Consumer expectations in the Middle East have intensified at a speed few other regions have experienced. While many markets moved gradually from multi-day delivery to next-day and then same-day, the GCC has compressed this journey dramatically — powered by a digital-first, mobile-first population and a rapidly growing ecommerce economy.

For retailers, this creates a massive commercial opportunity — and a structural operational challenge. The retailers that win are not simply those who sell well online, but those who can fulfil consistently at scale.

Traditional retail replenishment relies on cadence: known delivery structures, predictable store flows, and relatively stable order profiles. Ecommerce fulfilment breaks that model with:

• high order volume variability

• smaller order sizes

• unpredictable promotions and peaks

• increased packing and value-added services

• higher service-level expectations

Warehouses built for case or carton movements now must handle single-item picking at pace — often without facilities being physically or operationally designed for that workload.

As same-day expectations expand, last mile becomes the most expensive and complex part of fulfilment — particularly in dense urban markets where consumers expect speed as standard.

To meet those promises, retailers build hubs, micro-fulfilment locations, and “dark store” fulfilment setups. But that introduces new operational questions: how to stock these locations, how to manage inventory accuracy, and whether automation is required to deliver consistently at volume.

Many retail supply chains are fragmented across channels, systems, and inventory pools. Ecommerce, wholesale, franchise, marketplace, and retail operations may each run separate systems and reserve separate inventory — sometimes even storing the same SKUs separately within the same distribution centre.

Fragmentation creates three recurring failure modes:

1. Fragmented inventory: no single view of available stock across DCs, stores, suppliers, and in-transit inventory.

2. Fragmented fulfilment: limited ability to dynamically change fulfilment nodes when stock or capacity changes.

3. Fragmented execution data: delayed confirmations and batch updates prevent real-time customer visibility and proactive recovery when issues occur.

The result is avoidable cancellations, missed SLAs, and customer uncertainty — often driving high volumes of “Where is my order?” contact-centre requests even before an SLA is breached.

Point-to-point integrations move data, but they often don’t create decisions. Orchestration is what enables decisions to happen automatically, based on real-time execution signals.

A practical example: a next-day order is sent to a warehouse, but the picker can’t find the item. Without orchestration, the order is shorted or cancelled. With orchestration, the order can be re-routed to store stock (or another node) to protect the customer promise — while simultaneously improving inventory utilisation and saving a sale.

A unified execution model allows stores to act as fulfilment nodes — not just as retail endpoints. This unlocks several benefits:

• faster delivery by fulfilling closer to the customer

• better inventory utilisation (reducing discounting and returns to DC)

• improved click-and-collect speed, potentially within the same hour

• incremental sales by surfacing store inventory online

Crucially, store fulfilment requires store-friendly tooling — not a warehouse system forced into a store environment. Execution must be designed for store associate workflows and customer experience.

AI is only useful when it has accurate, real-time execution signals. Without timely updates on inventory, labour, and progress, AI becomes hindsight reporting rather than operational decision support.

One of the most practical applications is labour orchestration: systems continuously monitor progress across functions (receiving, putaway, picking) and can recommend or trigger labour reallocation before service-level failures occur — reducing reliance on manual supervision and “gut feel”.

Legacy on-premise systems often trap retailers on old versions, limiting access to continuous capability improvements. Cloud-native architectures enable frequent releases where every customer stays current — accelerating adoption of new execution features, new AI capabilities, and faster iteration.

GCC retailers face a high-growth, high-expectation environment where fragmented systems and inventory can’t keep up. The next era requires unified execution and orchestration across orders, inventory, warehouse, transport, labour, and stores — enabling consistent customer outcomes, lower cost-to-serve, better SLAs, and AI-driven operational decisions at scale.