As enterprises continue to embrace globalization, digital transformation, and expansion strategies, IT is continuously required to be agile (and self-innovating), enabling competitive differentiation across all types of enterprise businesses. As a result, a CIO is increasingly seen as someone playing a strategic role in delivering on-time, flawless, and secure services within the ever-shrinking spending budget.

Though enterprises have started embracing the cloud services, the internal datacenter is still expected to be the primary load bearer before the demand is evenly balanced between cloud services and these datacenters in the coming years. As datacenters continue to evolve as hubs of information processing and repositories supporting business transformation, it is increasingly becoming clear that design, management, and operations of these need to be transformed at a higher pace than the business itself or in other words, the datacenter needs to continuously evolve itself into a smarter one to support strategic decisions. 

This smart transformation of datacenters essentially includes metrics to provide understanding about best placement of workloads (considering limitations and other constraints), better view and analysis of costs, granular data for chargeback, identifying issues even before they happen (proactive management and problem solving), enabling enterprise-wide collaboration (user-base expansion), presenting highly automated and real-time (data) environments, complete workflow support, ability to integrate/migrate live and legacy environments, and a reporting structure that is appropriately suited according to the business workflows of the organization, to mention a few.

The CIO and datacenter team (collectively) will have to go beyond the usual issues of downtime and latency and consider creating an efficient and agile environment rather than a repository of equipment in the datacenter. The building blocks of these would essentially include the smarter components like intelligent PDUs and racks, sensors (for environment, location, or geography-based data), new-age DCIM (data center infrastructure management) software, intelligent algorithms, infrastructure (software-defined/converged/hyper-converged), aggregation and analysis engines, intelligent and layered security approach (context-aware/behavioral), and intelligent workflow implementations.

Thus, management and operations would necessarily involve gaining better visibility into datacenter implementations, planning meticulously for future demand while being flexible toward the current scenario, real-time management of different environments but in a collaborative manner, leveraging the (millions) data points and information collected in real time, and analytics-led reports that essentially transform the C-level decision-making capabilities. This could also entail the marrying of various best practices, frameworks, and standards (like ITIL, 27001, etc.) to develop another set that provides better and customized security and management features best suited to an organization.

In the short term, this would essentially mean consideration of DCIM, analytics-based solutions, and implementation of smarter solutions as listed above, in a phased manner. In the long term, focus should be on to include big data initiatives at all levels (with an eye on varied benefits and accordingly the implementations), granular metrics for identifying cost associated and earmarked for every resource and service, creating new roles and responsibilities and designing architecture (and components) to drive pro-active management and operational features.

Given the constantly dynamic ecosystem, changing customer demands, and rapidly available options, the trick, however, remains to rationalize the placement of workloads in an increasingly diversified IT environment that includes on-premise and off-premise resources and services to extract maximum value in a time-bound, secure, and cost-effective manner. Once the datacenters are on the path of transformation, CIOs will necessarily have their share of time and focus from regular operations that can be spent on customer facing, impactful IT services to support strategic initiatives, and leading transformational projects.

Does Digital Transformation start with data or your business process?

 

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