Risk and Technology

Case study

Part (a)

Winglet Travel (Winglet) is an online travel agency and meta-search engine founded in 2013 by four information technology professionals. Winglet’s two main customer groups are business travellers and leisure travellers.

Winglet helps travellers search for and book travel options for their flights through its online booking platform. The booking platform enables customers to compare flights from different sources across the internet, including from online travel agents and directly from the airlines. Using the booking platform’s interactive mapping feature, customers can search for the cheapest flights from any airport to anywhere in the world on specific dates, and view prices over an entire month to find the best offers.

The Winglet website and the ‘Smart Winglet' app

Customers like using the Winglet website’s booking platform because it eliminates the need to compare flights across multiple web pages by browsing each page individually. To make a reservation, customers simply choose an available flight, select a seat and service option, enter their details, and make a payment. The booking process takes a few minutes for a first-time booking, and subsequent bookings take even less time for customers who create and book via a Winglet account.

Winglet’s booking platform can also be accessed through the company’s booking app, ‘Smart Winglet’, which can be downloaded from the leading app stores.

The app provides the same booking functionality as that of the website, but it also offers additional benefits to customers and the company:

 The automatic flight check-in feature simplifies the check-in process: As the boarding pass is sent to the customer’s phone, they can then skip the check-in counter, proceed straight to the security checkpoint and continue to their assigned gate.

 The app integrates with Google Maps to provide customers with real-time travel information about their route to the airport, including possible traffic delays or train service cancellations.

 The app integrates with airline baggage-handling features and offers real-time tracking of customer baggage items.

 When a customer arrives at selected airports, the app receives signals from Wi-Fi-based real-time locating systems and beacons to send location-specific information, for example, about sales promotions, delays, and gate changes. The app can also help customers to navigate the airport via interactive maps.

Winglet uses its website and app to collect data on the customer experience via regular customer surveys. The app also collects data on customer movement patterns inside airports, including arrival times, queuing times and time spent at certain airport locations. The data is also used for in-app advertising, and Winglet uses the advertising to promote selected third parties. For example, the app displays special deals on accommodation and car-hire that are available at the customer’s destination.

Winglet customer satisfaction

As part of preparation for the annual process evaluation meeting, two members of Winglet’s management team, the Chief Executive Officer (CEO) and Chief Information Officer (CIO), have asked for your assistance.

Winglet’s executive management team has recently noticed a slightly decreasing customer satisfaction score. They consider a minimum average satisfaction rating of 5 out of 7 as a benchmark that they need to meet to remain competitive in the market. As part of Winglet’s risk management process, the executive managers identified two main operational factors that may be related to the decreasing customer satisfaction: customer satisfaction risk and reputational risk.

First, in relation to the customer satisfaction risk, the managers have become aware of customer complaints about long refund times. Winglet’s policy is to refund customers for cancelled flights, but customers have complained that the refund process takes too long

Second, in relation to reputational risk, business travellers have expressed concern about customer data privacy. For example, some business travellers are concerned about providing their personal payment details to make a booking, and then the flight is cancelled. This gives them the impression that Winglet just wants to collect customers’ personal data for marketing purposes, such as generating targeted ads.

Your involvement

Winglet’s managers are concerned that the customer’s complaints about the long refund times and negative impression of Winglet’s use of customer data could impact brand loyalty and Winglet could lose customers. Based on their experience, they consider a minimum average brand loyalty rating of 5 out of 7 as a benchmark to meet to remain competitive in the market.

The managers provide you with Microsoft Excel Dataset files A and B, including summary statistics (please see the second tab in the Excel worksheet, ‘Summary Statistics of Data’). Winglet’s CEO and CIO ask you to cleanse, analyse, and interpret the dataset to generate insights into the customer experience with the booking platform.

Your tasks

Using the datasets provided in the Microsoft Excel documents, complete the tasks in Part (a).

The tasks in Part (a), (b) and (c) form the basis of your report. In your report you will need to refer to and/or copy relevant data from your Microsoft Excel files, and submit your updated Microsoft Excel files, along with your report and a 3-minute video (Part (d)). (See additional instructions provided below about what you must include in your Excel files).

You are provided with two versions of the Microsoft Excel dataset files, including Dataset File A and Dataset File B, each with the same dataset.

Use Dataset File A for Task 1 (cleansing). Use Dataset File B for Task 3 (analysis) and Task 6 (dashboard preparation).

Task explanations

Task 1: Cleanse Dataset File A.

The cleansing should focus on the columns A – AF in the Dataset File A. You can assume that the data in all other columns is already cleansed.

This dataset was created for the case study and does not necessarily reflect real-world data. You can assume that the data is semantically correct, and it is not necessary to check whether the data in different columns are correctly aligned or reflect real-world data. For example, you do not need to check whether the given zip code of a city is correct or that the name of an airport is correct.

Task 2: In your report, explain and justify the data-cleansing process you used in Task 1 by:

 providing an explanation of the applied cleansing categories.

 outlining how cleansing was applied to the dataset. 

Task 3: Perform a numerical analysis of the Dataset File B to inform your advice to the executive managers on the following:

 An acceptable maximum time to refund customers for cancelled bookings.

 A potential relationship between customer satisfaction and:

 refund time

 data privacy concerns.

 A potential relationship between Winglet’s reputation and:

 refund time

 concerns about data privacy concerns

 satisfaction with Winglet.

 Whether data privacy concerns are more of a problem for business travellers than for leisure travellers.

You do not need to interpret the results of the numerical analysis in Task 3 – you will do this in Task 5.

Limit any inferential statistical techniques to correlation analysis and comparison of means. Assume that business traveller variance and leisure traveller variance are equal for the variables ‘Satisfaction Rating’, ‘Process Refund Time’, ‘Brand Loyalty’, and ‘Data Privacy Concerns’. You do not need to test this assumption with an F-test.

Task 4: In your report, justify the numerical analysis approach you used in Task 3, including an explanation of your choice of data.

Task 5: In your report, interpret the summary statistics provided by the executive managers in the second tab in the Excel worksheet ‘Summary Statistics of Data’, provided in Dataset File B, and the results of the numerical analysis you performed in Task 3. You can assume that the summary statistics provided by the executive managers is correct.

Task 6: Based on Dataset File B, the results of your numerical analysis, and the summary statistics provided, prepare a dashboard in Microsoft Excel to present to the Chief Executive Officer (CEO) and Chief Information Officer (CIO). The dashboard should provide relevant information to enhance the CEO’s and CIO’s understanding of the issues raised. Take a screenshot of your dashboard and include it in your report.

Dataset-fileA-forCandidatesxlsx