Robotic process automation (RPA) Pitfalls and How to Avoid them

What is Robotic Process Automation (RPA)?

Robotic process automation (RPA) has the potential to save companies significant amounts of money by shifting mundane, repetitive tasks, such as data extraction or data translation, from humans to robotic software agents.  In fact, the McKinsey Global Institute estimates that half of the activities that workers are currently paid $15 trillion in wages to perform globally could be automated with current technologies. An example of RPA would be a robotic agent that automatically opens and reads word documents or spreadsheets, identifies and extracts the necessary data, and transfers the data quickly and accurately to the appropriate business processing system. When it works right, RPA can speed up business processes, reduce manual data entry errors and free up employees to be more productive. RPA is also the first step on the road to higher value activities like machine learning and AI.

Unfortunately, many companies that have launched RPA projects have been disappointed when the savings have failed to meet lofty expectations. Other organizations have achieved early successes with proofs of concept, but have been unable to scale beyond the “low hanging fruit” processes.

In order to avoid the pitfalls that have prevented companies from realizing the full benefits of RPA, there are several key points to keep in mind, particularly when it comes to deciding whether to deploy assisted or unassisted RPA.

The Pitfalls of RPA Adoption and the Perils of Jumping in Too Quickly | Nearshore Americas

The first mistake companies make is jumping ahead and trying to grab quick and easy wins before doing the necessary strategic planning required to support a scalable, long-term and sustainable RPA deployment.

For example, companies need to make sure they don’t try to automate processes that are inherently inefficient because simply doing the wrong things faster doesn’t help the company achieve lasting business process improvement. Companies also need to analyze business processes in a holistic, end-to-end way, otherwise speeding up one part of the process might just create a bottleneck somewhere else.

For many companies, it’s tempting to implement unassisted RPA in which the software agent operates without human intervention. That can lead to early wins, but it can also lead the company into a dead end where they run out of projects that lend themselves to unassisted RPA.

Unassisted RPA requires processes that can be completed with simple decisioning, but it turns out that these processes are few and far between in the real world.

Assisted Vs Unassisted Robotic Process Automation (RPA)

The real value of Robotic Process Automation will only be realized when companies adopt assisted along with unassisted RPA, combining the speed and accuracy of robots with the complex decision-making and creative abilities of humans. By working in tandem, humans and robots can achieve the efficiency goals that companies are seeking. And RPA, if done with the requisite strategic planning, can serve as the foundation for the organization’s business process automation journey to more complex, higher-value technologies like cognitive computing, machine learning and AI.

Learn these 5 scaling RPA secrets to transform your organization

Robotic Process Automation (RPA) for Manufacturing: driving efficiency further - The Manufacturer

With robotic process automation (RPA) pilots almost everywhere, creating industrial scale has emerged as the new challenge for IT departments and shared service centres (SSCs) alike. The organisation, processes, tooling and infrastructure required to quickly develop a few in-house robots cannot simply be incremented at scale. Enterprises need to re-design their entire approach.According to a survey by HFS Research, the biggest gap in RPA services capabilities is not in RPA planning and implementation, but rather in post-implementation.

Here are five ways to meet the key challenges we hear from both IT and SSC executives about scaling robotics:

Top 5 RPA Questions that Customers Ask & Our Answers - CiGen | Robotic Process Automation | RPA

  1. Begin with the end in mind and start looking at an operating model strategy that supports the bots where they will eventually be running. However, whether you manage the bots from a centralised production environment or on agents’ desktops, there is no way around the IT department once you’ve decided to scale robots. IT departments have to make technical resources and support staff available; manage the configuration, software distribution and robot scripts; provide and maintain security access; plus track and respond to incidents. Unfortunately, it takes time and effort to configure such processes, and IT can have more pressing priorities, but presenting a clear operating strategy can help spur them on.
  2. If a business continuity plan has not yet been devised, it needs to be. If systems go down, the bots need to be re-started along with the entire software stack. Some organisations create mirrored environments they can switch to in case of extended system failures.
  3. Leverage the cloud. Cloud is generally acknowledged as the way forward for large-scale RPA operations. Cloud makes it possible to provision extra bots with one click, for example, to address sudden peaks in transactions. Cloud also enables efficient, consumption-based models. However, some large enterprises have ring-fenced clouds due to regulations in critical industries, such as in defence or banking, and this needs to be considered.
  4. Bring corporate security policies into force. Can hundreds of robots running in parallel access all corporate systems that require a human being’s credentials? They do not have an address, ID badge, a manager, an office, or a birth date – which may be mandatory to comply with existing corporate security policies. Corporate security policies need to reflect the new complexities.
  5. Realize that constant change is a rule, not the exception, for bots. Some companies leave the technical changes to IT, but manage the functional changes in the business units (finance, human resources, etc.) that own the business process, and this approach does provide more speed to resolution. For the same reason, the relevant business units can also maintain re-usable libraries of standard information. Things become more complex, though, when third parties are in the picture, like tool vendors, RPA consultants and/or business process outsourcing (BPO) providers. In fact, governance is most often cited by IT and SSC leaders as a key challenge here. It is common that RPA investments do not progress past development and test phases due to governance roadblocks. A preferred approach tends to be establishing a centre of excellence — typically within the enterprise SSC organisation — with responsibility over the policies, governance and tool/vendor selection for RPA. Still, once bots take a significant share of workload from human agents, does it make sense to keep the SSC and IT under separate organisations? And also, what is the impact on the human workforce? As we train bots to act as humans, businesses need to train and acclimatize their human workforce to co-operate with bots, understand how they operate and where to intervene.

In summary, RPA is a very hot topic currently and whilst a lot of the hype these days is around enabling technologies to accelerate the development of robots, the real challenge in scaling up your RPA digital workforce lies in better operating model design, a flexible cloud-based platform and of course, better appreciation of human nature.

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