Supply and Demand Gap Analysis

Supply and Demand Gap Analysis in the Airline Industry

Aim:

The aim of this project is to identify the gap between demand and supply in the airline industry using flight fare data. By analyzing the data, we will provide insights into the patterns and trends in flight fares, which can help the organization make strategic decisions to minimize the supply-demand gaps and optimize pricing.

Introduction:

The airline industry is highly competitive, and understanding the demand and supply dynamics is crucial for airlines to stay profitable. By analyzing historical flight fare data, we can gain insights into pricing patterns, peak demand periods, and potential supply-demand imbalances. This project aims to analyze flight fare data and provide recommendations to minimize the supply-demand gaps in the airline industry.

Data set:

The dataset contains the following columns:

• Date_of_journey: The date of the flight journey.
• Journey_day: The day of the week for the flight journey.
• Airline: The name of the airline.
• Flight_code: The code of the flight.
• Class: The class of the flight (e.g., Economy, Business).
• Source: The departure city or airport.
• Departure: The departure time of the flight.
• Total_stops: The number of stops in the flight.
• Arrival: The arrival time at the destination.
• Destination: The destination city or airport.
• Duration_in_hours: The duration of the flight in hours.
• Days_left: The number of days left between the booking and the journey date.
• Fare: The fare price for the flight.

These columns provide information about the flights, including their dates, airlines, departure and arrival details, duration, pricing, and other relevant factors for analyzing the supply-demand gaps in the airline industry.

Problem Statement:

The airline industry faces challenges in balancing the demand for flights with the available supply. Airlines need to understand the factors influencing demand and adjust their pricing and supply accordingly. The problem statement for this project is to identify the supply-demand gaps in the airline industry based on flight fare data and provide recommendations to minimize these gaps.

Methodology:

• Data Collection: Flight fare data was collected from the EaseMyTrip website using web scraping techniques. The data includes information such as the date of the journey, airline, flight code, class, source, departure time, total stops, arrival time, destination, duration, days left, and fare.
• Data Cleaning: The collected data were cleaned to remove any inconsistencies, missing values, or outliers. The cleaned dataset will be used for analysis.
• Exploratory Data Analysis: Various exploratory data analysis techniques will be applied to understand the distribution of flight fares, identify trends, and explore relationships between variables.
• Demand and Supply Analysis: The demand for flights will be analyzed based on factors such as journey day, departure time, duration, and days left. The supply will be analyzed based on factors such as airline, class, and total stops. By comparing the demand and supply trends, the supply-demand gaps will be identified.
• Insights and Recommendations: Based on the analysis, key insights regarding supply-demand gaps, pricing patterns, and peak demand periods will be derived. Recommendations will be provided to minimize the gaps and optimize pricing strategies.

Analysis:

The analysis will include various visualizations, charts, and tables to present the findings. Some of the analysis techniques that will be applied include:

• Distribution of flight fares
• Demand trends based on journey day and departure time
• Supply trends based on airline, class, and total stops
• Comparison of Demand and supply trends
• Identification of supply-demand gaps
• Pricing patterns and fluctuations

Insights:

Based on the analysis, the following insights can be derived:

• Peak demand periods: Identify the days and times when the demand for flights is highest.
• Pricing strategies: Understand the pricing patterns and fluctuations based on factors such as journey day, departure time, and duration.
• Supply-demand gaps: Identify the areas where there is a significant gap between the demand and supply of flights.
• Optimal supply allocation: Determine the airlines, classes, and routes that experience the highest demand and adjust the supply accordingly.

Recommendations:

Based on the insights, the following recommendations can be made:

• Pricing optimization: Adjust the fares based on demand patterns to maximize revenue and minimize supply-demand gaps.
• Capacity management: Allocate the available capacity efficiently based on demand patterns and peak periods.
• Marketing and promotions: Target marketing efforts during periods of low demand to stimulate demand and fill supply gaps.
• Route planning: Identify popular routes and adjust the flight schedules to meet the demand.
• Customer segmentation: Analyze customer preferences and behaviour to tailor offerings and pricing strategies.

Deliverables:

• Detailed Documentation: A comprehensive document outlining the aim, introduction, problem statement, methodology, analysis details, insights, recommendations, and conclusions of the project.
• Power BI Report: A Power BI report (.PBIX file) containing interactive visualizations and dashboards to present the findings and analysis of the project.
• PowerPoint Presentation: A PowerPoint presentation summarizing the project as a case study, including key highlights, methodology, analysis results, insights, and recommendations.

Conclusions:

In conclusion, this project aims to identify the supply-demand gaps in the airline industry using flight fare data. By analyzing the data and providing insights and recommendations, airlines can make informed decisions to minimize the gaps and optimize their pricing and supply strategies. The project will be presented as a case study using PowerPoint, and a detailed documentation report and Power BI report will be provided.

Project report by

BELBIN BENO R M