December 11, 2020, ainerd

How Process Mining Accelerates Hyperautomation.

Using intelligent automation for core business processes is critical for organizations looking to succeed in today’s highly competitive global market. Many experts estimate that more than half of all work today can be automated. Companies want to build and grow. They need automation to squeeze more performance and business insights out of operations. But organizations often lack an executive summary of the tools to understand their processes—including the inefficiencies and bottlenecks that adversely affect business growth. Lacking that insight, they will struggle to understand what they are automating and why, and they won’t be able to fully leverage the power of automation solutions.
The leading Robotic Process Automation (RPA) products are helping businesses automate tasks and gain insights into their operations’ performance. One of its newest products to assist organizations is automated process mining, which gives companies deep insights into their existing processes. It allows companies to identify problems, redesign processes when necessary, and establish continuous monitoring and improvement.
Process mining is another in a series of powerful offerings that enable “hyperautomation”— the combination of process automation components, integration tools, and technologies such as artificial intelligence (AI) and machine learning (ML) that help standardize and accelerate automation in the enterprise.
Organizations often lack the tools to understand their processes. They often think they have an idea of the steps and flow of a particular process, but they aren’t aware of all possible deviations and bottlenecks.
Successful businesses must always look for ways to improve their growth through leaner, more efficient operations. For example, excessive operational expenses can hamper new business initiatives and reduce the bottom line. Customer service problems affect loyalty and can threaten a company’s reputation. Routine internal tasks can absorb countless employee hours that could be better spent on innovations and more productive business activities. Governance procedures and guidelines that aren’t properly enforced can lead to costly and legally problematic mistakes.
Business process automation can address all of these challenges with technology to manage processes and workflows that, in the past, were paper-based and Business challenges – and how automation addresses them handled by people. Automation can be applied to most any process that is repetitive and doesn’t require logic or human intervention to complete. And it can be deployed for consistent results and quality control, helping to eliminate human-caused errors that interfere with business functions and create money-wasting corrections.
Operational expenses can be reduced, for example, by automating the receipt and payment of invoices or by automatically routing contracts through approvals instead of using manually intensive paper processes. Customer service can be improved by automating responses to routine customer queries or technologies that help employees find emerging customer trouble spots. Companies can improve internal processes like automatically generating routine team reports or paying recurring bills. This frees up employees to execute and enjoy more important work. Today’s automation solutions can also provide an excellent means of implementing and enforcing governance across business operations.
Business automation saves valuable time for employees and enables them to focus on higher-value work initiatives. RPA is an integral part of business automation. It provides software robots and AI that watch users perform tasks within an application’s graphical user interface (GUI) and then creates automation by repeating the tasks within the GUI. RPA helps organizations increase business efficiency, drive quality improvements, and lower costs.
Now organizations recognize that they can take automation to a new level in what Gartner calls a top strategic business trend: hyperautomation. Gartner predicts that by 2024, organizations will, on average, reduce operational costs by 30% by combining hyperautomation technologies with redesigned operational processes using a combination of multiple machine learning, packaged software, and automation tools to deliver work.
Hyperautomation builds on the momentum of RPA. It encompasses RPA and disruptive technologies such as machine learning, decision management, and natural language processing for comprehensive automation solutions. It also fosters the democratization of automation, enabling technical employees and business users across the enterprise. With easy-to-use tools, employees become participants in identifying and automating mundane, repetitive tasks—and in the process, redefining their jobs and improving the business.
Process mining is an integral part of hyperautomation. It helps companies identify and fully understand existing processes to fix or eliminate the poorly designed or unnecessary ones and implement new ones to improve business performance.
Process Mining is the ideal fit for companies seeking to take advantage of hyperautomation. It accelerates RPA, providing an essential driver of successful digital transformation for companies in the coming era of hyperautomation.
Process mining gives companies a way to identify, analyze, correct, and monitor their processes across the enterprise. It complements business intelligence (BI) tools while helping organizations extract information from enterprise systems such as SAP, Oracle, or Salesforce, using that data to identify process deviations and implement improvements.
Historically, process mapping techniques were manually intensive and time-consuming. Process models were typically drawn by hand, and often, there was not enough precise data to fill in, or the input was biased. Business analysts and managers required a lot of effort and cost to extract the right data, organize workshops, and write down desired processes. This changed when data scientists at academic institutions proposed using existing system data to identify, monitor, and improve business processes. Instead of relying on drawings of idealistic business processes that could potentially overlook dozens or even hundreds of different scenarios, this new technique uses actual data for every scenario and every event.
An event log is the minimal initial data set needed to perform process mining. This event log contains every step that is performed (the activity) during the process, it records the moment at which the event happened (the Timestamp), and it provides an instance of the process (the Case ID). Based on this event-log data, process mining algorithms generate a model that shows the process as it is, not as it is perceived. Analysis can be enhanced by adding other concepts to the minimal initial data set. The result is then used for process discovery, conformance checking, and process enhancement.
Achieving a holistic view of end-to-end processes starts with task mining—which identifies, monitors, and analyzes user actions at the desktop level—and moves to process mining, which analyzes data from IT systems. Process mining helps surface high-value, high-impact automation and aligns and optimizes business goals with KPIs and tags.
Use continuous process insights and process visualization to understand how RPA performs in the context of end-to-end processes. This information helps businesses optimize how robots, systems, and humans interact, with robots handling repetitive tasks and enabling people to perform creative, value-added work. As part of this process, Process Mining connects IT system data using built-in ETL functionality to create a digital visualization of processes, which shows where deviations and bottlenecks exist and how they occur. The resulting automation delivers a high return on investment because they focus on important deviations and bottlenecks.
Optimize automation not only in end-to-end processes but also in surrounding environments. This includes other systems and the people who execute the manual steps in the process. Process Mining identifies where the greatest improvements can be made with the least amount of effort.
Achieve broad employee support for automation by providing intuitive visualizations and democratized insights. With user-friendly visualizations, users are more engaged and become active participants in process optimization, becoming stakeholders focused on a single source of truth that helps achieve desired business outcomes.
Most RPA solutions have a limited view of how their robots operate within a larger process. Most process mining solutions lack the features needed to act on the insights derived from process mining activities. Process Mining is the only end-to-end solution that tightly integrates process understanding and monitoring to act on insights with automation. This combination of robust understanding and resulting automation activities provides immense value to businesses.
Process mining provides monitoring functionality that is fast and easy to use, with a rich graphical interface. The combination of business intelligence and process mining techniques helps business users become process-aware to identify the exact cause when their KPI’s are out of bounds. Through continuous monitoring, organizations can find the necessary process improvements to achieve operational efficiency and excellence.
Providing end-users with a self-service software tool can lead to analytic sprawl as each user builds a dashboard for each new question. This results in a proliferation of dashboards and inconsistent or even conflicting results. Process mining addresses this issue by enabling a centralized data model, controlled accessibility for business users, security functions to ensure that people can only access the data they are allowed to see, and user-friendly reporting tools that help employees leverage their business knowledge and respond to issues quickly.
Process mining delivers enterprise-grade capabilities. These include server-based processing on-premises or private cloud servers, with data connections available to multiple and/or different databases; adherence to enterprise security policies and procedures; and broad access from modern browsers and operating systems, with authorization mechanisms to allow for controlled access to data. It also allows administrators to establish user roles for broad or very specific functions for groups or individuals.
Process Mining complements and enhances task mining. Task mining is used to understand processes performed by end-users, including the number of keystrokes or clicks required to perform a task. It’s the most effective way to discover and prioritize easily automated, repetitive tasks that leave a footprint on backend systems such as SAP. Combined with Task Mining, Process mining offers the most comprehensive process understanding solution.
In conclusion, An “automation-first” mindset helps organizations and their employees imagine a future that prioritizes human engagement, creativity, and productivity while using advanced technology solutions to handle mundane but important business processes. Process Mining can enhance a company’s long-term, stable growth by improving process efficiency and customer experience as it reduces labor-intensive manual tasks. It unlocks data-driven insights and unveils optimization opportunities, providing a holistic overview of company processes while delivering greater transparency and continuous improvement.