Demand planning is the process of estimating future demand: how much will be needed, when, and where. This happens through analyzing customer trends, seasonality, promotions, and sales opportunities.

It is typically conducted at or at least translated to the SKU level and plays a crucial role in supply chain management, helping to align production and inventory with expected demand.

Unlike a sales forecast, which is often aggregated at a higher level and used for revenue projections, demand planning provides granular insights that drive operational decisions in supply chain and production planning.

Additionally, it differs from financial planning, as it focuses on units and volume projections, ensuring the right stock levels rather than just revenue streams.

The demand planning process typically follows these steps:

1. Data Collection: gathering historical data from orders/ shipments, typically out of the ERP system.
2. Data cleansing & preparation: cleaning outliers, missing values, and anomalies to ensure accurate forecasting is crucial. Stockouts, promotional effects and some major external events need to be considered. 
3. Portfolio & lifecycle management: ensuring new product introductions (NPI) and product phase-outs are included correctly in demand plans.
4. Forecast generation & review: using statistical models and advanced forecasting methods like machine learning, planners refine the demand plan for each SKU (typically done at a higher level and then disaggregated to SKU level).
5. Collaboration with sales and other teams: integrating market knowledge, customer info, and sales forecasts into the demand plan.
6. Performance monitoring & adjustment: regularly tracking forecast accuracy, reviewing forecast value add (FVA), and improving processes based on those reviews.
7. Integration with S&OP and IBP: aligning demand planning with broader business objectives, finance, and supply chain strategies for a cross-functional view of demand and supply.

AI and machine learning play an increasing role in enhancing demand planning accuracy by:

• Detecting outliers and anomalies: identifying unusual demand patterns or missing data points automatically.
• Recognizing trends and demand shifts: learning from external factors, such as economic indicators, weather, and real-time sales inputs.
• Understanding context in sales inputs: AI can analyze sales comments, CRM data, and demand drivers.
• Automating forecast updates: ML-based models dynamically adjust forecasts based on the latest data feeds, ensuring real-time adaptability.

Demand planning software should allow planners to improve forecast accuracy, automate workflows, and collaborate effectively. Key benefits include:

• Baseline forecasting: automatically generates demand forecasts using historical sales, statistical models, and machine learning.
• Tracking changes and auditability: logs adjustments and user modifications for better accountability.
• Automated alerts and outlier detection: flags anomalies in sales patterns, seasonality, and unexpected demand shifts.
• Collaboration and multi-user access: enables seamless input sharing across demand planners, sales teams, and finance.
• ERP and system integration: connects with ERP, inventory management, and supply planning tools to ensure synchronized decision-making.
• Scenario planning and what-if analysis: helps planners evaluate different demand scenarios and adjust forecasts accordingly.

Horizon provides a powerful demand planning platform that combines advanced models, AI suggestions, and collaborative tools to help planners optimize forecasts efficiently. Key features include:

• Multiple forecasting models: auto-selection from different demand forecasting techniques, including statistical models and machine learning models, tailored to your business trends.
• Collaborative planning: seamless interaction between planners, sales teams, and finance with real-time data visibility and approval workflows.
• Proactive recommendations: Horizon suggests forecast adjustments, identifies risks, and flags anomalies.
• Customizable for each user: Horizon is designed to be flexible, allowing planners to customize parameters, override forecasts, and adapt to industry-specific requirements.

Horizon ensures planners have full control over their demand planning while benefiting from AI-guided automation and insights.