Practical Use Cases of Process Mining

Process mining supports continuous improvement across the organisation and is a vital part of modern business development.

Instead of asking "How is our process supposed to work?", process mining asks "How did the process really proceed in every single case?" By making system event data visible, process mining helps organisations uncover the real flow of operations and offers a fact based view into what's really happening behind the scenes.

Why is process mining relevant right now?

In recent years, process mining has become one of the most powerful tools for organisational development.

Digitalisation has led to massive volumes of data being generated from processes, but making full use of that data requires new methods. Process mining enables organisations to analyze and improve their operations based on facts rather than assumptions or theoretical models. This allows companies to quickly identify improvement opportunities and target their efforts where they will have the greatest impact.

Process mining helps organisations across industries make the most of their data, improve operational efficiency, and boost performance. It has become a key part of the modern company’s toolkit, especially for those aiming for continuous improvement and stronger competitiveness.

Process Mining in a nutshell: what is it?

Process mining leverages transactional data generated by an organisation’s information systems.

In practice, this means reconstructing and visualizing the real paths that processes take - directly from the data - creating a “digital twin” of the process. This gives companies an entirely new, fact-based perspective on process performance.

It helps identify where bottlenecks, exceptions, or delays occur and reveals the root causes behind current challenges. This makes it possible to focus development resources on the areas with the most significant business and time impact.

In other words, process mining enables continuous process improvement and a new level of operational efficiency.

What data do you need for Process Mining?

To successfully conduct process mining, you need detailed and high-quality data on how your processes actually function. This data can be pulled from ERP systems, CRM platforms, ticketing systems - or practically any system that records process-related events.

The data must be precise enough to highlight key steps and exceptions within the process. In addition, contextual data is crucial: relationships between events and dependencies between different parts of the process must be captured in order to generate accurate analysis. This level of insight allows you to truly dig into process development and uncover impactful improvement areas.

The five key phases of Process Mining

Process mining typically follows five steps to ensure effective and impactful development:

1. Data integration: Pull together process data from all relevant systems
2. Process discovery: Automatically generated visualisations reveal how processes really unfold in practice
3. Root cause analysis: Deep analysis identifies the underlying reasons behind process challenges and bottlenecks
4. Automation targeting: Based on the analysis, you get a prioritised list of automation oppportunities, along with the right order to tackle them for maximum impact
5. Performance prediction: With performance metrics tracked and forecasted, process mining enables you to address issues proactively, not just reactively

This step-by-step approach helps organisations evolve and automate their operations with clarity and precision.

The moment of truth in finance: What does the purchase ledger really looks like?

One of the clearest use cases for process mining is in financial management, particularly in accounts payable.

On paper, the process might look linear: invoice received, reviewed, approved, and paid. In practice, the event flow is anything but straightforward. That’s exactly where process mining shines.

A concrete example comes from Cervi, a company specializing in ventilation solutions. Cervi uses Greenstep’s services extensively for accounting, payroll, group reporting, and BI reporting. In late 2023, Cervi launched a process mining project focused on accounts payable, aiming to uncover manual workloads and improvement opportunities based on data.

“In the fall, I noticed that our accounts payable included several manual processes that consumed a significant amount of work time. We began the process mining project with the goal of improving efficiency and achieving cost savings,” says Sami Karppi, CFO at Cervi.

The mining revealed exactly where delays occurred, how payment terms were handled in reality, and the extent to which automation was- or wasn’t - being used. The findings were eye-opening: the data revealed supplier-specific and invoice-specific exceptions that had never been detected before. The development work got underway quickly, since the rationale for action was embedded in system data.

Karppi describes process mining as the foundation for efficient business operations: it helps the organization identify pain points in everyday work and eliminate unnecessary steps. And the results weren’t just buried in reports: they led to real, concrete improvements.

Going beyond metrics in customer service

In customer service, measuring success only by response time doesn’t tell the whole story. Often, the more important questions are:

• How many times did the customer have to reach out?
• How many tickets were escalated to multiple customer service agents?
• How many exceeded SLA even though the system didn't flag it?

A common finding is that some customers need to contact support multiple times for the same issue. This may be because the initial contact didn’t reach the right expert, or because the issue was only partially resolved. With process mining, you can identify these repeated contacts and pinpoint exactly where the customer journey breaks or gets complicated.

Another typical discovery is the so-called “ping-pong” effect, where a ticket bounces between multiple agents before resolution. This branching adds to resolution time, consumes team resources, and worsens the customer experience - even when the system reports the case as resolved on time.

By mapping out the full chain of customer interaction, process mining gives customer service teams a whole new level of understanding. Alongside metrics, you gain insight into the how and why, so you can spot friction points and actively remove them.

Revealing hidden bottlenecks in logistics and supply chains

In logistics, even small delays can quickly become costly. Processes are tightly connected, and a hiccup in one area can disrupt the entire supply chain.

Process mining helps uncover:

• Bottlenecks
• Incorrect handling
• Stalled phases

All based purely on system event data.

A typical use case is urgent deliveries. Even when a delivery is marked as urgent in the system, it may not be prioritized in the warehouse or production workflow, if the flag isn’t part of the operational view. As a result, a critical order may be handled at normal pace and only noticed after customer dissatisfaction.

Another common issue involves outdated product information. If an order process relies on incorrect data (e.g. inventory levels, delivery options), it can trigger mismatched warehouse cycles, causing rework and production delays that go unnoticed unless the process is examined through data.

That’s where process mining proves its strength in logistics: it makes visible those hidden exceptions and slowdowns that silently add up. With systematic analysis, you gain solid grounds to adjust steering logic, automate alerts, or reallocate resources. The outcome is a smoother supply chain, better compliance, and often a more satisfied customer.

Using Process Mining to improve IT and ERP systems

Process mining also plays a major role in developing IT and ERP systems.

With it, organisations can continuously monitor performance and identify improvement areas quickly. Process mining supports intelligent automation, data governance and change management, based on real-life process data.

It also helps with system implementations and migrations by ensuring that processes function as planned during transitions. This helps reduce maintenance, development and support costs, and ensures that processes remain effective and up to date.

Ultimately, process mining makes ERP and IT development more data-driven, efficient and impactful.

Where else can Process Mining be used?

Process mining can be applied to practically any data-driven process.

It provides deeper insights into how internal processes really work, thus enabling better understanding and smarter development.

For example:

• In recruitment, it helps measure time-to-hire and identify where candidates drop-off occurs
• In IT service management, it reveals why certain support requests generate repeat tickets or remain unresolved
• In sales, process mining can show why offers stall, especially when multiple systems, CRMs and personal sales habits are involved

Across all functions, process mining supports performance improvement by offering precise data on bottlenecks and opportunities for smarter workflows.

Greenstep as your Process Mining partner

At Greenstep, we don’t just provide technology. We help you interpret what the data reveals; why it looks the way it does, and what actions it calls for.

You’ll get expert support at every stage of the journey. Our team combines process mining experts, data analysts, and finance or business-minded developers who speak your language.

We’ve supported projects that have reimagined entire accounts payable functions, optimised customer service workflows, and standardised internal group processes. Process mining becomes a powerful management tool that enables smarter decisions and strategic development.

Our goal isn’t just visibility. It’s measurable, lasting change in time savings, cost reduction, and improved customer satisfaction.

Want to see how your processes really work?

Process mining doesn't replace people. It gives you the facts you need to make bold, informed decisions. If you'd like to see what your processes actually look like in practice, get in touch. Let's find out where to start.