Process Discovery vs. Process Mining

Process Discovery and Process Mining continuously monitor processes in any industry to help you achieve business success and improve your return on investments (ROI).

Process Discovery and Process Mining provide many benefits including:

  • Aid in the improvement of processes before adding automation.

  • Determine the most valuable area to add automation.

  • Assist in identifying what machines, employees, and organizations are doing, not just what we may think they are doing.

  • Help with workflow management, improvement, and productivity.

  • Analyze and track processes.

While both are similar standalone solutions, some differences set them apart. When used in conjunction, however, they can solve many common business challenges that we face today.

Before we compare the two, we first need to understand a process.

What is a process?

A process is a series of interrelated tasks that together transform different inputs into a given output. People, nature, or machines may carry out these tasks using various resources.

A process consists of four major elements:

  1. Steps and decisions: The flowchart. A series of tasks and decisions describing the way work is completed.

  2. Variability of processing time and flow: The pattern and consistency of processing times.

  3. Timing and interdependence: The times that employees work and break.

  4. Assignment of resources: How many resources there are and where they are assigned.

Process Mining and Process Discovery differences:

  Process Mining Process Discovery with Nintex Process Discovery
Objective The high-level goal of process visibility and optimization The high-level goal of process visibility and optimization driven by the need to streamline automation
Source Event logs from enterprise software systems Real-time user behavior via the employee desktop
Systems Vertical support: mainly for applications that are creating collectible log files Support for all types of systems and technologies
Setup Requires integration to each application separately Minimal setup time with zero integration
Output Process modeling (on levels), conformance, intelligence, and documentation Set of repetitive actions for RPA investigations, CSV file, BPMN, and a framework for RPA
Granularity Transaction level and user action: task level User action level
Time to Value Several weeks or even months 1-2 weeks

Process Mining utilizes event logs and unique IDs, allowing you to gather the data to gain insight into business activities. It analyzes based on the digital footprints of IT systems. The primary focus is optimizing business processes from end to end.

Nintex Process Discovery runs discovery robots on a user machine and records in real-time, as the user executes actions (keyboard and mouse activity) in approved applications for recording. It then sends the data to the server to get analyzed by the algorithm based on front-end features and metadata. Its primary focus is on automation opportunities and auto-generated RPA robots.

Some processes work better for Process Mining and some work better for Process Discovery. For a simpler process, Process Mining would be excessive. Process Discovery could be a lot more helpful.

Once you get all the data from Process Mining, and there is an area that you want to delve into deeper, you can use Process Discovery.

If an organization wants to see how a specific department or application is contributing to the business based on costs or missed opportunities, they can send Discovery robots to a specific area.

For example, Nintex Process Discovery robots can be sent into the finance department and then zoom into the accounts payable team. There they can get some insight into why invoices take so much time, see which employees are not performing as well, or seek ways to improve their process based on the gathered data.

How can organizations link Nintex Process Discovery data to Process Mining?

After Discovery Robots collect data from all the applications, the data gets analyzed in the Nintex Process Discovery server and mapped in Nintex Process Discovery. From the available interactive map views, Linear Graph and Unified Graph, there are four available output options:

  • Automation file: Download the visible variants as automation workflow files that can be imported into the Studio. See Downloading an Automation.

  • Discovered process report: Download the selected process and variants to an editable MS Word format. See Downloading a Discovered Process Report.

  • Event Log Download the selected processes and variants to use with a Process Mining tool.

  • BPMN diagram: Download the selected processes and variants to a Business Process Model and Notation (BPMN) diagram. This flowchart provides a graphical notation for specifying business processes and it can be added to process modeling, process mapping, or a process mining solution.

When the Nintex Process Discovery server analyzes the data, it creates an action event log in a CSV file format. This can be added to your Process Mining solution. If you want to zoom into a specific part of a process in your Process Mining tool, you can use the CSV file output from the Nintex Process Discovery action event logs as additional input and visibility into deeper-level activities.

There are also BI dashboards such as Appsight, to help you bridge between Process Mining and Process Discovery. There you can view the metadata from a high level and see what kind of trends or patterns you can identify, or focus on specific parts of the business analyzed from Process Mining and then complement it with the processes that were identified from Process Discovery.