Model where AI could save effort, increase capacity, and create reusable ways of working—with assumptions your team can challenge.
Activity alone does not explain value. Bring workflow activity and team assumptions together to compare potential benefits, expose gaps, and decide where to investigate next. The result is an estimate to review, not a claim of realized savings.
Set the activity period, team size, and cost assumptions. Agree what the review needs to inform.
Starts with: a defined scope and business assumptions.
Review the supplied conversation and workflow records. Group the kinds of work being done and flag gaps in the evidence.
Produces: an activity baseline and evidence gaps.
Estimate labor effort avoided, additional capacity, reusable methods, and remaining opportunity. Keep observed activity separate from modeled benefits.
Produces: a scorecard with assumptions and calculation notes.
The business owner reviews the estimates, changes assumptions where needed, and decides which findings are credible enough to use.
People decide: which assumptions and estimates to accept.
Save the reviewed scorecard, its source period, and the next questions to test. Use the same method when reviewing progress.
Produces: an agreed baseline and follow-up priorities.
Estimates depend on the supplied records and agreed assumptions. Usage is evidence of activity, not proof of business value.
Understand intent, knowledge use and working patterns, then act on recommendations to strengthen AI adoption and literacy.
People validate the interpretation, choose the actions and approve what is shared.
Explore workflowBring your process and a sample result. We’ll map the sources, steps, and review points around the way your team works.