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FMCG Demand Forecasting & Cost Data
Retail & Consumer Behavior
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About
Fast-Moving Consumer Goods (FMCG) sales, inventory, and cost metrics are captured in this detailed collection, offering a granular view of daily operational performance. Designed to support demand forecasting and supply chain optimisation, the data tracks the flow of goods across categories such as Beverages, Snacks, Dairy, Household, and Personal Care. It enables analysts to evaluate promotion effectiveness, monitor stock levels against replenishment lead times, and perform time series analysis to drive data-led decisions in the retail sector.
Columns
- Date: The specific calendar date of the record, ranging from daily entries between 2022 and 2024.
- Product_Category: Classification of the item sold (e.g., Beverages, Household, Snacks, Dairy, Personal Care).
- Sales_Volume: The total quantity of units sold for the specific product on the given date.
- Price: The selling price per unit of the item.
- Promotion: A binary indicator (0 or 1) specifying whether the product was part of a promotional campaign.
- Store_Location: The geographic setting of the retail outlet, categorised as Urban, Suburban, or Rural.
- Weekday: Numerical representation of the day of the week (0 = Monday, 6 = Sunday).
- Supplier_Cost: The cost incurred to acquire the product from the supplier.
- Replenishment_Lead_Time: The duration (in days) required to restock the product.
- Stock_Level: The quantity of product units currently held in inventory.
Distribution
The data is structured in a CSV format containing 10 columns. It includes 1,000 distinct rows of daily records, ensuring a consistent dataset for statistical modelling and analysis without missing values.
Usage
- Demand Forecasting: Develop models to predict future sales volumes based on historical trends and seasonality.
- Inventory Management: Optimise stock levels by analysing replenishment lead times and current stock availability to prevent overstocking or stockouts.
- Cost Optimisation: Analyse the relationship between supplier costs and sales prices to improve profit margins.
- Promotion Analysis: Evaluate the impact of promotional activities on sales volume across different product categories.
- Supply Chain Decision Making: Enhance operational efficiency for stores in urban, suburban, and rural locations.
Coverage
- Time Range: The data covers the period from 01/01/2022 to 26/09/2024.
- Geographic Scope: Includes store locations classified as Urban, Rural, and Suburban.
- Demographic/Category Scope: Covers five major FMCG categories: Beverages, Household, Snacks, Dairy, and Personal Care.
License
CC0: Public Domain
Who Can Use It
- Supply Chain Managers: For optimising inventory flow and reducing holding costs.
- Data Analysts: For practicing time series forecasting and regression analysis.
- Retail Strategists: For understanding the impact of location and pricing on sales performance.
- Business Students: For learning operational analytics using real-world retail scenarios.
Dataset Name Suggestions
- Daily FMCG Sales and Inventory Pulse
- Global FMCG Supply Chain & Sales Metrics
- FMCG Demand Forecasting & Cost Data
- Retail Operations: Sales, Stock & Promotions
Attributes
Original Data Source: FMCG Demand Forecasting & Cost Data
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