Life never slows down. With 91% of organizations reporting accelerating IT investment, you'd expect that to mean cloud migration and data center consolidation (in fact, that's what 89% of them told a survey by Omdia company ESG). In reality, their cloud and on-premises infrastructure both keep expanding. Companies aren't replacing old data storage systems. They're adding new ones alongside them as they gear up for greater AI development and deployment.
With another ESG survey finding two-thirds of enterprises wrangling 10 petabytes of data or more, the problem is only going to get worse. That data sprawls across multiple platforms, each with its own storage vendor relationships and management tools. Every deployment adds complexity rather than reducing it.
What changed? Five years ago, on-premises data storage infrastructure was supposedly dying. Now IT leaders view it more favorably than before, particularly as AI workloads demand specific hardware configurations that cloud storage providers can't always match cost-effectively.
Why data storage consolidation keeps getting postponed
Why is it that complexity continues to rise even as enterprises report more consolidation of their data storage? It's partly because procurement happens project by project. Teams solve their immediate needs without considering the operational debt they're creating. Each data storage solution works fine alone, but the friction between systems is what creates complexity.
Procurement decisions happen in silos. For example, one team purchases the data storage required for its AI project. Nobody asks how this storage will integrate with the seventeen other systems already humming in the data center.
Everyone is solving today's problems while creating tomorrow's headaches. That also creates retention problems because skilled engineers are becoming disillusioned. They didn't sign up to watch lights and run patch cycles. Mundane maintenance tasks will send talent running to jobs that offer them actual problem-solving challenges.
Consumption-based pricing to the rescue
One remedy for all this is to adopt consumption-based pricing. It's still relatively uncommon (I estimate just 20-25% of organizations have adopted it), but satisfaction is nearly universal among those who have. Flexible consumption models let customers pay only for the infrastructure they're using, and not what's sitting idle in the rack. It's like having groceries in the fridge that you only pay for when you eat them. That might not be an option in your kitchen, but the enterprise data storage equivalent is a reality now.
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Download NowThe real benefit goes beyond cost efficiency. Data storage vendors handle more of the maintenance, which frees teams for work that isn't reactive firefighting. One early adopter reported better employee retention because IT staff were doing less mundane maintenance and more meaningful work. It's no coincidence that ESG research found employee experience and retention to be the most commonly cited benefit for this consumption model.
That same survey found that 39% of organizations are working to reduce the number of physical systems in their data centers. This means they're finally moving from aspiration to action when it comes to data consolidation. Still, six in ten companies are not doing this. There's much work left to do.
Why seamless data migration is key to successful consolidation
For enterprises to finally achieve greater data consolidation, they will need storage solutions that can scale up or down quickly and non-disruptively. We know that container environments can experience radical fluctuations in infrastructure requirements. A Kubernetes cluster that needs 50TB today might need 500TB next month. Or 5TB. Traditional procurement can't handle that volatility.
Seamless data migration isn't just a technical feature; it's what makes consolidation feasible without risking downtime. Downtime or data loss can be disastrous for businesses, especially when they're trying to simplify their environment, so smooth migration is key. The data storage vendors that understand this and can help customers with their transition to consumption-based pricing will do well as complexity mounts.
