04 Apr The Lifecycle of Enterprise Robotic Process Automation
The use of robotic process automation (RPA) tools is increasingly essential to enterprise efficiency. RPA helps streamline operations, improve quality, and create cost efficiency. Not surprisingly, the RPA market was the fastest growing enterprise software segment in 2018 with 60% growth. All indications suggest that the field will continues to explode, with new offerings and models emerging and megavendors including Microsoft and SAP entering the market.
Here’s how it works: RPA tools use software, or robots (bots), to capture and interpret different applications that are employed to process transactions, communicate with other systems, initiate responses, and more. For example, when you open a pdf and begin to enter your name, a pop-up screen may appear that allows you to complete all necessary fields with one click. While this type of repetitive use function is commonplace, RPA takes it further by interpreting the form (perhaps a job application), determining how to process it (forward to human resources), evaluating it against other candidates, prioritizing candidates for interviews, and generating an appropriate response to candidates (“Please come in for an interview” or “Thank you for your interest but…”). This efficiency reduces human error and allows employees to focus on more critical aspects of their job.
Many companies have incorporated RPA as part of their information technology (IT) initiatives but have not been able to fully realize a return on their investment. This is because in attempting to catch up to the technology, enterprises often end up creating a “band aid” system that addresses only their immediate or critical needs. This comes at the expense of a comprehensive and integrated approach that can meet a wider range of needs, work seamlessly within the IT ecosystem, and adapt for future growth.
To effectively maximize the benefits of an RPA requires a deep dive with process mining and discovery. Process mining provides intelligence by looking at data driven event logs, extracting the knowledge within them, and enabling organizations to make the necessary process changes to ensure conformance that leads to sustained benefits. It analyzes where in the process RPA can be implemented effectively and monitors the preparation, transition, and implementation of the customization process. In other words, process mining provides insights and direction throughout the RPA journey to ensure continuous improvement. Combining process intelligence with process automation enables organizations to attain a comprehensive and sustainable path for benefit realization.
The Automation Lifecycle Model
The Automation Lifecycle Model identifies six critical elements in the RPA process. These elements, described below in more detail, create a roadmap for your digital operations.
Throughout the RPA journey, process discovery tools are used to identify bottlenecks and discover how automation can be leveraged. Data is gathered from desktops and system logs to understand the workflows specific to each functional area across the enterprise. This also provides visibility on how individual users interact with the software and enact these workflows. Each process is customized to meet both departmental and enterprise-wide needs, so that implementing RPA offers a competitive advantage that leads to cost optimization and revenue enhancement.
Key performance indicators (KPI) and desired business outcomes should be the driver during the analysis process. Develop a clear roadmap that identifies inefficient enterprise processes that need to be reengineered and automated, and don’t forget to address gaps across and between legacy and newer core systems. The importance of systematic analysis cannot be overemphasized. Analysis is critical to the overall strategic plan in ensuring that the right processes are automated. How RPA is implemented makes all the difference, making it critical to identify and prioritize your processes before you begin to automate.
Automated bots are configured and customized to capture data and interact with applications as though they were human. They respond to events and complete the subsequent action or set of actions required to move the process forward. They can do this quickly and efficiently through machine learning (ML). ML tools allow organizations to utilize artificial intelligence advancements and applications to deal with different formats and origins of data. These tools can extract, decipher, and analyze structured and unstructured data by recognizing patterns and key phrases, which enables the combined automation and analysis of internal and external data. These tools also are self-learning so the time required to implement and analyze automated processes is compressed, allowing enterprises to realize benefits even as they scale up their automation.
In addition to process mining and machine learning, RPA incorporates several types of technologies including optical character recognition (OCR), user experience, decision modeling, and analytics. These combined technologies add to your toolbox and allow business processes to work across functions. It may be tempting to focus on specific initiatives that address the greatest number of uses but it is important to consider system-wide implications. A benefit of RPA is that it can be built using complementary technologies. This allows for the addition of solutions that will create the system architecture your enterprise needs to meet current and future KPIs.
As noted, benefits from efficiencies and cost optimization result from reaching KPIs and business goals – the primary measures of successful implementation. Other areas that demonstrate processes have been effectively employed include an increase in automation throughout the enterprise. For example, some workflows initially considered low priority may become more critical as processes in other, newly automated areas find use for that data. Further, as automation is implemented, you can increase your RPA footprint internally within the enterprise and expand your proof of concept through efficiencies and cost savings.
RPA provides continuous improvement to ensure long-term success. Thoughtful, considered analysis of users’ needs and existing gaps will help identify areas prime for automation. As processes become more efficient and users interact differently with the system, these changes likewise will be incorporated into the automation, creating even greater efficiencies. To ensure enduring effectiveness, employee education, training, and reskilling should be offered to focus resources where they can be most productive. Likewise, the creation of a managing committee or center of excellence to address governance, ongoing changes, and training will ensure that new gaps do not arise and that business goals and KPIs continue to be met.
Benefits of RPA
There are multiple benefits to implementing an RPA solution at your enterprise. Because RPA performs repetitive tasks quickly and without human error, reduced costs and operational risk, improved enterprise-wide processes, enhanced customer experiences, greater responsiveness, and improved business outcomes are seen quickly.
To achieve these benefits enterprises must optimize their RPA, which can seem daunting. Identifying a qualified and experienced partner will help smooth the journey and ensure seamless integration with existing infrastructure. RPA is disrupting the market and those who do not begin to adopt will watch their employees continue to waste time on repetitive tasks while their customers’ loyalty wavers and their competitors soar to the head of the pack.
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