Lean Engineering Readiness Scorecard

A practical assessment to understand whether your engineering setup supports speed, quality, and business outcomes.

Engineering organizations today face increasing pressure to deliver faster, operate more reliably, and clearly demonstrate business impact. Many teams have adopted automation, AI-assisted tools, and globally distributed delivery models. However, without clear structure, governance, and alignment, these initiatives often increase complexity instead of improving performance.

This scorecard provides a simple, structured way to assess how well your engineering organization is set up to deliver predictable results. It focuses on how work flows from idea to production, how tools and platforms are used, how teams collaborate across locations, and how leadership steers engineering effort toward business goals.

The questions are intentionally written so they can be answered by both technical and non-technical leaders, based on observable practices rather than detailed technical knowledge. No preparation is required beyond an honest view of how engineering work is currently done.

By completing this assessment, you will gain a clear, shared understanding of your organization's current strengths, gaps, and risks. The results help prioritize improvements, guide investment decisions, and identify where additional focus or support may be required before scaling further.

Scoring Structure

Total Score Range: 0-100

Pillar 1: Delivery Flow & Predictability

How reliably engineering work moves from idea to production.

We have a clear view of how long it takes for engineering work to go from start to production.

Rate 1-5:

Software changes are released frequently in small increments, rather than large, infrequent releases.

Rate 1-5:

When incidents occur, we review causes and improvement actions, not just fix the immediate issue.

Rate 1-5:

Engineering teams can deliver urgent fixes quickly without disrupting ongoing work.

Rate 1-5:

Pillar 2: Use of Automation & AI in Engineering

How tools are used to reduce manual effort and improve consistency.

Automated testing and build processes are in place and run by default, not optionally.

Rate 1-5:

AI-assisted tools (e.g. code generation, testing, documentation) are used in a controlled and approved way.

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We review whether automation or AI actually saves time or reduces errors, rather than assuming benefits.

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Engineers spend more time solving problems than handling manual setup or repetitive tasks.

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Pillar 3: Engineering Platform & Technical Foundations

How easy it is for teams to build, deploy, and operate systems consistently.

Teams use standard ways to build and deploy software, rather than inventing their own approaches.

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Setting up a new service or environment is predictable and repeatable, not dependent on specific individuals.

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Security and compliance requirements are built into engineering workflows, not added later.

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Engineering teams have clear ownership and support for shared platforms and tooling.

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Pillar 4: Global Collaboration & Right-Shoring

How work is distributed across teams and locations.

Engineering work is assigned based on capability and risk, not just cost or availability.

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Teams across locations have clear responsibilities and handover rules.

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Time zone differences are actively managed for critical work and decision-making.

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Access to systems and data is controlled according to role and location.

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Pillar 5: Governance, Outcomes & Improvement

How leadership steers engineering toward business outcomes.

Engineering priorities are clearly linked to business goals, such as revenue, reliability, or efficiency.

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Leadership regularly reviews delivery performance and risks, not just project status.

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Decisions about speed, quality, and cost are explicit trade-offs, not accidental outcomes.

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Time and budget are intentionally allocated to improve engineering processes and reduce future risk.

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