Lilly Tech Systems
Process Enhancement with AI
Learn how AI enhances discovered processes through bottleneck analysis, predictive monitoring, simulation, and intelligent automation recommendations.
From Discovery to Optimization
Process enhancement uses the insights from discovery and conformance checking to actively improve business processes. AI takes this further by predicting future process behavior, simulating changes before implementation, and recommending specific optimizations with estimated impact.
Bottleneck Analysis
| Analysis Type | Method | Insight |
|---|---|---|
| Time Analysis | Measure waiting and processing times between activities | Where cases spend the most time |
| Resource Analysis | Analyze workload distribution across teams and individuals | Who is overloaded and who has capacity |
| Rework Analysis | Identify loops and repeated activities in process flows | Where errors cause rework cycles |
| Batch Analysis | Detect artificial delays from batching behavior | Where items wait unnecessarily for batch processing |
Predictive Process Monitoring
Remaining Time Prediction
Predict how long each running case will take to complete based on its current state, path taken so far, and historical patterns of similar cases.
Outcome Prediction
Forecast the likely outcome of each case, such as approval or rejection, on-time or late delivery, enabling proactive intervention for at-risk cases.
Next Activity Prediction
Predict the next step in a running process, enabling intelligent routing, resource pre-allocation, and workload planning.
SLA Violation Alerts
Identify cases at risk of breaching service level agreements early enough to take corrective action, reducing SLA violations by up to 60%.
AI-Driven Improvement Strategies
Process Simulation
Create digital twins of processes and simulate the impact of proposed changes before implementing them. Test staffing changes, automation, and process redesigns risk-free.
Automation Identification
AI analyzes activity characteristics like rule-based decisions, data transfers, and repetitive tasks to recommend candidates for RPA, workflow automation, or AI assistance.
Resource Optimization
Optimize resource allocation across activities based on skills, availability, and workload. AI balances efficiency with quality and employee satisfaction.
Continuous Monitoring
Deploy real-time process monitoring that detects performance degradation, emerging bottlenecks, and deviation trends as they develop rather than after the fact.