Decoding Common RPA Mistakes That Can Cost You

Why are there so many robotic process automation (RPA) failures? Studies have shown that even large companies have seen 30-50% of initial RPA projects fail. The good news is that we all can learn from those failures and optimize a successful RPA deployment.

Over the past decade, RPA has become a common subject in enterprises, and it is already delivering value. From helping with aggregator e-commerce apps to automating payment reconciliation processes, RPA allows companies to enhance their productivity. The early adopters are achieving significant benefits; however, businesses need proper RPA guidance and to take the correct approach to automate their tasks.

Current state of RPA

The RPA market is predicted to grow by 57% in 2019, and Forrester has said more than 4 million robots will be in production by 2021. Besides regular data automation and processing, what is RPA being used for?

  • RPA is leading at automating repetitive manual tasks. RPA, together with business process management, delivers next-level enterprise agility.
  • RPA is allowing a new generation of intelligent apps. Technologies like optical character recognition (OCR), natural language processing (NLP), machine learning (ML), artificial intelligence (AI) and predictive analysis are jointly leading to an intelligent automation architecture that will help the future workforce.

Despite different industry use cases, the success of RPA tools is linked to an enterprise’s data management strategy. Many enterprises are eagerly waiting to develop a deeper understanding of what RPA is, how it applies to their work process and how to take the plunge.

Requirements of RPA implementation

Many enterprises get confused about which process to automate first instead of focusing on an analysis of workflow. A framework aligned with the business and objective needs to be checked to confirm the fit of RPA and its desired impact on the existing process. Here are the three perspectives to keep in mind:

Suitability. When discussing RPA, it’s wrong to assume that the entire process can be automated. RPA is best used for high volume, time-consuming and repetitive tasks. Consider the volume of transactions, scalability requirements, system dependencies and constraints to check the suitability.

Value. Though RPA can’t solve all your challenges, it can support employees and allow them to work more efficiently. With time, a business can see the changes and what value RPA has added to their workflow. Businesses can gain both financial and strategic value.

Risk. Businesses must talk about the degree of risk involved in automating a process. Risks associated with regulatory needs, customer experience and system stability need to be considered.

Understanding and overcoming common mistakes and challenges

  1. Often, businesses think about the initial automation project rather than focusing on the ultimate results of RPA helping with the process across the entire office. RPA is a business-led initiative that has a strong partnership with IT, HR, security and other departments. Using RPA, IT can manage and govern the change and process.
  2. Many businesses fail to frame a comprehensive strategy, instead focusing on proof of concept (POC) or a pilot program to see that RPA delivers what it promised. Companies should conduct opportunity assessments along with the POC to ensure they are clear on the aim, cost and return to all employees involved in the process.
  3. Some businesses neglect an important part of the journey: determining how to process the software and who will take charge. This delays the work and timely delivery of the project. An RPA Center of Excellence (COE) arrangement provides the best way to manage and enhance the virtual workforce.
  4. An incomplete understanding of RPA may mean a failure to follow the correct steps, leading to failure in subsequent phases of automation production. When considering adopting RPA, it is important to have a strategy in place well in advance of the project launch, and that strategy must be adhered to.
  5. Businesses often try to apply an over-engineered software delivery method to RPA. This might take more time to implement, test and run, which in turn slows down ROI. Companies need to simplify the existing method and opt for an agile approach for the timely delivery of projects.
  6. Eliminating humans from the process results in additional costs and few benefits. Automating 70% of the tasks that are lowest value and transferring 30% of the high-value jobs to human employees optimizes the whole process. It’s always possible to make room for both the virtual workforce and human employees and complete the work within the desired time.
  7. Neglecting the IT infrastructure can slow down the process. Companies can talk to RPA vendors to know precisely which IT infrastructure can support the project. Monitoring the performance and the impact of IT infrastructure and environment must start early.
  8. RPA is not the only path toward a significant ROI. Many early adopters of RPA software are getting less than 10% of the intended ROI as an enterprise. While RPA tools can automate a large part of the process, they cannot do it all; especially tasks that require frequent customer or client interaction.
  9. The dearth of skills for production automation is another common mistake. With a little training, one can automate simple processes. But to create a scalable, resilient RPA process requires solid knowledge, skill and hands-on exposure. Companies should consult this while talking to an RPA vendor.

When considering RPA tools or RPA vendors, there are many choices. Don’t blindly select an RPA tool just because it’s what the competition uses. Use these tips to help you to avoid the common pitfalls and achieve desired results.