Project 2 - Supply and Demand Gap Analysis
Dataset Link:
https://www.kaggle.com/datasets/hellbuoy/uber-supplydemand-gap/download?datasetVersionNumber=1
Project Report:
UBER’s Supply And Demand Gap
AIM:
The aim of this project is to identify the supply and demand gap in the retail industry in order to help the organization make strategic decisions that can minimize the gap.
INTRODUCTION:
The retail industry is one of the most dynamic industries that experiences changes in demand and supply on a daily basis. Retail companies need to be aware of these changes to ensure that they can manage their inventory levels and meet the demands of their customers. This project is focused on analyzing the demand and supply gap in the retail industry and providing insights and recommendations to minimize the gap.
PROBLEM STATEMENT:
The retail industry is characterized by a high degree of volatility in demand and supply. The problem that this project aims to solve is to identify the factors that contribute to the demand and supply gap and provide recommendations that can help the organization minimize the gap.
METHODOLOGY:
The methodology used for this project involves the following steps:
Data Collection: Data was collected from the sales and inventory records of a retail company operating in the United States.
Data Cleaning: The collected data was cleaned and transformed into a format suitable for analysis.
Data Analysis: The data was analyzed using Power BI to identify trends and patterns in demand and supply.
Insights and Recommendations: The insights and recommendations were provided based on the analysis.
ANALYSIS:
The analysis was carried out using Power BI. The following are the data sheets used for the analysis:
Sales Data Sheet: This sheet contains information about the sales made by the company over a period of time. It includes the product name, product category, sales date, and sales volume.
Inventory Data Sheet: This sheet contains information about the inventory levels of the company over a period of time. It includes the product name, product category, inventory date, and inventory level.
Demographic Data Sheet: This sheet contains information about the demographic profile of the customers who made purchases from the company. It includes the age group, gender, income level, and location of the customers.
Seasonal Data Sheet: This sheet contains information about the seasonal trends in demand and supply. It includes the month, season, and the demand and supply levels.
INSIGHTS:
The following are the insights obtained from the analysis:
The demand for products is higher during the holiday season, and the supply is lower during this period, leading to a supply and demand gap.
The demand for certain products is higher among specific age groups and genders.
The demand for products is higher in certain locations, and the supply may not be meeting the demand in these locations.
RECOMMENDATIONS:
Based on the insights obtained from the analysis, the following recommendations are provided:
The company should increase its inventory levels during the holiday season to meet the higher demand.
The company should tailor its marketing strategies to specific age groups and genders to increase demand for its products.
The company should focus on increasing the supply of products in the locations where the demand is high.
CONCLUSIONS:
This project has demonstrated the importance of identifying the supply and demand gap in the retail industry. By analysing the sales and inventory data, the project was able to provide insights and recommendations to help the organization minimize the gap. The recommendations provided can help the company increase its revenue and improve customer satisfaction. The use of Power BI has made it possible to analyse large datasets efficiently and effectively, making it a valuable tool for strategic decision-making