Does your data center strategy cover technology, processes… and people?

In today’s data centers, it’s all about automation and orchestration. Hyperconverged infrastructure has led to a ground-up rethink of all the services provided in a data center. Not surprisingly, an ever growing number of organizations are moving towards these hyperconverged infrastructures, enticed by benefits such as a rapid time-to-value, simplified management, scale-out opportunities, a lower total cost of ownership and simpler lifecycle management.

Furthermore, hyperconvergence allows organizations to dip their toes into the cloud with a step-by-step approach. They can start small and fast, allowing them to set up the right organizational processes before moving the whole data center to the cloud. It’s highly likely that our future data centers will be dedicated to specific workloads while all less critical workloads are lifted to the cloud.  

An evolving workforce

Today, many organizations are very much looking into technological challenges and their impact on processes, but there is another perspective which they must be careful not to overlook. Automation and orchestration impact not only processes, but also people. And perhaps even to a greater extent.

One of the advantages of hyperconvergence is that it allows generalists to manage the entire infrastructure with a single and familiar set of tools, instead of having specialized engineers managing each aspect of the data center separately. The good thing about this is that traditional IT roles, such as storage specialists, can expand their expertise and focus on more strategic projects – a crucial step in IT becoming a true driver of business value. The bad news is that such an evolution doesn’t come overnight.  

Plan for talent development

In an ideal scenario, it should be possible for traditional IT profiles to evolve towards more value-adding roles. For example, that of data scientist. True, these skills are often not a natural part of traditional IT roles, but nor does that mean that you should start hiring an army of PhDs in data science right away. It's good to think of several strategies that could get you the talent you want, including training your internal staff. Start by defining competencies, not just skills, for your data science teams, then identify high-potential employees and invest in them. And finally, don’t just focus on current expectations, but keep in mind your organization’s future needs as well.

On the technological side alone, your IT organization will probably need a couple of years to make the shift towards a truly software-defined data center that is fit for purpose for your cloud ambitions. So it shouldn’t come as a surprise either that the people side of the equation will also demand proper preparation. Automated technologies will be increasingly present, but for a long time to come optimum results will come from man and machine working together. Especially when they have both been optimally trained for the job!