Intelligent Automation: The Final Frontier for Infrastructure and Operations

According to Gartner, intelligent automation is the springboard for digital transformation

Gartner Research, Vice President, Milind Govekar, has delivered a presentation exploring how Infrastructure and Operations (I&O) leaders can capitalize on intelligent process automation to deliver faster, more informed, data-driven decision making. The presentation is packed with best practice advice on making the most out of intelligent automation in I&O – and includes a step-by-step action plan for deploying the technology for digital transformation success.

I won’t spoil that advice – it’s all in the presentation – but Govekar makes a powerful case for intelligent automation being the ‘final frontier’ for I&O.

Despite the undeniable popularity of automation, Govekar argues, it is typically an opportunistic move within Infrastructure and Operations (I&O) teams. Although organizations use it to orchestrate a complex, diverse landscape of applications, platforms and technologies, islands of automation become a barrier to scaling and standardizing workload activities. Processing errors are common because of manual handoffs. And the lack of an end-to-end view of the business process makes inefficiencies and problems difficult to resolve. Moreover, 24×7 operations makes it difficult to find maintenance windows to upgrade the infrastructure in order to innovate.

Indeed, a Gartner study reveals that 53% of organizations report a shortage of people, skills, and process expertise, 46% cite challenges with process documentation and standards, and 44% report a cultural resistance to automation.

As a result, says Govekar, pockets of automation are flooding out from all areas: from server, IT process, and network automation, to client, mobile management, and cloud automation. All fragmented, siloed and sitting in islands.

Intelligent, data-driven automation

By contrast, a systematic approach to automation is policy-driven: the enterprise knows which automation artefacts exist and how to build intelligence. Systematic, enterprise-centric automation is also scalable. It can also be measurable, answering questions like: how much money is saved? How agile are the systems? What is the TCO?

According to Govekar, intelligent, data-driven automation I&O technology uses heuristic algorithms to build knowledge in the tools. In other words, automation driven by knowledge and analytics learned from human experience. Automation that is smarter. This is the direction I&O automation is heading – and the direction where automation can make a real difference.

However, when you’re faced with a spaghetti of automation, delivering I&O intelligent automation can be daunting. So how can intelligent automation move from this spaghetti towards a layered ‘lasagna’ type of automation? The solution is to think about three layers of automation that can help maximize the return on your digital transformation investments

Bottom layer: Here you have IT task automation, supporting the automation of services such as provisioning, patch management, and configuration access.

Middle layer: Above that sits IT service automation, where you might automate cloud management or application release management, for example.

Top layer: The top layer is business service automation, where IT service orchestration spills into continuous configuration automation.

All three layers are linked together, with tasked being connected to different services – provisioning to cloud management, for example. IT operations analytics is ideally suited to IT task automation and certain aspects of IT service automation. Intelligent automation, meanwhile, becomes more important for business service automation.

Make no mistake: automation provides a critical differentiator in today’s competitive environment, but only if it provides intelligent automation driven by data analytics.