Obstacle 1: dealing with data proximity

Organizations are still grappling with how to craft a cohesive strategy made more complicated by data gravity challenges as well as aging data storage methods. The need for data to reside near the applications that consume it presents proximity and bandwidth concerns. We can’t ignore that moving data is challenging and impacts the whole business. IT decision makers and business units need to work together to overcome that challenge. When it comes to hybrid cloud strategy, what once was a differentiator in today’s market, is now a foundational piece of the larger puzzle.

Only 55% of companies have signed on to multi-cloud and hybrid cloud as their preferred approach, according to 451 Research. But because of the elasticity of both the storage capability and the economic efficiencies, it’s become one of the key strategies to help IT organizations actualize digital transformation for their businesses. Santhosh Rao, Senior Director Analyst at Gartner believes that “organizations without a cloud-first strategy — where the cloud is primary, prioritized and promoted — will likely fall behind competitors.”

Obstacle 2: Processing and storing increased data volume

As we see enterprise use of AI move past the pilot phase and into the production reality, complexities also start to emerge. Aside from the unsurprising resource skill gaps, legacy data systems can’t handle the new volume of data that AI heaps upon them. In addition, their ability to process that information using existing technology infrastructure and turn it into real-time insights is still lacking. Power density and cooling are two major limiting factors for existing data center infrastructures. These challenges are forcing IT to re-architect towards a decentralized infrastructure which removes data gravity barriers and accommodates distributed workflows that vary by participant, application, information and location-specific needs.

“New infrastructures must be designed to allow the business to do what it needs to do, when it needs to do it, anywhere in the world.” – Gartner, Infrastructure is Everywhere: The Evolution of Data Centers, July 2019

Those who fail to tackle their AI hurdles risk being left behind as other companies with more nimble infrastructure investments gain advantage.

Obstacle 3: Keeping data safe

Data security has been a challenge since we started collecting data en masse. But with the maturation of evolving technologies like artificial intelligence and the unknowns that come along with it, increased risk follows closely behind. In fact, cybercrime is estimated to cost enterprises in excess of $3.5 billion in 2019.

According to Bobby Ford, CISO at Unliever, interviewed for a ComputerWeekly article, “legacy IT systems are often at the heart of cyber breach incidents….” Although sometimes it's about patching, more likely it’s about rethinking the way it's done from a physical and digital security standpoint. This isn’t just limited to the technology. The business itself needs to rethink the way they collaborate to ensure that risk points across the organization are being addressed in real time. Without evolving the process, enterprises run the risk of losing data and the trust of their customers.

As organizations invest more deeply in cloud services, each additional risk point must be assessed and secured. Understanding where data lives within the hybrid and/or multi-cloud environment and maintaining regulatory compliance is critical to maintaining enterprise integrity at both the technical and business level.

Obstacle 4: Adequately responding to disaster

Organizations are still grappling with protecting business revenue, reducing risk of shutdowns, and simplifying the recovery process in times of unexpected interruption. As groups lean more on digital transformation to change the face of their business, the loss of data they collect and interruption of the newly transformed processes will have devastating effects to any progress they make. Nowhere is that better illustrated than with the outbreak of COVID-19. A spotlight is being shone on the business’ need for flexible network capacity and remote access. Enterprises are rethinking their business continuity and preparedness approaches in real-time because “infrastructure teams [are] responsible for making sure those services stay online” according to DataCenter Knowledge.

But pandemic isn’t the only issue. Predicted weather-based uncertainty as well as the steady rate of crimes against data centers all need to play a part in preparing to defend critical data used to serve the customers goes uninterrupted.

The path forward: Imperfect iteration

Regardless which of those obstacles you’re facing, there’s a path forward. Whether it’s a comfort or a curse, no enterprise is starting with a blank sheet of paper to start a new strategy. This is about progress over perfection. Here are the steps we recommend so that your organization can make progress:

Turn your vision into a roadmap

Digital transformation doesn’t happen in a vacuum. It starts with a vision with leadership buy-in and then it’s up to IT leadership to set clear targets. But to completely evolve the organization, it needs to go beyond just a plan. It needs to be a roadmap that can clearly show value. McKinsey maps out the ten guiding principles of digital transformation that tidily serves as a way to take the roadmap you’ve sketched out into a full-blown digital transformation plan.

Of course, plans for anything as comprehensive as digital transformation isn’t going to be a one-and-done approach. This process will likely be done with every new initiative to move incrementally towards the more productive business and technology future we imagine.

4 digital transformation obstacles and how to overcome them