The first step in automation is to gain a complete understanding of the current state business processes. Often enterprises do not have a knowledge base of all their existing processes and hence identifying automation opportunities becomes a challenge.
There are two techniques to address this challenge:
Process Discovery
Process Discovery tools typically record an end-user's interactions with the business applications. This recording is then intelligently transformed into process maps, BPMN diagrams and other technical documentation. The output from the Process Discovery tool can also be used to serve as a foundation for building automation bots. Given below are some examples of Process Discovery tools:
- https://www.atos-syntel.net/insights-and-resources/publications/syntbots-process-recorder
- https://www.uipath.com/product/task-capture
- https://www.automationanywhere.com/products/discovery-bot
- https://www.blueprism.com/products/process-assessment-tool/
Process Mining
Process Mining is all about extracting knowledge from event data. Today all IT systems and applications emit event logs that can be captured and analysed centrally using tools such as Splunk or ELK stack. As one can imagine, the biggest drawback of Process Mining is that it would not work if your legacy IT systems do not emit logs/events.
By analysing event data, Process Mining tools can model business process and also capture information on how the process performs in terms of latency, cost and other KPIs (from the log/event data).
Given below are some examples of Process Mining tools:
- https://www.uipath.com/product/task-mining & https://www.uipath.com/product/process-mining
- https://www.celonis.com/solutions/celonis-snap
- https://www.abbyy.com/timeline/
- https://fluxicon.com/disco/
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