Why Robotics Process Automation (RPA) Projects Often Fail and How to Be Successful

Why Robotics Process Automation (RPA) Projects Often Fail and How to Be Successful

Demand and popularity of Robotics Process Automation (RPA) is increasing with time. However, letting armies of robots move into the corporate ecosystems is not so straightforward as many people may think. Why do so many RPA projects fail and what can you do about it? 

Not having clear goals or alignment of goals 

Companies should start from the “why” of wanting to implement RPA project. Stating the reasons for wanting to do automation may seem like the obvious thing to do, but many companies somehow miss this. A project that is aimed to achieve greater accuracy of output will be run very differently from another one that is aimed at increasing speed of the work.

Another important thing about goals is that they should be agreed by stakeholders. If goals are not set out properly, it will be difficult to measure whether the automation project met the expectations of stakeholders. 

Not understanding the processes to be automated 

With robot-supported process automation, the risk is with the process itself. Some projects fail because the automation processes envisaged are not understood or the underlying automation tools are not sufficiently understood.

Projects for robotic process automation often fail because people try to apply RPA automation to their work before they even know the details of the process they are working on. If there is no proper information on the “SOP” (standard operating procedure), your RPA project will fail. Thus, it is important for the implementation team to communicate clearly with process-owners to know the processes in detail before embarking on the automation. 

Read About How to Deploy Your No-Code RPA Project Successfully in 2021

Not incorporating A.I. (artificial intelligence) correctly

RPA or Robotics Process Automation enables companies to automate tasks without the need for people to complete the tasks in the application system. RPA is able to optimize end-to-end automation initiatives and enable employees to manage the project more efficiently. This helps companies harness the power of automation in a wider range of process scenarios.

However, RPA alone has limitations and would not be able to handle processes involving semi-structured or unstructured data. For example, if your process involves getting/ reading data from printed documents which need to be verified before entering into an I.T. system, RPA will fail badly. You would need Artificial Intelligence. Imagine receiving a scanned document with watermarks! You would need various types of A.I. to ignore the watermark as “noise” and be able to make sense out of the rest of the document to pull out important data points. 

 

You can also integrate robot-based process automation with AI and ML technologies and redesign complex processes into smaller, complex tasks and then automate each task individually.  

Not choosing the right processes

A successful RPA implementation is achieved by selecting the right processes for automation. Before you can plan an effective implementation of the robot processes, you need to know about the processes you are automating, where you are, and which process you want to automate. Make sure you think critically about which processes you want to automate, your current processes and the processes you hope to achieve, and the requirements of each process.

Robotics_Process_Automation_Chart
Flowchart of Tips on implementing Robotics Process Automation (RPA) with Artificial Intelligence

The ideal processes for Robotic Process Automation should involve large volumes, requiring access to multiple I.T. applications. If your process involves just structured digital data (e.g. spreadsheets, databases, I.T. systems with data in specified fields), then plain RPA will be sufficient. However, if it involves data that is less structured (e.g. invoices, forms) or worse, unstructured (e.g. emails, contracts), then artificial intelligence will be required to various degrees.

Then there is the issue of having pre-defined rules. RPA is good for rules-based processes, but fail when the rules are not so obvious. Human-intervention and exception handling can also be tricky if there is no A.I. involved. 

Not having proper governance 

Many companies underestimate the workload required to implement initial automation and believe that RPA software and robots will continue to run autonomously without support. 

Users start to blame the lack of support from the implementation team and other key players in the organization. To get around this, responsibilities should be assigned for managing the access rights and maintenance of the automation scripts. Proper implementation of robot-based process automation will ultimately produce positive results.

Benefits of doing things right  

There is much work to be done to implement Robotic Process Automation (RPA) system from scratch, and there are related challenges that businesses need to recognize, manage, and effectively address. If you are not ready to implement the Robotic Process Automation yourself, do not step on the brakes. There are experts that you can rely on. 

Fortunately, there are tools for business automation that can eliminate these problems. Now organizations can work on RPA projects much easier with no-code software from Gleematic. RPA Deployment with Gleematic can save up to ~85% of the time needed for typical integration projects. The Gleematic RPA software is also flexible to be used in various departments of multiple industries, easy to set up, and no coding.

Reference

Goddard, W. (2021, January 14). Robotic Process Automation – Everything You Need to Know – Part 1. ITChronicles. https://itchronicles.com/automation/rpa/robotic-process-automation-everything-you-need-to-know-part-1/ 

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