Manhattan OMS vs IBM Sterling OMS

In this article I explore the differences between arguably the two most powerful order management systems available to enterprises today, IBM Sterling Order Management and Manhattan Active Omni. Both are used by large retailers, brand manufacturers and distributors. An OMS is a key component of a modern ecommerce architecture and selecting the right OMS for your business is critical.


Table of Contents

Active Omni vs Sterling - Main Differences

Active Omni is a cloud-native, API-first, microservices application built from the ground up and released in 2017. IBM Sterling has a 20+ year history and while it is moving in a similar architectural direction, it is not cloud-native throughout.

Active Omni has modern, sleek user interfaces for contact centre, store and logistics colleagues, whereas Sterling user interfaces are less intuitive and modern.

Active Omni has a store POS user interface for customers needing this, IBM does not. While this POS is unlikely to be used by a major retailer as its main system, it has credibility for line busting, a small services business, or for store service desks.

IBM has a huge installed base of enterprise clients and processes the biggest volumes of any OMS in the market. Manhattan has some solid brands using its system, but not to the same extent as IBM.

IBM has a wide range of language packs so that business users can operate in a UI in their native language.

Sterling has proven its ability to be customized and extended for use in several niche, complex areas of business. Manhattan does not have this breadth and depth of variety in its installations to prove its viability in multiple niches.

IBM has a huge network of consulting partners (large and small) for advice, implementation and change management, whereas Manhattan has relatively few and tends to perform the implementation itself, with the consequent risk of resource shortages.

Now let's dive into the detail of both products, starting with IBM.

IBM Sterling Order Management

IBM Sterling Order Management has been in development for many years both prior to and since its acquisition by IBM from AT&T in 2010 for $1.4bn in cash. It is arguably the most feature rich distributed order management system available today.

Core functional components include:

  • Inventory Visibility and ATP - including supply & demand matching, it is designed to collate a centralized view of inventory in stores & trade counters, in warehouses and 3PLs, at manufacturers and distributors, at drop ship suppliers, including future and in-transit stock
  • Order Orchestration - including configurable order lifecycles, event and alert management, omni-channel fulfillment, order promising and rules-based order sourcing
  • Optimized Order Sourcing - an AI approach to order sourcing optimizing against shipping cost, labor, capacity, stock & stockouts, markdowns, it includes a simulator and ability to explain the reasons why the source was chosen or not
  • Call Center Experience - including order capture, inventory visibility, order & customer maintenance, order & shipment visibility, appeasements, returns and exchanges
  • Store Experience - including clienteling, mobile line busting, product & inventory search, ship-from-store, BOPIS, omni-channel returns, store inventory management
  • Delivery & Service Scheduling - plus management of calendars, resource capacity, event-driven monitoring
  • Configure, Price, Quote (CPQ) - CPQ plus guided configuration, real-time product and service availability, automated pricing, approval processes
  • Reverse Logistics - including cross-channel returns, returns dispositions, return order status visibility, returns linked to sales orders, refunds and credits
  • Supply Collaboration - including inbound PO monitoring, linking with inventory supply & availability, inbound event handling

This collection of capabilities comes along with APIs, comprehensive business user tooling, and an analytics module.

IBM Sterling customers are predominately large brands, retailers and distributors including Burberry, IKEA, John Lewis, Pandora, M&S, Adidas, FedEx, DHL, GSK, Caterpillar, Carter's, DB Schenker, Sherwin-Williams, US Foods, Honda, HP, Lindt, Superdry. Walmart is reported to process 8 billion order lines per year through Sterling, and Monotaro processes orders from a catalog of over 10 million SKUs.

IBM Sterling Order Management Architecture

IBM Sterling is able to be deployed in multiple modes - On premises, containerized for public cloud, as SaaS, or hybrid.

IBM Sterling Order Management is also available in a so-called "next generation platform", meaning it is a SaaS offering hosted on IBM Cloud Kubernetes Service allowing elasticity and resilience. Customers can configure firewall policies and manage certificates with the platform's self service tools.

SaaS versions of Sterling are available in 6 environments:- Master Config, Integration, QA, Pre-Prod, Production, Disaster Recovery. It offers recovery time objective of 4 hours, with 2 hours recovery point objective. The cloud application is certified to ISO 27001/17/18.

For customization, each service has User Exits where custom code can be added, as well as propagating events that can be trapped, and exchanges XML or JSON data via APIs documented on the IBM developer website here. More than 1,200 APIs are available. Note that customer-created extensions are subject to evaluation for production readiness by IBM and they can require a customer to make changes to protect the service availability for other customers, if the impact of a piece of custom code is deemed too high.

The application can be configured to emit events at any point in a business process, propagated as email notifications, exception alerts, SMS, published XML to external queues or systems, invoking custom extensions or as events sent to applications such as data warehouses.

IBM Sterling Call Center is a separate application enabling contact center agents to manage orders, customers, inquiries, returns, appeasements and so on.

IBM Sterling Store (Aurora) extends the OMS to use at a store or trade counter environment where it can be used for tasks such as ship-from-store and store inventory management. 

Manhattan Active Omni History

Manhattan Active Omni, its flagship order management system, was built from the ground up as a cloud-native, API first application consisting of a set of containerized microservices. It was released in 2017, in 2018 it was a leader in the Forrester Wave for OMS, and was the only leader in the in the 2021 edition of the OMS Wave.

Active Omni pioneered a successful new technical direction for Manhattan Associates products, and was joined by Active Warehouse Management (WM) in 2020, Active Allocation in 2020, and Active Transportation Management (TM) in 2021.

Active Omni is in use by large brands and retailers such as Under Armour,  Barnes & Noble, TJ Maxx, Levi's, Lacoste, Diesel, Bottega Veneta, Gucci and many more. WM has over 60 customers.

Manhattan Active Omni Functionality

Active Omni has the following components

  • Customer Service and Engagement - including case management, telephony integration and social listening
  • Contact Center - including capturing, modifying, cancelling orders, applying promotions, managing returns and exchanges, appeasements, tax and sales posting, fraud detection, payment authorization and settlement, access to customer and order history
  • Enterprise Promotions - enabling the creation, publication and execution of promotions across all channels
  • POS Clienteling and Selling - including fixed and mobile POS user interfaces, in-store ordering / save the sale, omni-channel carts, returns & exchanges, appointments, access to customer and order history
  • Distributed Order Management - this is the heart of order management, including a centralized consolidated view of inventory across the enterprise, inventory segmentation, routing and fulfillment optimization, ATP, reservations, order orchestration and order workflow pipelines, order analytics
  • Store Inventory & Fulfillment - including ship-from-store function, pick, pack, despatch, pickup confirmation, store receipts and transfers, inventory visibility & adjustments

The product follows a quarterly release cycle, with zero downtime, for example adding an enterprise promotions engine and clienteling in 2018, RFID & store cycle counts in 2019, contactless curbside pickup in 2020, self-service BOPIS "ship it instead" in 2021, predictive promising (using machine language) in 2022. New functionality is first released to non production environments, and then to production two weeks later.

Manhattan Active Omni Technical Architecture

The whole Active Omni application is built on a cloud-native, stateless, microservices architecture that is highly available, always current, extensible and scalable.

Active Omni is hosted on the Google Cloud Platform using Docker containers consisting of REST endpoints, business logic, app core frameworks, Spring Boot, JDK and Debian Linux. Auto-scaling is turned on for live but not for staging.

Services hosted in a microservice propagate events that can be used to trigger external actions and also contain specific extension points to enable further customization.

The architecture uses several well regarded open-source middleware components including MySQL, Consul, Apache, Kubernetes, Apache Camel, Docker, Spring, Kafka, RabbitMQ and Elastic. Grafana and Kibana are used for monitoring and logging.

Active Omni has been SOC 2 Type 1 certified since Q2 2018 and continues to be validated twice per year.

Active Omni exposes all business logic as an accessible RESTful API. There are over 40,000 of these APIs available to developers, all documented in the developer docs. API response time is consistently extremely rapid; I have seen median API response times of well under 20ms and a 90th percentile of less than 125ms.

All code modifications or extensions for a specific customer are developed outside of the application and integrated using the APIs. This enables the core platform to be always latest version. User Interfaces can similarly be extended for specific customer need.

Manhattan provides its ProActive tool, a WYSIWYG configuration tool, to enable customers to extend the data model, services and user interfaces.

Machine Learning is embedded in several areas of Active Omni, for example the Adaptive Network Fulfillment (ANF) (optimal routing of an order for fulfillment). The fulfillment of each order takes into account fulfillment capacity, workload balancing, cut off times, labor costs, past performance of a node in the network, inventory on hand and in transit, margins from selling prices by location and markdowns, customer satisfaction as measured by achieving promised delivery dates, probability of delivery failure, and shipping costs, taking into account split shipments & consolidation. This part of Active Omni is extremely rich and very mature.

Screenshot of Active Omni Store Fulfillment
Screenshot of Active Omni Store Fulfillment

This article was updated on May 14, 2022

M Ryan

M Ryan is an ecommerce consultant with twenty years experience working with retailers, consumer brand manufacturers and other consumer-facing businesses helping them to develop their ecommerce strategy, implement ecommerce technology and improve their ecommerce operations. He works extensively throughout US and Europe, with clients including global brands, large retailers and household names in consumer goods.