Where Process Mining delivers

Process Mining provies the X-ray of how work really flows across ERP, CRM and workflow systems. But insight alone won’t reduce cycle time, cut leakage, or tame compliance risk. The organisations that win treat Process Mining as a product with owners, SLAs and a roadmap. Not a one-off analytics exercise. Here’s how to make it real.

Use Case Benefit Assessment

Choosing the first use case sets your momentum. Intellifold’s Use Case Benefit Assessment scores candidates by:

• Value leakage: process related cost, time, revenue at risk
• Risk exposure: compliance, audit findings, policy breaches
• Data readiness: quality and availability of activity logs
• Stakeholder pain: a motivated owner who wants it fixed
• Automation potential: Repetitive high-volume steps ready to automate
• Time to delvier value: where can improvements be realised quickly

Start with objectives and pain points

Before touching data, state the key objective in one sentence and list the pain points sourced from stakeholders. Then sketch a wireframe: a simple mock-up of the target solution (process flows, KPIs, dashboards). A wireframe creates a shared vision so development and end-users speak the same language from day one.

A playbook for successful delivery typically involves steps like:

• Discover & Assess: Understand the process and its unique aspects, the key process challenges, regulatory and compliance requirements, and how to best measure the success of the process and improvement outcomes. Also confirm data ownership, stakeholders, and who makes the decisions.
• Implement & Deliver: Connect to relevant source systems (API, database, warehouse etc.), develop the MVP solution to gather feedback. Refine based on feedback from users and workshop sessions, and enable live data feeds.
• Support & Improve: It doesn't stop after roll-out. Implement the processes for change, the action workflow and alerts for continuous monitoring. End-user and technical, and consultancy services to help optimise your processes. And very importantly, how to track impact and ROI of improvement and process automation initiatives.

Intellifold implementation steps

Working as one team (data, continuous improvement, process owners)

For success it's essential for relevant teams to be aligned and worj towards shared goals. These disciplines are complementary, not competing:

• Process owners carry the authority to change steps, policies and tools.
• Data & analytics delivers and maintains the solution, governed metrics and reliability.
• Lean/Six Sigma provide problem framing (DMAIC), change discipline, and stakeholder buy-in.
• Technology take ownership for access, data pipelines, and changes.

Centre of Excellence

We've helped companies create Centres of Excellence (CoE) responsible for process improvement and for process insight & analytics. The setup of such functions can really drive the uptake of technology and becoming more data driven. The aim is continuously improving insight, adoption, and improvement actions.

Operating model: Core team with CoE Lead, Product Owner, Data Engineers, Process Mining Analysts, Continuous Improvement Lead.

Intake & prioritisation: Intake based on Use Case Benefit Assessment and prioritise by value, risk and readiness. Have a transparent backlog and roadmap.

Engineering standards: Leverage reusable connectors, establish naming conventions, privacy/access controls. A clear definition of 'Done' with validated data quality, signed-off KPI logic, documentation, and monitoring.

Service management: Create SLAs for refresh frequency, alert latency and incident response. Have pipeline observability and clear change controls and communication.

Does & Don't

• Do: Clearly defined process use case with supportive process owner.
• Do: Involve key users from the start to create ambasidors for the solution.
• Do: Start with the process steps everyone understands before adding further detail.
• Do: Limit the number and complexity of KPIs, but have everyone aligned on how they are measured.
• Do: Define ROI measures at the beginning and measure impact from the start.
• Do: Implement alerts only where essential and make sure personnel and escalation paths are defined.
• Don't: Implement a solution without clear data ownership and ways to address gaps and quality issues.
• Don't: Gold-plated dashboards that include everyone's wishes without clarity on what actions are expected.
• Don't: Select a process that isn't stable, where execution depends on external factors, or actions can'tbe owned.

Where to start

• Run a Use Case Benefit Assessment across a few key processes.
• Select a process with high value, clear improvement opportunities, and a higher level of standardisation.
• Document objectives, pain points to address, KPIs to measure, and wireframe dashboards.
• Define roles and involvement of technology, data, process improvement, and business stakeholders
• Work with clear project phases (MVP, tailoring, continuous monitoring) and validation points
• Track progress and results and share with leaders and stakeholders.