Process Mining: Your new superpower providing direct visibility into your business processes
Process Mining is a new discipline, quietly developed in Europe in the last decade, and now ready for prime-time. It is a surprisingly simple, yet robust data science which provides almost magical visibility into business processes. It is now used in various productivity improvement projects, such as Robotic Process Automation, but also by Internal Audit and Compliance Departments to identify deviations and irregular transactions.
Any organization aiming to improve its productivity, quality and regulatory compliance must adopt a proactive approach to Business Process Management. According to the Capability Management Model, an organization must be able to explicitly describe its activities in terms of standard business processes and continuously measure their performance and deviations.
Documenting business processes in a large organization is not trivial. It is a costly initiative, where external and internal consultants need to interview multiple stakeholders. Most of the time, it delivers an incomplete version of the truth, as;
- nobody has an end-to-end understanding of the complete business processes
- stakeholders are likely to forget exceptions and special cases
- variations will take place in different regions, business units or departments
- some stakeholders may not cooperate fully, especially if they feel their job is at risk
Performance Management is also challenging; traditional Business Intelligence tools provide common statistics on business process performance such as average processing time, but they cannot explain why certain transactions took longer than others, or easily detect non-compliant events.
How Process Mining works
Process Mining algorithms analyze transactions logs extracted from Information Systems (ERP, CRM, Call Center) and automatically presents a clear visualization of the business processes and the path taken by all transactions.
Once the Process Mining Software has imported the transactions log and creates a business process visualization, Business analysts can efficiently detect:
- bottlenecks and stalled activities
- drivers influencing process performance
- loops in the process which are causing additional costs and delays
- non-compliant transaction instances
Synergies with Internal Audits and Compliance
Internal Audit and Compliance teams have until now used samples to conduct their investigations, as they did not have the resources to review all transactions. Process Mining is a game-changer for them as they can now define the compliance rules they need to monitor and have the Process Mining software conduct this analysis automatically on ALL transactions. For example, one may want to look at all non-compliant transactions, such as:
- the same resource (or department) both initiated and approved a transaction
- the sequence of a transaction is wrong (a cheque was issued before it was approved)
Synergies with Robotic Process Automation projects
Robotic Process Automation is currently being tested and deployed by many organizations to automate manual and repetitive tasks. According to the RPA & AI Benchmarking report from PEX Network 2017, the main obstacle for RPA deployment is the standardization of the business process before RPA implementation. Another common challenge is the identification of strong candidates for RPA.
Process Mining is the ideal companion to Robotic Process Automation projects;
- Before RPA deployment – Process Mining provides a business analyst with a quick and complete view of the business processes. They can identify the best activities to automate, model the cost savings that RPA will generate and understand the impact on the complete business process.
- During RPA deployment – holistic process analysis gathered from human session recorders and event logs and transactional systems can be used for the development of the robots.
- Post RPA deployment – Process Mining is used to measure the Business Value delivered by the Robots (costs and time savings) by easily compare before and after performance. It can also be used to identify new bottlenecks that may be created when the process shifts from robotic to human activities.
For more information
If you are interested to learn more or if you would be interested in a Proof-of-Concept using your organization’s data, please contact us.