Process mining is often associated with bringing savings to businesses. But how does it help them bring in money faster?
The scenario: A large IT and services distributor was expanding rapidly into new regions when its workers noticed something alarming—their cash flow was becoming strained due to slower customer payments. The trend posed a significant threat to their growth strategy. Without liquidity, they would be forced to find new means of financing their expansion.
Employees were left scratching their heads in confusion. Their total orders, bookings, and margins had been increasing, yet their liquidity had worsened in the previous quarter. Were customers taking more time to pay their invoices? Was order processing taking too long? How could they validate any of their assumptions—or perhaps discover entirely different reasons for their troubles?
Enter process mining. The business was soon able to visualize all orders, step by step. They could see not only the bigger picture of how and where things were going right or wrong, but they could dive deeper into problem areas and discover exactly what was happening and why.
The good: Most customers were paying on time.<!— htmlmin:ignore —>
The not-so-good: An unanticipated issue—the average time from delivery to first invoice took up to 26 days.<!— htmlmin:ignore —>
The root cause: Maintenance or repair service orders. Different service billing models based on hours, milestones or contractual quota agreements caused confusion due to poorly maintained, missing, and delayed records. On average it took 5-6 days to get the required information from the departments and enter it into IT systems.<!— htmlmin:ignore —>
The fix: Started with 20 of their biggest clients and standardized the billing to hourly rates. Improved IT-based processing by requiring departments to enter service hours as soon as they come back from a job. Early results sped up invoicing by more than 40%.<!— htmlmin:ignore —>
The not-so-good: Many of the orders in the system were later canceled or rejected.<!— htmlmin:ignore —>
The root cause: Most common reasons were failed credit checks (due to individual customer purchasing limits), lack of inventory, or end-of-life parts that had been replaced by newer part numbers (and a server error meant the customer interface and inventory system were not exchanging information correctly).<!— htmlmin:ignore —>
The fixes:<!— htmlmin:ignore —>
Set a higher limit to trusted customers.<!— htmlmin:ignore —>
Corrected the system error that prevented users from seeing the actual availability of items and replacement part numbers.<!— htmlmin:ignore —>
The not-so-good: The system was only partially in use.<!— htmlmin:ignore —>
The root cause: High-volume customers were still using non-automated ordering methods such as phone or fax.<!— htmlmin:ignore —>
The fix: Key customers were trained in electronic ordering, reducing cycle times and manual processing. Invoicing subsequently dropped from 3 weeks to 10 days.<!— htmlmin:ignore —>
Process mining was the first step in helping this company follow their revenue trail and bring things back in line. By identifying the areas that would contribute the most to improving their payments, they were able to make the changes that enabled them to pursue their original goal and drive toward sustainable growth and success.