Has process mining become another software good? – RTInsights

There is a growing trend of integrating process mining features with business intelligence, and some companies have built solutions on business intelligence tools.

The emergence of mining operations has opened up new horizons for program combination and collaboration. Enterprise software giants such as Microsoft, SAP, and IBM are buying mining startups to add to their intelligent process automation capabilities. Besides the giants, there are companies, large and small, that are joining the mining industry by acquisition or with flashy new start-ups. Many of these companies are already specialized in automation, for example, Microsoft Power Automate. The trend appears to be towards organizations buying or building process mining technology to take advantage of its capabilities to accelerate the adoption of their core offerings of automation products. These new sets of programs are opening up new industries, but will they open an end to the stand-alone operational mining industry?

Get down to basics

Process mining software is an event logs-based tool that enables organizations to understand their business processes, identify bottlenecks, and improve the efficiency of their work. Some of the advantages that mining processing software provides are:

  • Assist in identifying and resolving bottlenecks in operations,
  • Provide a better understanding of the workflow for better analysis and design,
  • Identifying process improvement opportunities, etc.

Applications such as ERP, CRM, ITSM, and other log systems automatically create event logs that record user actions in workflows. The data in these logs can then be collected, or ‘extracted’ to visually analyze the audit trail of operations.

Prior to the mining process trend, the role of data analysis always required a lot of manual work to achieve little results. No matter what process is investigated, business needs place demands on manual review or writing endless lines of code for answers. Process mining has significantly reduced analysis time to easily understand business processes. Business process owners were then able to easily connect to data sources and could immediately begin to understand what was working and what was broken in their process execution systems. Process mining technology in and of itself is very valuable in helping to understand processes and implement processes in real time, but the real value to an organization lies in its ability to identify transformation and automation opportunities before implementation and monitor the performance of automated robots in production after deployment. It makes sense that this fast-moving acquisition landscape has less to do with process mining itself and more about what automated process automation, business process management and process mining together can achieve.

Process mining solutions are seen as gateway technologies for many organizations to enable and scale automated process automation and other transformation initiatives across their businesses. At this point, automation companies are chomping to give their customers access to insight that will help them develop their automation projects and sell more automation. Eventually, automation vendors began to run into hurdles in finding new opportunities for transformation, and mining solutions are the key to unlocking new ventures and, of course, new revenue. Choosing the right technology can make all the difference.

See also: The mining process comes to the surface

Built from the same German building blocks

The term process mining was first coined in a research proposal written by Will van der Aalst at the University of Eindhoven in 1999. Since then, many process mining vendors have approached data analysis and process optimization in similar ways all of which have been learned from their postgraduate education. Its founders are at the University of Eindhoven. All of these are primarily based on the schematic approach. How do you distinguish one miner from another, while sharing so much alike? When products become indistinguishable from one another, this leads to rapid commodification, and there is probably something we’re seeing already happening as automation players get any stand-alone mining solutions.

This isn’t something mature players fear. They knew that process mining alone wasn’t enough to drive the kinds of operational improvements companies are seeking. That’s why advanced partnerships and integrations have been so important in the mining industry. It is clear through the mining process that you can discover repetitive work and then provide the information needed to properly automate the work. However, the real gold is in the ability to build an ecosystem that can communicate with multiple systems and relay information back and forth when processes go wrong, so BPM or RPA tools and even the humans in the loop can take action to fix things. These real-time alerts and predictive capabilities provide unprecedented visibility and forward-looking control over the execution of the process. Unfortunately, only a few people have mastered this capability and have escaped the set of features of a self-contained mining process. Those who still only provide the visualization of the basic process diagram analysis should be most concerned because those will be the first to see the effect of commodification. In today’s shows, anyone can show the process is performed on a Visio-like diagram.

Why do automation companies care about mining in operations?

For many years, hands-on mining applications have provided business process owners with new understanding and insight capable of saving countless manual hours and helping companies discover improvement opportunities. By itself, this was not enough. The recent acquisitions point to the logical evolution of prominent technology vendors who have the necessary process and operational data in their systems but lack the ability to understand and leverage this data for improvement. They already have the data, and they’re discovering that they can offer more value to their customers through process mining to help make processes flow better, faster, and with fewer errors. According to Ernst & Young, 50 percent of initial robotic process automation (RPA) projects fail due to a lack of quantifiable process data. This new trend gives automation vendors access to information to help determine ROI and sell bigger and better automation projects. There are also big successes too. Recently, a multinational telecom company has used hands-on mining to improve customer support and service truck rolls. During the first six weeks, Operation Intelligence revealed how to save $8 million after identifying the root cause of repetitive tasks and trucks being sent to the same service requests.

The success of the smart operation depends on the ecosystem

There is more than just asking for cash, buying to paying, and ITSM operations. Many traditional tools are limited to connecting to specific data sources such as SAP, Oracle, Salesforce, or ServiceNow. It must be said that no one should be tied to a single resource or set of solutions. Success depends on organizations’ ability to remain flexible and agile in their approach to process automation. The tools will help them thrive but must remain flexible and allow organizations to create their own automation system using the best solutions.

There is a growing trend of integrating process mining features with business intelligence, and some companies have built solutions on business intelligence tools like PowerBI and Qlik. This type of integration places an understanding of the process within business intelligence consoles, which many companies already use. Others stand out with their unique insights into process understanding, control, and monitoring to aid the automation lifecycle. Uniquely from the start, these solutions have been crafted as process intelligence since their inception and go beyond the traditional mining process and spaghetti chart analysis. A better approach is to use a “timeline” to create an unfiltered, unedited history for each iteration from start to finish. These timelines are then analyzed to compare, filter, search, aggregate, etc., similar to how a business intelligence application analyzes records in a table. The importance of integrating with multiple back-end systems spanning across an organization becomes essential to make an impact on the entire process lifecycle.

These integrated technologies move from the integration of emerging technology to the industry standard. It is important to note that process intelligence solutions are on the rise, offering more than simple mining. They are not glued to a single automation or workflow tool. It helps analyze all aspects of an organization, regardless of system, and puts people at the forefront of process automation. They expand into a new world of task mining to help understand how people work and act as helpers and execution drivers to automate processes. They are opening up new industries that go beyond just the mining process. It enables process improvement projects to reach a new level in delivering on the promise of greater productivity, reduced risk of compliance violations, and streamlined efficiencies that can remove friction from the customer experience, improve employee workflows, and deliver greater competitive advantage.

Instead of building them, which some have experienced, automation vendors buy these technologies and give their customers access to these features for customers more quickly in their automation system. Will this continue to commodify standalone solutions faster? This is possible because it has become imperative for companies to understand processes and identify automation opportunities before automating them. More industry consolidation awaits mining, BPM, ERP and RPA operators. These mergers and acquisitions are moving the organization toward a more integrated, intelligent orchestrated cognitive automation. Just don’t get stuck in one solution.

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