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Summary – Facing opaque processes, workarounds, manual re-entries and hidden bottlenecks, management faces delays, cost overruns and compliance risks. Process mining extracts and normalizes ERP/CRM/TMS event logs to reconstruct actual flows in real time, identify variants, friction points and bottlenecks, and prioritize optimizations for order-to-cash, procure-to-pay, compliance and ERP migrations.
Solution: deploy a data-driven diagnostic as a foundation before any overhaul or automation, ensure standardized process design, accelerate timelines, reduce hidden costs and secure scalability.
Most organizations have only a partial view of their processes: workarounds, unexpected variants, manual re-entries, redundant approvals and personal dependencies remain invisible. Process mining leverages the event logs from your ERP, CRM and line-of-business applications to reconstruct, objectively and exhaustively, the real path each transaction follows. This transparency uncovers bottlenecks, lengthy cycles and hidden costs.
By acting on these insights, you can prioritize optimization initiatives, standardize your flows and anticipate scalability. More than a mere audit, process mining provides the technical foundation essential for any successful digital transformation.
Visualize Your Operational Processes in Real Time
Process mining automatically reconstructs your flows from digital footprints. It delivers an accurate map of existing variants and deviations.
Rebuilding Flows from Event Logs
Process mining extracts and normalizes histories from your systems to create a detailed representation of each step, using data wrangling techniques. Unlike subjective workshops, this approach relies on tamper-proof records from your ERP, CRM or TMS.
Each timestamped event becomes a landmark in the transaction journey, enabling precise identification of the action sequence, the actors involved and the actual duration of each phase.
This automated reconstruction guarantees full fidelity to real operations and eliminates biases from interviews or individual recollections.
Identifying Variants and Deviations
Within a single process, it’s not uncommon to find dozens of different paths. Teams introduce workarounds to overcome obstacles, generating undocumented divergences.
Process mining groups and ranks these variants by frequency and impact, making it easy to detect critical deviations that lengthen cycles and raise error risk.
This granularity lets you prioritize corrective actions by targeting the variants that generate the most cost or delay first.
Transparency on Friction Points and Bottlenecks
By measuring waiting times between activities, process mining highlights organizational and technical blockers, whether it’s an overloaded approval service or an undersized software interface.
These friction points, often hidden in Excel sheets or internal procedures, translate into accumulated delays and non-quality costs.
Cluster visualizations of activities also streamline communication between IT, business units and executive management to define appropriate corrective actions.
Concrete Example
A mid-sized Swiss distributor implemented process mining on its procurement cycle. The analysis revealed that a duplicate manual approval delayed nearly 20% of orders by an average of 48 hours. This insight demonstrated the importance of relying on actual data to eliminate unnecessary steps and accelerate procure-to-pay.
Immediate Benefits and Typical Use Cases
Process mining quickly delivers cost and time savings through a factual view of critical processes. Its main applications cover order-to-cash, procure-to-pay, record-to-report and supply chain.
Optimizing the Order-to-Cash Cycle
In the sales flow, any billing delay or customer dispute directly impacts working capital and cash flow. Process mining pinpoints steps where invoice issuance, dunning or payment posting experience bottlenecks.
By mapping the exact paths of bounced or rejected invoices, you can more easily address root causes: data formatting, ERP integration or manual approval methods.
This data-driven approach reduces collection times and improves inventory turns, without a complete process overhaul.
Improving Procure-to-Pay
From purchase order to supplier payment, many steps remain governed by manual interventions and excessive security checks. Process mining uncovers the number of reminders, receipt anomalies and authorization blockages.
Financial managers can then streamline approval thresholds, automate reconciliations and drastically shorten payment cycles.
This responsiveness with suppliers leads to better purchasing terms and lower financing costs.
Strengthening Compliance and Quality
In regulated industries, detailed traceability of operations is essential. Process mining verifies the actual conformance of processes against target models and legal requirements.
Non-conformities are automatically reported, with transaction details, facilitating both internal and external audits.
Beyond compliance, this traceability helps standardize practices across sites and disseminate the identified best practices.
Concrete Example
A Swiss financial services provider discovered via process mining that 15% of bank reconciliations were manually re-entered three days after close, causing reporting discrepancies. This factual diagnosis cut manual interventions and accelerated monthly close.
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We support companies and organizations in their digital transformation
Integrating Process Mining into Your ERP Projects
Process mining is the indispensable preliminary step before any ERP migration or workflow redesign. It ensures a future design aligned with operational reality.
ERP Migration Readiness
Before transitioning to a new ERP (S/4HANA, D365, Oracle…), it’s essential to understand the actual structure of your processes. Workshops based on theoretical diagrams often omit post-deployment exceptions and adaptations.
Process mining captures these gaps and provides an objective basis to define a standardized future model, while identifying exceptions to retain or reclassify.
This preparation reduces configuration costs, limits surprises during testing and speeds user adoption.
Designing a Reality-Based Process Model
Rather than imposing an ideal flow, process mining informs modeling with historical data. Business constraints and frequent variants are thus considered from the outset of target-model design.
This contextual approach—favoring modular open-source building blocks and selective bespoke development—avoids vendor lock-in and ensures continuous scalability.
The result is an ERP tailored to your specific environment, minimizing post-implementation gaps and maximizing ROI.
Post-Deployment Monitoring and Continuous Improvement
After go-live, process mining remains a continuous monitoring tool. It measures compliance of new processes, quickly detects deviations and validates the projected gains.
By integrating automated alerts, it enables immediate response when a flow degrades or a new variant appears, ensuring proactive governance.
This iterative approach guarantees your ERP stays aligned with business reality and adapts to changes without a full overhaul.
Concrete Example
A mid-sized industrial SME used process mining post-migration to a modular ERP. The post-deployment analysis showed that 10% of orders were still processed manually in a deprecated module. These insights drove a targeted migration effort and accelerated system stabilization.
Complementing BI, BPM and Automation with Process Mining
Process mining differs from BI and BPM while complementing them, and serves as step zero before any RPA or AI initiative.
Process Mining vs. BI: Flows vs. Metrics
BI delivers KPIs and consolidated reports but doesn’t show the exact paths each transaction takes. It indicates an average delay without explaining how or where it actually occurs.
By reconstructing flows, process mining answers those questions precisely and guides BI toward contextualized metrics aligned with real processes.
Coupling BI and process mining enables a granular link between operational performance and financial results through a BI-ERP approach.
Process Mining vs. BPM: Reality vs. Ideal
BPM models a target process often based on business assumptions and an idealized version. It doesn’t reflect local adaptations or operational drifts.
Process mining brings field evidence, enriching BPM with proven variants and prioritizing improvements by frequency and impact.
This complementarity ensures a realistic, pragmatic BPM repository, fostering team buy-in and sustainable optimizations.
Step Zero before RPA and AI
Automating a process without mastering all its nuances often leads to fragile, costly-to-maintain bots. Process mining acts as a preliminary diagnosis, identifying the most repetitive, stable scenarios to automate first.
It maps out the most profitable RPA/AI use cases and defines clear workflows, avoiding unnecessary or incomplete scripts.
Thus, automation becomes a truly cost-effective and sustainable efficiency lever.
Moving to Process Mining: Toward Sustainable Operational Performance
Process mining offers an objective, exhaustive and measurable view of your processes, revealing bottlenecks, costly variants and scalability barriers. It serves as the foundation for continuous optimization, ERP migration readiness and controlled automation. This data-driven approach reduces hidden costs, improves timelines and strengthens compliance, regardless of organization size.
Our experts are available to analyze your event logs, define a contextualized roadmap and support your digital transformation on factual, secure grounds.
