In recent years, companies have increased their investments in automation technology to stay competitive and keep pace with changing market conditions. At the core of this shift is robotic process automation (RPA).

When executed successfully, RPA deployments can transform an organization, helping it achieve increased productivity and improved customer service.

However, as we’ve seen with ERP implementations, it’s easy for technology initiatives and business transformations to veer off track.

Today, we’re sharing a few common reasons for RPA failure and a few tips to help your company avoid it.

7 Reasons for RPA Failure

1. Lack of Project Management for RPA Projects

RPA projects fail without proper governance and oversight. While RPA can take the place of many manual tasks, project management isn’t one of them.

For example, the formation of a project team and the assignment of project sponsors are two tasks that can’t be automated.

Read our blog, What is a Project Sponsor?, to learn more.

A Large Governmental Entity's Failed Implementation

Panorama’s Expert Witness team was retained to provide a forensic analysis and written report to the court regarding the failed implementation of a major software developer’s ERP/payroll system.

2. Underplaying Bot Training

You put in the work and built the bot. Now, you can start enjoying the easier work, right? Not quite.

Even when the bot development process is complete, it will still require support to run successfully. This is especially the case right after you build it because it’s still learning different scenarios.

All too often, companies forge ahead and expect the bot to keep up, only training the bot for a short period of time and expecting the bot to navigate the rest.

However, even with a robust development model, your bot will still encounter new situations that it wasn’t initially prepared to maneuver.

These are valuable learning opportunities for the bot, as long as you harness them as such. On that note, plan to provide multiple re-training sessions until the bot is fully prepared to handle any condition it encounters.

Still, remember that there will likely be environmental changes that will require human intervention. In this way, the bots are more like employees than machines, requiring reminders and assistance any time their surroundings shift.

Success Strategy: While navigating the complexities of scaling automation projects across an organization, many companies find success by establishing a Center of Excellence (CoE). A CoE acts as a central hub for RPA expertise and resources, providing support, training, and best practices guidance to various departments. Think of it as your RPA command center, ensuring smooth implementation, knowledge sharing, and continuous optimization. This not only empowers individual teams to build effective automations but also fosters a collaborative culture for maximizing the overall impact of your digital transformation.

3. Automating the Wrong Tasks

When you first research RPA, you may think you’ll want to automate many basic tasks as soon as possible. Yet, before diving into this effort, it’s important to understand the true costs and benefits of doing so.

While automating smaller, easier tasks might be beneficial, those benefits are often low in value and limited to individual users.

Remember: Having the ability to automate doesn’t give you the green light to do so. Instead, take a look at your business processes and conduct business process management.

Then, consider how your company could leverage automation to support improved processes. This way, you can optimize a widespread function, rather than a single task.

4. Unauthorized Deployments

With a bot, it’s easier than ever to create new code. While this has traditionally been a task reserved for the IT team, that power could extend to frontline employees as soon as you implement RPA.

In some cases, this could leave your organization vulnerable to shadow deployments, or deployments that operate outside of your company’s direct jurisdiction.

At worst, shadow IT can negatively impact your operations and undermine your cybersecurity. It can also compound the complexity of a task, making it more complex than if it were handled manually.

We recommend educating users early regarding the proper usage of RPA bots. For example, you should provide training around how to measure, monitor, and log the creation and usage of bots. Not every task will be suitable for RPA, and team members should know how to measure each task’s viability in this regard.

5. Sky High Expectations

To reach its full potential, RPA implementations must be handled with care. This means taking the time to perfect your RPA environment, fine-tune your requirements and designs, and test your automated processes.

RPA fails when you rush ahead and set unrealistic goals. Then, you prematurely assume the project has failed when it doesn’t deliver on those expectations. Our computer software expert witnesses have analyzed a number of projects that have fallen short of expected benefits because no one understood what it took to get there.

Success Strategy: Unrealistic expectations can quickly derail an RPA project. Some might dream of overnight automation miracles, while others underestimate the effort and resources required.

Take AT&T, for instance. Initially driven by high hopes for effortless automation, they encountered challenges and adjusted their approach. By focusing on achievable goals, investing in training, and establishing a Center of Excellence, they transformed their initial vision into a robust RPA program delivering $100 million in annual benefits. This example serves as a reminder that success lies in setting realistic expectations, adapting to challenges, and continuously optimizing your RPA journey.

6. Strictly Technical Focus

Your RPA implementation is more than a technology project. At its core, it’s a business initiative that affects everyone in your enterprise.

As such, it’s important to address the “people side” of the change just as much as you emphasize the software developments. When you shift your mindset in this way, you can prepare your employees to embrace and correctly use the new tools at their fingertips.

Organizational change management is a key part of this. This involves communicating the change to your team members and ensuring they’re equipped with the knowledge and skillsets required to use the new technology.

7. Inexperienced Partners

If you hire a system integrator and a software consultant to help you navigate this change, both parties should have a solid amount of RPA experience within your industry. This ensures they can take the lessons they’ve learned in the past and apply them to your project.

Read our blog, What is a System Integrator?, to learn more.

How to Avoid RPA Failure

Avoiding RPA failure requires careful consideration of how your company can make the best use of advanced technology. While RPA has many benefits, it can also drain your resources and frustrate your employees if the rollout isn’t planned correctly.

Learning from the mistakes of other RPA projects can help you begin your RPA journey on the right foot.

If you’ve already encountered issues, it’s not too late to correct them. If you’re just starting out, we can help you stay the course. Contact our ERP implementation consultants below to learn how to select the right ERP software, AI tools, and RPA bots for your organization.

Posts You May Like:

Buzzword Breakdown: Predictive vs Prescriptive Analytics

Buzzword Breakdown: Predictive vs Prescriptive Analytics

In today's data-centric world, the terms "predictive analytics" and "prescriptive analytics" are increasingly becoming part of the business lexicon. Both methodologies offer a forward-looking perspective but cater to different needs and outcomes.  Understanding the...

AI Implementation Tips for Savvy Business Leaders

AI Implementation Tips for Savvy Business Leaders

Embarking on an AI implementation can feel like navigating uncharted waters. From virtual assistants to computer vision to deep learning, the knowledge gaps companies face can be vast. However, before you become a data scientist, remember that an AI project is...