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This case, along with its B case (UVA-QA-0865), is an effective vehicle for introducing students to the use of machine-learning techniques for classification. The specific context is predicting customer retention based on a wide range of customer attributes/features. The specific techniques could include (but are not limited to): regressions (linear and logistic), variable selection (forward/backward and stepwise), regularizations (e.g., LASSO), classification and regression trees (CART), random forests, graduate boosted trees (xgboost), neural networks, and support vector machines (SVM).

The case is suitable for an advanced data analysis (data science, machine learning, and artificial intelligence) class at all levels: upper-level business undergraduate, MBA, EMBA, as well as specialized graduate or undergraduate programs in analytics (e.g., masters of science in business analytics [MSBA] and masters of management analytics [MMA]) and/or in management (e.g., masters of science in management [MScM] and masters in management [MiM, MM]).

The teaching note for the case contains the pedagogy and the analyses, alongside the detailed explanations of the various techniques and their implementations in R (code provided in Exhibits and supplementary files). Python code, as well as the spreadsheet implementation in XLMiner, are available upon request.

T Education is a leading educational science and technology enterprise in China with technology-driven, talent intimacy and quality leadership as the core development objectives. Since its inception, it has been committed to creating better learning experience for children. As the predecessor of T-education, X-education was founded in Beijing in 2003. At first, it mainly provided after-school math counseling for school-age children. Over the past 10 years, its business has been expanding, covering almost every aspect of school-age education. This case studies accounting issues and business ethics challenges that firms may face when they transform from a single (traditional education) line of business to a multiple channel business.

In this case, lessons from the Chicago Benchmarking Collaborative illustrate key principles of collaborative action and the importance of using data to achieve SMART goals.

In 2015, the Chicago Benchmarking Collaborative (CBC) was a network of seven agencies in Chicago, Illinois, serving 12,000 low-income residents. Each of the agencies had early childhood, school-age children, and adult education programs. At the prompting of the Chicago Community Trust, they came together to (1) benchmark their education programs outputs and outcomes; (2) learn and share best practices through developing a common set of metrics and measurements and implementing these measurements into a case management software system; and (3) share the costs of the case management software system to be used for program evaluation and continuous quality improvement.

Three aspects of CBC are particularly noteworthy. First, there are no joint program activities or clients among these agencies. Their exchange is limited to sharing data and other information. This makes CBC distinct from collaborations formed to begin a program or to advocate for a policy. Second, the group requires each agency to enter data on a timely basis and to set SMART goals based on the data reports. The agencies are held mutually accountable for their work to achieve their own SMART goals during the year and report on progress. Third, CBC used monetary incentives to ensure that data entry and SMART goal action remained a priority for each agency.

This compact case provides a relatively large data set that students explore using visualization and a Tableau dynamic dashboard that they create. Students were asked to describe what the data set contained in relation to employee attrition experience of Baca Beverage Distributors (BBD). The application and managerial questions are set in human resources and a company that is facing high attrition during the pandemic.

BBD shared their data and problem scenario for this compact case. The protagonist, Morgan Matthews, was the authors’ contact and provided significant clarification and guidance about the data. Both the company and the protagonist have been disguised. Some of the job positions have been rephrased. All names of employees, supervisors and managers have been replaced with codes.

During the 2020–2022 pandemic years, BBD experienced, like many companies, a higher than usual employee turnover rate and Morgan Matthews, Director of People, was concerned. Not only was it time-consuming, expensive and disruptive but the company had prided itself on being a good place to work. Were they hiring the right people, people that fit the company culture and people that fit the positions for which they were hired? The company had been using the Predictive Index [1] when on-boarding employees. In addition, there were results from self-reviews and manager reviews that could be used. Morgan wondered if data visualization and visual analytics would be useful in describing their employees and whether it would reveal any opportunities to improve the turnover rate. Before seeking a solution for the high turnover, it was important to step back and learn what the data said about who was leaving and the reasons they gave for leaving.

This compact case can be used in courses that include visualization using Tableau and dashboards. As it is a compact case, it requires less preparation time from the students and less class time for discussion. The case is for students who have been recently introduced to business analytics, specifically visualization and data storytelling with Tableau. For this reason, significant guidance has been provided in the case assignment. The level of the case can be adjusted by the amount of guidance provided in the case assignment. Courses include introduction to business analytics, descriptive analytics and visualization, communication through data storytelling. The case can be used for all modalities – in person, hybrid, online. The authors use it here for visualization and dynamic dashboards but using the same data set and compact case description, exploratory data analysis could be assigned.

Supplementary material for this article can be found online.

Finance, accountancy, auditing.

Supports information systems audit (ISA), auditing practises and controls, corporate governance and internal controls and financial management modules, business administration and MBA programmes.

The case study focuses on the implementation of ISA and information technology in the highly responsible task of executing financial audits The case emphasises on the fact that the advantages of ISA can only be reaped when they are amalgamated with an auditor's scrutiny, sharp eye, extensive knowledge of auditing systems and accounting principles and a rich experience of the auditing function. The suggested synergy also facilitates a reduction of around 60 per cent, in the cost of executing the audits and the man-hours required to complete the audit, as in the case of Jain Chowdhary & Company.

The case helps students to comprehend the relevance of audit trail. It emphasises on the importance of identifying the source of information and tracking raw data backward. It familiarises the students with the complexities involved in a real audit and emphasises on the role of logic, intelligence, diligence, patience and farsightedness while performing the auditing function. It is important for them to understand how White collar crimes take place in real business economy. This case, hence exposes students to these nuances and can make a student, from a non-commerce background, understand the key elements of efficient auditing. (Elaborate teaching objectives are appended in the teaching note.)

Teaching note.

Human resource management.

Postgraduate and graduate management programs.

Watson and Lilly (W&L) Berhad is the subsidiary of Wanger Group of Company, established in 1822 by Wanger Watson Group, and engages with transportation and logistics, communication and media, and electricity storage activities. The company provides freight forwarding by air, sea, and land, warehousing and distribution, industrial logistics, and stevedoring and port services. The case is all about the issues related to operations and human resource management in W&L Berhad, company in Malaysia. The company management observed that there has been an increasing trend on the number of mis-shipment. The investigation report was too worrisome to the Managing Director. The mis-shipment recorded in September 2011 was 5.91 per cent and by the end of first quarter in November 2012, the mis-shipment increased to 6.71 per cent. On the second quarter starting from December 2012, the mis-shipment continues to increase to 6.99 per cent and by February 2013, the mis-shipment was at 7.56 per cent. An independent consultancy was assigned to analyze the root causes of the issues. The agency found that the business having high operating cost due to operational inefficiency, documentation issues and human resource issues. The case study proposed several solutions to enhance the manpower efficiency, operational effectiveness, and achieving customer's satisfaction.

Learning the nature of business: to explain the nature of freight and forward business and the base of W&L Berhad, Malaysia. Nature of business operation issues: the case can be used to examine the issues of business operations due to mis-shipment in freight and forward companies. Nature of manpower issues: the case can be used to examine the issues of manpower in correlation with a mis-shipment of freight and forward companies. Integrating business and operational issues with customer delight and business loss. Strategic intervention: instructor can explore varied strategic interventions that curb the operational and manpower issues that may lead to business growth and development in freight and forward companies, achieving customer's satisfaction.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

Wall Street hedge fund manager Kim Meyer is considering investing in an SFA (slate financing arrangement) in Hollywood. Dave Griffith, a Hollywood producer, is pitching for the investment and has conducted a broad analysis of recent movie data to determine the important drivers of a movie’s success. In order to convince Meyer to invest in an SFA, Griffith must anticipate possible questions to maximize his persuasiveness.

Students will analyze the factors driving a movie’s revenue using various statistical methods, including calculating point estimates, computing confidence intervals, conducting hypothesis tests, and developing regression models (in which they must both choose the relevant set of independent variables as well as determine an appropriate functional form for the regression equation). The case also requires the interpretation of the quantitative findings in the context of the application.

Uber had pioneered the growth and delivery of modern ridesharing services by leveraging the explosive growth of technology, GPS navigation, and smartphones. Ridesharing services had expanded across the world, growing rapidly in the United States, China, India, Europe, and Southeast Asia. Even as these services expanded and gained popularity, however, the pickup experience for drivers and riders did not always meet the expectations of either party. Pickups were complicated by traffic congestion, faulty GPS signals, and crowded pickup venues. Flawed pickups resulted in rider dissatisfaction and in lost revenues for drivers. Uber had identified the pickup experience as a top strategic priority, and a team at Uber, led by group product manager Birju Shah, was tasked with designing an automated solution to improve the pickup experience. This involved three steps. First, the team needed to analyze the pickup experience for various rider personas to identify problems at different stages in the pickup process. Next, it needed to create a model for predicting the best rider location for a pickup. The team also needed to develop a quantitative metric that would determine the quality of the pickup experience. These models and metrics would be used as inputs for a machine learning.

Information management, IS alignment.

Undergraduate.

The case examines the use of Information and Communication Technology (ICT) in one of Egypt’s top mobile service providers, through closely analyzing their systems, the way they work and how technology could be optimized to provide greater benefit and value to support an organization’s business goals. The main objective of the case was to identify business problems that information systems have managed to solve as well as grab a potential opportunity that the organization can or have captured. The main contribution of this case is to emphasize and provide real case application on information management concepts and theories related to Information Systems Alignment (IS Alignment), business value from IS adoption, IS implementation issues and information and process integration.

This case was written to present a practical example about the strategic use of ICT within a specific organizational context. It enables students to apply some theoretical concepts studied in information management courses (such as IS alignment – or strategic alignment –, IS assessment and IS implementation) on a real-case study. In particular, teaching this case aims to realize a number of learning objectives: understand telecom industry and acquire an overview about its environment and the challenges it faces in general and within a developing context in particular; identify the different technologies used by telecom companies; develop a business strategy based on a thorough analysis of an organization’s internal business operations as well as its external environment; and learn how to align IT use with organizational strategies and analyze critically both its tangible and intangible added values.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 11: Strategy.

Jennifer McDougall is considering investing in mutual funds for the first time, and has narrowed her options down to three: one that is domiciled in Germany, and two that are domiciled in Luxembourg. As a cautious and risk-averse investor, Jennifer has done extensive research on the three funds, and has come across a curious fact: the beta of the German fund is surprisingly low. After speaking to her financial planner, she learns there is no legal requirement in Germany for mutual funds to compute net asset values at a particular time of the day. If the German fund is closing its books in the middle of the day and its net asset values reflect its midday holdings, rather than end-of-day holdings, this could explain the low beta. Thus, the German fund might appear less risky, without actually being so. Jennifer needed to get a clearer picture of what was going on before making her decision.

Using the data provided with the case, students will determine the closing time of the three funds and how that affects the beta of each. Then they must make a recommendation about which fund would be the best investment for Jennifer.