Case Study #5: Process Analytics for Order Management
Gut feeling or data? For this manufacturer, the company's data did not reflect how orders were really handled. Management wanted to stop reacting and start predicting, with end-to-end data support for proactive, data-driven decisions. We applied process analytics to order management and fulfilment: the actual process matched the documented one only 5% of the time, and most deviations were unexplained. Standardised process metrics, KPIs and process mining tooling now show management exactly what is happening and where to act.
At a glance
Client: manufacturer with multi-step order management and fulfilment · Industry: Supply chain, manufacturing · Scope: process analytics, KPI standardisation, process mining
5%
Process compliance
actual process versus the documented process
58%
Deviations labelled “Other”
of actual process variants had no clear reason
29%
Deviations explained
share of cases with a straightforward reason
Business challenges
- Company data did not reflect the real order management process.
- Management reacted to problems instead of predicting them.
- No end-to-end data support existed for proactive process management.
- Risk and missed opportunities accumulated in unexplained process deviations.
Project objectives
- Measure how orders actually flow against the documented process.
- Standardise process metrics and KPIs across the operation.
- Compare facts with opinions and make deviations visible.
- Enable targeted resolution of the issues that matter.
Our approach
1. Process discovery
We reconstructed the actual order management process from the client's data and compared it with the documented paper process.
2. Compliance and deviation analysis
Only 5% of actual cases followed the documented process; 58% of the variants were described by factors listed as "Other", and only 29% of the time was there straightforward information on the reason for the deviation.
3. Metrics, KPIs and monitoring
We set up process metrics and KPIs, standardised the analytics, and implemented tools such as Celonis to monitor standardised process performance continuously.
What the data told us
- The documented process described almost none of the real work: 5% compliance.
- Most deviations were unclassified, hiding the true causes of delay and cost.
- Reasons for deviation were clear in fewer than a third of cases.
What we put in place
- Standardised process metrics and KPIs for order management and fulfilment.
- Fact-based comparison of actual versus intended process, replacing opinion.
- Process mining monitoring so deviations are seen as they happen.
- Targeted fixes for the deviations with the highest impact.
Business impact
Improved process visibility lets management understand ongoing order processes precisely and resolve the pertinent issues in a targeted way, boosting efficiency and transparency while reducing risk.
Conclusion
With facts replacing gut feeling, the client now manages order fulfilment proactively, with faster deliveries, lower costs and clearer accountability.
Does your data reflect how orders really flow?
We apply process analytics to order management and fulfilment. See our Supply Chain Optimization solution, or talk to us about your processes.
Tools used
