If You Cannot Measure Productivity Before Gen AI, You Cannot Measure It After
Organizations are deploying Gen AI to increase productivity without having defined what productivity means in their context. The measurement gap will undermine the investment.
Three Takeaways
- 1
Productivity is not hours saved. It is value created relative to resources invested.
- 2
Most organizations measure activity, not output. Gen AI accelerates activity.
- 3
The organizations that will demonstrate Gen AI ROI are the ones that defined their productivity baseline first.
One of the underdiscussed problems in Gen AI adoption is the measurement problem. Organizations are investing in Gen AI to increase productivity. Most cannot define what productivity means in their specific context.
This is not a new problem. Gen AI is just making it urgent.
The Activity vs. Output Problem
Most organizational productivity measurement tracks activity. Calls made. Emails sent. Reports produced. Meetings attended. These are activity metrics.
Gen AI can accelerate activity dramatically. A Gen AI tool can produce a first draft of a report in minutes that would have taken a human hours. This looks like productivity improvement. It may not be.
The relevant question is: Does the report drive better decisions? That is an output question. Most organizations cannot answer it.
Why the Baseline Matters
To measure whether Gen AI improved productivity, you need a productivity baseline. Most organizations do not have one at the level of specificity required.
They know headcount. They know output volumes. They do not know the relationship between specific workforce activities and business outcomes.
Without this baseline, Gen AI adoption will produce compelling activity metrics and unclear business impact. Leadership will ask: Where is the ROI? The organization will not be able to answer with confidence.
Building the Measurement Infrastructure
The organizations that will demonstrate Gen AI ROI are building measurement infrastructure before or alongside deployment. This means defining what productivity means for each role, establishing baselines for that measure, and building the data infrastructure to track change.
This is an operating model investment, not a technology investment.
The Implication
Gen AI will accelerate whatever your organization is already doing. If you cannot measure the value of what you are doing today, you will not be able to measure the value of Gen AI.
Fix the measurement problem first.
*Informed by KPMG, "HR holds the keys to creating value from generative AI," 2024*
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Disclaimer: The views and opinions expressed in this article are for informational purposes only and do not constitute professional advice. Readers should consult with qualified professionals before making any decisions based on this content.
About GeneralArc
GeneralArc is operating model architecture for the AI transition. Its methodology was built across more than two decades inside the operating models of JPMorgan Chase, McKinsey & Company, Nomura, and Deutsche Bank — leading change across 100,000+ employees.
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