RPA is a technology that aims to reduce costs and improve results for organizations by automating key business processes. While it has been around in various forms for the past few decades, only in recent years has RPA experienced widespread adoption and become a recognized and valuable tool in driving enterprise digital transformation. Organizations worldwide are rapidly adopting this innovative technology to automate repetitive, rules-based tasks – work previously done by employees was now able to be performed with software robots or “bots” that simulate real people performing jobs such as data entry, form processing and record-keeping.
Despite its promise for increased productivity and reduced operating expense (OpEx), many organizations struggle when trying to implement RPA successfully, both from an IT capability standpoint and also because they lack a plan on how to implement and successfully run the solution.
In fact, more than half of all RPA projects fail for various reasons. Even though we hear about successful (and not as successful) project implementations, such as those at Aon Hewitt, Bank of America or CBRE, there is little information or guidance on the “how” – the strategies and techniques that organizations should employ when implementing this innovative technology. And because of its similarities with traditional application development initiatives, it is easy to assume that simply automating business processes can be achieved through standard IT practices and methodologies.
However, this is often not the case: RPA projects require different implementation approaches and consequently must be different from traditional software development projects – while there is some overlap, what works well for RPA projects will not necessarily work for traditional application development or IT operations.
In this blog post we will look at the 5 secrets to successful RPA implementation and give you a checklist of things to do before your RPA project kicks off.
1. Do Your Homework: Gain Business Alignment
Although it is certainly useful and important that organizations gain business alignment around their digital transformation initiatives, such as that provided by Gartner’s AIOps technology and AI-assisted pre-production adoption programs, this also holds true when implementing RPA. In fact, gaining business alignment around an RPA project may be even more crucial than with other types of digital transformation initiatives because of the importance of human interactions in the overall business process; there are numerous manual tasks that will be carried out, even if only slightly changed. As such, it is important to gain business alignment around RPA at all levels within an organization (i.e., financial businesses, departments and jobs) rather than just at the enterprise level.
Furthermore, this is particularly valuable when involving key stakeholders who manage workflows with inbound or outbound manual processes. They should also be involved in the process of defining how RPA can automate these processes through bots taking on existing IT applications and infrastructures which they already know well – thus avoiding wasted time-to-market by having to learn new technologies or technology stacks for no reason.
2. Do Your Homework: Plan Your RPA Implementation
Before proceeding with an RPA implementation, it is important to understand all the key stakeholders, what they are responsible for and how their efforts tie together – this will provide a big picture of where you are going. For example, there may be multiple teams responsible for different aspects of resolving an issue or performing a particular job function that results in manual work. Before beginning your project definition process, it is important to gain organizational alignment around the following high-level areas which must be addressed before kick-off.
3. Do Your Homework: Plan for Standardization and Continuous Improvement
In order to make RPA accessible to a wide range of people across an organization, it is necessary to standardize on tools, methodologies and business practices. This means more than just following best practices from one project to the next – it requires embracing a culture where automation processes are continuously improved upon by making them smarter and integrating new features into existing solutions and continually reducing any repetitive work that may exist in the business process.
4. Do It: Implement Automation for Processes That Already Have Support with Low Risk
While we’re all excited about automating new processes using emerging technologies, such as AI-assisted pre-production adoption programs or cognitive/AI solutions, this will not be possible in every case – especially not at the beginning of an RPA implementation. Instead, we recommend that you start by automating processes which already have support and low risk: By taking on existing IT infrastructure and applications with well-known data and functionality, bots can be developed and deployed quickly to begin delivering value to the organization.
5. Do It: Build a Robust Governance Model with Leadership Support
What differentiates successful RPA implementations from unsuccessful ones is often not the technology but rather how it is adopted across an organization: Where there is little or no governance model requiring leadership buy-in for continuous improvement efforts while establishing automated business rules; where users are free to take shortcuts without any consequences; where key stakeholders do not know who is responsible for particular business functions; or where data governance is not well-defined… failure is almost certain.
Conclusion:
Robotic Process Automation has already become the basic need for all leading business because of its sophisticated features which are helpful to simplify day-to-day tasks.
