Review of OMP, Supply Chain Planning Software Vendor
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OMP, founded in 1985, has evolved from its early days of developing simple planning software into a global leader in digitized, integrated supply chain planning solutions. With its flagship Unison Planning™ platform, the company combines end-to-end planning—covering demand forecasting, supply planning, production scheduling, inventory management, and distribution—with real-time simulation and scenario analysis. OMP’s offering leverages robust data integration (notably with SAP-based ERP systems) and is delivered as a cloud-based SaaS on Microsoft Azure, ensuring scalable performance, secure deployment, and low total cost of ownership. Advanced AI and machine learning techniques, including explainable AI (XAI) modules, underpin its dynamic forecasting and decision intelligence features, making the platform both agile and transparent. Backed by strategic investors and employing over 1,200 people across regions from Belgium to Asia and North America, OMP represents a mature, decision-centric approach to modern supply chain challenges.
Overview of OMP
OMP, established in 1985, has grown from humble beginnings into a global supplier of supply chain planning solutions. Backed by investors such as Ackermans & van Haaren,1 OMP serves industries ranging from chemicals and consumer goods to metals. Its flagship Unison Planning™ platform and a workforce exceeding 1,200 employees—spread across regions including Belgium, China, and the US2—underscore its longstanding presence and expansive reach in the market.
Company Background and Global Presence
From its initial forays into planning software, OMP has continuously refined its offerings. Today, the company’s solutions are recognized for integrating strategic planning with operational execution, ensuring that every facet of the supply chain is both visible and actionable.
Capabilities and Deliverables of the OMP Solution
OMP’s supply chain planning solution is built to deliver a comprehensive, end-to-end planning capability.
Practical Capabilities
The platform offers integrated planning that covers demand forecasting, supply planning, production scheduling, inventory management, and distribution decisions—all consolidated into a “telescopic digital twin” that aligns strategic direction with day-to-day operations. With modules such as Data Genie ensuring synchronized master data between ERP systems and operational reality, planners can model different scenarios, conduct rapid what‐if analyses, and adjust operations in real time.3
Technological Advancements
OMP emphasizes advanced optimization methods by harnessing classical mathematical programming (LP-MIP), meta-heuristics, and so-called “intelligent solvers” to address complex, multi-period planning challenges.4 Its digital twin concept uniquely allows users to seamlessly zoom between operational detail and strategic overview. Complementing these capabilities, the platform integrates AI and machine learning—for example, deep learning in demand forecasting—while deploying explainable AI (XAI) modules that clarify model predictions and limitations, thereby fostering trust among supply chain planners.5
Technical Implementation of the OMP Solution
OMP’s technical foundation combines established optimization techniques with modern cloud, integration, and AI approaches.
Underlying Technology & Architecture
At its core, the OMP solution employs classical optimization techniques such as LP-MIP and meta-heuristics embedded within a robust simulation engine. The system utilizes a comprehensive data model for bi-directional integration with ERP systems (via the OMP Integrator for SAP), ensuring consistent, real-time data flow across platforms. Moreover, being deployed on Microsoft Azure enables scalable, secure operations with minimal IT footprint for clients.346
AI/ML and Explainability
OMP integrates machine learning models to continuously improve demand forecasting and refine its digital twin. By learning from both historical and real-time data streams, the solution adapts its models dynamically. Its built-in explainable AI features address the “black box” challenge typically associated with deep learning, offering transparency into the data inputs and model outputs to build user confidence.5
Tech Stack and Deployment Insights
Insights from recruitment materials indicate that OMP’s tech stack requires expertise in both proprietary planning tools and standard enterprise technologies such as SAP ERP/APO. Delivered as a cloud-based SaaS, the platform transforms traditional, batch-oriented planning cycles into agile, near real-time operations while keeping the total cost of ownership low and offering scalable deployment options.7
Critical and Skeptical Observations
While OMP’s solution is positioned as state-of-the-art—with features such as a telescopic digital twin, intelligent solvers, and integrated AI—the technical documentation offers only high-level descriptions of its proprietary algorithms. Buzzwords like “telescopic digital twin” and “intelligent solvers” may mask underlying complexities that warrant independent performance benchmarking. Furthermore, despite robust integration with SAP systems and dependable cloud deployment on Azure, the lack of in-depth algorithmic transparency calls for cautious evaluation in real-world, complex supply chain settings.
OMP vs Lokad
Although both OMP and Lokad operate in the supply chain planning domain, their approaches diverge significantly. OMP, with its origins in 1985, focuses on an integrated, end-to-end planning ecosystem that emphasizes classical optimization techniques (LP-MIP, meta-heuristics) and seamless ERP integration—particularly with SAP—to synchronize strategic and operational data. In contrast, Lokad (founded in 2008) leverages a quantitative, programmable approach through its domain-specific Envision language, relying on probabilistic forecasting, deep learning, and differentiable programming to provide prescriptive, automated decision-making capabilities. Essentially, while OMP consolidates planning processes into a unified digital twin backed by robust simulation and real-time dashboards, Lokad offers a more agile, highly customizable platform centered on algorithmic rigor and tailored optimization. The choice between them will likely depend on an organization’s existing ERP investments, appetite for technical customization, and preference for either a comprehensive integrated suite or a programmable, data-intensive optimization engine.8
Conclusion
OMP’s comprehensive, cloud-based supply chain planning solution combines time-tested optimization methodologies with modern AI and seamless data integration. Its capabilities—from real-time simulation and dynamic scenario planning to explainable deep learning—offer supply chain executives a powerful toolkit for both strategic alignment and operational excellence. Nonetheless, the platform’s reliance on industry buzzwords and a lack of detailed technical disclosure suggest that prospective users should perform rigorous, independent evaluations to ensure the solution delivers in line with its promises. For organizations ready to embrace a digitally integrated, decision-centric approach to supply chain planning, OMP represents a compelling, albeit complex, option.