It is common knowledge that demand forecasting can be difficult. Retailers in Europe typically have a 15% accuracy in predicting the demand in a given season.
However, by using a simple fifteen-metric approach to assist with your demand forecasting for individual products, you can improve the accuracy of demand forecasts and reduce inventory levels. Let us discuss these metrics demand planning in detail:
1) Unique Sales Forecast per Item
This metric is based on historical data gathered from all stores combined. The challenge is to identify significant changes in consumer preferences and account for them when determining future sales.
2) Gherkin Analysis
In this metric, retailers analyze their top 10 most popular items to understand how they are performing each week so that they can forecast demand for these items more accurately.
3) Seasonality
This metric takes into account cyclical patterns of demand that are regularly repeated, such as clothing sales in the spring and fall.
4) Trending Analysis
Trending analysis looks at long-term changes in demand in order to determine whether there is an overall increase or decrease in demand for a particular product.
5) Historical Sales Patterns
This metric looks at how sales have changed over time for a particular product, in order to predict future demand.
6) Direct Analysis
Wikimedia Commons This metric uses key selling elements, such as sales numbers and product promotion, to determine how much demand should be forecasted.
7) Historic Stock Turnover Ratio (STOR)
This uber stock forecast ratio examines the number of times an item has sold compared to its inventory level. If customers are not buying an item as quickly as it is being restocked, it may be a sign that demand for the product is waning.
8) Promotional Analysis
This metric analyzes how demand changes when a store offers discounts on a particular product.
9) Backorder Rate
This metric measures the percentage of products that are ordered but not available for immediate delivery.
10) Vendor-Managed Inventory (VMI)
This metric takes into account the impact that supplier lead times have on inventory levels.
11) Capacity Utilization
This metric measures how efficiently a company is using its production resources.
12) Supplier Delivery Performance
This metric looks at the number of late deliveries from suppliers and their impact on inventory levels.
13) In-Stock Rates
Measuring the percentage of products that are in stock can help retailers to identify which items are selling well and should be ordered more often.
14) Gross Margin
Knowing a product’s gross margin can help retailers to determine whether a product is worth stocking.
15) Overall Profit and Loss
This metric looks at the big picture and provides an overall assessment of a company’s profitability.
By using these essential metrics, demand planners can develop more accurate forecasts for future sales, which will help to reduce overstock and understock levels.
Metrics discussed: Unique Sales Forecast per Item, Gherkin Analysis, Seasonality, Trending Analysis, Historical Sales Patterns, Direct Analysis, Historic Stock Turnover Ratio (STOR), Promotional Analysis, Backorder Rate, Vendor-Managed Inventory (VMI), Capacity Utilization, Supplier Delivery Performance, In-Stock Rates, Gross Margin, Overall Profit and Loss.
Key Points: Eighty percent of inventory shortages are caused by inaccurate forecasts. Effective demand forecasting can reduce overstock levels by 20-40%. A simple fifteen-metric approach is used to improve the accuracy of demand forecasting when planning for individual products. Different techniques can be used in order to obtain more accurate forecasts, such as analyzing historical sales patterns or trending analysis. Seasonality is another essential metric that looks at cyclical patterns of demand that are regularly repeated. Trends can be analyzed in order to determine an overall increase or decrease in demand for a particular product.
Direct Analysis uses key selling elements, such as sales numbers and product promotion, to determine how much demand should be forecasted. The Historic Stock Turnover Ratio (STOR) examines the number of times an item has sold compared to its inventory level. Promotional Analysis analyzes how demand changes when a store offers discounts on a particular product. The In-Stock Rates metric measures the percentage of products that are in stock and can help retailers to identify which items are selling well. By using these metrics, demand planners can develop more accurate forecasts for future sales, which will help to reduce overstock and understock levels.
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Summary
Retailers can improve the accuracy of demand forecasts and reduce inventory levels by using a simple fifteen-metric approach to assist with their demand planning for individual products. By using these metrics, retailers can develop more accurate forecasts for future sales, which will help to reduce overstock and understock levels.
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