What's the difference between RPA and hyperautomation?

Customers expect personalized service from businesses, no matter how big the company is or the industry it’s in. To meet these growing demands, brands are focusing on using automation to scale customer experiences (CX) and develop more streamlined and individualized interactions.

Notably, automation offers brands many benefits, including:

• Greater customer satisfaction. In addition to reducing call wait times, support team members can spend more time with customers as automated digital solutions will have helped filter out cases that do not need the attention of a live agent.
• Higher team member satisfaction. Frontline team members can spend time engaging in more meaningful interactions instead of performing simple, repetitive tasks.

Two of the most popular types of automation in customer service are Robotic Process Automation (RPA) and hyperautomation. RPA has been used for decades, whereas hyperautomation is an emerging trend in CX strategies.

While companies are skilled at identifying opportunities for RPA, brands often miss ways to improve the customer experience through hyperautomation. They may also not understand how RPA can help build hyperautomated processes. Knowing the differences between the two and using each to their full potential is essential for brands to make the most of their automation investment.

Here are five key differences between hyperautomation and robotic process automation to help you better identify opportunities that are ripe for change and investment.

1. Hyperautomation simulates human reasoning ability

With RPA, the system follows a series of programmed actions that are the same for every task, such as a traditional assembly line using robotic arms to put the same product in every box. Hyperautomation is an expansion of RPA, where various intelligent automation tools are combined to make decisions for each task depending on factors and data collected. Consider the same assembly line, but envision being able to detect and ensure that each product meets quality standards.

2. Hyperautomation incorporates artificial intelligence, machine learning and natural language processing

To simulate human reasoning ability, hyperautomation relies on technologies that allow systems to make predictive decisions based on data. For example, hyperautomation may use past purchase history to preselect a customer’s shipping address based on the type of purchase, such as sending large purchases to their office address and smaller ones to their home. By using these technologies, hyperautomation learns from each decision and becomes smarter with the data that is continually collected. However, the success of the reasoning depends largely on the amount and quality of data gathered and fed into the technology.

3. Hyperautomation focuses on business outcomes

With RPA, you automate each task as a standalone function. Hyperautomation addresses a complete business process and aims to automate every task possible. This begins with determining the business goal you are tackling, and then the specific outcome you are looking to address.

For example, a business may be looking to reduce their cart abandonment rate, which involves a number of complex factors and processes. The AI and machine learning aspects of hyperautomation can help companies predict which products and options a customer is likely to choose based on their history, decisions similar consumers have made and the customer’s current behavior on the website.

By analyzing this data, the technology can make decisions at specific junctures along the process that create a personalized experience for the customer, such as recommending products, using photos that are likely to appeal to them and offering customized shipping options.

Enabling a global transportation giant to achieve its hyperautomation goals

Uncover how TELUS Digital’s digital automation solutions helped to drive efficiencies, improve customer resolutions and facilitate positive customer experiences for the client.

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4. Hyperautomation easily enables future integrations

Once you automate a process using RPA, the task exists in a silo of its own, which can sometimes make it challenging to integrate it with other tasks. There may also be a limit to how many tasks can be performed. Because intelligent reasoning is built into hyperautomation, businesses can more easily modify processes as customer and business needs change.

5. RPA is a tool in the DigitalOps toolbox used to create hyperautomation

Many brands assume they need to choose one type of automation over the other, but companies often benefit from using both. When hyperautomating an entire business process, companies should consider which parts can be automated using RPA, with hyperautomation integrating the tasks into a single process.

Brands that are focused on improving the customer experience often start by using hyperautomation in one business process with a defined outcome, and then expand it to other processes. Not surprisingly, those that are not using automation may quickly fall behind competitors that are more efficient. Brands should consider leveraging hyperautomation as a key component of moving towards engaging consumers more effectively and seamlessly.