The Productivity Formula

Slide showing SaaS engineering productivity benefits with icons and factors like features, revenue, deploys, developer hours, headcount, and cloud costs.

What you should Expect

A SaaS Engineering Productivity formula generally looks like this. But an AI Engineering Productivity should include:

❋ Total (Output) Value Delivered

Organisation can choose among a few things like number of features, increase of revenue, number of deployments or all of them together.

Product and engineering costs includes:

  1. Team resource costs

  2. Infrastructure costs

  3. (New) AI Tooling costs

❋ Total (Input) Cost
Slide explaining that SaaS engineering productivity equals total value delivered divided by resource cost and headcount, highlighting factors like features, revenue, deploys, infrastructure cost, and AI tooling cost.

  • "Budget Planning and Cost Control: For the same budget, this means cost has to be reduced somewhere else (to pay for new AI Tooling costs)."

    CTO

  • "In early stage of AI Adoption, productivity metric should not be measuring AI Adoption Rate (only)."

    Engineering Manager

  • "How can I free up resources for critical projects (since AI has increased productivity)?"

    CPO

The Transformation Issues

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