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Quota Planning

Assign more accurate, equitable and attainable sales quotas with intelligent models and integrated data

Pyplan Quota Planning combines historical data, market potential, team capacity and dynamic scenarios to define realistic, balanced goals aligned with business objectives.

More justice, more clarity, more commercial performance.

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More realistic and potential-oriented goals

It integrates customer data, territories, history and projections to build attainable shares adjusted to the true potential of each portfolio.

Increased transparency and internal alignment

It standardises criteria, eliminates arbitrariness and ensures traceability throughout the quota definition process.

Optimizing business performance

It allows you to simulate scenarios, redistribute loads and anticipate risks of over- or underallocation to maximize team effectiveness.

Fewer conflicts and greater commitment

By assigning quotas fairly and based on data, teams' trust is strengthened and motivation to achieve results is improved.

Main Features

Multidimensional quota modeling

Define and distribute quotas by vendor, team, region, channel, product or customer, reflecting the real complexity of the business.

Integration with budgeting and forecasting

Build quotas directly from the financial plan, maintaining consistency between business objectives and expected results.

Simulation of quota scenarios

Evaluate the impact of changes in objectives, mix, headcount, or territories on revenue, margin, and incentives.

Business capacity analysis

Incorporate historic productivity, ramp-up of new sellers, and market potential for more realistic allocations.

Governance and approval workflows

Manage versions, validations and adjustments with full traceability and clear rules.

Real-time tracking dashboards

Monitor share vs. achievement, gaps, risks and their impact on forecasts and financial results.

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

AI knows business. It doesn't know yours.

Why the competitive advantage of AI in business doesn't lie in the LLM, but in a model of your own business that learns from every period you close.

Article

What is DRP? How to plan distribution

What DRP is, how to calculate it step-by-step with an example, how it differs from MRP, and the benefits it brings to a distribution network.

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?

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