Pros and Cons of RPA

Of course, quite a bit of time for a typical employee—in the back office—is spent on routine tasks. But with RPA, companies can often get a strong ROI (Return on Investment)—so long as the implementation is done right.

Here are some other advantages:

• Customer Satisfaction: RPA means minimal errors as well as high speed. A bot also works 24/7. This means that customer satisfaction scores—like the NPS (Net Promoter Score)—should improve. Note that increasingly more customers, such as from the Millennial generation, prefer to deal with apps/web sites, not people! RPA also means that reps will have more time to spend on value-added tasks, instead of dealing with the tedious matters that waste time.
• Scalability: Once a bot is created, it can be quickly expanded to meet spikes in activity. This can be critical for seasonal businesses like retailers.
• Compliance: For people, it’s tough to keep track of rules, regulations, and laws. Even worse, they often change. But with RPA, compliance is built into the process—and is always followed. This can be a major benefit in terms of avoiding legal problems and fines.
• Insights and Analytics: Next-generation RPA platforms come equipped with sophisticated dashboards, which focus on KPIs for your business. You can also set up alerts if there are any problems.
• Legacy Systems: Older companies are often bogged down with old IT systems, which makes it extremely tough to pull off a digital transformation. But RPA software is able to work fairly well with legacy IT environments.
• Data: Because of the automation, the data is much cleaner as there are minimal input errors. This means that organizations will—over time—have more accurate understandings of their businesses. The data quality will also increase the likelihood of success of AI implementations.

While all this is great, RPA still has its drawbacks. For example, if you have current processes that are inefficient and you rush to implement the RPA system, you will be essentially replicating a bad approach! This is why it is critical to evaluate your workflows before implementing a system.

But there are certainly other potential landmines to note, such as the following:

• Brittleness: RPA can easily break if there are changes in the underlying applications. This could also be the case if there are changes in procedures and regulations. It’s true that newer systems are getting better at adapting and may also leverage APIs. But RPA is not about hands-off activity.
• Virtualized Apps: This type of software, such as from Citrix, can be difficult with RPA systems because they cannot effectively capture the processes. The reason is that the data is stored on an outside server and the output is a snapshot on a monitor. But some companies are using AI to solve the problem, such as UiPath. The company has created a system, called “Pragmatic AI,” which uses computer vision to interpret the screen snapshots to record the processes.
• Specialization: Many RPA tools are for general-purpose activities. But there may be areas that require specialization, such as with finance. In this case, you may look at a niche software app that can handle it.
• Testing: This is absolutely critical. You want to first sample some transactions to make sure the system is working correctly. After this, you can do a more extensive rollout of the RPA system.
• Ownership: The temptation is to have IT own the RPA implementation and management. But this is probably not advisable. The reason? RPA systems are fairly low tech. After all, they can be developed by nonprogrammers. Because of this, the business managers are ideal for owning the process since they can generally handle the technical issues and also have a firmer grasp of the employee workflows.
• Resistance: Change is always difficult. With RPA, there may be fears that the technology will displace jobs. This means you need to have a clear set of messages, which focus on the benefits of the technology. For example, RPA will mean more time to focus on important matters, which should make a person’s job more interesting and meaningful.

What Can You Expect from RPA?

When it comes to RPA, the industry is still in the early phases. Yet there are clear signs that the technology is making a big difference for many companies.

Take a look at the research report from Computer Economics Technology, which included roughly 250 companies (they were across many industries and had revenues that were from $20 million to over $1 billion). Of those that implemented an RPA system, about half reported a positive return within 18 months of deployment. This is definitely standout for enterprise software, which can be challenging in getting adoption.⁶

And to get a sense of the strategic importance of this technology, look to see what the US Defense Department—which is engaged in over 500 AI projects—is doing. Here’s what the agency’s Joint Artificial Intelligence Center director, Air Force Lt. Gen. Jack Shanahan, had to say during a Congressional hearing:

• When you talk about smart automation, or in the vernacular of the industry, Robotic Process Automation, it’s not headline grabbing in terms of big AI projects, but it may be where the most efficiencies can be found. That’s the case if you read some of the dailies in industry, whether it’s in medicine or finance, this is where early gains are being realized in AI. Some of the other projects we take on in the department are probably years in the making in return on investment.⁷

Despite all this, there are still many failed RPA implementations as well. Ernst & Young, for example, has received large amount of consulting business because of this. Based on this experience, the failure rate for initial RPA projects ranges from 30% to 50%.⁸

But this is inevitable with any type of enterprise software system. Yet so far, the problems appear mostly to be about planning, strategy, and expectations—not the technology.

Another problem is that the hype surrounding RPA may be raising expectations to excessive levels. This means that disappointment will be fairly common, even if implementations are successful!

Of course, technologies are not cure-alls. And they require much time, effort, and diligence to work.

How to Implement RPA

Then what are some steps to take for a successful RPA implementation? There is no standard answer, but there are certainly some best practices emerging:

• Determine the right functions to automate.
• Assess the processes.
• Select the RPA vendor and deploy the software.
• Set in place a team to manage the RPA platform.

Let’s take a closer look at each of these.

Determine the Right Functions to Automate

Yes, excessive automation at Tesla was a mistake. To be precise, my mistake. Humans are underrated.

—Elon Musk, CEO of Tesla⁹

Even though RPA is powerful and can move the needle in a big way for a company, the capabilities are still fairly limited. The technology essentially makes the most sense for automating repetitive, structured, and routine processes. This involves things like scheduling, inputting/transferring data, following rules/workflows, cut and paste, filling out forms, and search. This means that RPA can actually have a role in just about every department in an organization.

Then where does this technology generally fail to deliver? Well, if a process requires independent judgment, then RPA probably does not make sense. The same goes for when the processes are subject to frequent change. In this situation, you can spend lots of time with ongoing adjustments to the configurations.

Once you establish a part of the business where the technology looks like a good fit, there are a myriad of other considerations. In other words, you’ll likely have more success with a project if you focus on the following:

• The areas of the business that have serious levels of underperformance
• The processes that take up a high percentage of employee time and involve high error rates
• The tasks that need more hiring when there are higher volumes
• The areas that you are thinking of outsourcing
• A process that has a large number of steps and in which there are various applications involved

Assess the Processes

It’s common for a company to have many unwritten processes. And this is fine. This approach allows for adaptability, which is what people are good at.

However, this is far from the case with a bot. To have a successful implementation, you need to have a deep assessment of the processes. This can actually take a while, and it may make sense to get outside consultants to help out. They have the advantage of being more neutral and better able to identify the weaknesses.

Some of the RPA vendors do have their own tools to help with analyzing processes—which you should definitely use. There are also third-party software providers that have their own offerings. One is Celonis, which integrates with RPA platforms such as UiPath, Automation Anywhere, Blue Prism, and others. The software performs essentially a digital MRI that analyzes data, providing insights on how your processes really work. It will also identify weakness and opportunities, such as to increase revenues, improve customer satisfaction, and free up resources.

Regardless of what approach you take, it is critical that you formulate a clear-cut plan that has the input from IT, higher management, and the departments impacted. Also make sure to get analytics people involved, as there could be opportunities for leveraging the data.

Select the RPA Vendor and Deploy the Software

By going through the first two steps, you’ll be in a very good position to evaluate the different RPA systems. For example, if your main goal is to cut staff, then you would look for software that is focused on unattended bots. Or, if you want to leverage data—such as for AI applications—then this will lead to other types of RPA platforms.

Then, once you have selected one, you will begin the deployment. The good news is that this can be relatively fast, say less than a month.

But as you go on to do further RPA projects, you may run into something called automation fatigue. This is where the returns generally start to deteriorate.

Think of it this way: When you start out, the focus will usually be on those areas of the business that need automation the most, which means the ROI will be significant. But over time, there will be a focus on tasks that are not as amenable to automation, and it will likely take much more work to realize even slight improvements.

Because of this, it is a good idea to temper expectations when engaging in a widespread RPA transformation.

Set in Place a Team to Manage the RPA Platform

Just because RPA provides a high degree of automation does not mean it requires little management. Rather, the best approach is to put together a team, which is often referred to as a center of excellence (CoE).

In order to make the best use of the CoE, you need to be clear on each person’s responsibilities. For example, you should be able to answer the following questions:

• What happens if there is a problem with a bot? At what points should there be human intervention?
• Who is in charge of monitoring the RPA?
• Who is in charge of training?
• Who will have the role for the first line of support?
• Who is responsible for developing the bots?

For larger organizations, you might also want to expand the roles. You could have an RPA champion, who would be the evangelist of the platform—for the whole company. Or there could be an RPA change manager, who provides the communication to help with adoption.

Finally, as the RPA implementation gets larger, a key goal should be to look at how all the parts fit together. Like many other software systems, there is the risk of sprawl across the organization—which can mean not getting higher performance. This is where having a proactive CoE can make a major positive impact.

RPA and AI

While still in the initial phases, AI is already making strides with RPA tools. This is leading to the emergence of Cognitive Robotic Process Automation (CRPA) software bots.

And this makes sense. After all, RPA is about optimizing processes and involves large amounts of data. So vendors are starting to implement systems like machine learning, deep learning, speech recognition, and Natural Language Processing. Some of the leaders in the CRPA space include UiPath, Automation Anywhere, Blue Prism, NICE Systems, and Kryon Systems.

For example, with Automation Anywhere, a bot can handle tasks such as extracting invoices from emails, which involves sophisticated text processing. The company also has prebuilt integrations with third-party AI services like IBM Watson, AWS Machine Learning, and Google Cloud AI.¹⁰

“There has been a proliferation of AI-enabled services in recent years, but businesses often struggle to operationalize them,” said Mukund Srigopal, who is the director of Product Marketing at Automation Anywhere. “RPA is a great way to infuse AI capabilities into business processes.”¹¹

Here are some other ways CRPA can allow for AI functions:

• You can connect chatbots with your system, which will allow for automated customer service (we’ll cover this topic in Chapter 6).
• AI can find the right moment to send an email or alert.
• IVR (Interactive Voice Response) has gotten a bad reputation over the years. Simply put, customers do not like the hassle of going through multiple steps to solve a problem. But with CRPA, you can use something called Dynamic IVR. This personalizes the voice messages to each customer, providing for a much better experience.
• NLP and text analysis can convert unstructured data into structured data. This can make the CRPA more effective.