When we think of process mining, traditional applications like procurement or order-to-cash processes often come to mind. However, the versatility of process mining extends far beyond these conventional use cases. Today, we want to shed light on some atypical yet impactful examples from our experience that can broaden your understanding of the areas in which using process mining can be beneficial.
1. Optimizing Hiring Processes
Hiring is a complex process involving multiple steps and interactions, often both within and outside formal systems. By applying process mining, we were able to map out the entire recruitment journey, from job posting to onboarding. This helped with identifying bottlenecks and streamlining communication between departments. It was one of the first atypical cases we took on, and the results surprised us! Firstly, we helped our client to expand the recruiting funnel by twofold without hiring new recruiters. Secondly, we quickly realized the lack of data in certain areas and further digitized the process, expanding the resources while eliminating repetitive tasks. In any case of hiring process mining can reveal delays in candidate communication or inefficiencies in interview scheduling, allowing HR teams to make data-driven improvements. The result is a more efficient and effective process that helps to win the top talent over and reduces time-to-hire.
2. Enhancing Customer Support
Customer support often involves various channels like emails, chatbots, and phone calls. It is what is considered unstructured communication, and often processes with such data pose a challenge for process miners. Fortunately, here is where GenAI can help in the most straightforward way: from chats and email chains LLMs can extract additional steps and attributes that can shed light on what actually happens within a non-descriptive process status, as those can slow the process down without a clear reason. We are working on further implementation of this technology to ensure we use all the data in the most efficient way.
Process mining can integrate data from the disparate sources to provide a unified view of the customer support journey. This enables us to identify common issues, reduce resolution times, and improve overall customer satisfaction. For example, by analyzing the flow of support tickets, we can pinpoint stages where tickets get stuck or are frequently escalated. Addressing these pain points leads to faster resolutions and better customer experience, ultimately boosting customer loyalty.
3. Enhancing ESG Initiatives
Environmental, Social, and Governance (ESG) initiatives are becoming increasingly important for businesses. Process mining can help track and analyze ESG-related activities across the organization. By identifying inefficiencies and areas for improvement, companies can enhance their sustainability efforts, ensure compliance with regulations, and achieve their ESG goals more effectively. For instance, process mining can uncover wasteful practices in resource usage or highlight areas where social initiatives are lagging. This data-driven approach enables organizations to make informed decisions that align with their ESG commitments and drive meaningful change. From the process mining point of view, an ESG initiative looks very similar to an optimization request - just with a different focus for the analysis. Here we look not at the costs of operations, or the timeline of all the diverse steps - but at the resource distribution, or carbon emissions calculations - and optimize accordingly.
Here we came up with a few examples of how we used process mining in less common cases - and even if they are fewer in numbers than standard procurement or O2C instances, you can apply the technology pretty much anywhere. If there is data, the process can be made more efficient with process mining! Hope we can inspire you to try it out!
