The enterprise is caught between a rock and a hard place when it comes to digital transformation. On the one hand, transition to an agile, scalable and highly virtualized data infrastructure is vital to future competitiveness, but on the other, there is still a massive investment in static legacy infrastructure that can’t be replaced at the drop of a hat.
Managing this conversion is likely to occupy the majority of the CIO’s attention for the rest of the decade, with the added burden of not fully knowing what a digitally transformed data environment will look like or how it will function.
The heaviest burden in all of this is the fact that infrastructure, applications, services, processes and a host of other elements must all transition in a coordinated fashion if the enterprise is to emerge intact on the other side. As tech consultant Andrew Froehlich notes on InformationWeek, IT executives will have to take a fine-toothed comb through virtually the entire data stack to determine what to keep and what to junk. Timing will also be a critical factor, as you don’t want to move forward too quickly and risk finding yourself in a technological dead-end, nor too slowly and lose out to a more nimble competitor. And it’s important not to overlook the human factor in all of this as well, particularly the need for retraining and the hiring of new skill sets.
Most organizations view the cloud as a chance to make a fresh start in data infrastructure, but even this strategy has its pitfalls, says Google Cloud’s Loren Hudziak. In an interview with Diginomica, Hudziak points out that the temptation to simply recreate legacy data environments in the cloud is strong, but this should not become the ultimate goal. Instead, a cloud-native approach should be implemented across infrastructure, applications and services – essentially producing a complete operational make-over that is more in tune with the demands of a digital economy. Moving to the cloud, then, is a good time to assess whether past practices are necessary for business outcomes, or were simply instituted due to the limitations of available technology.
In many cases, this may lead to the conclusion that certain applications are best left in the data center.
