Background
Various information systems are frequently used by enterprises today to support the execution of business activities. Organizations need effective tools to analyse and monitor their business processes as they speed up their digital transformation activities. Understanding the current process, however, is essential to determining whether improvements are worthwhile, where performance issues exist, and how much variance there is in the process throughout the business.
Solution
Coforge used intelligent mining (AI) algorithms like Alpha, Heuristic, Inductive and Correlation miner along with visual analytics based solution to discover, monitor and improve business processes. The solution offers fact-based insights, derived from actual event logs, databases and other source system. It has extensible and scalable architecture, built using open source technologies. The application also displays an animated view of the execution of individual instances of processes.
Key challenges solved
The application understands the current state and discovers the business process flows - at high scale and low human effort. It speeds up the investigation time in process discovery compared to traditional methods of interviews & workshop. The user can zero in on bottlenecks in a process flow and identify opportunities to automate. The user can also find deviations between historical runs and a new process flow and inefficient processes.
Opportunities
Audit: The solution can give complete and real time coverage of all processes and transactions. It can identify the risks and can compare and verify the improvements when there is a change in the process.
Manufacturing: The solution can identify the inefficiencies within the production processes and reduce the production cycle time by fixing them. Reduced cycle time will result in increased output. It can reduce reworks by having alerts when the manufacturing deviates from the standard. This will also result in improved product quality.
Order-To-Cash: The solution can find out the reasons behind late deliveries resulting in increased on-time delivery. It can point out the root cause of long-running holds or order cancellations resulting in increased revenue and improved order-to-cash process.