As inflation skyrockets and supply chain issues continue to pose challenges for companies around the world, more businesses say they are looking for ways to cut costs and improve the efficiency of the business. To do that, some seem to be turning to process mining and task mining tech that can help them map out their existing workflows and gain insights into where and how to make meaningful changes.
Process Mining And Task Mining Are Related But Not The Same
Process mining is the discovery, analysis and monitoring of end-to-end processes. Essentially, that means observing the journey of a project from start to finish and mapping out all the paths and variants that it could go through along the way.
Task mining, meanwhile, can be thought of as a smaller-scale version of process mining. Where process mining would analyze the entire process of putting a new car on the market, task mining would zoom in on a specific task like manufacturing a door or loading the finished cars onto a truck for transport.
For both techniques, the goal is to find ways to improve efficiency by looking at when and where the problems or delays are in your business.
The key differences are the scale and the kinds of insights and improvements you’re finding. With process mining, you’re looking at the path that car takes from initial concept to being purchased by a consumer and asking whether there are any alternate routes you could take that would be better.
With task mining, you’re looking at a more granular and practical level. These smaller, subtler improvements will have a ripple effect across the entire process, but they won’t fundamentally alter the process map.
Which Kind of Mining Should A Business Be Using?
The short answer, according to some experts: both — process mining and task mining are each important parts of diagnosing the parts of a business that need to be improved. To understand why, take the example of a major meat processing firm that used Apromore, a process mining software that says it uses algorithms and machine learning to help reduce waste in its production plants.
The company had recently implemented an automated logistics solution for its cold storage, but that decision had actually slowed down the turnaround time for multiple products. The slowed turnaround also increased waste across the process: more raw materials and more final goods were going to waste as a result of this less efficient cold storage system.
Using Apromore, the meat processor was able to pull data from its enterprise resource planning software and its execution system into the process mining software. Apromore was able to create a detailed workflow of how materials were moving through the plant.
That process map revealed multiple tasks that were delaying production and increasing wait times leading to spoilage and waste. Overall, the company was able to improve the average turnaround time by 10%, resulting in about $800,000 in savings per year in reduced waste.
Process mining helped map out the journey through the production plant while task mining allowed the company to figure out how to improve the bottleneck tasks that were contributing to the increasing waste.
Similarly, a global manufacturing company making advanced cables was able to successfully curb maverick buying by using myInvenio, a process mining software owned by IBM IBM and distributed in Japan by HeartCore Enterprises Inc. HTCR.
Maverick buying is the tendency for some employees in larger companies to make purchases on the company’s behalf without going through the established procurement channels. Sometimes, it’s an intentional refusal to use the existing channels because they’re inefficient or difficult. It could be a matter of not being aware that those channels exist. It can also be the result of errors or issues in the procurement process.
For this cable manufacturer, executives were noticing widespread non-compliant purchasing that was costing hundreds of thousands of dollars in unauthorized spending.
To figure out when, where and why that was happening in a process that should be mostly automated, it used myInvenio to map the ordering process from order creation to delivery. What the process map revealed was that half of the order creation processes were being done manually — meaning that an issue came up that the system couldn’t resolve like an invoice without a matching purchase order.
By identifying these problems, the company was able to figure out where to implement additional tools to reduce errors and help the system operate more smoothly. The end result was a new process that minimized maverick buying and reduced costs by about $110,000.
Process mining helped the company see how purchases were moving from order creation to final delivery while task mining helped it rework the points in that journey that were making it vulnerable to non-compliant purchasing.
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