Three metrics. Eight diagnostic patterns. One framework that turns process mining from a one-off project into a repeatable discipline for every process, every application, and every investment decision.
How much of your process runs through the system versus around it? DWR quantifies off-system work: the email approvals, personal spreadsheets, and workarounds that are invisible, uncontrolled, and expensive.
The fully-loaded cost to process one invoice, one purchase order, one hire. CTS connects operational performance directly to financial outcomes in a language CFOs speak.
A purchase requisition takes 12 days but only 4 hours is actual processing. CTE exposes this: typically 90–95% of process time is non-value-added. A process design problem with direct working capital implications.
One Language
Portfolio Process Mining gives every executive the same conversation. No more finance talking budgets while IT talks technical debt and operations talks headcount.
Diagnostic Patterns
Three binary states (high or low) across three metrics produce eight distinct diagnostic patterns. Each demands a fundamentally different intervention. The matrix prevents the most common mistake: applying the wrong fix to 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.
Best-in-class. System is used, cost is competitive, cycle time is efficient. Document as reference model and roll 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 high-value process. Establish the measurement standard. Then apply the same three metrics and methodology across the entire portfolio.
Measure DWR, CTS, CTE 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: all three metrics, eight diagnostic patterns, intervention examples, and the continuous improvement methodology.
Select 2–3 high-value processes. We extract event logs, validate data quality, and calculate DWR, CTS, and CTE. Two to four weeks. Fixed fee. Quantified improvement roadmap.