Hyperautomation

 Hyperautomation

Hyperautomation is the concept of automating everything in an organization that can be automated. Organizations that adopt hyperautomation aim to streamline processes across their business using artificial intelligence (AI), robotic process automation (RPA), and other technologies to run without human intervention.

Hyperautomation is an emerging approach to automation, but has already identified it as one of the top 10 strategic technology trends. They conducted a recent survey which showed that 85% of participants will “either increase or sustain their organization’s hyperautomation investments over the next 12 months, and over 56% already have four or more concurrent hyperautomation   initiatives.  “Hyperautomation is rapidly shifting from an option to a condition of survival”, ranking "outdated work processes as the No. 1 workforce issue”.

It is also important to note that the role that the pandemic has played in the adoption and acceleration of hyperautomation within the market, fueling the prioritization of digital transformation and automation initiatives over the last year. With the business ecosystem operating in a distributed manner, hyperautomation eases the burden that repetitive processes and legacy infrastructure incur on an organization and its resources. The transformation that hyperautomation affords an organization enables it to operate in a more streamlined manner, often resulting in reduced costs and a stronger competitive position.

Legacy infrastructure and processes can slow an organization down and affect their ability to be competitive. Simple, task-based automation does not deliver the cross-functional results that will drive business decision making and results. Hyperautomation transforms an organization by automating as many processes and tasks as possible.

Getting started with hyperautomation

Several steps and components can help organizations navigate their hyperautomation journey. These steps are as follows:

Gather insights on the processes, workflows, and environment. Use process mining to research how existing processes operate, where gaps, latency and bottlenecks exist, and identify opportunities for digital process automation. To generate a clear view of existing processes, some organizations will create a duplicate model of a process, also known as a digital twin. A digital twin uses technology to duplicate an ecosystem to better visualize processes, inputs, and outcomes, identify areas for improvement, and create efficiencies.

Identify the structured and unstructured data and other inputs that will be needed to accomplish the processes.

Predict outcomes in terms of efficiencies and return on investment (ROI).

Determine the automation platform and automation technologies that best serve your needs, possibly leveraging tools and algorithms that already exist. This may include using RPA, optical character recognition (OCR), AI, and machine learning with other strategic technology tools to design purpose-built bots that will perform the automated tasks.

Automate complex business and technology processes and tasks, often even automating the automated to gain greater efficiencies or further cost reductions.

Use AI tools to achieve the identified tasks, including technologies such as cognitive learning, OCR, and natural language processing (NLP). Low-code or no-code technologies, which use a graphical user interface for configuration, are incorporated to simplify the automation process, requiring less technical expertise and faster deployment.

Benefits and challenges of hyperautomation

Hyperautomation transforms businesses by streamlining business processes by eliminating repetitive tasks and automating manual ones. This has a number of key benefits. It allows organizations to complete tasks with consistency, accuracy, and speed. This, in turn, reduces costs, and generally improves the customer experience.

Any new approach to business processes or infrastructure is bound to present challenges, and hyperautomation is no exception. Many companies do not feel ready to tackle automation efforts due to raw or poor-quality data and lack of resources with technical skills to address it. Retraining programs are available which can help organizations address these needs and develop an approach that is well-suited to accomplish their goals.

Other challenges include choosing from the ever-growing and evolving marketplace of products. The decision regarding which products organizations should make available to their clients can be daunting. Given this flooded marketplace, the market expects a series of mergers and acquisitions to narrow redundancies across product offerings, helping clients evaluate potential vendors more effectively.