RPA is the most rigorously adopted technology in the current scenarios. No matter if a business is big or small, automation has primarily become the most important technology to invest in. While robotic process automation promises to reduce costs while improving the efficiency of your workforce, its implementation poses a lot of challenges. If these challenges are not addressed at the very initial stage, it could lead to RPA failure.
According to a 2019 report published by EY, as many as 30% to 50% of the RPA implementations projects fail due to the lack of proper planning. Moreover, even when the organizations are successfully able to implement RPA, they struggle to keep it going.
Here are the top challenges that the firms should pay a lot of attention to get the desired returns on their RPA and intelligent automation investments.
Automating the wrong processes
As mentioned by Shared Services & Outsourcing Network in one of their surveys, organizations end up automating the wrong processes during the initial RPA phase and that ends up being the top reason for the failure of their automation implementation. As an implementer of RPA in my organization, I cannot emphasize enough the importance of selecting the correct approach to automate. Don’t pick the ‘low-hanging fruits’ without doing a thorough examination of their workflows and how they impact other operations.
As an initial step, use modern process mining and discovery tools to conduct a complete analysis of your business processes. This approach will provide you with a “digital twin” of how they now operate, allowing you to determine which processes are most suited for digital transformation. Once this is done, you can then choose from a variety of procedures, ranging from rule-based and repetitive to data-intensive and error-prone.
The main purpose of your RPA projects’ should be to limit human involvement in labor-intensive jobs that don’t demand a cognitive effort. For instance, data transmission from an invoice to an ERP system is one example. Simply described, this entails extracting information from a document, classifying it, and entering it into a business system. The procedure is broken if the necessary information is absent or mislabeled, and the bot will continue to make mistakes or cease working because certain exceptions were not included in the rules.
Rushing to automate the wrong processes will eventually lead to project delays, increased expenditures, or even project termination at the very initial stage.
Primary focus on reducing the workforce
While leaders and commentators talk about empowering staff by minimizing repetitious labor, some businesses have chosen initiatives to reduce the organization’s headcount. However, what is important to understand here is that RPA is about augmenting human intelligence, not replacing it.
The biggest advantage of using RPA is that it allows your employees to focus on higher-value work. This relieves the pressure of executing manual tasks that provide little value to the company’s growth or customer experience.
Companies also overlook the importance of training the workforce in digital skills so that they can operate alongside their digital counterparts. For instance, the developer shortage can be addressed by automation. Verticals such as Legal, HR, accounts, claims, and customer service can augment and increase their productivity by implementing no-code/low-code platforms that allow them to train bots with drag-and-drop.
Training Bots in Content Intelligence
The entire purpose of bots is that they must be clever enough to “read,” “understand,” and “make choices” about the content they’re processing because all business processes rely on both structured and unstructured data. This is just like hiring a resource who is completely capable of both reading and understanding the information present in a document.
It is important to understand that RPA cannot understand unstructured documents on its own. You’ll need content-aware AI bots for this. Bots or digital agents, as we call them at AIRA should be able to read documents, categorize, route, extract, and validate data from them, and do other jobs linked to comprehending and processing unstructured text in this way.
Using content intelligence in conjunction with RPA can help your company speed up processes and prepare for new ways to communicate with customers, such as interactive mobile apps, cognitive virtual assistants that mix voice and conversational AI, and chatbots.
Dedicated monitoring post Deployment
Many organizations’ centers of excellence use process mining to assist firms to keep a track of what their bots do well and identify areas where they may improve. This approach to process improvement, powered by advanced machine learning and data analytics, can significantly help organizations optimize their automation.
This analysis, when combined with the event logs from bots, will aid in the identification of bottlenecks, inefficiencies, control, and data quality issues, and more, providing leaders with comprehensive process intelligence.
Keeping track of deployed, active bots will also help you monitor your KPI so you can take fast action if the goals aren’t being fulfilled or you run into problems.
RPA can be a useful tool for accelerating an organization’s ongoing change across multiple dimensions. It must, however, be linked to a broader, more holistic digital intelligence plan that includes AI and process mining technologies to provide an end-to-end perspective of your business workflow.