The Covid-19 crisis has accelerated the pace of digital transformation. In the past 1.5 years, business models have changed completely, and there is an immense need for enterprises to quickly improve the time taken to launch new products or services. The economic uncertainty caused by the Covid-19 pandemic has forced enterprises to reduce their overall spending and focus more on improving their operational efficiencies. As the pandemic has changed the way the world does business, organizations have been quick to pivot to digital mediums, as their survival depends on it. The results of a Gartner survey published in November 2020, highlights this rapid shift. 76% of CIOs reported increased demand for new digital products and services as a result of Coviv-19 and 83% expected that to increase further in 2021, according to the Gartner CIO Agenda 2021.
The rapid shift to digital mediums has hugely impacted the backend IT teams, as most of them were not prepared for the huge demand. From ensuring secure access to thousands of people scattered across the globe to maintaining business continuity of IT operations, the IT team is under tremendous pressure. This has accelerated the move towards hyperautomation, which is different from automation. For example, while the goal of automation is to primarily automate processes or tasks done by human beings, hyperautomation goes a step forward. Hyperautomation is best defined by Gartner, when it says, “As no single tool can replace humans, hyperautomation today involves a combination of tools, including robotic process automation (RPA), intelligent business management software (iBPMS) and AI, with a goal of increasingly AI-driven decision making.” The goal of hyperautomation is end to end automation. Hyperautomation enables organizations to visualize and gain continuous intelligence and insights to drive significant business opportunities.
As the world looks for squeezing more efficiency gains, the drive towards hyperautomation will be faster. Gartner says that the worldwide market for technology that enables hyperautomation will reach $596.6 billion in 2022. Process-agnostic software such as RPA, Low code tools and AI, will be in huge demand, and organizations will move away from transitioning from using automation technologies in isolation to a more holistic and integrated automation strategy. Gartner expects that by 2024, organizations will lower operational costs by 30% by combining hyperautomation technologies with redesigned operational processes.
In the context of a data center, hyperautomation technologies can make a significant difference. Using hyperautomation, enterprises can track and scale their IT infrastructure (compute, storage and network) in an agile manner, in line with the changing demands in business. Hyperautomation technologies can also help in understanding the root cause of an issue in a better way. For example, if an application has to deliver a good customer experience, the developers must have the ability to automatically detect issues at the customer’s end, while simultaneously raising an alert to fix the issue. To do this manually and analyze the issue faced by customers at different locations, is a next to impossible task. This is where hyperautomation technologies can make a huge difference, and do this automatically. This combines different technologies such as AI and RPA to create a holistic automation solution. For example, an auto-discovery agentless bot can collect system or network or application information and populate a Configuration Management Database (CMDB), which can be later analyzed for further insights. These insights help the hyperautomation solution to better understand how applications consume infrastructure resources. Over a period of time, the hyperautomation solution gains an accurate understanding of the resources consumption vis-à-vis applications and scenarios. These insights help in proactively resolving issues and improving customer experience. The hyperautomation solution can also learn and unlearn from the issues raised, and suggest a smart and efficient way to resolve the issue.
By using hyperautomation tools, organizations can quickly automate and orchestrate more complex workflows. This includes tasks such as patching systems automatically in case a vulnerability is detected, predicting low resources (whenever the threshold is reached with respect to infrastructure consumption) and automating change requests. The biggest benefit is the promise of automatic resolution, which is much beyond what traditional automation tools provide.
In the future, as the world increasingly looks for more autonomous IT operations, expect hyperautomation to play a major role. From self healing infrastructure to databases that can recover quickly in the event of a failure or networks that can automatically configure and re-configure without any human intervention, hyperautomation can be a significant factor in making data centers more efficient.