According to a Harvard Business Review study, more than $3 trillion is wasted every year on inefficient business processes in the United States (such as billing, customer interactions, order processing, for example). Sadly, this research was conducted long before everyone was sent home to work and login from their personal laptops, which likely exacerbated inefficiencies.
So how can you fix the problem? The solution for managing inefficient (or redundant) processes is to conduct an analysis called “process mining” that aims to discover what processes (or which individuals) are causing the lag and recommend solutions for solving them – often resulting in multiple processes becoming optimized or automated with the goal of improving profitability.
According to a recent Gartner report, however, traditional process discovery and modeling is costly and time-consuming, because of gaps in business knowledge, a lack of objective validation techniques and poorly executed standard operating procedures.
So, what options exist to replace those traditional methods? Digital Journal sat down with Sofia Passova, CEO of StereoLOGIC, a leading integrated process and task mining technology firm, to discuss the latest methods in process mining, task mining and operational intelligence.
Digital Journal: What is process mining?
Sofia Passova: Process mining is a computer-based algorithm that searches through a company’s processes, visualizes them, and determines exactly how well or poorly those processes are working in real-time. Task mining is similar in that it tracks how employees interact with applications and where they lose their time.
DJ: What is the goal of process mining?
Passova: Process and task mining aim to answer the question, “How long should it take for this process or task to complete in ideal case, and why is it taking this long?” An integrated approach identifies which of the company’s “processes, tasks, applications or human activities” are hindering workflow and what are the specific choke points that typically are either highly prone to errors or are repetitive in nature. Usually, the solution is to optimize or automate the process at those points to reduce human errors, streamline the employee experience, or increase profitability – sometimes all of the above. More efficient employee processes, in turn, lead to acceleration of customer service, improvement of customer experience and ultimately increased revenues and profits.
DJ: How did the Covid pandemic exacerbate the problem?
Passova: In many cases, companies were able to seamlessly shift to a work-from-home model, but almost all companies found there were problems with their processes because of the transition. Home computers/laptops did not interact well with corporate systems. Employees spent more time toggling between multiple screens to accomplish simple tasks that were relatively streamlined before. The pandemic workforce model highlighted the many gaps between what employers wanted the processes to be, and what employees were doing day-to-day. This is where remote process and task mining can help tremendously by detecting specific issues and helping to resolve them quickly.
DJ: Why is “traditional” process mining not enough and how can task mining fill the gaps?
Passova: Traditional Process Mining Tools allow companies to visualize processes only partially, usually from the viewpoint of IT systems behavior. However, human behavior – what the employees do day-to-day, like working in email, MS Excel and other productivity tools – is not tracked, meaning the activities and time they spend performing these tasks remain out of scope. By integrating process mining with task mining tools that can capture human tasks, companies can cover this gap and better visualize and analyze the processes. With these new integrated capabilities, organizations can easily control employee performance, compare their approaches to resolving different tasks, analyze compliance risks and detect deviations from standard operating procedures.
DJ: Does it matter what programs or platforms a company uses?
Passova: The short answer is, “It should not matter.” But many solutions on the market are platform dependent. To be fully effective, the technology used for discovery, analysis and optimization should be deployable regardless of the corporation’s technology platforms, which software the employees use, and the location of its servers.
DJ: How has process mining changing today?
Passova: To be effective, process and task mining tools should transition from strictly using analytical algorithms, requiring hours of human consulting and a prolonged implementation cycle, to a more practical set of engineering tools that are easy to implement and return results quickly. The quality of process analytics, diagnostics and optimization lies in the technology’s ability to provide an up-to-date picture of key performance indicators and how to improve the processes that affect them. Mining tools that use a “digital twin” model as the foundation for their analytic capabilities have significant advantages in this area.
DJ: Digital Twin?
Passova: By creating and analyzing a virtual model (or digital twin) of employees’ actual activities, the exact cause of a performance delay or client complaint can be pinpointed and lead to a more direct solution – not just a generic tweak that is applied across the board. This is an important factor, especially as we go deeper into the “century of automation” where efficiency is the key to not only corporate success and profits, but employee satisfaction and retention. It is not possible to conduct a successful digital transformation or robotic process automation (RPA) deployment without the proper process and task mining tools.