What is hyperautomation?

When robotic process automation (RPA) hit the scene, many called it macros on steroids. RPA is the use of software robots to mimic repetitive, rules-based tasks traditionally performed by humans. But RPA had its limitations, including working on unstructured data and focusing on a single task. Hyperautomation represents an evolution. Instead of depending on a single, out-of-the-box technology, it adds more intelligence by leveraging a broader set of tools. Think of it as RPA on steroids.

By combining the right technologies, hyperautomation seeks to automate, simplify, discover, design, measure, and manage workflows and processes across the enterprise. Depending on an organization’s needs, there are many ways you can mix technologies to create a hyperautomation stack. A standard recipe includes the following:

● RPA

● Business process management (BPM)

● Artificial intelligence (AI) and/or machine learning (ML)

● Advanced analytics

The amalgamation of RPA, BPM, AI, MI, and analytics automates all the tedious but essential tasks and workflows - freeing up your human workers to add value on a higher plane.

Why should your business adopt hyperautomation now?

In April 2020, Coherent Market Insights released a report forecasting that the hyperautomation market will increase at a compound annual growth rate (CAGR) of 19% between 2019 and 2027, surpassing $23.7 billion by the end of the forecast period. The manufacturing segment is the fastest-growing segment in terms of adopting hyperautomation because of the pressure to convert traditional factories into smart factories.

In addition, it’s likely that the demand for goods and services across all industries will come back with a vengeance once economies begin to recover from the current restrictions in movement and limitations related to COVID-19. Businesses that want to leverage digital transformation and reap the rewards of a post-pandemic business climate should be considering a hyperautomation strategy now.

So what do the processes look like?

The pandemic has accelerated the pace of many hyperautomation projects. It's safe to say that several government agencies are stretched like never before. In the United States, GCN reported that the Affordable Care Act health insurance program processes tens of millions of consumers each year, along with up to 45 million documents annually, and this will only increase this year. The program uses an intelligent automation platform to automate the eligibility verification process plus AI-enabled tools to extract data on a massive scale.

The RPA bots use the same case management systems, rules, and governance as a human employee would - but at an impressive rate of six times faster - while the analytics capabilities monitor the processes and workflows. Ultimately, hyperautomation completes as many as 300,000 processes per month, saving thousands of labor hours and providing surge capacity that would otherwise be manual.

Let’s look at another example. Employee onboarding is typically a complex, multistep, manual process that requires a lot of HR bandwidth. But it’s also an area that can be easily streamlined with cognitive automation. Companies like Walmart and Amazon are growing now more than ever, and they are continually hiring to meet the demands of the new normal.

Hyperautomation can help by taking care of many required tasks in a fast, efficient, predictable, and error-free manner. RPA bots can transfer data from a new hire’s forms to internal HR systems. Based on the role of the new hire, AI can recommend the most relevant policies and training programs based on actual employee usage for that position. This provides new hires with a starting point so they can be immediately proactive and productive, rather than waiting to be told what to do or wasting valuable time searching the company's intranet for the right information.

Proof of concept to implementation: the mindset
So, how can you ensure that a hyperautomation strategy delivers exactly what you need? The key is to scale your vision of this innovation by understanding what's possible and channeling all deployment efforts to deliver tangible, consequential outcomes over time. To avoid getting stalled in the proof-of-concept stage of a digital transformation, you need a solid, cross-departmental strategy and clear expectations. Be sure to weigh the following considerations:

● Know your processes. When asked to illustrate a process from end to end, people often conflate or miss steps. Automating complex processes requires developing a crystalline understanding of every step along the way to completing a task. Thankfully, significant vendors are now developing automated process discovery tools.

● Set clear business goals. Here’s an example of a clear, concrete goal: Hyperautomating 80% of the manual processes to secure a 20% higher profit margin by Q4. An objective like this would motivate managers across departments to be proactively involved in the initiative.

● Working with the right partner. Businesses often lack the expertise to initiate a cross-functional Center of Excellence (CoE). Intelligence from a consulting and innovation partner is critical to set the criteria for success, calculate the costs and expected ROI, and deliver on it. When it comes to hyperautomation, the best partner is the one with both technology expertise and knowledge of your industry.

Hyperautomation technology and tools can empower you to advance sustainability by reducing operational costs and increasing revenues. It can also democratize technology by giving your team easy access to technical and business expertise. The advantages of hyperautomation can free your people to do what humans do best: think and do creatively. The possibilities are endless, and with the right mindset and a perfect partner, you can reach new levels of success through hyperautomation.