In omnichannel retail, the customer promise is the system’s most fragile output. Delivery dates, pickup availability, and fulfillment options are calculated once, early in the order lifecycle, and then treated as facts. The environment changes. The promise does not.
Traditional OMS platforms assume that availability and fulfillment feasibility are static at the moment of checkout. They calculate a promise based on inventory snapshots, generic lead times, and preconfigured routing rules. Once the order is placed, the promise is effectively frozen, even though the conditions that justified it continue to evolve.
First, omnichannel environments are inherently volatile. Inventory moves, workloads fluctuate, cut-off times pass, carriers miss handovers, and stores open and close. Most OMS platforms detect these changes, but they do not re-evaluate the promise against them. They react operationally, not contractually. The result is late shipments, manual interventions, and customer communication that explains failure instead of preventing it.
Second, promises are calculated without sufficient context. Availability is treated as a quantity, not as a capability constrained by location, capacity, timing, compliance, and cost. A unit in stock is considered equally fulfillable regardless of whether it sits in a congested store, a distant warehouse, or a location that cannot legally or economically serve the customer. The system confirms what is technically possible, not what is realistically executable.
Third, traditional OMS architectures separate promise from execution. The checkout promise is produced by one logic layer. Fulfillment decisions are made later by another. When execution reality diverges from the original promise, the system has no coherent mechanism to reconcile the two. Re-routing, split shipments, or substitutions are applied as exceptions, often without recalculating the customer commitment or preserving a clear audit trail.
The consequence is structural. Promises are optimistic, execution is reactive, and trust is repaired manually. The OMS becomes a coordinator of failures rather than a guarantor of commitments.
In modern retail, a promise cannot be a static estimate. It must be a continuously validated commitment, recalculated against real-world conditions throughout the order lifecycle. Without this capability, omnichannel scale does not increase reliability. It accelerates failure.
With EVA, the Order Management System (OMS) is no longer a back-office utility; it’s a real-time, intelligent decision engine. EVA’s OMS is built around a simple philosophy: order management should be contextual. Every promise to a customer whether about delivery time, pickup availability, or stock should be based on a complete, real-time understanding of the entire operational context.
Traditional OMS systems operate in isolation, processing orders through fixed rules and static fulfillment hierarchies. EVA takes a different approach: every decision from fulfillment routing to delivery promises is contextualized using live operational and customer data.
When a customer places an order, EVA evaluates:
- Customer profile and loyalty status
- Customer location and preferred pickup options or distance to fulfillment location
- Real-time inventory across stores and warehouses
- Store workload
- Warehouse capacity and carrier SLAs
- Opening hours and regional cutoffs
Contextual awareness allows EVA to make informed, dynamic promises, not generic ones.
The Order Promise in EVA isn’t a static estimate. It’s a commitment calculated from a living, real-time model of your retail network.
EVA uses orchestration logic to evaluate all eligible fulfillment points, scoring them against operational and experiential factors. The result: the best possible fulfillment location for that specific customer, at that specific moment.
This isn’t batch logic it’s continuous orchestration. If a store becomes overloaded, or stock levels change, EVA can re-orchestrate open orders in real-time, rerouting them to new fulfillment locations while maintaining full order traceability.
EVA’s Order Management System acts as the single source of truth for all orders across every channel, online, in-store, marketplace, or B2B. It’s not just a pipeline for sales transactions, but a real-time repository that holds the full lifecycle of every order, fulfillment, shipment, and return in one place.
Split Fulfillment by Design
EVA is built for split and distributed fulfillment. When a customer’s order spans multiple products or locations, EVA dynamically allocates each line to the optimal source. One order may be partially shipped from a store, partially from a warehouse, and partially drop-shipped by a supplier, all coordinated and tracked under a single order identifier.
Multi-Entity and Cross-Border Compliance
Retailers rarely operate within a single legal or fiscal entity. EVA OMS is designed to operate across multiple legal entities, currencies, and tax jurisdictions, automatically handling the creation of the necessary Sales Orders, Purchase Orders, and Transfer Orders to ensure legal and financial compliance.
One Order object, Infinite Perspectives
In EVA, there’s no data fragmentation between channels or systems. Customer care, stores, warehouses, and finance all see the same order, in real-time, enriched with contextual logistical and financial information.
Every stakeholder, from the associate on the shop floor to the customer calling support or visiting their my account page, interacts with the same source of truth.
EVA’s Order Orchestration engine continuously determines which locations can fulfill each order or even each order line. Using orchestration sheets, you can define logic based on country, stock, service levels, or supplier type.
Once orchestration runs, EVA creates Order Fulfillment Lines, the granular assignments that connect each item to a specific fulfillment location. If one location can’t complete a fulfillment, EVA automatically re-orchestrates until the order is shipped.
This automation ensures maximum agility across your network from ship-from-store to external supplier drop-ship with consistent financial and stock tracking.
EVA’s orchestration engine operates through a powerful scripting layer that defines how orders are evaluated, routed, and fulfilled. These orchestration scripts are written in a low-code, domain-specific language that allows retailers to express business logic in a human-readable way defining rules for fulfillment eligibility, or routing preferences.
Because orchestration logic is interpreted in real time, any change to a rule, for example, prioritizing a new carrier, adjusting a service level, or excluding a store under pressure is instantly applied across all channels. This means orchestration in EVA is not a background process, but a living configuration layer: low-code, context-aware, and immediately effective wherever orders are created.
In EVA, the customer promise begins with a clear understanding of what is truly available.
Stock exposure is not a static feed or a nightly export; it is a living, contextual reflection of your operational reality. Every stock call, whether from eCommerce, store, marketplace, or replenishment process, is evaluated in real time against the rules that define what can be sold, where, and to whom.
EVA’s allocation engine allows retailers to define how inventory is shared across their channels and customer segments. Stock can be prioritized for online sales, reserved for stores, or even protected for specific loyalty tiers or B2B accounts. These allocation rules ensure that each channel only sees the stock that it is entitled to promise, preventing overselling and maintaining a balanced network.
Unlike traditional systems that treat inventory as a fixed quantity, EVA’s OMS dynamically exposes availability across all nodes in the network, from warehouses and stores to suppliers and dark stores. Each of these sources can be surfaced to channels through configurable stock feeds or real-time service calls. In both cases, EVA evaluates the context of the request: the channel, the customer, the location, and the current operational capacity. What is returned is not just a number, but a contextual availability statement, stock that can actually be promised, delivered, or picked up under current or future conditions.
This includes physical stock, allocated quantities, pre-order inventory, and future stock arriving through open purchase orders. EVA merges all of this information to present a single, accurate view of availability. A product might be shown as immediately deliverable from a local store, available for next-day fulfillment from a central warehouse, or open for pre-order with a known replenishment date. Each scenario is calculated in real time, reflecting the live capacity and constraints of the network.
Because all availability data originates from the central OMS repository, every channel digital, physical, and service works with the same truth what a customer sees online matches what store associates and customer care agents see in their own interfaces. This unified visibility ensures that every promise made to a customer is both realistic and profitable, balancing experience, compliance, and operational precision.
Brand loyalty is no longer driven by habit or product alone, but by the human need for purpose, belonging, and shared values in a world of endless choice. As traditional forms of community decline, brands have the opportunity—and responsibility—to step in by creating hybrid communities that connect people both online and offline, foster shared identity and rituals, and allow meaning to emerge organically from within the group. By offering experiences that resonate emotionally and socially, brand communities counter declining loyalty, enable collective self-expression, and build deeper, more durable relationships that translate into advocacy, loyalty, and sustainable growth
Leni Hakvoort
When you’re leading a global brand, quick assumptions about cost can lead you astray. In enterprise retail technology - specifically modern POS (point-of-sale) systems - there’s a persistent belief that Android solutions are inherently cost-effective, while Apple’s iOS-based solutions appear expensive by comparison. This perception, though widespread, deserves a closer, fact-based look.
Steven Bakker
Retailers widely recognize the significant impact digital interactions have on offline sales, often referred to as the ROPO effect (Research Online, Purchase Offline). Industry research consistently demonstrates that digital engagement precedes approximately 40% of offline retail revenue, with notably higher percentages observed in sectors such as electronics and home furnishings.
Steven Bakker & Lub ten Napel