Get a fully objective view of your processes solely by analyzing existing data from corporate information systems. Understand your processes thanks to dynamic visualization, discover bottlenecks, errors, and other inefficiencies, and know their causes. Brainstorm and run different simulations to bring your process closer to perfection and confidently make the necessary changes in your processes.


Understand and improve processes first, automate next. Before getting started with any automation initiative, it is crucial to take a step back and assess whether current processes are efficient and scalable. If an organization runs very complex and non-standardized processes, automation has to make space for other optimization tools. Process mining is one of them, and it helps quickly and easily understand the process maturity. By watching the flow of data and recognizing the behavior of the working staff, it allows to reconstruct, visualize, and analyze these processes. You can easily assess the degree of standardization by looking at the deviations in processes. You can also identify processes or their subprocesses with potential for other intelligent automation tools like Robotic Process Automation (RPA), etc. Several manual activities have to be assessed to identify suitable RPA initiatives. While analyzing various processes, one can not only evaluate but also prioritize further automation initiatives and their economic impact with just a few clicks. This allows to build and validate business cases and select suitable activities early on, both in terms of the physical processes in the warehouse, for example, and in terms of the processes carried out on the computer, such as order processing, etc.

How does process mining work?

When employees interact with different systems and applications, they leave traces of their activity in the form of data, referred to as event logs. Process mining uses this data to visualize the actual flow of processes in a company along with other insights drawn from event logs. The required event data includes the following three columns:

The case ID. It is a series of characters that identify different cases in the system, such as a purchase order number.

Event Type. It explains what process step has occurred, for example, that a purchase order was created.

Timestamp. It is the actual time at which each process step was completed.

The process mining software pulls this data directly from the information systems through built-in connectors. Based on this data, the process mining tool creates business process flow diagrams, finds root causes of problems, identifies automation opportunities, and more.

What processes in logistics can we improve?

Process mining supports all activities and all processes in the whole value chain in the logistics area. It supports core processes, as well as those identified as a “back-office,” yet still very important for keeping the business running.

One of the popular processes is order management in outbound logistics. It can be analyzed from many different perspectives. The date needs only to be connected once for process mining to be able to give any perspective valuable from the business point of view. Whether you want to investigate the process productivity or focus on customer satisfaction – it is available right away.


First: Understand Your Process

Let’s start with revenue leakage in outbound logistics. First, process mining will allow you to explore process data and identify all existing process variants. Starting from the processes called “happy path,” process mining will visualize and evaluate every process iteration, with the occurrence of every unknown violation or process deviation.

With such 100% process transparency, it is possible to investigate what activities have a major impact on revenue loss and then operate proactively amidst uncertainty by building the kind of processes that can adapt basing on black swan events.


One of the top inefficiencies in outbound logistics is returns, as they are don’t bring any value and consume the organization’s time and money. Returns are, of course, a very complex matter, especially in retail and e-commerce, where every customer is allowed by law to return the goods freely. Process mining proposes to act in two directions and helps to manage the situation.

Second: Detect Root Cause

Not only the total impact of returns is automatically measured, but one can deep-dive through all of the process dimensions and find the root causes.

Finding root causes in a fast and automated way is crucial for eliminating returns. Process mining allows to distinguish the orders returned due to, e.g., quality issues during the return process and helps take the proper actions. As a result, the ratio of returns will decrease. Process mining allows searching for other correlations in the process, like short picks, price changes, or even long execution time, leading customers to return goods or cancel the orders.

Third: Automate What You Can’t Eliminate

Not every inefficiency in the business process can be fully eliminated. Yet process mining act in line with the sentence: “Automation can make the business process better, but if the process is faulty, it will only increase the error rate.” It means, that only after completing the process examination and removing a maximum number of deviations is one ready to intelligently approach optimization through automation. In the context of returns, if they cannot be entirely eliminated, there is still an option to make them less painful for the organization. With process mining, it is easy to achieve by building automated workflows that will execute the process-driven actions.

Other Use Cases of Process Mining

Process mining can be applied to any common activity of an organization involving a process.

Typical use cases include auditing, compliance, digital transformation, robotic process automation (RPA), low code automation, machine learning automation, process KPI reporting and monitoring, process improvement, process excellence, ERP development & migration (S4HANA), system/process re-design and re-implementation, organization and process merge.




IBM Process Mining leverages data mining and process intelligence capabilities to provide actionable insights that help to analyse performance, address process inefficiencies, and streamline the business processes. It identifies the process flow in your enterprise applications, tracks the desktop interactions, and maps the extracted data to create process models. In addition, IBM Process Mining helps you discover, visualise, and monitor your process and compare your process models with simulations of the automated process models.

IBM Process Mining integrates with the third-party automation and enterprise applications seamlessly. The Robotic Process Automation (RPA) Bot generation capabilities of IBM Process Mining helps you to create and execute customised scripts to generate RPA Bots specific to your automation tool. IBM Process Mining also includes Accelerator, the data extractor tool, that automates extraction, transformation, and loading (ETL) of data from your enterprise tools to IBM Process Mining.

IBM Process Mining facilitates process automation by identifying the best process candidates for automation, providing the cost and perfromance estimations, and demonstrating the impact of automation initiatives on your entire process before implementation. In addition, IBM Task Mining helps you integrate with IBM Process Mining for a better understanding of how manual processes impact the business process. IBM Task Mining captures and sends your user interaction data to IBM Process Mining to create an augmented process model for deeper insights.

IBM Process Mining also supports process monitoring by enabling you to create customised monitors for your process. With the help of the process monitors in IBM Process Mining, you can set the thresholds and intervals for monitoring your process and configure the APIs (Application Programming Interfaces) of third-party communication tools for receiving the automated alerts and notifications.

UiPath, a global leader in process mining and RPA Trusted by hundreds of organizations worldwide, UiPath Process Mining is one of the most comprehensive and feature-rich available today. In its PEAK Matrix for ProcessMining technology 2021, the Everest Group places UiPath as a global leader and star performer in process mining9. In conjunction with UiPath Task Mining, UiPath Task Capture and UiPath Automation Hub, UiPath Process Mining delivers comprehensive solution to discover, evaluate, analyze, and monitor processes. It provides accurate, real-time data to accelerate and improve customer automation programs.

Celonis. founded in 2011, is a global market leader in AI-powered process mining and process excellence software. It has over 100 consulting and implementation partners and more than 1,000 customers from over 30 countries. Celonis features include process discovery, AI-driven process enhancement, simulations, machine learning (ML) for predictive analytics and root cause analysis, and task mining for capturing and learning from user interactions. The top implementations have taken place in the following industries: logistics, financial services, and manufacturing. Everest Group has named Celonis as a Leader in process mining in its report “Everest Group Peak Matrix® for Process Mining Technology Vendors 2020”.