ASACT - Data preparation for forecasting: A method to substitute transaction data for unavailable product consumption data
| Autor: | Bruno Agard, Paul W. Murray, Marco Barajas |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Consumption (economics)
Economics and Econometrics Computer science 05 social sciences Aggregate (data warehouse) 02 engineering and technology Management Science and Operations Research computer.software_genre General Business Management and Accounting Industrial and Manufacturing Engineering Synthetic data Product (business) Bullwhip effect 0502 economics and business 0202 electrical engineering electronic engineering information engineering Vendor-managed inventory 020201 artificial intelligence & image processing Data mining Transaction data computer 050203 business & management |
| Zdroj: | International Journal of Production Economics. 203:264-275 |
| ISSN: | 0925-5273 |
| DOI: | 10.1016/j.ijpe.2018.07.010 |
| Popis: | Strategic supply chain planning relies on accurate, long-range forecasts. Accurate forecasts, in turn, rely on the availability of suitable data and information from which a prediction can be made. In some domains, such as vendor managed inventory, product consumption data may not be available because of a lack of collaborative information. Delivery records are on occasion substituted for absent consumption data. This substitute information, however, can appear lumpy and intermittent due to the bullwhip effect and other logistics factors. The proposed ASACT (Aggregate, Smooth, Aggregate, Convert to Time-series) method applies aggregation and smoothing to transform delivery records into time-series data that creates a good approximation of actual consumption behavior; noise in the data is reduced while behavior patterns are preserved. Synthetic data is used to test the method against traditional methods, and real data is used to demonstrate the method's application in industry. Tests have shown that ASACT improves on the results produced by traditional methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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