What is process mining? It is a method of gathering information from the digital footprints of different phases of a single process to help you to rediscover your organization’s pitfalls that need to be fixed to improve performance and profitability
It is a systematic analytical approach used for discovering, monitoring, and improving real processes (i.e., not assumed processes) by extracting data from digital footprints that are readily available in today’s digital world. Here, data from within the process drives the process changes compared to the traditional methods of collecting feedbacks from customers/stakeholders.
Why process mining?
Today, organizations operate with a goal of continuous improvement. This is possible only when a real introspection is done using data than following an external feedback. Data-driven introspection is possible only by capturing digital information from multiple phases of an organization.
Few example use cases:
- Retail: From order placement until delivery, multiple channels are involved. Traditional methods of process improvement would involve data gathering from customer calls, feedback forms, ratings, etc. But, process mining would involve data collection from all digital foot prints. The gathered data will be used to find gaps in the current process. The gaps will then be filled based on the goals of the organization – be it customer satisfaction, efficiency improvement, or increasing profit. Overall, continuous improvement will be made possible through process mining.
- Tech support: Customer support as the starting point until problem resolution. Here, process mining will help find the gaps to be filled to improve service.
- Healthcare: How to improve the accuracy of clinical research results that are being collected around the world.
Other industries where process mining is applicable:
- Manufacturing processes
- Logistics processes
- Accounts payable processes
- Food processing and distribution.
Process mining tools:
UI Path: Provides a robust process mining capability with suitability to multiple domains and technologies.
- See workflows and spot bottlenecks: Produce a detailed “x-ray” of your end-to-end process by pulling log data from your enterprise systems.
- Align your projects with company KPIs: Use smart tags and KPIs to identify automation opportunities with the biggest impact. Then, measure performance after you automate.
- Optimize process over time: Continuously iterate and monitor to know what’s working, what’s not, and keep optimizing your process.
- Organizations would shift to process mining and replace the manual methods of collecting data.
- This will be the next-generation technology that will be used by organizations to mine data from all phases and channels, to act on the mined data, and to improve efficiency for continuous improvement based on organization’s goals.
For further details and questions, please reach out to Ghanashyam Sajankila (email@example.com), COE Leader, Data Analytics, Apps NA COE