PROCESS MINING.
AN X-RAY FOR YOUR BUSINESS PROCESS

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.

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.

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.

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.

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.