Enterprise-scale transformation takes hold – Dell weighs in – News

Enterprise-scale transformation is getting faster and a lot less forgiving as organizations discover that execution — not vision — is what separates progress from posturing.

Across industries, the conversation has shifted from what’s possible to what holds up under pressure. Companies are pulling back from scattered experiments, committing to platforms that can scale across the business and scrutinizing whether early gains can actually be repeated, according to Doug Schmitt (pictured), chief information officer of Dell Technologies Inc. and president of Dell Technologies Services.

“It’s really about taking our experiences on platform development, how we’re getting the results, the ROI for it and then leveraging that with and for our customers as well on the services side,” Schmitt said. “Taking what we learned with our customers and bringing that back internally as well. It’s a two-way street for learning, this customer zero.”

Schmitt spoke with theCUBE’s Dave Vellante for theCUBE + NYSE Wired: AI Factories – Data Centers of the Future interview series, during an exclusive broadcast on theCUBE, News Media’s livestreaming studio. They discussed how enterprises are moving from fragmented experimentation to scalable, results-driven transformation by narrowing focus, accelerating execution and compounding returns.

Enterprise-scale transformation requires focus, speed and ownership

Early-stage efforts often start with energy but quickly sprawl. When hundreds of initiatives compete for attention, scale becomes elusive. Progress accelerates when organizations make deliberate choices about what matters most and align around platforms that cut across teams, functions and workflows, Schmitt explained.

“We had way too many projects that we were experimenting with,” he said. “What we started to do then is say, ‘How do we get that down to a manageable few that really had scale across the company?’ Making sure there was clean ownership of the data is the first place to start, leveraging that data and then moving very quickly on your AI platforms or your AI use cases.”

Data readiness remains a critical factor, but waiting for perfect conditions can slow momentum. Many organizations are finding value by engaging with data as it exists today, identifying gaps through use and assigning clear ownership along the way. That approach favors motion over hesitation and creates faster feedback loops.

“You can’t let that stand in the way,” Schmitt said. “You’ve got to jump in. Speed matters. Start to work with the data, clean the data up. We actually learned that assigning the data.”

The shift from delivery to optimization

As transformation matures, service models are also evolving. Traditional linear approaches are giving way to continuous cycles of improvement, where outcomes inform the next phase rather than marking an endpoint. Value builds incrementally, reinforcing confidence and encouraging further investment, Schmitt noted.

“What you get to after that is that’s becoming circular,” he said. “It’s not just the initial ROI you’re getting. You’re getting repeat ROI and improved ROI as that continues to speed up … and we can help and do help our customers with that.”

The most compelling signal of progress appears when results directly affect experience, capacity and performance. In healthcare settings, reductions in wait times or length of stay translate into both operational efficiency and improved patient outcomes. Those tangible gains help organizations justify expansion and push transformation further upstream, according to Schmitt.

“What they’ve seen with us helping them is an 80-minute reduction in wait time for their patients. They saw a half-a-day reduction in people staying in ICU,” he said. “These are real tangible results for their customers.”

Here’s the complete video interview, part of News’s and theCUBE’s coverage of theCUBE + NYSE Wired: AI Factories – Data Centers of the Future interview series:

Photo: News