This article aims to address the impacts that companies can have with the application of machine learning to carry out their demand forecasts, knowing that a more accurate demand forecast improves the performance of companies, making them more competitive. The methodology used was a literature review through descriptive, qualitative and with bibliographical surveys in International Journal from 2010 – 2022 by different authors. Findings show that the references prove that demand forecasting with the use of machine learning brings many benefits to organizations, for example, since the results are more accurate, there is better inventory management, consequently customer satisfaction for having the product at the right time and place. Further...
Sales and operations planning process has been a part of organizations’ everyday life al-ready tens ...
ABSTRACT: Machine learning has untapped potential in many branches of knowledge. Moreover, this pote...
This article explores the application of machine learning algorithms and big data analytics in predi...
Title: Exploring the technology of machine learning to improve the demand forecasting Authors: Vikto...
Inventory is an investment and a potential source of waste that needs to be carefully controlled. Fr...
Purpose In fast moving consumer goods sector (FMCGs), manufacturers’ access to demand related data (...
In a global market that makes room for more competitors by the day, some companies are turning to AI...
Retail companies, as production systems, must use their resources efficiently and make strategic dec...
The primary objective of this study was to design and implement a machine learning-based sales forec...
In today’s complex and ever-changing world, concerns about the lack of enough data have been replace...
Abstract—Sales-Demand Forecasting uses machine learning model to forecast demand of a product and to...
Using artificial intelligence (AI) and machine learning to improve demand forecasting is o...
The Product Demand Prediction Model is a machine learning-based approach that utilizes historical da...
Context: The context of this research is to forecast the sales of truck componentsusing machine lear...
The field of machine learning (ML) is of specific interest for production companies as it displays a...
Sales and operations planning process has been a part of organizations’ everyday life al-ready tens ...
ABSTRACT: Machine learning has untapped potential in many branches of knowledge. Moreover, this pote...
This article explores the application of machine learning algorithms and big data analytics in predi...
Title: Exploring the technology of machine learning to improve the demand forecasting Authors: Vikto...
Inventory is an investment and a potential source of waste that needs to be carefully controlled. Fr...
Purpose In fast moving consumer goods sector (FMCGs), manufacturers’ access to demand related data (...
In a global market that makes room for more competitors by the day, some companies are turning to AI...
Retail companies, as production systems, must use their resources efficiently and make strategic dec...
The primary objective of this study was to design and implement a machine learning-based sales forec...
In today’s complex and ever-changing world, concerns about the lack of enough data have been replace...
Abstract—Sales-Demand Forecasting uses machine learning model to forecast demand of a product and to...
Using artificial intelligence (AI) and machine learning to improve demand forecasting is o...
The Product Demand Prediction Model is a machine learning-based approach that utilizes historical da...
Context: The context of this research is to forecast the sales of truck componentsusing machine lear...
The field of machine learning (ML) is of specific interest for production companies as it displays a...
Sales and operations planning process has been a part of organizations’ everyday life al-ready tens ...
ABSTRACT: Machine learning has untapped potential in many branches of knowledge. Moreover, this pote...
This article explores the application of machine learning algorithms and big data analytics in predi...