When a purchasing process is designed, everything looks clean on paper: a requisition is created, a manager approves it, a purchase order is issued, goods arrive, the invoice is matched, payment is released. The procedure manual says so. The ERP implementation blueprint says so. But the same company’s ERP system has quietly recorded hundreds of variations on that flow. Some orders were pushed through without an approval step. Some requisitions went back three times for correction. Others never closed at all, sitting in limbo with no one accountable. Management rarely sees this picture because ERP reports typically show completed transactions, not the paths those transactions actually traveled.
Process mining is an analytical approach built precisely to close this gap. The underlying idea is straightforward: ERP systems store every transaction step as an event log entry. Each record captures who moved a transaction, when, and from which state to which state. Process mining tools take these raw logs, reconstruct the actual process flows using statistical methods, and compare them against the intended design. The resulting visualization tends to surprise managers: instead of one clean path, they see dozens of deviations, loops, and shortcuts that were invisible in conventional reporting.
For Turkish SMEs, the relevance of this approach is growing. The mandatory e-Invoice and e-Ledger requirements introduced by the Turkish Revenue Administration have pushed companies toward more systematic ERP process management. Structured data obligations mean that processes need to be documentable and traceable. In this environment, not knowing what is actually happening inside your ERP is no longer just an operational risk — it becomes a compliance risk. Process mining offers one of the most direct ways to quantify that risk and bring it to the surface.
In practice, the most common findings fall into three categories. First, approval bypasses: whether driven by urgency or habit, these shortcuts leave traces in the ERP that process mining surfaces, showing which users take this path and how often. Second, rework loops: documents that cycle back repeatedly due to missing information, incorrect pricing, or wrong supplier selection inflate total cycle times significantly and in ways that standard ERP dashboards rarely capture. Third, manual workarounds: coordination handled outside the system via phone or email shows up as stalled steps inside the ERP, and that idle time translates directly into labor cost.
Putting a number on these findings gives decision-makers a concrete foundation for action. When process mining measures the average cycle time of a purchasing workflow, it becomes possible to calculate how many minutes of additional labor each rework loop generates. Multiplied by average hourly labor cost and annualized, the resulting figure frequently exceeds the cost of the improvement project itself. This kind of ROI analysis, grounded in data rather than intuition, carries far more weight in executive conversations than process diagrams alone. Companies that exclude process inefficiency from their total cost of ownership (TCO) calculations are systematically underestimating the true return on their ERP investment.
Two practical obstacles stand in the way of this approach. The first is data quality: process mining only produces meaningful results when ERP event logs are consistent and complete. Many SMEs in Turkey do not use their ERP systems at full depth — some steps are handled outside the system, and records are sometimes entered in bulk after the fact. In that case, the process map reflects data entry habits rather than operational reality. The second obstacle is interpretive capacity: even a powerful tool produces nothing more than a report if the organization lacks the analytical skill to read the output and convert it into action. For this reason, process mining projects should be positioned not as software installations but as investments in analytical maturity.
For managers at the decision stage, a practical starting point is this: verify with your technical team which ERP modules retain event logs and whether those logs can be exported in a usable format. Select one process — purchasing, production orders, or customer order fulfillment — as a pilot, and map the gap between the designed flow and the actual flow. That first analysis will show which processes are most amenable to improvement and where investment will return fastest. The digital transformation conversation in most companies centers on acquiring new systems; but asking the right questions of existing ERP data often delivers faster and more measurable results than any new platform purchase.
This article was originally written in Turkish by Gökhan MERCANOĞLU on May 14, 2018 and has been automatically translated into English and other languages using machine translation.