Lean and waste analysis
Quantify how much of a process's effort is genuinely removable, step by step.
— Operations & Process
Classifies each process step as value-add or waste, quantifies removable effort, charts the stream, and writes a savings case with quick wins.
1 week → ~10 minutes
For a full population, not a sample
No coding required
— USE CASES
Quantify how much of a process's effort is genuinely removable, step by step.
Convert a step table into a numbers-backed argument for change.
Identify the smallest changes that release the most effort first.
— HOW IT BEHAVES
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Every row of your table is processed on the same basis, however long the table is.
The pattern is visualised from the computed data, so the trend is legible at a glance.
Findings are written up as a document that reads like professional output rather than raw model text.
Each row gains derived columns from the analysis, keeping the source data and the judgement side by side.
Load a table of process steps with time or effort per step. Lean and waste analysis is the typical trigger — quantify how much of a process's effort is genuinely removable, step by step. Get it right and the conclusion holds up in the room; get it rushed and it gets picked apart. Either way it costs roughly 1 week of experienced attention.
Here the same job runs as a Skill. Your material goes in; value-add / non-value-add classification per step with waste type comes out, alongside a step-by-step chart of the stream. What sits between input and output is the codified method: thresholds, sequencing and the points where a human confirms a call — all of it visible and editable in the Skill. The practical effect: 1 week of manual work becomes a ~10 minutes run, held to an identical standard on the tenth engagement as on the first.
Value-stream / waste analysis exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
Automation opportunity map
Maps team or function activities to automation potential, computing addressable effort and bucketing opportunities into a prioritised roadmap.
Control failure → incident RCA pattern engine
Joins control test results to incident logs by process to show where control failures are actually producing incidents, grouped by systemic weakness with residual risk quantified.
Process diagnostic
Inventories every process step with its owner, system, effort and wait time, tests each against bottleneck, duplication, handoff and control-gap lenses, and returns a prioritised 30/60/90 improvement backlog.