There is a growing trend to integrate process mining functions with BI, and some companies have built solutions based on business intelligence tools.
The rise of process mining has opened up a new frontier of software combination and collaboration. Enterprise software giants such as Microsoft, SAP, and IBM are buying process mining startups to expand their intelligent process automation capabilities. In addition to the giants, there are companies, large and small, that are joining the process mining industry through acquisition or with flashy new startups. Many of these companies already specialize in automation, for example Microsoft’s Power Automate. The trend appears to be moving towards organizations buying or building process mining technology to leverage its capabilities to accelerate adoption of their primary offering of automation products. These new combinations of software are opening up new industries, but are they putting an end to the standalone process mining industry?
Going to the basics
Process mining software is an event log based tool that helps organizations understand their business processes, identify the bottlenecks and improve the efficiency of their work. Some of the benefits that process mining software offers are:
- Help identify and resolve bottlenecks in processes,
- Provide a better understanding of workflows for better analysis and design,
- Identifying opportunities for process optimization, etc.
Applications such as ERP, CRM, ITSM and other recording systems automatically create event logs that record the actions of users in workflows. The data in these logs can then be collected or ‘mined’ to visually analyze the audit trail of the processes.
Before the process mining trend, the role of analyzing data has always required a lot of manual work for few results. Regardless of which process was examined, business needs demand that you manually review or write endless lines of code to get answers. Process mining has drastically reduced this analysis time to easily understand business processes. Business process owners could then easily connect to data sources and immediately begin to understand what worked and what was broken in their process execution systems. Process mining technology on its own is quite valuable in helping to understand operations and process execution in real time, but the real value to the enterprise lies in the ability to identify transformation and automation opportunities ahead of implementation and monitor the performance of automation bots in production after implementation. It makes more sense that this rapidly changing acquisition landscape is less about process mining itself and more about what robotic process automation, business process management and process mining can achieve together.
Process mining solutions are seen by many organizations as gateway technologies to enable and scale robotic process automation and other transformation initiatives across their business. Right now, automation companies are trying to give their customers access to insights that will help them develop their automation projects and sell more automation. Eventually, automation vendors begin to hit hurdles in finding new opportunities for transformation, and process mining solutions are key to unlocking new projects and, of course, new revenues. Choosing the right technology can and will make a world of difference.
Also see: Process Mining comes to the surface
Built from the same German building blocks
The term process mining was first coined in a research proposal written by Wil van der Aalst at the University of Eindhoven in 1999. Since then, many process mining vendors have approached data analysis and process improvement in similar ways all learned from graduate school training of their founders at Eindhoven University. These are all mainly based on the schema diagram approach. How can you distinguish one process miner from another, when so many share the same thing? When the products become indistinguishable from each other, this leads to rapid commoditization, which we may already see happening as automation players take up any stand-alone process mining solutions.
This is not something to be afraid of for the adult players. They knew that process mining alone was not enough to drive the kinds of operational improvements that enterprises seek. That’s why partnerships and advanced integrations have been so important in the process mining industry. With process mining, it is clear that you can detect repetitive work and then provide the information needed to properly automate it. However, the real gold is in the ability to build an ecosystem that can communicate with multiple systems and pass information back and forth when processes go wrong, allowing BPM or RPA tools and even people in the loop to take action. to solve things. These real-time alerts and predictive capabilities provide unprecedented insight and forward-looking control over process execution. Unfortunately, only a few have mastered this capability and have escaped the standalone process mining features. Those who still only offer the visualization of fundamental process schema analysis should be most concerned, as they will be the first to see the impact of commoditization. Today’s offerings allow almost anyone to represent the execution of processes in a Visio-like diagram.
Why are automation companies so interested in process mining?
For many years, process mining applications have provided business process owners with new understanding and insight that can save countless manual hours and help companies discover opportunities for improvement. In itself this was not enough. Recent acquisitions point to the logical evolution of leading technology vendors who have the necessary process and operational data in their systems, but are unable to understand and use that data for improvement. They already have the data and they are discovering that they can provide more value to their customers with process mining to make processes run 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 identify ROI and sell bigger and better automation projects. There are also great successes. Recently, a multinational telecommunications company used process mining to improve their customer support and service truck roles. Within the first six weeks, the process intelligence solution discovered how to save $8 million after identifying the root cause of multiple repetitive tasks and trucks sent to the same service requests.
Success of intelligent process automation depends on an ecosystem
Your business is more than just order-to-cash, procure-to-pay and ITSM processes. 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 one supplier or solution stack. 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 ecosystem using the best solutions.
There is an increasing trend to integrate process mining functions with business intelligence, and some companies have built solutions on business intelligence tools such as PowerBI and Qlik. This type of integration brings process understanding to the BI consoles that many companies already use. Others are distinguished by their unique vision of understanding, controlling and monitoring processes to support the automation lifecycle. Uniquely conceived as process intelligence from the start, these solutions go beyond traditional process mining and spaghetti diagram analysis. A better approach is to use a “timeline” to create an unfiltered, raw history of each process iteration from start to finish. These timelines are then analyzed to be compared, filtered, searched, aggregated, etc., just as a BI application analyzes records in a table. The importance of integrating with multiple backend systems spanning the enterprise becomes necessary to impact the entire process lifecycle.
These integrated technologies are moving from emerging technology integrations to an industry standard. It is important to note that process intelligence solutions are emerging and offer more than simple process mining. They are not glued to one automation or workflow tool. They help analyze all aspects of the organization, regardless of the system, and put people at the forefront of process automation. They are expanding into a new area of task mining to help understand how humans work and act as process automation assistants and execution engines. They are opening up new industries that go beyond just process mining. They enable process improvement projects to reach a new level in delivering on the promises of increased productivity, reduced risk of compliance violations and streamlined efficiency that can remove friction from the customer experience, improve employee workflow and provide a greater competitive advantage .
Instead of building them, which some have tried, automation vendors buy these technologies and give their customers access to such features to integrate customers more quickly into their automation ecosystem. Will this continue to accelerate the commoditization of standalone solutions? It is possible because it has become essential for companies to understand processes and identify automation opportunities before automating them. Further industry consolidation lies ahead for process mining, BPM, ERP and RPA players. These mergers and acquisitions move the company toward more integrated cognitive automation and intelligent orchestration. Don’t get stuck with one solution.