to foster continuous improvement and attain improved outcomes.