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Inventory Optimization

The perfect balance between cost and service

Pyplan Inventory Optimization reduces excesses, minimizes shortages and ensures the optimal level of service.

Less fixed capital, more fluidity in the operation.

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Balance between cost and service

Optimizes inventory levels considering replacement times, demand, risk and critical issues for each product.

Reduced obsolescence and waste

It improves turnover and avoids unnecessary accumulations, reducing losses due to expiration or deterioration.

Comprehensive inventory visibility

It allows you to monitor stocks throughout the chain, plant, warehouses and points of sale, in real time.

Adapting to changes in demand

Adjust inventory policies based on consumption variability or supply conditions.

Main Features

AI-based optimization models

They automatically adjust security inventories based on variability, lead times and critical aspects of each SKU.

Inventory Health Dashboards

Key indicators such as aging, slow movers, dynamic coverage and risks of obsolescence.

Simulation of replenishment policies

Evaluate the financial and operational impact of MOQ, economic batches, delivery frequency and lead times.

Multilevel visibility of inventories

Analysis by SKU, category, plant, channel, region or customer, with interactive filters.

Discover the supply chain and financial planning platform

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They trust Pyplan

Coty redefines its planning: from fragmented processes to decisions with real business impact

Coty transformed its S&OP by integrating demand, supply and finance into a single model, improving decisions and efficiency.

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When financial complexity requires another level: EDP Brasil redefines its FP&A with Pyplan

EDP Brasil transformed its financial planning by integrating projection, consolidation and scenarios into a single intelligent model.

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From complexity to total control: Coca-Cola Andina redefines its planning with Pyplan

Coca-Cola Andina transformed its financial planning by integrating data, scenarios and decisions into a single intelligent model.

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When planning ceases to be a risk and redefines InterCement's performance

InterCement transformed its S&OP with Pyplan, integrating demand, supply and costs to decide with greater precision and profitability.

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Planning under strict rules without losing agility: the new ENEL model

ENEL unified regulated margin planning, integrating data, scenarios and decisions into a single collaborative model.

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Resources

Article

Agentic AI in planning: separating the hype from the product

The 2026 tariff volatility requires replanning in days, not months. What capabilities do Supply Chain and Finance need to avoid being exposed?

Webinar

New Skills for the Demand Planner of the Future

The skills demand planners need as AI reshapes planning: more judgment, sharper analysis and better decisions.

Article

Demand Sensing: Process, Solutions and CPG Examples

What demand sensing is, the 5-step process, how to choose demand sensing software and how CPG companies use it to cut short-term forecast error.

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