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SKYHACK

668 Registered Allowed team size: 1

668 Registered Allowed team size: 1

This campaign is over.

CHECK OUT OTHER HACKATHONS

Prototype Submission
Online
starts on:
Aug 25, 2023, 06:30 PM ()
ends on:
Aug 28, 2023, 12:30 PM ()

About
 * Overview
 * Themes
 * Prizes

FAQs Resource center Discussion




OVERVIEW





ANNOUNCEMENT


TOP 3 WINNERS :

 

Participant Name

Participant College Name

Winner category

Kunal Saini

Delhi Technological University

1st prize

Aryan Tanwar

Delhi Technological University

2nd prize

Varun Laul

Delhi Technological University

3rd prize



TOP 10 WINNERS :

 

Participant Name

Participant College Name

Winner category

Kunal Saini

Delhi Technological University

1st prize

Aryan Tanwar

Delhi Technological University

2nd prize

Varun Laul

Delhi Technological University

3rd prize

AIBHINAV UPADHYAY

Netaji Subhash University of Technology

Top 10

AMAN MISHRA

Delhi Technological University

Top 10

Manish Kumar

Delhi Technological University

Top 10

SAIBAL PATRA

Netaji Subhas Institute of Technology

Top 10

Satyam Mishra

Netaji Subhash Institute of Technology

Top 10

Vidit Pareshbhai Patel

Netaji Subhas University Of Technology

Top 10

RAGHAV KRISHAN GARG

Netaji Subhas Institute of Technology

Top 10

Calling all aspiring analytics enthusiasts and problem solvers! Are you ready to
showcase your analytical skills and innovative thinking? Join us for the SKYHACK
Data Analytics Hackathon, a thrilling competition that challenges you to harness
the power of data to solve real-world challenges for the airline industry!

Why Participate:

 * Hands-On Experience: Put your theoretical knowledge into practice by working
   on real-world datasets and challenges.
 * Prizes and Recognition: Compete for exciting prizes and gain recognition for
   your analytical prowess and problem-solving abilities.
 * Skill Enhancement: Sharpen your data analytics, critical thinking, and
   teamwork skills under tight deadlines.
 * Career Opportunities: Showcase your talents to get a direct interview call
   from United Airlines.

Objectives of this Hackathon:

 * Talent Identification: Identify and connect with top data analytics talent
   among recent graduates who demonstrate exceptional skills, creativity, and
   problem-solving abilities during the hackathon.
 * Recruitment Opportunity: Source potential candidates for internships,
   entry-level positions, or even future roles within your organization's data
   analytics teams.
 * Innovation Showcase: Witness firsthand the innovative solutions and fresh
   perspectives participants bring to data-related challenges, potentially
   inspiring new approaches within your company.
 * Engagement and Branding: Enhance your United Airlines' brand visibility by
   associating with an educational event that supports skill development and
   showcases our commitment to nurturing young talent.

Expectations from participants:

 * Active Engagement: We expect participants to actively engage in the hackathon
   activities, including data analysis, and problem-solving.
 * Data-Driven Approach: We encourage participants to use data-driven
   methodologies, tools, and techniques to analyze and interpret the provided
   datasets.
 * Innovative Thinking: We're looking for innovative and creative solutions that
   go beyond the obvious, showcasing participants' ability to think outside the
   box.
 * Technical Proficiency: Participants should demonstrate a solid understanding
   of data analytics concepts, programming languages (such as Python, R, or
   others), and relevant software tools.
 * Problem-Solving Skills: We expect participants to approach challenges
   analytically, breaking down complex problems into manageable components and
   proposing effective solutions.
 * Time Management: Participants should manage their time effectively,
   allocating sufficient time for data analysis, brainstorming, solution
   implementation, and presentation preparation.
 * Attention to Detail: We encourage participants to pay attention to detail in
   data cleaning, analysis, and visualization to ensure accuracy in their
   results.

Presentation Skills: Participants should be prepared to present their findings
and solutions confidently, using visuals and storytelling to convey their
insights effectively.

For your submission, please provide the following:-

 1. Your report containing your Findings, Insights & Recommendations in the form
    of a PPT or PDF. You can add visualizations like charts, flow diagrams,
    snapshots etc. in the report
 2. Any codes/scripts in Python/R used to work on the data along with
    instructions to run them. If you have put your scripts on a repository, you
    can share the link of the same
 3. Any additional material used to create your report

Please note that there is no limit on the number of slides/pages. The structure
of your report should include -table of contents, executive summary, headings ,
references, footnotes, and appendices


THEMES



Increase F&B service satisfaction rate

PROBLEM STATEMENT

As United Airlines is on its journey to becoming the largest airline in the
world, our focus continues to be on what our customers think of our products and
service and ensuring they are taken care of in the friendly skies. As an
analyst, you are required to leverage data to help in identifying opportunity
areas in United’s current Food &Beverage(F&B) service and make recommendations
which can help in increasing F&B (Food &Beverage) service satisfaction rate by
identifying pain points for our customers and challenges in our current
inventory planning.

Participants are expected to perform a Descriptive analysis to understand
patterns in our data and identify key drivers of overall customer satisfaction
and make recommendations based on their analysis.

BACKGROUND

Various studies suggest that airline F&B service has a significant impact on
customer experience and loyalty generation. F&B is also one of the key concerns
of unhappy customers as captured in their feedback forms. We have spent the last
few years focusing on improving F&B service by partnering with global & regional
vendors, encouraging customers to prebook their meals wherever applicable and
improving forecasts for inventory. However, with constant network expansion
plans and evolving demand, this continues to be an area of focus. Customers who
pre-order their meals have a better satisfaction rate compared to those who do
not. However, a small fraction of travelers prebook meals at this point.

Meal options can vary by market and haul type (Haul type is defined based on how
long the flight is based on duration/miles). Some short haul markets (specially
<500 miles) would not offer any meal-service which can be of concern specially
for customers with multiple connections.

United uses a hub-and-spoke model to connect passengers between different
cities. In a hub-and-spoke model, there is a central airport, called the hub,
that serves as a connecting point for flights to and from other airports, called
spokes. This helps in consolidating traffic from multiple spokes into the hub,
and then flying larger aircraft on the hub-to-hub routes and can lead to lower
operating costs for airlines. However, from the perspective of Inflight service,
hub-spoke model can result in better customer experience on hub flights compared
to spoke flights.

How is F&B Satisfaction Calculated?

United measures F&B satisfaction using our NPS (Net Promoter Score) survey.
Customers are asked - How satisfied were you with the food & beverage served on
your flight from [CITY] to [CITY]? Customers can score between 0-5 and can also
provide additional feedback under - Is there anything else you would like to
share about the food & beverage served on your flight from [CITY] to [CITY]?

% Inflight Satisfaction = Satisfied Sample/Total Sample*100

Satisfied Sample = Score is either 4 or 5 (Score ranges from 0-5)

 

DELIVERABLES

 * Perform root cause analysis to identify key drivers of F&B satisfaction score
   during summer months
 * Use survey comments to understand major themes related to F&B that customers
   are complaining about
 * Showcase your coding skills, write queries in SQL/Python/R to summarize data
   at different levels and draw meaningful conclusions
 * Tell a story from the data and share some initial recommendations. What
   further deep dives would you like to do to gain better understanding of
   underlying issues?
 * Create a presentation with your key findings and recommendations (4-5 slides
   covering your understanding of the problem)

Please be thorough in your response.  We are interested in the process used to
arrive at your answer, as well as any assumptions made as you answer the
questions.  Feel free to ask clarifying questions or request additional
information on discussion forums.

Data description

 * Survey data – Inflight Satisfaction Score
 * Survey data – Customer comments/feedback
 * Inflight Service – Pre order data
 * Inflight Service – Inventory data (only for Business/First Class)

 


TABLE 1 - INFLIGHT SATISFACTION SCORE


TABLE 2 - CUSTOMER COMMENTS/FEEDBACK


TABLE 3 - INFLIGHT SERVICE: INVENTORY DATA (ONLY FOR BUSINESS/FIRST CLASS - J)


TABLE 4 - INFLIGHT SERVICE: PRE ORDER DATA (FOR ALL CABINS – J/Y)


DATASETS




PRIZES



Main Prizes
Prizes




Top 10 Winners Get : Skip the written test and get a direct shot to interview
with United!


Top 10 Winners Also Get : A bag full of surprise goodies from United!




SOCIAL SHARE




HELP & SUPPORT

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Daniel Joseph at daniel.joseph@united.com

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