Automation as a Path to Innovation (And With More Time to Achieve It)

By Rich Morris, Area Vice President
October 26, 2017 • 3 minute read

Leveraging automation technology, such as virtual engineers, to automate routine tasks frees up human engineers to focus on innovation.

A recent Forbes article on Gartner’s Top 10 Predictions for 2018 and beyond stated that “CIOs will be more accountable than ever for revenue generation, value creation, and the development and launch of new business models using proven and emerging technologies.”  In order to successfully transition from IT leader to business leader, CIOs must free up their teams to explore, evaluate, and deploy innovative technologies that will deliver revenue, value and new business models.

Yet for years IT organizations have struggled with the disproportionate amount of time required to ensure infrastructure and applications run securely and efficiently at optimal levels, all the time. How then does an organization free up the resources and time to explore and innovate solutions that will enable the digital organizations of tomorrow?

Enterprise IT organizations have long been in a race against time – and a race searching for additional time – as they balance managing their current IT state while innovating to keep IT and the business moving forward. In response, for years IT vendors have been selling infrastructure and applications with the promise of reducing operational overhead and the pressure on operational staff. While there is no question that systems and stacks have become more intuitive, consolidated, and easier to manage, substantial erosion of the day-to-day management overhead is not commonplace for many organizations.

Time is still precious and a luxury for many IT shops, even as corporate IT has evolved with new trends and technology that have alleviated some time challenges, but not solved them. Cloud computing has seen rapid adoption due to reduced time-to-value, utility-based computing, burst capability, and other key attributes. In its most recently published figures, Gartner predicts that public cloud services – including infrastructure-as-a-service (IaaS), software-as-a-service (SaaS), platform-as-a-service (PaaS) and Business-Process-as-a-Service (BPaaS) – will have a compound annual growth rate (CAGR) of 16.6% through 2021.

Even with the proliferation of cloud, and as many Service Providers pivot to an asset-light [1] model because of cloud, there is still ample operational overhead required to ensure off-premise deployments run at optimal levels. It is becoming a forgone conclusion that traditional datacenter deployments and cloud deployments will converge to form hybrid cloud, but does that end state solve the ongoing challenge of onerous IT operational overhead? Unless automation is a fundamental design element of the migration to hybrid cloud, the answer is likely to be no.

Enter autonomic and cognitive technologies. Their distinction from traditional infrastructure and applications is that their core design element is to alleviate the mundane, rudimentary activities among data center staff that stifle innovation.  Consider for example the impact to an organization if 90% of L1 tickets and 60% of L2 tickets could be automated via autonomic technology and virtual engineers.  What if account verification, password resets, and other basic IT help desk services could be handled exclusively by cognitive agents? In addition to the potential cost savings to the business, when automation and cognitive becomes the underpinning of IT operations, people are now free to focus on forward-looking technology considerations, and engage in higher-value tasks that ultimately could bring greater IT and business benefits.

IT is no longer a necessary back office function but rather a strategic imperative for any organization looking to sustain growth and longevity.  If IT executives are under pressure to create new revenue streams and business models, and enhance value to all stakeholders through technology, their teams are going to need ample time to figure out how to do it.

IPsoft’s autonomic and cognitive technologies optimize IT and business processes by allowing virtual engineers and agents to automate routine tasks, freeing up human talent to focus on innovation. Organizations are exploring what autonomic and cognitive can bring. As Gartner points out in another recent report,Staff Metrics for Best-in-Class Providers in Global Data Center and Hybrid Infrastructure Managed Services,” for some data center providers, “more efficiencies still need to be gained, especially as automation has not yet been fully exploited.” Meanwhile, there are dozens of customers that already have deployed these technologies with IPsoft, and are realizing real business and IT benefits.

As organizations finalize 2018 budgets and initiatives, and more importantly how to achieve those goals, they should remember to ask a very simple question: Are we going to have enough time?

Sources: Forbes, Gartner, Gartner report

[1] Generally accepted term referring to Service Providers who help customers migrate on-premise deployments to the public cloud and then provide ongoing monitoring and management of those environments.  Historically Managed Service Providers hosted those deployments on their own in-house infrastructure.

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