Inventory forecasting is a continuous process that helps you gauge future demand and optimise stock levels. By blending historical sales data, market trends, and other factors, you can estimate the quantity of items required for specific periods. AGR’s software can break this demand down according to your BOM structure to forecast component or raw material needs.

Accurate forecasting delivers the ability to predict what customers will buy, when, and in what quantities. This is crucial for Halma companies to maintain high service levels while controlling inventory costs. By balancing stock levels, you can prevent lost revenue from stockouts and minimize excess inventory that ties up cash flow and increases storage costs.

Accurate forecasting supports strategic decision-making, helping you strengthen supply chain resilience and navigate challenges like prolonged lead times, fluctuating prices, and diverse sales channels. Ultimately, it improves your bottom line and frees up working capital for growth.

What’s Holding You Back?

Data is key. From historical sales figures to real-time transaction feeds, accurate forecasting hinges on leveraging diverse information. While your ERP system is a valuable data repository, it likely lacks strong forecasting tools, leaving you reliant on cumbersome spreadsheets.

Common ERP limitations:

• Rigid forecasting models: Limited to a single model, which reduces forecast accuracy.
• Difficulty with seasonality and trends: Inadequate for managing fluctuating demand patterns.
• Integration challenges: Difficult to connect with other systems or data sources.
• Complex implementation and upkeep: High effort required for setup and ongoing maintenance.

 

Look Ahead with AGR

AGR’s cloud-based software helps Halma companies reduce carrying costs, avoid stockouts, and maximise sales by providing accurate demand forecasts.

Why Choose AGR:

• Multiple forecasting models: Find the most accurate fit for each item’s future demand.
• Smart forecasting engine: Analyse demand patterns and select the best forecast model.
• Fast implementation and scalability: Start seeing results quickly.
• User-friendly interface: Make data-driven decisions with ease

 

Optimising Inventory Turnover

Once forecasting is in place, the next step is to optimise inventory turnover—how quickly products sell and are replaced. A high turnover ratio indicates strong sales or understocking, while a low ratio suggests excess inventory.

Why Efficient Inventory Turnover Matters

• Lower holding costs: Free up capital for reinvestment.
• Improved cash flow: Faster sales conversion into cash.
• Reduced risk of obsolescence: Avoid outdated stock.
• Better decision-making: Improve pricing, purchasing, and promotions.
• Enhanced competitiveness: Respond quickly to demand and avoid stockouts

Common Inventory Turnover Challenges

• Accurate data and analytics: Manual data entry can lead to poor decisions.
• Forecasting accuracy: Difficult for wholesalers managing diverse products.
• Internal collaboration: Siloed teams lead to poor order planning.
• Supplier relationships: Long lead times impact planning.
• Limited technology: Outdated systems hinder real-time tracking and forecasting.

 

Tips for Optimising Inventory Turnover

Enable Data-Driven Decisions

• Invest in data analytics tools to track demand, sales, and inventory levels.
• Use advanced forecasting techniques, such as machine learning, for complex demand patterns.
• Implement ABC analysis to categorise products based on value and turnover.

Optimise Purchasing & Supply Chain

• Strengthen relationships with reliable suppliers.
• Negotiate shorter lead times and flexible order quantities.
• Explore just-in-time (JIT) inventory principles.

Use Safety Stock Effectively

• Maintain safety stock for critical items.
• Calculate optimal safety stock based on demand variability and lead times.
• Regularly review and adjust safety stock levels.