000			01639nam a22002057a 4500
999			_c5078 _d5078
005			20230314152851.0
008			230314b ||||| |||| 00| 0 eng d
020			_a9783030858575
082			_a658.500727 _bCOH
100			_aCohen, Maxime C _911889
245			_aDemand prediction in retail: _ba practical guide to leverage data and predictive analytics
260			_bSpringer _aSwitzerland _c2022
300			_axvii, 155 p.
365			_aEURO _b64.99
520			_aFrom data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture. This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.
650			_aBusiness logistics--Management _912229
650			_aDemand (Economic theory) _912230
650			_aProduction management _9434
942			_2ddc _cBK