Gartner: CIOs need to focus on supporting mobile, context-aware services, analytics

 

A recent Gartner poll of 2,800 chief information officers globally reveals public cloud is in itself of minimal focus among a wide range of deployment options they must consider to support the next generation of applications, services and devices. The firm said CIOs need to instead focus on supporting mobility and using analytics to improve operations.

According to the Garnter survey, nine per cent of CIOs today are not even considering cloud computing for software-as-a-service projects, a number that increases to 15 per cent for infrastructure-as-a-service projects.

“I&O leaders have been more protective of their existing infrastructure and, in many cases, have been the biggest obstacle to cloud-based solutions, often resorting to cloudwashing as an excuse to not seriously pursue a true cloud-based solution,” said Dave Russell, vice president and analyst at Gartner.
“Instead, I&O leaders should institute a ‘cloud-first’ consideration for every project on an application-by-application basis,” Russell said.

“Rather than ignoring the cloud outright, or only reluctantly considering it, evaluating all implementation models at the outset of a project can help save time and produce better results,” added Mike Chuba, research vice president at Gartner.

The firm said the results show enterprises are recognizing the need for advanced analytics to improve operations and enhance the IT department’s understanding of internal users, and the need to support more mobile workstyles, which both have infrastructure implications.

“The CIO survey responses indicate that mobile devices are now the primary or secondary interface for a significant number of IT investments. The survey also showed that 71 per cent of CIOs felt an increasing need for context-aware services. For I&O leaders, this means mobility must now be a top concern in system design,” the firm said.

“To support the changing analytics game, I&O leaders will need to lay an IT foundation for predictive analytics — an effort that is difficult but decreasing in cost thanks to parallel processing frameworks that can run analytics solutions.”


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