a·gen·tic a·gil·i·ty

Engineering Excellence in Action: How NKD Agility Helped SLB Streamline Build and Release Across 90 Teams and 13 Countries

NKD Agility helped SLB unify build and release processes across 90 teams in 13 countries, boosting team ownership, efficiency, and engineering accountability.

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Client Context

SLB (formerly Schlumberger), a global energy technology company, had over 90 engineering teams in 13 locations across 9 countries contributing to a single product: Petrel. Each team operated independently, choosing its own source control system, build environment, and branching strategy. Some used Git, others Team Foundation Version Control (TFVC), SVN, or even in-house tools.

The result? A sprawling mess of incompatibilities, blind spots, and inefficiencies.

The Ask: Build System Simplification and Consolidation

Martin Hinshelwood from NKD Agility was asked to assess the situation and recommend a path forward. The goal: consolidate build and source control processes to enable faster, more reliable, and more autonomous development.

Diagnosis: Extreme Fragmentation and Build Fragility

Martin’s assessment uncovered:

Approach: Advisory Engagement Rooted in Engineering Principles

Martin didn’t implement the solution directly. Instead, he provided:

Outcomes: Ownership, Speed, and Significant Cost Reduction

Strategic Reflection: Engineering Excellence Through Real Ownership

This case represents a core NKD Agility principle:

Real engineering excellence isn’t about tighter control—it’s about giving teams the right structure so they can take responsibility for quality, speed, and stability.

Martin’s advice helped SLB do just that: reframe build and release as team-owned practices rather than operational burdens.

Why It Matters for CTOs and Tech Leaders

Final Takeaway

When engineers own the system they work in, magic happens. NKD Agility helps organizations create the clarity, structure, and culture where that ownership can thrive.

Smart Classifications

Each classification [Concepts, Categories, & Tags] was assigned using AI-powered semantic analysis and scored across relevance, depth, and alignment. Final decisions? Still human. Always traceable. Hover to see how it applies.

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