Process mining is a family of techniques in the field of process management that support the analysis of business processes.
Log-based vs Realtime Process Mining
Log-based Process Mining
Most process mining tools on the market use event logs and apply specialized data mining algorithms to identify trends, patterns, and details recorded by an information system.
The input data streams used in log-based process mining are unqualified. The major challenge in using these tools is the time-consuming task of qualifying data by parsing the logs, detecting events and patterns, and assigning it to the correct business activities.
The result is a business process model used to identify weak paths to optimize the process. Log-based process mining usually works in a time-shifted manner.
While log-based process mining tools may understand various input formats, often there is an additional step required in the setup to gather this data from the original systems before processing it.
Realtime Process Mining by Flow Director
Flow Director doesn't use event logs but instead intercepts the message flows of realtime systems. The result is a live process model generated on the fly, used to monitor the business processes as they occur and take appropriate actions when they deviate from the optimal path (aka Happy Path). For example, orders from an order system could be tracked live by their order ids over the various stages of processing. If necessary, the company could intervene when the shipping of a particular order takes too long.
The input data streams of realtime process mining are qualified and intercepted from queues and topics that already
have a semantic relationship to business activities, i.e., messages received on a topic
order_entry can be directly assigned to a
Order Received. All required data fields are usually already part of the message, i.e., the unique key that
identifies a business object (process). If not, they could collect from other sources, i.e., a database, before the messages pass into the process mining.
Therefore realtime process mining mitigates the need for time-consuming log parsing, event and pattern detection task and can instead directly generate the process model.