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Operational Inventory Forecasting Data
Data Science and Analytics
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About
This data product focuses on inventory management and prediction, providing detailed operational metrics necessary to predict the Material Requirements Planning (MRP) for forecasted quantities. The core objective of the data is to allow users to analyse supply chain flows, demand patterns, and lead times to effectively manage inventory levels and future material requirements. The dataset offers insight into specific item configurations, product details, and weekly demand periods across various supply chain types.
Columns
The dataset contains fifteen distinct columns detailing various aspects of the inventory and forecasting process:
- CCN: Core Customer Number, identifying the main customer classification.
- COMP_ITEM_ID: A unique identifier for the component item.
- COMMODITY: The classification of the raw material or item (e.g., ODM Mechanical).
- LEAD_TIME: The time, measured in relevant units (e.g., days/weeks), required from initiation to completion of a product or component delivery.
- CFG: Configuration details related to the item.
- ITM_DESC: A description of the item.
- CHANNEL_ID: The identifier for the sales or distribution channel.
- PRODUCT_ID: The unique identifier for the end product.
- PRODUCT_NAME: The name of the end product (e.g., PARTS, TULIP15SKLBTX).
- SCHEDULER_NAME: The designation of the scheduler responsible for planning (e.g., BTX_LATITUDE).
- DMND_WEEK_STRT_DATE: The calendar date marking the start of the demand week.
- VRSN_WEEK_STRT_DATE: The calendar date marking the start of the version week.
- MRP_FCST_QTY: The Material Requirements Planning Forecast Quantity, which is the key predictive target variable.
- SUPPLY_CHAIN_TYPE: Classification of the supply chain methodology employed (e.g., CTO - Configure to Order, BTO - Build to Order).
- DW_PKG_UPD_DTS: The package update timestamp.
Distribution
The data is provided in a single CSV file,
inventory.csv, with a file size of approximately 17.36 MB. It features 15 columns and contains approximately 106,000 valid records or rows. Missing and mismatched values are zero across all primary inventory and item identifier fields, ensuring high data quality for key columns.Usage
This dataset is ideal for:
- Developing predictive models to forecast future MRP requirements.
- Analysing correlations between lead times, scheduling methodologies, and forecast quantities.
- Optimising inventory holding costs and identifying bottlenecks in the supply chain process.
- Segmenting demand patterns based on channel identifiers and product configurations.
Coverage
The data provides a temporal scope focused on demand and version weeks spanning dates seen across 2015 and 2016, specifically covering periods around October 2015 and July 2016. Coverage is focused on internal supply chain operations, detailing types such as Configure to Order (CTO), which represents the largest segment of the data, and Build to Order (BTO). Geographic or external demographic information is not included.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Machine Learning Engineers: For building and testing time-series or regression models aimed at forecasting the MRP quantity.
- Supply Chain and Operations Managers: For auditing current inventory forecasting methodologies and enhancing strategic planning.
- Business Intelligence Analysts: For creating dashboards and reports on lead time distributions and product demand trends.
Dataset Name Suggestions
- MRP Forecast Quantity Predictor
- Supply Chain Inventory and Demand Data
- Lead Time and Material Planning Dataset
- Operational Inventory Forecasting Data
Attributes
Original Data Source: Operational Inventory Forecasting Data
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