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Alcohol Sales Regression in the state using AutoML

Supply chain management is a key component in operating any type of business successfully. The alcoholic beverages sales industry accounts for 222.5 billion US Dollars (Statista) and is one of the largest sectors in the sales industry. The importance of maintaining a sufficient inventory of liquor is essential to boost sales of the liquor store. Liquor stores in the state of Iowa, United States generate the highest monthly sales every year during December (Christmas Season). These liquor stores achieve 15 - 20 percent of their annual sales in this period. Under such circumstances, Supply Chain Management is crucial to ensure that the supply of liquor meets the demand accordingly. However, due to incorrect Sales predictions for December, the majority of liquor stores within Iowa had not been able to succeed with Supply Chain Management over the years. By the end of the Christmas season (December), the liquor stores might have run out of stock or might have a significant amount of unsold stock. As a result, these liquor stores lose an opportunity to generate sales by running out of stock or possessing a high cost with the remaining stock. In the year 2020, due to the COVID-19 pandemic, alcohol sales rose nearly 13% and caused an imbalance in the demand to supply ratios. (Iowacapitaldispatch,2020)

The reason for this problem is that majority of the liquor stores predict sales for December by calculating the moving sales average for the month over the last 5 years. A monthly predicted sales amount is generated from this calculation. The only aspect that is considered for the calculation is the month and year. Other aspects influencing sales such as day, region, product, and vendor are not considered for this calculation. As a result, there is a drastic difference between the sales predicted and the actual sales. In some situations, actual sales are drastically higher than the predicted sales while in some situations it is drastically lower than the predicted sales.

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