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Source: OMP
OMP Unveils Decision-Centric Planning to Accelerate Supply Chain Decision Velocity
New approach shifts planning from reactive processes to AI-driven decision intelligence

ANTWERPEN, BELGIUM, Mar 3, 2026 - (ACN Newswire) - OMP, a leading provider of AI-powered supply chain planning solutions, launches Unison Decision-Centric Planning, a new approach that helps organizations move from reactive, process-driven planning to proactive, event-driven decision-making.

Built on OMP's flagship Unison Planning™ platform, Unison Decision-Centric Planning combines advanced AI, autonomous agents, real-time scenario modeling, and human validation to accelerate decision velocity. The approach enables organizations to anticipate disruption, evaluate trade-offs, and act with confidence in increasingly volatile supply chain environments.

From reactive to proactive supply chain planning

Traditional planning cycles are often too slow to keep pace with today's volatility. Unison Decision-Centric Planning replaces static, process-driven planning with a dynamic, decision-first approach that continuously senses change, identifies relevant scenarios, and quantifies business impact. By aligning AI-driven intelligence with human judgment, organizations move from reactive firefighting to proactive value optimization.

"With Unison Decision-Centric Planning, we help customers move beyond reactive firefighting," said Tom Wouters, Chief Product Officer at OMP.

"By combining human expertise with advanced AI and scenario modeling, we enable confident, proactive decisions that drive agility, resilience, and measurable business impact."

Human-AI synergy for smarter, faster decisions

Unison Decision-Centric Planning leverages UnisonIQ to orchestrate AI agents, generative AI assistants, and advanced optimization engines. Routine manual tasks are automated, freeing planners to focus on cross-functional collaboration and decision-making. Explainable AI ensures transparency and trust, while autonomous agents continuously monitor supply chain signals and act in real time.

Proven impact at Evonik Oxeno

Evonik Oxeno, a leading producer of C4 chemicals, partnered with OMP to transition from reactive planning to always-on, scenario-based decision-making. By leveraging real-time insights and simulations through Unison Planning, planners can anticipate disruptions and respond faster, improving agility and overall business performance.

"Unison Decision-Centric Planning has reinforced trust in the system among planners and executives. Scenario-based decision-making enables us to respond faster and improve company performance," said David Kochanek, Supply Chain Solution Manager at Evonik Oxeno.

"Scenario-based decision-making enables us to respond faster and improve company performance."

Always-on decision intelligence at scale

Unison Decision-Centric Planning introduces event-driven agents that continuously assess opportunities or risks, aligning decisions with strategic and financial objectives. By running hundreds of scenarios, organizations can anticipate disruption, optimize outcomes, and achieve measurable gains in service levels, cost efficiency, sustainability, and decision velocity.

"Organizations can run hundreds of scenarios to prepare for disruptions and optimize outcomes."

Learn more about decision-centric planning

Discover how decision-centric planning can transform your supply chain. Explore OMP's resources, including the always-on e-book and the full Evonik Oxeno success story. Learn more.

About OMP

OMP helps companies facing complex planning challenges to excel, grow, and thrive by offering the best digitized supply chain planning solution on the market. Hundreds of customers in a wide range of industries - spanning consumer goods, life sciences, chemicals, metals, paper, packaging, plastics - benefit from using OMP's unique Unison Planning™.

Solution and product inquiries
Contact OMP

Media inquiries
Kira Perdue (Carabiner)

SOURCE: OMP



Topic: Press release summary
Source: OMP

Sectors: Transport & Logistics, Artificial Intel [AI]
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