Project 2 - Supply and Demand Gap Analysis

Detailed Documentations of Uber Supply and Demand Gap Analysis

• Aim - Main aim of our report is to analyze the supply demand gap of uber cars having two pickup points airport and city how did happen based on time.

• Introduction - In this blog, we are going to explore Uber supply demand gap data and try to find out the inference of how the increase the business.

• Problem statement - In this project, we find out uber is facing trip cancellation and non-availability of cars from airport and city leading to impact on the business and loss of potential.

• Methodology
• Data collection, cleaning and define new variables:

1. Import the data and transform the data to power query editor
2. Identifying the data quality issues and clean the data by using power query editor
3. Format date, time and extract new variables required for analysis
4. Relaced null value required for analysis

• Data exploration and analysis:

1. Analyze variables across different time slots
2. Identify the types of requests, time slots and locations that constitute for the supply demand gap.

• Outcome and recommendations:

1. Using different visualizations like bar graphs, line graphs to Visualizing the problem
2. Presenting the observations and recommendation to resolve the problem

• Methodology - Analysis
• Analysis - Problem:

 

1. Overall pickup request is the same in city and airport
2. From the request, around 19% of the cars get cancelled
3. From the request, around 39% of the cars are not available

• Analysis – Problem based on location:

 

1. The Percentage of cars that get cancelled from city is 16%
2. No cars available -is mainly at the airport –25% and city – 14%

• Analysis – Problem based on time:

1. The cars that get cancelled in the city are during the morning 10%
2. No cars are available in the airport are during evening 16%

1. There is gap of 58% in the supply of cars
2. In that 58%, 20% gap happens in the evening and 18% in the morning timeslot.

• Insights - In conclusion, we can take a look at the final Dashboard for further Analysis. We analyzed the data according to the request ID and driver Id for city and airport. In the Peak Morning Slot where the demand for City to Airport trips are high, there are maximum number of trip cancellations leading to great Gap in the Demand & Supply. A high gap of 10.54% can be seen during the morning peak hours. In the Peak Evening Slot where the demand for Airport to City trips are high, there are maximum number of “No Cars Available” leading to great Gap in the Demand & Supply. A high gap of 16% can be seen during the evening peak hours.

• Recommendations – Increase the no of vehicle in the evening slot from airport to city will be one solution. Promote continuous trip to airport with incentives and give special incentives for airport trips during peak time.

• Conclusions – Based on the data analysis and performed for supply demand gap. Following recommendation can be used by uber to reduce the between supply and demand gap from airport to city in the peak hours. In the morning and afternoon hours from airport to city demand is low, which means driver who completed a city to airport trips in the morning hours may be have to wait a long time to get a next trip or may be have to come back to city without passenger in the reason “No Cars Available” was observed in the evening from airport to city on peak hours.