Every technology market follows a predictable arc. In the early stages, buyers tolerate complexity because they have no alternative: the problem is new, the solutions are immature, and having any tool at all feels like progress. As the market matures, buyers accumulate experience and learn which capabilities actually drive value and which features are expensive noise. They stop asking “which product has the most features?” and start asking “which product solves my problem with the least friction?” That shift in buyer behavior reshapes the vendor market, often brutally.
The order management system market is in the middle of exactly this kind of transition. Over the past two decades, OMS technology has moved through four distinct eras: each driven not by vendor innovation alone, but by fundamental changes in what brands and retailers needed, what they were willing to pay for, and what they were no longer willing to tolerate. Understanding these eras, and the market forces that caused each transition, is critical for any brand evaluating its order management strategy today.
The Market Evolution at a Glance
Figure 1: The four eras of order management – each transition driven by shifts in buyer needs, not just vendor innovation
The First Era: Order Management Inside the ERP (1990s – 2000s)
For most of the 1990s and well into the 2000s, order management wasn’t a standalone software category. It was one of a dozen modules inside an ERP from SAP, Oracle, or JD Edwards. Companies invested millions in these systems and expected them to handle everything from general ledger accounting to procurement to manufacturing planning. Order management was simply another line item in the implementation scope. The logic was straightforward: orders were financial transactions, ERP systems managed financial transactions, and therefore order management belonged inside the ERP.
This approach worked when commerce was simple. Orders came in through a single channel: a call center, a fax machine, or a retail POS terminal; and got routed to a single warehouse, and shipped via a single carrier. For companies like Procter & Gamble and Unilever, SAP’s order management module handled wholesale order processing reasonably well because those were fundamentally batch-oriented, B2B processes. ERPs processed orders in batch cycles, often overnight, which meant inventory counts were hours or even days out of date. That was acceptable when the only people checking inventory were internal planners, not consumers expecting instant confirmation.
The major problem with this approach was that ERP-based order management was never designed to be customer-facing. It was built for finance teams and supply chain planners, not for the real-time demands that ecommerce would introduce. As online commerce grew in the mid-2000s, these ERP modules buckled under use cases they were never architected to support: real-time inventory visibility across channels, distributed fulfillment from multiple locations, split shipments, and customer-facing order tracking.
Forrester has noted that a surprisingly large portion of the market was still running homegrown solutions or highly customized ERP connectors well into the 2010s: systems that had aged poorly and couldn’t serve real-time inventory availability during the milliseconds of a digital shopping experience when a customer is most likely to abandon the cart. Order management is customer experience.
What drove the transition: The rise of ecommerce fundamentally changed what buyers needed from order management. When a consumer places an order online, they expect real-time inventory confirmation, immediate order acknowledgment, shipment tracking, and the ability to return through any channel. None of those capabilities existed in ERP-era order management because none of those requirements existed when the systems were built. ERPs are fundamentally batch mode. The demand side of the market had outgrown the supply side, and that gap created the opening for a new category of purpose-built solutions.
The Second Era: The Purpose-Built OMS (2005 – 2015)
The limitations of ERP-embedded order management created a market opening for specialized, standalone order management systems. Yantra, the original pioneer, was acquired by IBM in 2010 for $1.4 billion and became WebSphere Commerce Order Management and later was rebranded as Sterling.
Sterling had built its reputation on B2B integration and trading partner connectivity, with more than 18,000 customers and over 1 billion business interactions per year flowing through its platform. Major retailers including Best Buy, Walmart, Staples, and Lowe’s ran their order operations on Sterling. Follett, the largest campus bookstore operator in North America, used IBM Sterling to unify its 1,200 ecommerce sites into a single cooperating network with shared inventory, catalogs, and order fulfillment: the kind of complex, multi-node orchestration that defined the Second Era at its best.
Manhattan Associates brought deep supply chain DNA, combining warehouse management with order orchestration in a way that appealed to complex omnichannel retailers. Manhattan has been recognized as a leader in every Forrester Wave evaluation of the OMS market, earning the highest possible score in 20 of 27 criteria in its most recent assessment.
The Second Era represented a dramatic leap in sophistication. These platforms could handle distributed order management, buy-online-pick-up-in-store, ship-from-store, complex fulfillment orchestration, and enterprise inventory management across hundreds of locations. They were genuine workhorses: the term Forrester itself uses to describe what OMS platforms do at the heart of the commerce tech stack.
The challenge with the Second Era was that sophistication came at a cost, literally and operationally. Implementations routinely took 12 to 18 months, cost millions to implement, and required armies of systems integrators to deploy and maintain. The platforms were monolithic, on-premise, were deeply entangled with the surrounding technology stack and lacked native connectivity. Upgrades were painful multi-month projects. Customizations were brittle and difficult to unwind. And once deployed, these systems became so deeply embedded in a company’s operations that replacing them felt impossible, which is precisely why so many brands are still running them today, despite the systems being well past their architectural prime.
What drove the transition: Two forces converged. First, the composable commerce movement and the broader shift to cloud-native architectures made monolithic, on-premise software feel increasingly anachronistic. Brands that had spent 18 months and millions implementing an on-premise OMS watched cloud-first startups in adjacent categories deploy in weeks.
Second, the economics of Second Era implementations became harder to justify. When a single OMS deployment costs more than some brands’ entire annual technology budget it clearly signals the market is ready for an alternative. A new generation of cloud-native vendors was happy to provide one.
The Third Era: Cloud-Native OMS (2015 – 2023)
Beginning around 2015, a new wave of cloud-native OMS vendors entered the market with a fundamentally different architectural philosophy. Fluent Commerce, Kibo, and Blue Yonder (among others) built their platforms on microservices, API-first architectures, and cloud-native infrastructure. The promise was composability: the ability to deploy modular OMS capabilities incrementally rather than as a single monolithic installation. Fluent Commerce earned one of the top strategy scores in the 2023 Forrester Wave evaluation, and Kibo built a unified commerce and order management suite that combined storefront, OMS, and merchandising on a single headless platform.
The Third Era was an important step forward. Cloud-native architectures eliminated the on-premise infrastructure burden, APIs enabled faster integration than the old batch-file approaches, and modular deployment meant brands could theoretically start with inventory visibility and add fulfillment orchestration later.
Third Era platforms, however, carried forward two critical problems that the market is only now reckoning with. The first is complexity. Despite their modern architectures, these solutions were still built in the enterprise software tradition: designed by engineers for engineers, optimized for the most complex possible use case, and priced accordingly. Fluent Commerce, for example, offers a powerful rules engine for order routing and fulfillment logic, but implementation complexity and timelines can be significant for organizations without strong technical resources. The platform’s flexibility requires substantial configuration effort to realize full value. These aren’t business-user tools: they’re engines that require dedicated technical teams to configure, operate, and maintain. They lack the intuitive, self-service interfaces that commerce operations teams actually need in their day-to-day work.
This is a textbook case of the Innovator’s Dilemma playing out in real time. Third Era vendors are competing with Second Era incumbents by adding more features, more configuration options, and more enterprise-grade capabilities. They’re getting more complex, not less, because their existing enterprise customers demand it. The competitive pressure pushes them up-market, toward the same large-scale, high-touch implementations that defined the era they were supposed to replace.
Meanwhile, the broader market has matured. Brands and retailers increasingly know exactly which OMS features actually drive value (real-time inventory visibility, intelligent order routing, delivery promising, and customer self-service) and which features are expensive shelf-ware that never gets used. In a maturing market, buyers become willing to accept fewer features in exchange for solutions that are simpler, faster to deploy, and dramatically lower in total cost of ownership. The 80/20 rule applies forcefully: 80% of the value comes from 20% of the features. The remaining 80% of features serve the needs of a small minority of enterprise buyers while adding complexity and cost for everyone else.
The second problem the Third Era inherited from the Second Era is the integration problem. Every OMS, regardless of how modern its architecture, requires connections to the systems around it: commerce platforms, ERPs, WMSes, 3PLs, and shipping carriers. Third Era platforms assumed the OMS should be the central system of record for all order operations, and that the surrounding ecosystem should integrate into it. Those connections have historically taken months to build, cost a fortune to maintain, and break with alarming regularity. The OMS itself may be cloud-native, but if it takes six months and a systems integrator to wire it into the rest of the stack, the architectural elegance is largely theoretical.
What is driving the next transition: The market isn’t waiting for Third Era vendors to simplify. Buyer expectations are being reset from the outside: specifically, by what Shopify has done to commerce platforms. When brands see that they can stand up an enterprise-grade storefront in weeks with Shopify, they’re no longer willing to accept 6-to-12-month OMS implementations on the back end. The front office has gotten dramatically simpler and faster; the back office hasn’t. That gap is unsustainable, and it’s the primary force pulling the market into the Fourth Era.
The Shopify Effect: Why the Back Office Has to Keep Up
Before examining the Fourth Era, it’s worth understanding the market dynamic that makes it necessary. On the commerce front-end side, Shopify has fundamentally reset enterprise expectations for speed, simplicity, and total cost of ownership.
The pattern illustrated by Shopify is unmistakable, and it follows the same market maturation curve that’s playing out in OMS. Major brands are choosing simpler, faster, lower-TCO commerce platforms at an accelerating rate because the market has matured to the point where enterprise-grade complexity is no longer a selling point: it’s a liability for those who don’t need it.
The brands making these moves are simultaneously discovering that their back-office order management infrastructure (the Second Era and Third Era systems connecting their commerce platform to their ERPs, warehouses, and fulfillment partners) is now the bottleneck. A brand can stand up a Shopify storefront in weeks, but if connecting it to the rest of the operational stack takes six months and a six-figure integration project, the front-end speed advantage evaporates.
The Fourth Era: AI-Native Order Operations (2024+)
The Fourth Era represents a philosophical shift in order management. It is the natural response to a maturing market: the kind of response that Clayton Christensen described decades ago when he observed that disruptive solutions win not by out-featuring incumbents, but by being dramatically simpler, cheaper, and faster for the use cases that the majority of the market actually needs. Fourth Era solutions are built around a recognition that the hardest problem in order management has never been the order management logic itself: it has always been connectivity, getting the OMS connected to everything around it and keeping those connections running reliably. The Fourth Era solves for that problem first, and everything else follows.
There are six defining characteristics that separate the Fourth Era from everything that came before.
1. Connectivity as a First-Class Capability
An OMS can’t operate without connections to the systems around it: commerce platforms, marketplaces, social commerce, AI, ERPs, WMSes, 3PLs, payment processors, and shipping carriers. In the first three eras, these connections were treated as an implementation detail, something that happened after the OMS was selected and configured. The result was integration projects that consumed six months or more, cost as much as the OMS license itself, and required ongoing maintenance that quietly drained operational budgets year after year.
Fourth Era solutions treat connectivity as the foundational layer. Pre-built connectors, AI-assisted endpoint configuration, and standardized data models mean that connecting an OMS to Shopify, NetSuite, a 3PL, and a shipping carrier can happen in hours rather than months. Brands that deploy Shopify as their commerce front end can connect to their entire back-office ecosystem in weeks, not quarters. This isn’t a marginal improvement: it’s the difference between a solution that delivers value immediately and one that delivers value eventually.
2. Dual-Mode Operation
Forrester’s recent Total Economic Impact study on dual-OMS strategies validated something that practitioners have known for years: most brands don’t need to rip and replace their existing OMS. They need to augment it. The study found that companies implementing a dual OMS strategy achieved 180% ROI with payback periods under six months, dramatically outperforming traditional full replacements that typically cost $500,000 or more and take 12 to 24 months to generate returns.
Perhaps the most revealing finding was that three out of four companies that initially intended to maintain both systems indefinitely ended up shifting toward full migration within two years. The dual approach had inadvertently jump-started their replacement, what Forrester describes as an unintentional “strangler” process. Companies that started by layering on real-time inventory visibility and intelligent order routing discovered that adding new modules from the secondary solution was as effective as a full replatforming initiative, just at a nondisruptive pace. The secondary OMS delivered 63% of its benefits from reduced cancellations and increased sales through real-time inventory management alone.
Fourth Era solutions are designed from the ground up for this dual-mode operation. They can function as the primary system of record (the master) or they can operate alongside an existing OMS, handling specific capabilities like real-time inventory synchronization, delivery promising, or multi-channel order routing while the legacy system continues to manage other functions. This isn’t a workaround; it’s the intended deployment model. The flexibility to operate as either master or complement is a defining architectural characteristic of the Fourth Era, and it means brands can start getting value in weeks without making a bet-the-company platform decision.
3. Designed for the Simplicity Era
Brands and retailers have reached a collective breaking point with complexity. After years of assembling sprawling composable stacks with dozens of best-of-breed vendors (each requiring its own integration, its own maintenance contract, and its own dedicated expertise) the market is swinging decisively back toward solutions that are simpler, faster to deploy, and dramatically lower in total cost of ownership.
This is what happens when markets mature. When a technology category is new, buyers accept complexity because they don’t yet know which features matter and which are noise. As the market matures, that changes. The 80/20 rule applies forcefully and mature buyers prove willing to trade feature breadth for speed, simplicity, and lower cost.
Shopify demonstrated what this looks like on the commerce side: a platform that made it possible for brands to launch and operate a store without a systems integrator, without a six-month implementation, and without a seven-figure budget. The fact that Estee Lauder, General Motors, and L’Oreal are choosing Shopify over legacy enterprise platforms tells the story clearly: the market has matured, and enterprise-grade complexity is no longer a selling point. Fourth Era order management follows the same principle. Implementations that previously took six months happen in weeks. Price points that previously started at six figures drop to a fraction of that. The operational overhead that previously required dedicated IT teams gets replaced by intuitive, business-user-facing interfaces and AI-assisted workflows.
This simplicity extends beyond deployment into daily operations. Fourth Era platforms provide business users (commerce operations managers, fulfillment coordinators, customer service leads) with the tooling and interfaces to manage their order operations directly, without filing a ticket with IT or waiting for a developer to write custom code. A commerce operations manager who needs to hold all orders from a specific channel like TikTok Shop during a promotion issue can do it in seconds through a business-user interface. In Third Era platforms, that same change typically requires a developer to modify routing rules, test in staging, and deploy: a process that takes hours or days for what should be a two-minute operational decision. Fourth Era solutions close the gap between the people who understand the business problem and the system that needs to act on it.
4. Built on an AI Foundation
Every OMS vendor in 2026 claims to use AI. The distinction with the Fourth Era isn’t whether AI exists in the product: it’s if AI is the foundation the product is built on. Third Era vendors have retrofitted AI into existing architectures, typically in the form of smarter order routing rules or demand forecasting models bolted onto legacy decision engines. The underlying platform remains the same; AI is a feature layered on top. Fourth Era solutions are AI-native from the ground up, meaning artificial intelligence isn’t just a feature, but the infrastructure itself.
This distinction manifests across every layer of the platform. At the setup layer, AI assists in mapping data models between systems, configuring connectivity endpoints, and resolving the schema mismatches that traditionally consume weeks of integration engineering. Rather than a team of developers manually building field mappings between Shopify and NetSuite, the AI interprets the data structures and proposes the correct configuration, turning what was a multi-week technical project into an afternoon.
At the operational layer, an AI assistant built directly into the platform serves as a copilot for commerce operations teams. This isn’t a chatbot bolted onto a help page: it’s an operational partner that sits at the center of the platform, available at every screen and every workflow. The assistant can surface order exceptions, diagnose fulfillment bottlenecks, recommend routing changes, and execute operational adjustments in natural language. A fulfillment coordinator can ask “show me all orders stuck in processing for more than four hours” and get an immediate, actionable answer. No report builder, no SQL query, no developer involvement.
Critically, the assistant is proactive, not just reactive. It monitors operations continuously and alerts teams before problems escalate: flagging a carrier that has started missing SLAs before it affects customer satisfaction, identifying an inventory discrepancy between Shopify and the warehouse before it causes overselling, or noticing that return rates on a specific SKU have spiked and surfacing it to the operations team with context. The assistant also guides users through unfamiliar workflows, walking a new team member through setting up a fulfillment rule or configuring a new channel step by step. This is fundamentally different from a dashboard that displays metrics and expects a human to interpret them. The assistant understands the operational context and can take action.
At the runtime layer, AI continuously learns from order patterns, inventory movements, carrier performance, and fulfillment outcomes to optimize system behavior without human intervention. Routing decisions improve over time. Inventory allocation becomes more precise. Exception handling becomes more automated. The system gets smarter with every order it processes.
The difference between “AI features” and “AI-native” is the difference between adding a chatbot to a legacy website and building the entire experience around conversational interaction from day one. Fourth Era solutions fall into the latter category, and the operational implications are dramatic. Brands that deploy a Fourth Era solution aren’t just getting an OMS with some AI sprinkled on top: they’re getting an operational platform where AI handles the heavy lifting that previously required dedicated technical teams.
5. Pluggable by Design
Third Era OMS platforms were built as closed systems: comprehensive, self-contained, and architecturally resistant to adding capabilities that weren’t part of the original design. Adding a new fulfillment option, a new delivery partner, or a new operational capability typically meant a formal enhancement request, a scoping exercise with a systems integrator, and months of development and testing. The platform did what it did, and extending it was expensive.
Fourth Era solutions are pluggable by design: built so that new capabilities, partners, and services can be added without a rebuild. A brand that wants to add estimated delivery date (EDD) promising to its checkout can plug in that capability without rebuilding its fulfillment workflows. A brand that wants to offer same-day local delivery through DoorDash can add it as a fulfillment option alongside its existing 3PL and ship-from-store capabilities in days, not months. A brand expanding into a new marketplace or adding a new warehouse partner can connect it to the existing operational fabric without disrupting what’s already running. This pluggability isn’t just a nice-to-have: it’s what allows brands to evolve their operations at the speed the market demands, adding capabilities incrementally rather than waiting for the next major platform upgrade.
6. Ready for the Agentic Commerce Era
Commerce is undergoing a structural shift that most OMS platforms are unprepared for. AI agents, from ChatGPT and Google Gemini to Microsoft Copilot and Claude, are no longer experimental chatbots. They’re completing real purchases for real consumers. eMarketer projects that AI platforms will account for $20.9 billion in retail spending in 2026, nearly quadrupling the prior year. Shopify launched Agentic Storefronts that syndicate products to ChatGPT, Google AI Mode, Copilot, and Perplexity simultaneously. Google and Shopify co-developed the Universal Commerce Protocol (UCP) with endorsement from Walmart, Target, Best Buy, Mastercard, Visa, and more than 20 other partners. OpenAI and Stripe launched the Agentic Commerce Protocol (ACP) to enable instant checkout inside ChatGPT. The infrastructure for agent-mediated commerce is being built right now, at speed, by the largest technology companies in the world.
This matters for order management because when a customer using an AI head or an AI agent places an order on behalf of a consumer, it needs real-time access to inventory availability, fulfillment options, delivery promises, and order status; not through a human-readable web page, but through machine-readable protocols.
Model Context Protocol (MCP), developed by Anthropic and now governed by the Agentic AI Foundation, has emerged as the standard for how AI agents connect to enterprise systems. MCP allows a single AI agent to query inventory, initiate orders, check fulfillment status, and manage exceptions across multiple backend systems through a unified interface. The Order Network eXchange (onX) protocol extends MCP specifically for commerce operations, providing a standardized language for post-purchase order flows across the entire ecosystem.
Fourth Era solutions are built with these protocols as foundational infrastructure, not retrofitted integrations. They expose order operations data and actions through MCP servers that AI agents can consume natively, meaning a brand’s inventory, fulfillment network, and order status become accessible to every AI commerce surface simultaneously. Third Era OMS platforms, built before agentic commerce existed as a concept, lack the APIs, data structures, and protocol support that AI agents require. Retrofitting these capabilities onto architectures designed for human-operated dashboards would be a fundamental rebuild. Fourth Era solutions, built in the age of AI agents, treat machine-to-machine commerce as a first-class use case from day one.
Where the Market Is Headed
The OMS market in 2026 is in a state of transition that Forrester has described as “augmented evolution.” The majority of digital leaders with an OMS are augmenting their current solution with modules from a more modern platform rather than pursuing full replacement. Vendors with open, modular architectures are pushing the market forward, while longer-standing systems are working to modernize their architectures. Meanwhile, 44% of digital businesses have been actively evaluating a new OMS: a number that reflects both the urgency of the problem and the dissatisfaction with existing solutions.
The direction is clear, and it follows the same market maturation pattern that has played out in category after category across enterprise software. On the front end, brands are consolidating onto simpler, faster, lower-TCO platforms: Shopify’s enterprise momentum in 2025 and 2026 is the most visible proof. On the back end, the same dynamic is beginning to play out in order management. The brands that moved to Shopify for speed and simplicity aren’t going to accept an 18-month, seven-figure OMS implementation on the other side of the stack.
For brands and retailers evaluating their order management strategy today, the question is no longer which OMS has the most features. In a mature market, feature count is a vanity metric. The questions that matter are: How fast can it be deployed? How does it connect to the existing stack? Can it operate alongside what is already in place? What is the real total cost of ownership? Is AI a bolt-on feature or the foundation the platform is built on? And does the solution reduce operational burden, or does it add yet another layer of complexity to an already complex stack?
Fourth Era solutions answer those questions differently than anything that came before. For the growing number of brands that are fed up with 18-month implementations, seven-figure budgets, and integration projects that never truly end, those answers matter more than any feature matrix ever could. The market has matured. The buyers have spoken. And the era of complexity-as-a-feature is ending.
