Four metrics. Eight patterns. One framework that works the same way for every process, every application, and every investment decision. Not a one-off project. A discipline.
How much of the work runs through the system, and how much around it. DWR counts the off-system work: email approvals, personal spreadsheets, workarounds. Invisible, uncontrolled, expensive.
The fully loaded cost of one invoice, one purchase order, one hire. CTS puts operations in the language your CFO already speaks.
A purchase requisition takes 12 days. The actual work takes 4 hours. CTE exposes the gap: typically 90–95% of process time is waiting, not work. That gap ties up your working capital.
The quality gate. FTR shows how much work gets done twice — the corrected invoice, the re-run requisition, the second-pass approval. Below 75%, quality is being checked too late. It matters most when an agent runs the process at machine speed.
One language
Four metrics, one conversation. No more finance talking budgets while IT talks technical debt and operations talks headcount.
High or low on DWR, CTS and CTE gives eight patterns in four quadrants, each with a matched intervention. FTR flags quality risk across all of them.
Diagnostic patterns
The four metrics combine into eight diagnostic patterns. Each needs a different intervention. The matrix stops the most common mistake: the wrong fix on the right problem.
Process is broken. Fundamental re-engineering needed before any system investment. Don't automate a mess.
System works but it's expensive. Simplify, then automate. RPA and intelligent automation after complexity is removed.
The workaround might be better than the system. Investigate before forcing adoption. Evaluate shadow IT rationally.
Good shape. Protect and scale. Use as the internal benchmark. Fine-tune for marginal gains.
The reference model. System is used, cost is competitive, cycle time is efficient. Document it and roll it out to other regions.
System is used and cost-effective, but elapsed time is dominated by waiting. Approval chains, batch jobs, or handoff delays are the bottleneck.
Over-engineered. People use the system and it moves fast, but too many steps, controls, or approval layers make it expensive. Strip back to the happy path.
System is used but poorly designed. Expensive and slow. Redesign the process first, then automate. Eliminate rework loops and unnecessary handoffs.
People work off-system but found a way to do it cheaply and fast. The workaround may actually be better than the system. Investigate before intervening.
Off-system, slow, but cheap. Under-invested and possibly low-volume. Assess criticality first. If volume is growing, intervene. Otherwise, leave it.
Skilled people doing manual work fast but expensively. They bypass the system because they're faster without it. Fix UX barriers that drove people away.
Everything is broken. Off-system, expensive, and slow. Highest-priority intervention. Don't optimise; rebuild. Challenge whether the application is fit for purpose.
Scale
Start with one process that matters. Set the measurement standard. Then run the same four metrics across the whole portfolio.
Measure DWR, CTS, CTE, FTR for 2–3 target processes. Two-week sprint.
Compare to APQC/Hackett benchmarks. Set realistic 90-day and 12-month targets.
Every intervention answers one question: which metric does this improve, and by how much?
Continuous metric updates from event logs. If metrics don't move, the intervention didn't work.
Roll the same framework to the next process, the next business unit, the next region.
POs, invoices, GR matching
Sales, delivery, billing, collections
Journals, reconciliation, close
Onboarding, transfers, separations
Master data, runs, corrections, costing
The complete Portfolio Process Mining paper: four metrics, eight diagnostic patterns, intervention examples, and the continuous improvement method.
Pick 2–3 high-value processes. We extract the event logs, validate data quality, and calculate DWR, CTS, CTE and FTR. Two to four weeks. Fixed fee. A quantified improvement roadmap.