Improve forecasts with demand planning software

Leverage demand sensing, statistical modeling and AI/machine learning and collaborative forecasting to generate highly accurate forecasts, enabling your business to anticipate market needs, optimize inventory and improve customer service levels.

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Explore how QAD DSCP leverages advanced technology to ensure better supply chain performance and resilience.

Key Benefits of Demand Planning

Increase Revenue

Ensure having the right product at the right place at the right time to meet customer expectations.

Minimize Expediting Costs

Limit the surprise orders and the associated costs in expedited freight and additional handling.

Improve Customer Service

Reduce penalties by having the best possible picture of your customer’s future requirements.

Reduce Inventory Costs

Lower working capital and excess stock write offs by ensuring optimal product availability.

Key Capabilities to Boost Forecast Accuracy

Demand sensing
Utilize real-time customer demand signals to drive a short horizon demand management approach.
Statistical forecasting
QAD’s solution addresses complex seasonality, external factors and trend analysis with artificial intelligence (AI) and a library of forecasting methods.
Dimension flexibility
Manage the forecast in days, weeks, or months; by SKU, category, brand, customer, warehouse, region; in units, pallets, kilograms or by other dimensions.
Management by exception
Your organization can manage extensive product portfolios more effectively and ensure your planners prioritize events that deliver the highest value.
Collaboration
Sales and Operations Planning (S&OP/IBP) facilitates communication and decision-making across your organization to balance supply and demand, supporting your business planning efforts.
CASE STUDY

ARMOR Group, a European leader in compatible cartridges, centralizes sales forecast planning and controls its supply chain with QAD Digital Supply Chain Planning solutions.

ALL customer stories

Featured Resources

Blog

Demand Planning Key Features

See how AI transforms planning and unlocks supply chain efficiency.

Blog

What Does AI Forecasting Look Like?

See how AI transforms planning and unlocks supply chain efficiency.

White Paper

Promotions Planning for Supply Chain Planning

Trade promotions for manufacturers are complex. Better understand how and why to include promotion activity in your planning efforts.

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Questions? Connect with QAD to discuss your supplier management needs and goals.

Frequently Asked Questions

What exactly is agentic AI?

Agentic AI is artificial intelligence designed to act autonomously toward a goal. Instead of just responding to prompts or offering recommendations, it can plan, make decisions, and take actions across systems to complete tasks and drive real business outcomes with minimal human input. In manufacturing, this means AI that can proactively balance supply and demand, adjust production schedules, resolve exceptions, automate routine ERP processes, and respond to disruptions in real time, helping manufacturers operate more efficiently, resiliently, and at scale.

What is the difference between generative AI and agentic AI?

Agentic AI is artificial intelligence designed to act autonomously toward a goal. Instead of just responding to prompts or offering recommendations, it can plan, make decisions, and take actions across systems to complete tasks and drive real business outcomes with minimal human input. In manufacturing, this means AI that can proactively balance supply and demand, adjust production schedules, resolve exceptions, automate routine ERP processes, and respond to disruptions in real time, helping manufacturers operate more efficiently, resiliently, and at scale.

What is the difference between generative AI and agentic AI?

Agentic AI is artificial intelligence designed to act autonomously toward a goal. Instead of just responding to prompts or offering recommendations, it can plan, make decisions, and take actions across systems to complete tasks and drive real business outcomes with minimal human input. In manufacturing, this means AI that can proactively balance supply and demand, adjust production schedules, resolve exceptions, automate routine ERP processes, and respond to disruptions in real time, helping manufacturers operate more efficiently, resiliently, and at scale.

What is the difference between generative AI and agentic AI?

Agentic AI is artificial intelligence designed to act autonomously toward a goal. Instead of just responding to prompts or offering recommendations, it can plan, make decisions, and take actions across systems to complete tasks and drive real business outcomes with minimal human input. In manufacturing, this means AI that can proactively balance supply and demand, adjust production schedules, resolve exceptions, automate routine ERP processes, and respond to disruptions in real time, helping manufacturers operate more efficiently, resiliently, and at scale.

What is the difference between generative AI and agentic AI?

Agentic AI is artificial intelligence designed to act autonomously toward a goal. Instead of just responding to prompts or offering recommendations, it can plan, make decisions, and take actions across systems to complete tasks and drive real business outcomes with minimal human input. In manufacturing, this means AI that can proactively balance supply and demand, adjust production schedules, resolve exceptions, automate routine ERP processes, and respond to disruptions in real time, helping manufacturers operate more efficiently, resiliently, and at scale.

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