Six RPA best practices to adopt
RPA offers tremendous opportunities, but enterprises need a carefully crafted strategy and execution approach to harness them. A combination of deep process expertise, technology prowess, and domain knowledge is also vital. An RPA deployment should build on six established best practices (see figure 3).
1. Prioritize the best-suited RPA use cases
Identify the most appropriate processes for RPA by looking for deterministic and rules-based parts of a process (see 1 figures 4 and 5). This will help quantify the value it can drive, and enable automation initiatives to deliver the expected results. The best approach is to start small, achieve quick wins, and build internal stakeholder confidence. As enterprises gain more experience, it becomes easier to scale RPA initiatives to address complex processes.
There are three process types that are excellent candidates for RPA implementation: ● Data-entry procedures in workflow processes: such as entering data from claims documents into a claims management system and invoice-processing functions ● Data extraction from standard databases: for example, extracting customer information to file tax claims and data migration activities from one system to another ● Routine processes: such as processing insurance claims and banking transactions
2. Determine realistic ROI expectations
The time taken to achieve ROI is one of the biggest challenges in RPA adoption. Enterprise processes continue to increase in complexity with greater seasonality, regulatory requirements, geographic variations, or numbers of exceptions, which result in longer development times and more user-acceptance testing. The time to reach break-even could range from six months for standard processes to up to two years for complex ones. The cost savings also range between 10–50% depending on the complexity (see figure 5). Enterprises should look at robot utilization in a critical way and use RPA platforms that allow robots to shift between processes during lean periods. Businesses managing large virtual workforces can consider creating centralized control to manage bots, monitor performance, and track benefits.
3. Establish a well-defined governance structure
A governance structure that defines roles and responsibilities for automation activities will help deliver successful RPA initiatives (see figure 6). Key elements include: 3 ● Guidelines and templates for assessing, designing, developing, and deploying robots, and enabling collaboration between business units ● Frameworks for internal change management ● The ability to track performance and productivity metrics to assess impact and highlight areas for improvement
4. Select capable RPA tools and operators
Leading RPA platforms are equipped to handle the most common automation scenarios. Organizations should evaluate tools with pre-built automation libraries that have re-usable components to connect to back-end systems, data extraction capabilities, and cost and licensing options. As companies mature to automate processes with unstructured data and require cognitive abilities, they integrate RPA with wider technology solutions to achieve greater benefits. It is also important to work with service providers that can offer end-to-end process support. Such providers can help your organization create an internal center of excellence that can support critical business functions or processes to improve your results.
5.Re-engineer processes to maximize RPA benefits
RPA practitioners recommend re-engineering business processes so that they produce the fewest exceptions. Inefficient processes that have critical inter dependencies on other processes and applications, along with those that are prone to a high degree of exceptions, do not generate the desired RPA outcomes. By re-engineering appropriate processes, you can increasingly include RPA as part of broader process and digital transformation initiatives.
6.Enable strong collaboration between the business and IT
A significant number of RPA failures are attributed to the lack of collaboration between business and IT functions. Business leaders often fail to include IT in RPA planning discussions as they assume that RPA systems don’t require extensive IT support. On the other hand, in the case of IT-intensive projects, IT leaders often undermine the value of a business function’s view point and do not take process nuances into consideration. RPA enablement should be a combined effort between the business and IT with an operating model that defines the roles and responsibilities of each player. While the function needs to own the operational requirements, process design initiatives, and performance monitoring, aspects such as reliability, risk management, technological compatibility, identity and access control, and compliance are for the IT organization to deliver. Enterprises considering introducing RPA to their organizations should evaluate these six practices to prioritize the processes that can best be performed by software robots, stay invested for the long term, create an effective governance plan, and lead their organization to intelligent automation.