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Ever since Gartner coined the concept of hyperautomation, it has garnered a lot of buzz across the business landscape. Hyperautomation brings together multiple components of process automation that stimulate the ability to automate work. It coalesces digital transformation technologies such as artificial intelligence (AI), NLP, deep learning, advanced analytics, vision/speech analytics and process mining, in addition to RPA at its core to automate complex processes.
Unlike automation that is the simple optimization of task processes, hyperautomation has an extra layer of robotic intelligence capabilities making the processes even smarter. Analytics Insight here compiled top real-world use cases of hyperautomation where it enables the industry on their automation journey.
Let's have a look at the top 10 hyperautomation use cases in 2020.
Implementing hyperautomation in banking, financial services and insurance empowers all banking processes. It is significantly apt for regulatory reporting, marketing, sales & distribution, bank servicing, payment operations, lending operations, back-office operations, enterprise support, among others. It is also able to prevent suspicious actions as intelligent automation solutions empowered by Al algorithms can efficiently monitor the transactions and proactively identify the fraudulent activities. As claims processing is the most critical process for insurance, it can considerably benefit from hyperautomation technologies.
Healthcare is a much regulated sector where effective process optimization, regulatory compliance, and better patient service are key priorities. However, hyperautomation represents a great opportunity for the healthcare ecosystem to deliver realizable business value and deliver superior patient care at a rational cost.
The emergence of e-commerce has propelled brick-and-mortar retail stores to make a paradigm shift towards digital transformation. It is also crucial because today's customers have so many options available to fulfill their requirements. In this context, hyperautomation technologies can help retailers by automating their numerous business areas such as order management, payments, transportation, warehousing & inventory, supplier management, risk management, procurement, data monitoring, among others.
As customers' expectations are multiplying exponentially, businesses need to resolve customer questions or concerns on time with increasing professionalism and proactivity, across all channels where their customers are. By integrating hyperautomation technologies like intelligent automation, businesses can fully automate end-to-end processes while enhancing others that still require some manual oversight and control. They can be advantageous in engaging customers in any digital or live touchpoint. Amazon Go grocery stores are one of the apt hyperautomation examples of effective customer service.
The rapid surge in fraudulent activities is one of the primary concerns for the payment industry. However, many companies have implemented robust anti-money laundering (AML) measures to thwart money laundering right at the point of origination and dodge further damage to the business as well as society. Hyperautomation technologies like RPA, AI and machine learning are further enabling institutions to continuously monitor their ecosystem in a highly automated manner. Combining RPA bots gleans related data and processes to validate customer records and detect fraud.
The construction industry is complex in nature where workers' safety is inevitable. Using hyperautomation in this space cannot only empower companies to transform how their business gets done, but also augments workers' safety and ability to do their work faster with available resources and fewer errors. The technology also allows them to direct time and energy to other essential work.
Reskilling or upskilling the workforce amplifies the opportunity for an organization to get the most out of their business strategy. In a UiPath survey of office workers from around the world, 86% of respondents say they wish their employer offered opportunities to acquire new skills (reskilling) while 83% wish their employer gave them more opportunities to enhance their current skills (upskilling). RPA leads to predictable redundancies along with a host of new opportunities for professionals willing to upskill.
Today, businesses are increasingly turning to hybrid-cloud or multi-cloud infrastructures where integration is an integral part of the efficiency process. The integration of systems powered by hyperautomation allows them to communicate seamlessly, ensuring all vital systems have access to the same centralized data.
Technologies like RPA, machine learning and AI make automation services effortless by eliminating possible human errors. They can boost productivity, save time, and lower costs. With all modes of automation working closely together, businesses can step beyond a single technology's one-off advantages to a state of true digital agility and versatility at scale.
Return on investment (ROI) is a key performance indicator that enables a company to determine its profitability of expenditure. The ability to calculate return on investment is extremely valuable for any business, regardless of size or industry. By using advanced analytics, businesses can analyze the efficiency of an investment based on the tasks automated and the money saved on a regular basis.
Moreover, Gartner predicts that by 2024, organizations will cut operational costs by 30% through hyperautomation technologies and redesigning their operational processes.
