The transition to data-driven operations within data centers is inevitable. In fact, it has already begun.
With this in mind, my last blog questioned why data centers still resist data use, surmising that because data use doesn’t fall within traditional roles and training, third parties – and new tools – will be needed to help with the transition. “Retrofitting” existing personnel, at least in the short term, is unrealistic. And time matters.
Consider the example of my Chevy Volt. The Volt illustrates just how quickly a traditional industry can be caught flat-footed in a time of transition, opening opportunities for others to seize market share. The Volt is as much a rolling mass of interconnected computers as it is a car. It has 10 million lines of code. 10 million! That’s more than a F-22 Raptor, the most advanced fighter plane on earth.
The Volt of course, needs regular service just like any car. While car manufacturers were clearly pivoting toward complex software-driven engines, car dealerships were still staffed with engine mechanics, albeit highly skilled mechanics. During my service experience, the dealership had one guy trained and equipped to diagnose and tune the Volt. One guy. Volts were and are selling like crazy. And when that guy was on vacation, I had to wait.
So, the inevitable happened. Third party service shops, which were fully staffed with digitally-savvy technicians specifically trained in electric vehicle maintenance, quickly gained business. Those shops employed mechanics, but the car diagnostics were performed by technology experts who could provide the mechanics with very specific guidance from the car’s data. In addition, I had direct access to detail about the operation of my car from monthly reports delivered by OnStar, enabling me to make more informed driving, maintenance and purchase decisions.
Most dealerships weren’t prepared for the rapid shift from servicing mechanical systems to servicing computerized systems. Referencing my own experience, the independent service shop that had been servicing my other, older car, very quickly transitioned to service all kinds of electric service vehicles. Their agility in adjusting to new market conditions brought them a whole new set of service opportunities. The Chevy dealership, on the other hand, created a service vacuum that opened business for others.
The lesson here is to transition rapidly to new market conditions. Oftentimes, using external resources is the fastest way to transition to a new skillset without taking your eye off operations, without making a giant investment, and while creating a path to incorporating these skills into your standard operating procedures over time.
During transitions, and as your facility faces learning curve challenges, it makes sense to turn to resources that have the expertise and the tools at hand. Because external expert resources work with multiple companies, they also bring the benefit of collective perspective, which can be brought to bear on many different types of situations.
In an outsourced model, and specifically in the case of data analytics services, highly experienced and focused data specialists can be responsible for collecting, reviewing and regularly reporting back to facility managers on trends, exceptions, actions to take and potentially developing issues. These specialists augment the facility manager’s ability to steer his or her data centers through a transition to more software and data intensive systems, without the time hit or distraction of engaging a new set of skills. Also, as familiarity with using data evolves, the third party can train data center personnel, providing operators with direct access to data and indicative metrics in the short term, while creating a foundation for the eventual onboarding of data analysis operations.
Data analysis won’t displace existing data center personnel. It is an additional and critical function that can be supported internally or externally. Avoiding the use of data to improve data center operations is career-limiting. Until data analysis skills and tools are embedded within day-to-day operations, hiring a data analysis service can provide immediate relief and help your team transition to adopt these skills over time.
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