Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023)

Business Challenges of Forecasting Sales in Bakery Industry: Applications of Machine Learning Algorithms

Authors
Perini PraveenaSri1, *, Vaddi Naga Padma Prasuna2, R. Murugesan3, S. P. Usha4
1ICFAI Faculty of Social Sciences, ICFAI Foundation for Higher Education, Hyderabad, Telangana, India
2Electronics and Communication Engineering, Atria Institute of Technology, Bengaluru, Karnataka, 560024, India
3Electronics and Communication Engineering, Narasimha Reddy Engineering College, Secunderabad, 500100, India
4Atria Institute of Technology, Bengaluru, Karnataka, 560024, India
*Corresponding author. Email: praveena.sriperini@ibsindia.org
Corresponding Author
Perini PraveenaSri
Available Online 10 May 2023.
DOI
10.2991/978-94-6463-162-3_30How to use a DOI?
Keywords
Bakery Industry; Sales Forecasting; Strategic Management tools; Machine Learning Algorithms
Abstract

The bakery industry is continually advancing with the send-off of inventive items there by making future development. The rising impact of western consuming regimens, expanding urbanization, the rising working ladies’ populace, essentially add to the advancement of the baked products industry. The worldwide pastry kitchen items market is anticipated to develop from USD 416.36 billion of every 2021 to USD 590.54 billion by 2028, developing at a Compound Annual Growth Rate of 5.12%. Taking cue from this, the research paper has deployed machine learning (ML) strategies in the area of sales forecasting for the purpose of easing production planning as an integral part of Business Management. Machine learning is used in the French Bakery Industry Data Set with a reference period of from 2021-01-01 to 2022-09-30 to use a wide range of varied variables. For example, total sales, total return, sales per return and sales forecasting that affect the production of products. The research investigation of a pastry shop organization shows that there are tremendous variations in the demand depicting the seasonality of sales across numerous differentiated products of bakery items. With our research study, the paper hopes to stimulate scholars to momentously investigate in the arena of sales planning using machine learning. The paper also ushers gainful insights by application of premeditated strategic management tools in the various Business processes in the Bakery Industry.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
10 May 2023
ISBN
978-94-6463-162-3
ISSN
2352-5428
DOI
10.2991/978-94-6463-162-3_30How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Perini PraveenaSri
AU  - Vaddi Naga Padma Prasuna
AU  - R. Murugesan
AU  - S. P. Usha
PY  - 2023
DA  - 2023/05/10
TI  - Business Challenges of Forecasting Sales in Bakery Industry: Applications of Machine Learning Algorithms
BT  - Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023)
PB  - Atlantis Press
SP  - 335
EP  - 352
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-162-3_30
DO  - 10.2991/978-94-6463-162-3_30
ID  - PraveenaSri2023
ER  -