))
S4 E27 - Dr. Bill Bellows - Bridging Deming, DevOps, and the Power of Systems Thinking Part 1
Manage episode 456630567 series 3568163
Content provided by John Willis. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by John Willis or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
In this episode, I engage with Dr. Bill Bellows in a deep dive into the application of W. Edwards Deming’s systems thinking in software development and DevOps. Dr. Bellows, a veteran in quality management and an expert in Deming’s principles, shares insights on variation, Taguchi loss functions, and the synthesis of parts in a system to highlight gaps in current industry metrics like DORA.
Key Topics:
- Misconceptions About Managing Parts vs. Systems:
- Dr. Bellows references Russell Ackoff’s assertion that managing individual parts optimally doesn’t guarantee an effective system. He relates this to the tendency in software and manufacturing to assess components in isolation rather than as part of a larger system.
- The Role of Variation in Quality:
- Building on Shewhart’s work, Dr. Bellows explains how statistical process control examines stability and variation within components. Taguchi’s insights are introduced to show how variation in individual parts impacts the whole system's functionality.
- Applying Taguchi to Modern Metrics:
- The conversation examines how DORA metrics, such as deployment frequency and mean time to recovery, serve as output measures but fail to address the underlying inputs driving these metrics. Dr. Bellows highlights the importance of understanding "failure" through operational definitions and its nuanced variations.
- Systems Thinking in Feedback Loops:
- Emphasizing tighter feedback loops, Dr. Bellows ties traditional Deming concepts to the promise of continuous improvement in DevOps. He advocates for a systemic view, where the interplay of individual variances contributes to collective outcomes.
Key Insights:
- Systems must be analyzed holistically to manage complexity and leverage opportunities effectively.
- Outputs like DORA metrics should inform adjustments to input characteristics rather than serve as the sole focus.
- Precision in defining failure and understanding its economic implications is critical to refining processes and delivering value.
85 episodes
Share
