I wanted to share our success story implementing automated log ingestion for AgilePoint Process Mining in the cloud. This completely transformed how we identify and resolve process bottlenecks.
The Challenge:
Our order-to-cash process was taking 12-18 days on average, but we had no visibility into where delays occurred. We were manually uploading event logs to Process Mining weekly, which meant we only discovered bottlenecks 7+ days after they happened - too late to fix them.
The Solution:
We implemented automated log streaming from AgilePoint process instances directly to Process Mining cloud analytics. This enabled real-time visibility into process execution and immediate bottleneck detection.
Results After 3 Months:
Order-to-cash cycle time reduced from 15 days average to 8 days (47% improvement)
Identified and eliminated 3 major bottlenecks we didn’t know existed
Real-time alerts now notify us within 2 hours when a process instance stalls
Management has live dashboards showing process health 24/7
The automated log streaming was the game-changer. We went from reactive (discovering problems weekly) to proactive (preventing problems in real-time). Happy to share implementation details if others are considering similar optimization.
Priya, valid concern. We process about 500 order-to-cash instances per day, which generates roughly 15,000 events daily. The data volume is approximately 50MB per day. Cloud storage and transfer costs increased by about $120/month compared to weekly uploads, but the business value far exceeds that cost. We discovered a bottleneck in credit approval that was costing us $30k/month in delayed revenue recognition. The ROI was immediate. We also implemented data retention policies - keep detailed logs for 90 days, summarized data for 1 year.
Emma, this is exactly what we need! Can you share more about the technical setup? How did you configure the automated log streaming from AgilePoint to Process Mining? Is this a built-in feature or did you have to build custom integration? We’re still doing manual CSV exports and it’s killing our ability to respond quickly.
What about data volume and costs? We’re worried that streaming logs continuously will generate massive data transfer charges in the cloud. How much data are you moving per day, and did you see significant cost increases with real-time streaming versus weekly batch uploads?
Can you elaborate on the bottleneck detection capabilities? You mentioned real-time alerts - how does the system know when a process instance is stalled versus just taking its normal time? We have high variability in our processes (some orders are complex and legitimately take longer), so we need intelligent alerting that doesn’t cry wolf constantly.