Automate the right work first.
Workshops, task mining and process mining combine into a scored, costed automation pipeline that finance and operations can both stand behind.
Pipelines built on guesswork stall.
Automation pipelines are often assembled from whoever asked loudest. The result is bots for processes with too many exceptions, too little volume or a system replacement due next year. Benefits miss forecast and confidence in the programme drops.
Discovery fixes the input. We combine what people say about a process with what systems and desktops show actually happens. Each candidate is scored on the same model for volume, rule clarity, input structure, stability and exception rate, then costed so the business case holds up to scrutiny.
Event logs and desktop data reveal the real variants, rework loops and handling times.
Every candidate is assessed against the same weighted criteria, so priorities are defensible.
Build effort, licences, run costs and residual manual work are all counted.
We flag steps to eliminate or simplify before anyone writes a bot.
Outputs you can fund and build from.
Discovery workshops
Structured sessions with process owners and practitioners to map steps, systems, hand-offs, volumes and pain points.
01Task mining
Consented desktop recording on a sample of users to measure keystroke-level effort, application switching and repeat patterns.
02Process mining
Event-log extraction from ERP, CRM and ticketing systems to reconstruct real process flows, variants and bottlenecks.
03Automation scoring model
A weighted assessment of feasibility and value for every candidate, tuned to your systems and priorities.
04Business case
Effort, licences, infrastructure and support costs set against hours released, error reduction and cycle-time gains.
05Prioritised pipeline
A sequenced backlog of quick wins, strategic builds and fix-first items, ready for PDD and delivery planning.
06Four to eight weeks to a funded pipeline.
Frame the scope
We agree the functions in scope, the systems that hold event data, the teams for task mining and the criteria that matter most to sponsors.
Gather evidence
Workshops run in parallel with task mining and event-log extraction. Privacy settings mask personal data and exclude non-work applications.
Analyse and score
We reconcile workshop maps with mined data, quantify variants and exceptions, and score each candidate on the agreed model.
Build the business case
For the top candidates we estimate build effort by complexity tier and calculate payback with run costs included.
Present the roadmap
Sponsors get a sequenced pipeline, the recommended platform and CoE implications, and the first wave ready for design.
Discovery tools we use.
Task mining
Process mining
Source systems
Analysis
What discovery typically gives sponsors.
Time to pipeline
A ranked, costed backlog is ready in weeks instead of quarters of debate.
Priorities
Every candidate has a score and a reason, so trade-offs are transparent.
Failed builds
Processes with unstable rules or systems are filtered out before money is spent.
Business case
Benefits rest on measured volumes and handling times instead of estimates.
Is task mining intrusive for employees?
It runs only with consent, on a defined group, for a defined window. Personal data is masked, non-work applications are excluded, and we share the configuration with HR and works councils where required.
Do we need a process mining licence for this?
Not always. For a first assessment we can extract event logs and analyse them directly. If you plan continuous monitoring, a platform licence usually pays for itself.
What goes into the automation scoring model?
Typical criteria are volume, frequency, rule clarity, input structure, number of applications, system stability, exception rate and business criticality. We weight them with your sponsors.
Will you recommend a platform?
Yes, if you have not chosen one. The recommendation follows from your systems, IT standards, existing licences and the mix of RPA, IDP and AI work in the pipeline.
Find your first ten automations in two weeks.
A structured discovery sprint that maps your processes, scores them for automation potential and hands you a prioritised roadmap with effort and payback for each.