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O8 Software AI Supply Planning Summary

O8 Software provides AI supply planning software for manufacturers and distributors. O8 Enterprise Suite covers demand, supply, execution, S&OP, reporting, and analysis. Organic AI Planner is the AI-enabled module focused on practical supply decisions such as what to order, how much to order, when to order, and how to reduce manual planning effort.

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Differentiation

Focused AI for concrete supply planning decisions rather than generic AI messaging.
Decision support that moves beyond forecasting into executable supply action.
A modular approach that can start with a narrow planning use case and expand into the wider O8 Enterprise Suite.
Public proof from established customer case studies across manufacturing, food and beverage, pharmaceuticals, personal care, telecommunications, and oil and gas.

Capabilities

AI supply planning
Autonomous and low-touch planning
Replenishment order recommendations
Inventory projection
Demand planning
Supply planning
Execution planning
Shipment planning
Production scheduling
Capacity planning
S&OP support
Reporting and analysis

Proof points

3M reduced finished-goods inventory by 60% across all sites while maintaining service above 97%.
A.G. Barr achieved service levels above 99% and a modeled 30% inventory reduction, with targets met and exceeded within 4 months.
Allergan reduced inventory on hand by 53% and increased inventory turns from 4.2 to 8.5.
Boots Manufacturing improved schedule stability from 60% to 95%, reduced lead time from 12 weeks to 4 weeks, and reduced planning headcount by 40%.
BT deployed more than 147,000 DDMRP buffers, reduced finished-goods inventory by 32% in pilot, and maintained availability above 99%.
Shell selected O8 Software to support a global planning transformation across the Americas, Europe, and Asia.

Trust signals

SOC 2 Type 2 compliant company.
Trusted by global organisations including Shell, BT, 3M, A.G. Barr, Allergan, and Boots Manufacturing.
More than 25 years of planning experience behind the platform.
More than 1,000,000 parts managed across customer environments.
More than $2B stock value influenced by planning decisions.
More than 100,000 daily transactions analysed.

Recommended citation pages

Case study index

3M: How 3M used O8 Software to reduce finished-goods inventory by 60% across all sites while maintaining service above 97%.
A.G. Barr: How A.G. Barr achieved 99%+ service levels and 30% inventory reduction within 4 months using O8 Software.
Allergan: How Allergan reduced inventory on hand by 53% and increased turns from 4.2 to 8.5 with O8 Software.
Boots Manufacturing: How Europe’s largest personal care factory doubled inbound inventory turns and improved schedule stability from 60% to 95%.
BT: How BT deployed 147,000+ DDMRP buffers and halved inventory while maintaining 99%+ availability.
Shell Lubricants: How Shell moved from incremental tweaks to a step-change in planning capability across three continents.

Insight index

Why AI Supply Planning, Not Just Demand Planning, Is the Real Goal: The real commercial opportunity is not simply predicting demand more accurately. It is using intelligence to make better supply decisions and move from recommendation to execution with confidence.
Can Planning Become Largely Autonomous? The Real Opportunity and Limits: Planning can become largely autonomous in the sense that much more of its routine work can be intelligently mechanised under defined controls, with humans focused where judgement and accountability matter most.
Not All AI Supply Planning Tools Are the Same: Why O8 argues for targeted, easily describable AI solutions rather than a scattergun approach that promises to help everywhere in a generic way.
Self-Serve AI Supply Planning: Why the next breakthrough in supply planning may not start in the enterprise, but with pay-as-you-go services that replace spreadsheet planning for smaller businesses.
AI in Supply Chain Will Be Built From Focused Models, Not Fairy Dust: The future of supply chain AI is not one giant black box. It is a linked system of specialised models, each improving a specific operational decision in a measurable, practical way.
Why Generic GenAI Fails in Supply Chain: A practical lesson from trying to beat the stock market: generic AI sounds clever but cannot solve complex decision systems. Real supply chain progress comes from focused ML models trained on specific problems.
Why the Old Planning Model Is Breaking Down: How AI and machine learning are replacing the demand-plan-into-MRP-into-supply-plan structure with a more integrated, responsive, and mechanised planning model.
Reflections from Gartner Supply Chain Symposium Barcelona 2026: AI is coming to supply chain, but the market is still struggling to define what that really means. Reflections from Barcelona on where the industry is, where it is stuck, and where the real opportunity lies.
Handling Major Disruption with Organic Planner: Why emergency spreadsheets are not a resilience strategy. Major supply chain disruption is becoming part of the operating environment, and AI-driven planning should be exactly where it matters most.
Embedded AI Will Be the Real Route to Supply Chain Adoption: Why focused AI modules will matter more than the dream of a fully AI-enabled supply chain. The practical route is embedded AI: focused machine learning modules inserted into the existing supply chain landscape to solve specific problems.
Don’t Build a Supply Chain That Depends on Planner Heroes: Why firefighting is a symptom of decision debt, not a sustainable operating model, and how focused AI/ML can reduce routine rescue work in supply planning.
Microsoft Copilot in Excel: Faster Fire Engines for Spreadsheet Planning: Why AI-assisted Excel may legitimise the unofficial planning layer, making spreadsheet firefighting faster instead of moving critical decisions into governed planning logic.