Technology
Fast brands, slow systems: Why retail's biggest players are running out of time
The biggest cost of legacy systems is not the technology itself – it's how people are used within the organization.
August 11, 2026 by Glebs Vrevsky — Co-founder and Executive Board Member, scandiweb
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ClaudeRetail has never moved faster. More channels, more markets, more customer expectations. The surface of the industry looks modern, responsive, and increasingly personalized. But underneath, many of the systems running this complexity were built for a much simpler version of the business.
The result is a growing mismatch. While the business accelerates, the systems underneath it do not. Most retailers don't notice it at first – orders still go through, stores still operate, revenue continues to flow. But the cracks show up where it matters most: when the business needs to move quickly or scale efficiently.
How it happened
Over the past decade, most investment has gone into what customers see – websites, mobile apps, personalization layers. The parts that shape perception. Yet the underlying systems are still tremendously slow and archaic. This didn't happen by accident. Businesses start small, systems are built pragmatically, and over time layers are added. Frontend improvements are faster to implement and easier to justify. Backend changes, by contrast, affect everything. Complexity accumulates. Systems that were never designed to work together are forced to operate as one.
The cost of this gap is rarely visible in one place. It shows up in slower decisions, duplicated work, inconsistent data, and operational friction across teams. In one case I've seen, a purchasing team spent four days each week gathering and cleaning data from different systems. Only on the fifth day could they actually analyze it and make decisions. This is not a technology issue. It is a business problem. When expensive experts spend their time on manual data processing instead of the work they were hired to do, the company loses money at scale. It becomes one of the most expensive inefficiencies in the organization.
Where it hurts most
The impact is most visible in core operational moments — inventory accuracy, pricing consistency, delivery promises, and product availability across channels. From the outside, many of these systems appear to work. But there is a growing gap between perception and reality.
Research shows that while expectations around AI-driven customer experience are rising, only 16% of organizations have successfully implemented these capabilities at scale, and less than half consider their data ready for AI. The systems gap is the reason.
For years, these issues could be delayed. AI moved that conversation to the boardroom. Expectations have shifted toward better personalization, smarter inventory, and faster decision-making. But these capabilities depend on something most organizations still lack: a connected, reliable data foundation. AI didn't create this problem, but it made it impossible to delay any longer.
To make AI work in practice, systems need to be connected, data needs to be consistent, and business logic needs to be aligned. Without that, AI doesn't solve the problem – it exposes it.
What fixing it actually looks like
The instinct in many organizations is to treat this as a large-scale transformation. In practice, that rarely works. If you want to build something complex that works, you first need to build something simple that works. The more effective approach is to start with one high-value use case, not a full transformation. One team, one process, one area where the impact is clear and measurable. From there, systems can be built and expanded incrementally without disrupting the business.
What has changed is the speed at which this can happen. With modern development approaches and AI-assisted tooling, cycles that once took months can now be compressed into weeks. Projects that once required years can be delivered in months.
What separates the winners
The gap between companies is defined by how quickly they can turn ideas into working systems. Legacy systems become a strategic constraint – not because they exist, but because they slow down the ability to respond. Many retailers still evaluate themselves based on surface-level performance: brand strength, revenue growth, market presence. But the more relevant question is operational. You need to ground yourself in the operational reality of the business, not the perception of how well it's doing.
The biggest cost of legacy systems is not the technology itself – it's how people are used within the organization. When highly skilled teams spend their time navigating broken processes instead of making decisions, the business loses money, clarity, and ultimately competitiveness. The companies that fix it will have teams focused on what actually drives the business forward. The rest will continue scaling complexity, not capability.
About Glebs Vrevsky
Glebs Vrevsky is co-founder and executive board member at scandiweb, a global e-commerce technology and growth company helping enterprise brands build and scale complex digital commerce platforms for more than two decades. He built scandiweb’s Growth division, which expanded the company’s capabilities beyond platform engineering into performance marketing and data-driven optimization.
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