Why RPA Solutions Aren’t Always the Answer

Key Takeaways: 

• Despite RPA’s popularity, there’s a high failure rate of up to 50% for projects. There are limitations you need to understand before undertaking RPA initiatives.
• RPA is best suited for simple tasks involving consistent data. It’s challenged by complex data processes and dynamic environments
• Complete automation platforms are the best solutions for complex data processes. They support advanced automation features, enabling broader and more efficient automation.

The market for robotic process automation (RPA) software solutions continues to be a growing segment of the digital transformation marketplace – with an estimated growth of over 20% per year, according to Gartner.

If you’re excited about the prospect of implementing RPA solutions at your organization, it’s important to keep in mind that despite the continued rapid growth, there are still many questions that need to be answered about the efficacy and reliability of these solutions.

RPA projects continue to have a high failure rate of up to 50%, so before adopting these technologies, it’s essential to understand the opportunities and limitations of automating complex processes that deal with mission-critical data.

Read on to discover more about the hype behind RPA technologies, the challenges of implementation, and alternative solutions.

Why is RPA So Popular?

Even with all of the technological advances introduced over the past few decades, many of the data creation and management processes used by businesses today are highly manual – meaning they’re slow, ungoverned, and error-prone.

Handling highly complex data records that include hundreds of data objects is a huge headache for master data and governance teams. These records often have high error rates and aren’t standardized, which only adds to the challenge. Plus, even a small change in a material record can take minutes, and when you’ve got thousands to update, the time required for manual changes isn’t realistic for many companies.

In these scenarios, it’s easy to see how RPA presents a very appealing solution to the inefficiencies and complexities in your master data processes. After all, it’s in RPA’s very nature to address almost any manual data entry challenge by replacing the human with a software “bot” that can reliably and consistently perform repetitive data entry tasks.

This ability to automate almost any task is why RPA solutions have become so popular. But despite this apparent flexibility, you need to be aware of some severe, real-world limitations of RPA that can create even bigger challenges for your business if you’re not careful.

Limited Capabilities and Technical Debt of RPA

RPA provides a flexible set of capabilities that can be custom-programmed to perform a specific business task or process – but it’s not the right fit for everything.

RPA solutions can be great for …

• simple, straight-through tasks
• collecting and moving predictable, consistent data from place to place

RPA can cause problems when …

• processes become complex or have dynamic components
• processes, data, or other conditions regularly change

When you run into these problem areas, RPA software can become more of a maintenance and management headache than a pillar of automation success.

With that, let’s dive deeper. While RPA bots excel at streamlining repetitive tasks with well-defined rules, they struggle with complexity. Here are some limitations to consider when automating complex processes with RPA:

• Limited decision-making: RPA bots follow pre-programmed instructions. They can’t handle situations requiring judgment, analysis, or exceptions to the rules. With a complex data validation process, for example, an RPA bot might struggle to identify and handle unexpected errors.
• Brittle by design: RPA bots rely heavily on applications’ user interface (UI). If the UI changes, the bot may break and require reprogramming. This can be a challenge for applications that update frequently.
• Integration issues: Complex processes often involve interacting with multiple systems and applications. RPA might struggle to integrate seamlessly with all of them, especially legacy systems without modern APIs.
• Lack of cognitive abilities: RPA bots can’t handle tasks requiring human-like understanding or creativity. For instance, an RPA bot wouldn’t be suitable for writing reports or resolving customer complaints requiring empathy.

In addition to RPA software’s limitations when dealing with complex processes, there are more technical constraints that can limit the utility of RPA bots. These include:

• Structured data dependence: RPA solutions thrive on well-organized, predictable data. It struggles with unstructured data like emails, scanned documents, or free-form text. It likely wouldn’t be able to process a handwritten customer complaint, for example.
• Limited exception handling: While you can program rules for handling exceptions, your RPA bot isn’t immune to intricate or unforeseen situations. They might be unable to identify and gracefully handle errors outside their pre-defined parameters.
• Security considerations: RPA bots often require access to various systems and data. You need to take extra care with security protocols to prevent breaches or unauthorized access.
• Scalability challenges: RPA can automate tasks efficiently, but scaling them up for significantly higher volumes or broader process automation can be difficult. They might not be well-suited for large, enterprise-wide deployments.

The Reality of RPA Solutions

There can be a stark difference between the promise of RPA bots and the reality of implementing them.

If you use RPA bots to replace manual data entry but have to hire expensive IT personnel to maintain them constantly, can you truly realize any value from them? Swapping a manual data entry team for a new team with technical expertise may ultimately deliver net negative returns to your enterprise and delay digital transformation.

While RPA may be suitable for straightforward processes, there are better solutions for automating complex, data-intensive processes.

What are those solutions, exactly? We’ll explore that next.

Automating Complex Processes

Ultimately, most master data creation and maintenance processes fall outside of the scope of RPA and require you to consider a robust, flexible automation platform.

With a complete automation platform like Precisely Automate, you get many of the capabilities delivered by RPA bots, along with:

• the ability to automate and streamline highly complex data creation and management processes that require contingent workflows, humans in the loop, and strong process governance
• integrated data stewardship and quality checks that deliver trusted data the first time and every time
• a low-code/no-code development experience so you can employ a citizen development approach for expanding automation across more of your organization – for faster and more reliable processes than possible when you rely solely on a centralized, IT-based automation team

By implementing a hyperautomation strategy based around citizen developers, you get the best combination of resilience, scale, and efficiency and start to see the value that automation can deliver. Ready to start your transformation today? Find out more about Automate Studio, the premier Excel-to-SAP solutions platform.