Which methodology is recommended for implementing usage optimization, according to the conclusions?

Which methodology is recommended for implementing usage optimization, according to the conclusions?

• A. Discover, Design, Deliver
• B. Plan, Do, Review
• C. Crawl, Walk, Run
• D. Define, Measure, Improve

Answer: (C)

The concept being tested is applying a staged, iterative approach to implementing usage optimization. Start small, learn fast, and then expand. Crawl, Walk, Run fits this idea perfectly. In the crawl stage you set up the basics: establish baselines, instrument data, and run simple, low-risk experiments to uncover quick wins. In the walk stage you broaden scope: implement more robust experiments, introduce governance and processes, and validate impact across more users. In the run stage you automate and scale the proven optimizations, with continuous monitoring and ongoing improvements across the organization. This progression minimizes risk while building capability and confidence before full-scale deployment. Other options describe different lifecycle approaches that don’t emphasize the deliberate ramp from small to large in usage optimization, so they’re less suited for guiding how to implement optimization in a measured, scalable way.

The concept being tested is applying a staged, iterative approach to implementing usage optimization. Start small, learn fast, and then expand.

Crawl, Walk, Run fits this idea perfectly. In the crawl stage you set up the basics: establish baselines, instrument data, and run simple, low-risk experiments to uncover quick wins. In the walk stage you broaden scope: implement more robust experiments, introduce governance and processes, and validate impact across more users. In the run stage you automate and scale the proven optimizations, with continuous monitoring and ongoing improvements across the organization. This progression minimizes risk while building capability and confidence before full-scale deployment.

Other options describe different lifecycle approaches that don’t emphasize the deliberate ramp from small to large in usage optimization, so they’re less suited for guiding how to implement optimization in a measured, scalable way.