order_processing · saas · workflow
Conrad Electronic realizes €10M+ value and doubles Order Management automation with Celonis
Conrad Electronic had achieved isolated process mining wins but struggled to scale them into lasting, company-wide improvements. Process knowledge was fragmented — individual departments suggested optimizations piecemeal — and the company lacked the structural foundation and documentation needed to support future AI use cases.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Process mining on support tickets
Process mining was deployed to analyze, organize, and reduce the tens of thousands of customer support tickets Conrad received each month due to a lack of process visibility.
Tools used
CelonisCelonis Process Management (CPM)Open Order Processing AppCelonis AI automation
Outcome
Conrad realized over €10M in value through Celonis in three years, achieved a 100% increase in Order Management automation, and raised order-block-processing automation from 40% to 90%, while also slashing product return rates and reducing service-ticket workload and throughput time.
Results
Time savedreducing workload and throughput time
Volume100%
Cost replaced€10M+
Running since2021
Grounding & classification
Source type: vendor customer story
32 fields verified against source quotes.
anomaly detectiondocument classificationpredictive analyticssupport ticketfailure mode describedhuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedecommerceautomation ratecost reductioncycle time reductionemployee productivityvendor customer storycustomer supportecommerce opsorder processingextract classify routemonitor detect alert