Challenges and Proper Practices for Measuring Software R&D Efficiency

Challenges of R&D Efficiency Measurement – In a volatile and complex internet environment, JD.com launched a digital management strategy to boost organizational performance, making R&D efficiency a key goal. However, defining good R&D efficiency is hard due to poor visibility of processes, arbitrary work segmentation, and parallel agile activities.

Existing Measurement Methods – Current practices rely on clock‑in or work‑hour data, local outputs such as lines of code or defect counts, and agile concepts like story points. These methods suffer from misleading resource utilization signals, encourage wasteful code, and lack comparability across teams.

Correct Approach to R&D Efficiency Measurement – Two core principles are recommended: focus on global metrics rather than local ones, and prioritize result‑oriented outcomes over intermediate work outputs. The proposed metric set is organized into three dimensions: delivery efficiency, delivery quality, and delivery capability, each with concrete indicators (e.g., demand delivery cycle, online defect density, release frequency, release lead time).

Metric Definitions and Implementation – Detailed definitions and calculation logic are provided, and JD.com’s extensive tooling (project management, CI/CD, monitoring, etc.) will be leveraged to collect data and present actionable efficiency insights for teams and managers.

Conclusion – By shifting from resource‑centric to flow‑centric measurement and adopting the outlined metrics, organizations can achieve faster, higher‑quality, and more sustainable delivery of user value, while continuously refining both outcome‑based and process‑level indicators.