INDIVIDUAL PROJECT
• Course: Data Driven Business
The Hospitality Industry Benefits From the Emergence of Big Data
When it comes to adopting technology as well as evolution driven by data, the hospitality industry is known to lag behind. Only recently that the industry are learning that there are gaps that should be filled, gaps which exist since they could not possibly be foreseen or controlled. Today, Big Data allows the hospitality industry to take better control of their business. Furthermore, insights from Big Data enable them to drive profits and lower costs faster and easily so they could go back to doing what they love. Some hospitality industry benefits from the emergence of big data:
• With Big Data and analytics hotels could target their best repeat clients. Moreover, they provide extra promotions and incentives while creating perks that help boost a business.
• Big Data analytics are valuable in helping hotels set the best prices for their rooms. The kind of optimization further extends other services that the hospitality industry provides.
• Big Data and analytics can be used to segment guests according to behaviour, booking trends and other factors to reveal the chance to respond to promotions. It is important for hoteliers to understand guest preferences and more.
The hospitality sector caters to millions of people on a daily basis. Meeting the expectations of these people is the key to getting them to return and avail of their services again and again. With customer data all gathered in a single place wherein it is easier to paint and see the huge picture, hotels could make better informed decisions when it comes to marketing and customer service. Through using analytics, hotel could target their best repeat clients with extra promotions as well as incentives, while building perks and separate deals that do not visit as often, with the hopes of boosting their business.
WORK TO DO
• Choose any hospitality company for your report
• Use Secondary research or existing data (If possible) to define the management problem of the company or to identify Data and information for your report
• Using Data analysis software such as SPSS or Tableau it’s optional
Using the 10 steps of the Data Strategy, develop the all process of the development of Data strategy for the company you choose. Please indicate what the objective of each phase is as well as the main activities you will have to undertake. Use examples in each step in order to explain better your approach.
Step 1 : What is a management / business problem ?
A problem is a gap between a current unsatisfactory situation and a situation defined as satisfactory
For Step 1, use CANVAS such as Data analytics strategy / Data management canvas / Data strategy is highly recommended but not mandatory
Step 2: Define a strategic objective
Based on the company you choose for your report, and in order to define the 1 strategic objective, you have to identify:
• What is the main business problem of the company?
• Why you think that the strategic objective you choose will be the optimal solution comparing to other?
Examples of strategic objectives:
• Increase the traffic on their website,
• Increase loyalty customer rate,
• Customer acquisition strategy,
• Reduce operational cost,
• Increase occupation rate,
• Develop new product or service,
• Etc.
Step 3: Data Needs & Data Collection
Based on the business case / problem or on the strategic objective:
• Identify which data needed
• Identify the type of the data (structured vs unstructured)
• How evaluate the quality of the data ?
Step 4, 5 & 6 : Data Sources, Data Extraction & Data Storage
• What are the different sources of the data needed?
• How Data will be extracted and acquired ?
• Where data will be stored?
Please specify if data have to be cleaned, transformed or consolidated
Step 7: Data Analysis & Data Modelling
Which type of data analysis will be used to achieve the strategic objective? You have to define:
• Data model analysis
• Identify the main methods and algorithms you will use and why?
• What are the main results expected?
Step 8: Data Team
Which type of competences and skills are needed for the project (data engineering, data architect, data analyst, data scientist, business analyst, etc.).
Step 9: Test phase
Specify if is needed to have a test phase to evaluate the quality of the model / solution obtained. If yes specify how you will do it and evaluate the results to validate the final solution.
Step 10: Implementation of the final solution
Describe how you will implement the final solution