Demand for process mining technology has grown rapidly across the globe in the last decade. Process mining solutions have demonstrated clear success rates, significantly improving the internal processes of companies in industries as diverse as audit & assurance, automotive and telecommunications.
Despite its popularity, many companies are still uncertain about what they can achieve with the technology. Certainly, the concept of process mining – the power to control your processes – sounds good enough to start using immediately, yet there is still some hesitation.
To simplify things, we’ve narrowed down the advantages of using process mining to two, simple reasons:
- Improve efficiency
- Decrease risk
From our experience, these two reasons are fundamental to process mining. They aren’t mutually exclusive, as they can be relevant to the same process. They do, however, influence the approach taken in the process mining solution and when performing analysis.
So, before we go in-depth about how it affects analysis, let’s take a closer look at each reason.
The constant drive for operational efficiency is the bane of many C-level managers, who face pressure from all directions: customers, investors, competition, financial markets and more. Therefore, a sure-fire way of deflecting pressure is to increase efficiency.
It sounds easier said than done, but it can be made simple with process mining. Once inefficient processes have been identified through Process Mining, organizations can be targeted and decisive in their decision making, increasing efficiency and saving substantial costs as a result.
Let’s take an example. Production processes need to run like a well-oiled machine to produce high-quality products. That is, the entire production process, as well as individual activities, need to be profitable with a short time to market. Process mining ensures most bottlenecks in the production process are identified and prevented, while still producing a high-quality product for customers.
The second basic reason to use process mining is to identify potential risks and ensure they are avoided. Naturally, there are some processes where decreasing risk is more important, such as financial processes, where companies have more to lose.
In financial processes, small errors can have big consequences, for instance, when an invoice is paid twice, or a payment isn’t processed at all, or unbudgeted costs need to be allocated as unexpected expenses.
The risk reduction perspective is important for processes where outliers need to be reduced as much as possible.
Let’s look at an example of a transportation company. For their customers, on time delivery is of utmost importance. Deviations from the ideal process can hugely impact revenue and long term customer satisfaction. Deliver a day early and there is no space in the warehouse, deliver a day late and cause further delays along the supply chain. Using process mining, our client was able to identify outliers and use this information to make adjustments, resulting in reduced costs and happier customers.
In a similar vein, regulation compliance processes largely rely on risk avoidance. All companies need to comply with certain regulations. For instance, companies need to file tax returns with authorities periodically. If not done on time, they may not receive their tax discount.
What effect does this have on analysis?
In short, the efficiency perspective looks at the majority of the cases within a process and aims to fine-tune where the most gains are realized. With a risk reduction perspective, the focus shifts to the outliers of the process, ensuring the process runs between certain boundaries.
In more detail, when analyzing a process from an efficiency viewpoint, you want the changes that you make to affect most of the cases within your process. For example, if you can decrease the throughput time of 80% of your executions by one hour, you’ll be more effective on overall throughput time, rather than if you looked at individual outliers. In short, the more cases are affected by the changes that you make, the more effective your changes are and the more efficient the process becomes.
For processes that rely on risk management, you’ll have to pay more attention to the outliers. Assuming the desired process flow is low risk, the process that does not follow the recommended path and has a few deviations will probably be riskier. To reduce the outliers, you want to reduce the variations of process execution, by analyzing why these cases do not follow the most common paths.
So, there you have it, two reasons to start using process mining and how it affects process analysis. To sum up, whether you want to reduce risk, improve efficiency or if both are a priority, process mining is a proven method of optimizing your processes. Once you have a clear overview of your processes, it’s possible to implement the necessary and appropriate changes for continuous process monitoring and improvement.