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Eliminating Human Error with Robotic Process Automation and Data Tasks

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Eliminating Human Error with Robotic Process Automation and Data Tasks

For several years, experts have discussed the future role of big data. Upcoming changes include robotic process automation and the Internet of Things.

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For several years, experts have discussed the future role of big data. Upcoming changes include robotic process automation and the Internet of Things.

What is robotic process automation? What role will it play in the workplace in next 5, 10 or 50 years?

Employees spend a large portion of their day doing remedial tasks, such as copying and pasting data from one location to another. Companies can rely on algorithms to automatically handle many of these tasks.

Deloitte claims that robotic process automation is beneficial because it eliminates the cost of retaining human employees.

“RPA has the potential to transform today’s workplace as dramatically as the machines of the Industrial Revolution changed the factory floor… Software, commonly known as a ‘robot’, is used to capture and interpret existing IT applications to enable transaction processing, data manipulation and communication across multiple IT systems. Multiple robots can be seen as a virtual workforce – a back-office processing centre but without the human resources.”

Deloitte makes a valid point, but there is even more important benefit of using robotic process automation to handle data tasks. Eliminating the need the need for human employees also reduces the cost of human error.

How Does RPA Mitigate the Role of Human Error?

According to the National Association of Software and Services Companies, domestic businesses can cut costs by up to 65% through robotic process automation. They can pay off their initial investment in as little as six months.

One of the main reasons RPA helps companies save money is by the reduction of human error. A 2008 whitepaper from IDC found that human error costs the average multinational corporation an estimated $62.4 million a year.

“Large enterprises are each potentially losing tens of millions of dollars to what is termed employee misunderstanding,” the paper states.

As long as the applications are properly programmed with the right data, they can handle the process more quickly and accurately than a human employee. Here are some examples of RPA applications.

Processing Customer Requests

Companies spend a significant amount of time every day responding to and resolving customer inquiries. These requests include increasing their credit line, asking for an extension on their next payment, filling out an incident report and applying for a new credit card.

Recent advances in digital technology allow customers to submit these inquiries online. With the exception of some highly regulated activities (such as requests for healthcare information, which are subject to HIPAA policies), information can be processed without involving a human employee. The RPA applications have access to important data, such as consumer billing information and credit scores, which allows them to automatically complete the task without an intermediary employee.

Consistency in Marketing

Marketing is one of the most important functions in any organizations. Organizations need to be consistent to build their brands. Unfortunately, marketing employees often have difficulty being consistent, because their mindset changes from day to day. Marketing automation tools such as GetResponse are eliminating these problems.

Compliance Reporting

Most organizations must correspond with multiple regulators and other government bodies. These include OSHA, the IRS, state insurance commissioners and the health department. They often need to submit W-4s and other paperwork at least once a year.

Human processing errors can lead to expensive fines, revoked licenses and other consequences. Fortunately, a properly programmed RPA application can handle these processes with minimal risk of error.

Risk Management

Every business faces various risks every day, including the possibility of fraud, delinquent payments, and supply chain disruptions. These risks can be minimized by establishing the right controls ahead of time. However, employees often ignore protocol and succumb to their own biases, which can expose the company to unacceptable risks. Creating a RPA application and training employees to follow it can drastically reduce these risks.

The insurance industry has started using RPA to improve its actuarial analyses. Accenture recently released a report titled “Robotics in insurance: A holistic approach to automation.” Accenture states that RPA will play an increasingly important role in the insurance sector in the future:

“There’s already a pervasive culture of change in the insurance industry. The quest for efficiency gains is a major driver, along with the need to keep pace with evolving consumer expectations and investment in new digital technologies. Robotic process automation (RPA) is a natural fit in this new environment because change can be delivered with speed and agility to realize benefits quickly. Further, RPA can automate the end to end lifecycle by integrating new front end digital technologies with back office environments.”

The gaming industry is also using robotic process automation for risk management. Fraud is a growing concern in this industry, especially after a £21 million fraud ring was discovered earlier this year. Daily Accas and other gaming brands are using new RPA fraud detection algorithms to combat the growing threat.

Once fraud is identified, these brands can report it to local prosecutors. They can also use various tools to find the district attorneys in the offender's jurisdiction and request extradition.

RPA is the Next Frontier

Robotics process automation is still a fairly new concept. However, it has already made substantial changes in many industries across the globe.

RPA will play an even more important role in the future. Are you prepared for the next industrial revolution?

Take a deep dive into Bluetooth mesh. Read the tech overview and discover new IoT innovations.

Topics:
big data

Opinions expressed by DZone contributors are their own.

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