Connecting Finance and Non-Financial Performance Through Data
One of the biggest challenges in corporate management is bridging the gap between planning and execution. Enterprise Performance Management (EPM) functions as a “compass” for planning and control through budgets and KPIs, but it cannot directly reveal what is happening on the ground. Process Mining, on the other hand, is like a “GPS for operations,” visualizing the reality of business execution from system event logs. By combining the two, organizations can create a powerful synergy that links management control with operational excellence.
■Practical Use Cases
Supply Chain Optimization
Even with an inventory reduction plan set in EPM, real-world issues such as delays in inbound/outbound logistics or approval bottlenecks often result in excess stock. Process Mining makes these inefficiencies visible—such as slow inter-warehouse transfers or approval cycles—so corrective actions aligned with EPM goals can be applied at the operational level.
Order-to-Cash Accuracy
By reconciling EPM’s sales forecasts with actual processing times captured through Process Mining, organizations can quickly detect supply-demand mismatches. This prevents stockouts and overstock, ultimately improving customer satisfaction.
Faster Financial Close
“Accelerated closing” is a frequent target in EPM, but in practice, it is often hindered by delays in approvals, postings, and reconciliations. Process Mining can pinpoint the exact bottlenecks in the approval process, directly connecting EPM’s management goals with tangible operational improvements.
■Data Architecture and Mechanism
To realize this synergy, it is essential to connect the aggregated KPIs of EPM with the transaction-level detail of operations:
EPM Outputs: Aggregated figures such as revenue, profit margin, and inventory turnover.
Transaction Data: Individual records of orders, invoices, postings, and other entries captured in ERP and core systems.
Event Logs: Structured execution history created by analyzing IDs, timestamps, activities, and attributes from transaction data.
Process Mining Analysis: Using event logs to reconstruct actual workflows and quantitatively identify root causes behind KPI underperformance.
Establishing this flow creates a single line of data that links top-down KPI management with bottom-up operational analysis.
■Contribution to Non-Financial Disclosure
Today, integrated reporting and sustainability disclosures demand transparency not only in financial performance but also in non-financial areas:
CO₂ Emissions: Set reduction targets in EPM, then track logistics and production data as event logs to verify real reductions.
Human Capital: Define KPIs such as training participation or attrition rates in EPM, then use Process Mining to analyze HR processes and ensure policies are effective.
Governance: Detect deviations or exceptions in approval processes through logs, strengthening internal controls and compliance.
By aligning the “targets” defined in EPM with the “realities” revealed through Process Mining, companies can present investors and stakeholders with a credible and data-driven management story.
■Conclusion
EPM acts as a compass, while Process Mining serves as a GPS. A compass alone shows only general direction, and a GPS alone cannot define the destination. When connected through the right data architecture, the two create a comprehensive, actionable management system that spans both financial and non-financial performance. This is the true synergy of EPM × Process Mining.
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