Sales Prediction of a Pharmaceutical Distribution Company

Authors

  • Smriti Keny New Horizon Institute of Technology and Management, Thane, University of Mumbai, India https://orcid.org/0000-0002-4849-122X
  • Sagarika Nair New Horizon Institute of Technology and Management, Thane, University of Mumbai, India https://orcid.org/0000-0003-2044-9705
  • Silka Nandi New Horizon Institute of Technology and Management, Thane, University of Mumbai, India
  • Deepak Khachane New Horizon Institute of Technology and Management, Thane, University of Mumbai, India

Keywords:

PDCs, SVR, Inventory management, Sales prediction, Data Analysis, Data Visualization

Abstract

The study aims to find an appropriate model to extract insights from the sales of a Pharmaceutical Distribution Company (PDC) and make it available in an interactive and readable manner for the company. In PDCs, it is highly important to obtain a good approximation of the medicine needs, due to the short shelf life of many medicines and the need to control stock levels. The presented method is a combination of analysis and interactive visualization tools along with prediction. In this paper, we explore the use of Support Vector Regression algorithm for the sales prediction of individual products. The proposed model helps to present the sales data in a better way such that understanding the trends and seasonality becomes easier for the PDCs. The dataset has information of hourly, daily, weekly and monthly sales of the drugs and hence the end results also give us a likely classified understanding of the sales. The study of the results obtained, suggest that the proposed model may be considered appropriate for product sales prediction.

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References

Khalil Zadeh, Neda &Sepehri, Mohammad Mehdi &Farvaresh, Hamid. (2014). “Intelligent Sales Prediction for Pharmaceutical Distribution Companies: A Data Mining Based Approach.” Mathematical Problems in Engineering. 2014. 1-15. 10.1155/2014/420310.

Ribeiro, I. Seruca and N. Durão, "Sales prediction for a pharmaceutical distribution company: A data mining-based approach," 2016 11th Iberian Conference on Information Systems and Technologies (CISTI), Las Palmas, 2016, pp. 1-7, doi: 10.1109/CISTI.2016.7521397.

Keerti Nilesh Mahajan et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, “Business Intelligent Smart Sales Prediction Analysis for Pharmaceutical Distribution and Proposed Generic Model”, Vol. 8 (3), 2017, 407-412

A G Kravets, M A A,-Gunaid, V I Loshmanov, S SRasulov, L B Lempert, Model of medicines sales forecasting taking into account factors of influence. International Conference Information Technologies in Business and Industry 2018.

C. I. Papanagnou and O. Matthews-Amune, "An Estimation Model for Hypertension Drug Demand in Retail Pharmacies with the Aid of Big Data Analytics," 2017 IEEE 19th Conference on Business Informatics

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Published

2021-05-25

How to Cite

[1]
S. Keny, S. Nair, S. . . Nandi, and D. . Khachane, “Sales Prediction of a Pharmaceutical Distribution Company”, international journal of engineering and applied physics, vol. 1, no. 2, pp. 186–191, May 2021.

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Articles