01 Blogs
Process insights for every industry
The process on paper and the process in practice are rarely the same thing
Writing on process mining, process intelligence and execution visibility — what the terms actually mean, what the numbers look like inside a bank, a plant or a portfolio company, and how to start without a six-month mapping exercise.
02 Start here
The vocabulary, before the argument
Process mining, process intelligence, process observability. The terms get used interchangeably and they are not the same. Start here for the definitions the rest of this writing rests on.
Execution Intelligence: defining the next enterprise capability
How organizations can continuously understand business execution across people, systems, automation, and AI to improve decisions and operational outcomes.
Process mining: how event data reconstructs the way work runs
The technique, its inputs, and the difference between a reconstructed process model and the flowchart it replaces.
Process intelligence: definitions, evidence and implementation
How continuous observation differs from periodic mining, the reported outcome ranges, and dispersion findings from three enterprise deployments.
AI-driven process mining: what models add and what they depend on
Where machine learning genuinely extends process analysis, and why output quality is bounded by the currency of the view beneath it.
03 In your industry
Same method, very different pain
A quality hold on a production line, a loss mitigation request that misses a regulatory window, and a portfolio company whose EBITDA keeps lagging the model are the same problem wearing different clothes. Here is what that looks like up close, sector by sector.
Execution visibility in manufacturing: what plant data shows that dashboards do not
Order flow across ERP, MES, WMS and quality systems, and the delay concentrated in a small minority of escalation paths.
Process observability in loan servicing: evidence-based risk and compliance
Why reconstructing a case timeline after an examiner asks is the expensive path, and what continuous instrumentation replaces it with.
Operational drag in portfolio companies: measuring the EBITDA gap
Hidden execution cost estimated at 15 to 25% of EBITDA, why outcome reporting cannot locate it, and what read-only visibility surfaces.
04 Putting it to work
Method and measurement
On the work itself: how an optimization effort actually runs, what gets decided before the technology is chosen, and when the return really starts.
Business process optimization: methods, measurement and failure modes
The four established frameworks, the six-phase project shape, the metrics that separate improvement from activity, and five recurring failures.
Transformation sequencing: what execution data changes about prioritisation
Prioritisation, automation candidacy and post-go-live drift, treated as measurement problems rather than judgement calls.
Measuring return on process intelligence: discovery, validation, realization
Why the first measurable return is usually a better-directed decision, and how to structure a return claim that survives scrutiny.
05 The common thread
Different subjects, one argument
Whatever the subject, the claim underneath it does not change: you cannot improve, automate or govern a process you have never actually seen run.
Execution data, not opinion
Every figure we publish comes from event data produced by systems already in production, not from a workshop or an interview.
Nothing gets touched
Visibility is built from read-only access to existing logs. No modelling sessions, no changes to live operations.
Living, not retrospective
A model rebuilt quarterly describes a business that no longer exists. A model that updates as work runs is an operating tool.
Start small, prove it
Every piece here lands on the same first move: pick the process that already hurts, and measure it before changing anything.
06 Next steps
See how work actually executes across your enterprise
RE-ViVE reconstructs how work actually executed from the evidence your enterprise already produces, then exposes where time, effort and complexity accumulate.