The brief, produced by IHL Group in partnership with Epicor, analyzes the 2026 retail‑technology survey of mid‑market general‑merchandise (GMS) retailers (apparel, mixed goods, hard goods, pharmacy/cosmetics). It reveals a widening performance gap between "Sales/Profit Winners" and "Laggards" that is driven primarily by data architecture. Winners have modern POS, microservices, mobile POS, and omnichannel fulfillment (BOPIS, ship‑from‑store, warehouse e‑commerce) and, crucially, a single up‑to‑date data lake (44 % of profit winners vs 0 % of laggards). Laggards remain on fragmented, siloed systems, leading to inventory distortion, poor omnichannel performance, and ineffective AI investments. The report argues that data unification must precede AI deployment; otherwise AI adds cost without return. It details the operational costs of piecemeal integration (integration tax, synchronization lag, fragility premium), the necessity of data cleansing across product, customer, and transaction domains, and outlines the capabilities a unified retail platform must provide (POS, inventory, purchasing, loyalty, e‑commerce, analytics) with a single data model. It also offers a data‑readiness assessment framework, criteria for selecting a platform partner, and a timing window for mid‑market retailers to execute a unified‑platform transition faster and cheaper than enterprise rivals. The overall message is a call to action: unify data now to gain a compounding competitive edge and unlock AI‑driven growth.
Topics
Performance Divide Linked to Data Architecture
Survey data shows Sales and Profit Winners outperform Laggards by large margins in growth, revenue, and AI impact, with the single data lake being the most decisive metric (44 % vs 0 %).