Search results

In May 2016, Sarita Digumarti, Chief Operating Officer of Jigsaw Academy in Bengaluru, India, faced a challenging situation. Jigsaw Academy provided online courses in data analytics and Big Data at the beginner, intermediate and advanced levels for students as well as working professionals. It was perceived that plenty of students from premier institutions in India had a high level of theoretical knowledge about the process involved in number crunching and data analysis; however, the hands-on experience on actual business problems or actual data sets was a major limitation with these students. Given the rapid growth of the analytics sector and the limited number of academic institutions offering analytics courses, there was a lack of availability of the right skills in the analytics market. Jigsaw Academy seized this opportunity and started offering relevant courses. All efforts were made to enhance the number of students enrolling for the courses, which in turn resulted in improving its customer base. Realizing the demand of industries for employees skilled in the analytics sector, Jigsaw Academy wanted to grow its brand equity and to achieve this through business to business (B2B) collaborations and/or alliances. However, expansion through B2B has its own challenges. Given the competitive landscape of analytics market, Jigsaw Academy was wondering whether they should opt for B2B channel, and if yes, the question was related to the process of choosing potential B2B partners.

The authors have collected the data from primary sources as well as secondary sources. Primary sources include field visits and audio-recorded interviews conducted with key departmental heads in the organization. Secondary sources include data retrieved from the company website and the relevant information available about the industry with the assistance of the internet. Except the founder’s name, all other names are disguised to protect the individual’s privacy as per instructions from the founders of Jigsaw Academy.

This case can be used at the graduate or MBA level in courses such as entrepreneurship, sales and distribution management, strategic alliances and mergers.

The case provides a great illustration of women leadership in crisis times. A failed merger forced a deep review of the firm strategy and a realization that the legacy leadership arrangement was not optimal anymore. The hustand-and-wife team ended up swapping executive positions, with Charlotte resolutely taking on the CEO position.

The case is designed as an integrative case looking simultaneously at key subjects such as leadership, entrepreneurship and management of a fast growing service firm, strategy as applied to IT consulting and finally gender studies, with the possibility to discuss the impact of gender roles.

The case investigates Charlotte's efforts at building an original Search Engine Optimization firm in Seattle, progressively taking control from her husband to save the firm from bad strategic decisions.

The case is written to convey the emotional rollercoaster lived by Charlotte and key decisions she had to make as the leader of this fast growing data analytics firm. Learning outcomes focus on what is expected of a leader in such situation, in particular a female leader in a male-dominated technology environment.

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

Consulting in general, and data analytics consulting in particular, are male-dominated worlds where a female leader faces many obstacles to realize their potential. Charlotte provides a masterful example of how to contribute to and lead a fast-growing firm and manage the family and the relationship to a partner who also happens to be the co-founder of the firm.

CSS 3: Entrepreneurship

The case is designed to be used with the digital business model framework developed by Peter Weill and Stephanie Woerner of Massachusetts Institute of Technology (MIT) (Weill and Woerner, 2015) and is referred to as the W & W framework. This approach provides a useful structure for thinking through the strategic options facing environments ripe for digital transformation.

Research for this case was conducted through face-to-face interviews with the protagonist, as well as through a review of their business planning documents and other data and documentation provided by the founder. Some of the market and industry data were obtained using secondary research and industry reports. Interviews were digitally recorded and transcribed to ensure accuracy.

The case follows the story of Kurt Waltenbaugh, a Minnesota entrepreneur who shared the dream of using data analytics to reduce costs within the US health-care system. In early 2014, Waltenbaugh and a physician colleague founded Carrot Health to bring together their personal experience and expertise in both consumer data analytics and health care. From the beginning, they focused on how to use data analytics to help identify high-risk/high-cost patients who had not yet sought medical treatment. They believed that they could use these insights to encourage early medical interventions and, as a result, lower the long-term cost of care.

Carrot’s initial success found them in a consultative role, working on behalf of insurance companies. Through this work, they honed their capabilities by helping their clients combine existing claims data with external consumer behavioral data to identify new potential customers. These initial consulting contracts gave Carrot the opportunity to develop its analytic tools, business model and, importantly, to earn some much-needed cash flow during the start-up phase. However, they also learned that, while insurance companies were willing to purchase data insights for one-off market expansion projects, it was much more difficult to motivate them to use data proactively to eliminate costs on an ongoing basis. Waltenbaugh believed that Carrot’s greatest potential lay in their ability to develop predictive models of health outcomes, and this case explores Carrot’s journey through strategic decisions and company transformation.

This case is intended for either an undergraduate or graduate course on entrepreneurial strategy. It provides an effective introduction to the unique structure and constraints which apply to an innovative start-up within the health-care industry. The case also serves as a platform to explore the critical criteria to be considered when developing a digital transformation strategy and exposing students to the digital business model developed by Weill and Woerner (2015) at MIT (referred to in this instructor’s manual as the W&W framework). The case was written to be used in an advanced strategy Master of Business Administration (MBA) class, an undergraduate specialty health-care course or as part of a health-care concentration in a regular MBA, Master of Health Care Administration (MHA) or Master of Public Health (MPH). It may be taught toward the end of a course on business strategy when students are building on generic strategy frameworks and adapting their strategic thinking to the characteristics of specific industries or sectors. However, the case can also be taught as part of a course on health-care innovation in which case it also serves well as an introduction to the health-care payments and insurance system in the USA. Finally, the case can be used in a specialized course on digital transformation strategy in which case it serves as an introduction to the MIT W&W framework.

The case is particularly well-suited to students who are familiar with traditional frameworks for business strategy and business models. The analysis builds on this knowledge and introduces students interested in learning about the opportunities and challenges of digital strategy. Equally, the case works well for students with clinical backgrounds, who are interested in how business strategy can influence changes within the health-care sphere. Finally, an important aspect of the case design was to develop students’ analytical confidence by encouraging them to “get their hands dirty” and to carry out some basic exploratory data analytics themselves. As such, the case requires students to combine and correlate data and to experience the potentially powerful combination of clinical and consumer data. Instructors should find that the insights from these activities give students unique insights into the potential for of data analytics to move health care from a reactive/treatment ethos to a proactive/intervention ethos. This experience can be particularly revealing for students with clinical backgrounds who may initially be resistant to the use of clinical data by commercial organizations.

After a successful transition from a projects-based IT business services company to a platform-driven analytics company, Saama's core leadership team gathered in 2017 to brainstorm the next phase of its growth. The year before, the team had decided to narrow its target market to the life sciences vertical. Saama now had to decide how to execute on this focused strategy by choosing a growth pathway within the life sciences vertical. Saama's leadership team was considering three alternatives: acquiring new customer accounts, developing existing customer accounts, or developing new products by harnessing artificial intelligence (AI) and blockchain technologies. The team had to evaluate these growth pathways in terms of both short- and long-term revenue potential, as well as their potential for sustaining Saama's competitive advantage.

Four years into a five-year contract with General Motors to be the exclusive website vendor to its U.S. network of more than 4,000 dealers, CDK Digital faced a crucial contract renewal at the end of 2012. The case follows Melissa McCann, director of strategic marketing, and Chris Reed, CMO, as they prepared for a critical meeting in July 2011: a presentation to the customer relationship management (CRM) subcommittee of the Chevrolet dealer council. Although GM dealers, like all auto dealers in the United States, were independent franchisees, GM saw the renewal of CDK Digital's exclusive contract as a collaborative decision between dealers and GM. According to Ed Vogt, GM's executive in charge of the renewal, if the dealer councils said no, the contract would not be renewed.

This case challenges students to use CDK's big data and analytics capabilities to address the inherent conflict between dealers and manufacturers: when marketing to potential customers, manufacturers wanted consistency across dealer websites to maximize sales of their targeted brands, while dealers wanted flexibility to sell what they had in inventory.

After analyzing the case, students will be able to:

• Demonstrate how big data and analytics can be used to solve channel conflict

• Explain how franchisors and franchisees have different perspectives on the value of data on retail operations

• Recognize benefits of big data and analytics beyond the obvious potential improvements to marketing and operational effectiveness

• Articulate the value of data analytics for channel management

• Appraise the benefits of real-time website customization

Demonstrate how big data and analytics can be used to solve channel conflict

Explain how franchisors and franchisees have different perspectives on the value of data on retail operations

Recognize benefits of big data and analytics beyond the obvious potential improvements to marketing and operational effectiveness

Articulate the value of data analytics for channel management

Appraise the benefits of real-time website customization

In the fall of 2014, Chad Kartchner, senior manager of marketing and product management at Honeywell Aerospace (HA), pondered how technology could transform the way aircraft were maintained. He had heard a lot of buzz about cognitive analytics, an artificial intelligence term referring to the use of computer models and algorithms to simulate human thought through self-learning systems, data mining, pattern recognition, and natural language processing. The sheer volume of parts and the time-sensitive nature of repairs in the aviation industry made it complicated to identify problems and address them quickly.

Kartchner contemplated the options for updating HA's ground-based maintenance system. Should he emulate HA's state-of-the-art on-board system for an entire aircraft or try something new? Emulating the on-board system, which HA developed internally, would be an easy sell to leadership given internal buy-in and satisfaction with the on-board system, but he contemplated new approaches because he did not want to overlook rapidly emerging technologies. The latter could include crowdsourced features that leveraged the abundance of knowledge among HA's customers' technicians or a cognitive analytics approach. Even if he could persuade leadership to try a new cognitive analytics approach, should HA partner with an established entity or work with a relatively unproven startup who promised lower cost, better features, and quicker turnaround to develop a new system?

Students will step into the shoes of Kartchner as he leads the internal discussion on whether and how to tap into the benefits of cognitive analytic solutions for Honeywell Aerospace and its customers.

The case traces the evolution of the offshore Analytics operations of a large US based bank in India. It recounts the challenges of coupling geographically-disparate, culturally-alien and, somewhat antagonistic groups of employees within the organization to ensure a productive operation. It touches upon the unique dimensions of organization design in a globally operated organization. Besides all these, the case points to the issues related to work flows and coordination across teams that are operating in different time zones, have skewed capabilities and, do not interact on a person-to-person contact except over the wire. Overall, this case provides exposure into more challenges than solutions for new age global organizations. Given the topical nature of these problems, the case provides ample opportunities for participants to delve into the long term issues of managing such geographically-spaced organizations.

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.

After completion of the case study, the students will be able to understand the calculation of cost of individual sources of funds and cost of capital, examine various tools such as economic value added and cash value added analyses which help determining whether a company has added value to its shareholders or not and explore the application of Benford’s law and the Beneish M-score in detecting manipulation of numbers in financial statements.

Nimmy Jacob, a newly recruited research analyst with an equity research firm, was entrusted with tracking the “auto ancillary industry”, specifically “Minda Corporation Ltd” (MIL). MIL was a leading diversified auto components manufacturing companies in India. The company’s share price meteorically rose during February 2021–2022 (Figure 1). The company’s turnover over the past few years had grown at a compounded annual growth rate of 15% during the three preceding years. The company had in the recent past bought a 15% stake in another competitor, Pricol Ltd, for a consideration of INR 400 crores and previously had used joint ventures and acquisitions to scale up its operations. Jacob, apart from the conventional financial analysis, had to ascertain whether all the strategic decisions were adding value to the shareholders’ investments by exploring the various tools available for the same and also calculate the minimum expected rate of return for MIL. Jacob was apprehensive about the financial statements, although the numbers for the company were good. Jacob was skeptical about a high-growth company having the incentive to manipulate its earnings. Manipulations could be in the form of abnormal increase in accruals, inconsistency in expenses and high days of receivables. Therefore, Jacobs used certain analytics/statistical tools to detect any manipulation of numbers in the financial statements of the company and to ascertain apt findings about the company.

This case study is intended for discussion in corporate finance, financial reporting and analysis and financial analytics at Master of Business Administration/undergraduate level.

Teaching notes are available for educators only.

CSS1: Accounting and finance

The case is presented as descriptive in nature and primarily involves exploratory research.

Ashraf, a young graduate from Bangalore, India, started a chain of lifestyle shops, his family business in Khartoum, Sudan. To modernize the shops, Ashraf approached a small finance bank for financial assistance. However, after submitting the required documents and with a good credit score, he was denied a loan. The bank officials had mentioned that the loan automation software did not approve the application. Hence, the bank personnel said that they could not do anything further. Disappointed, Ashraf sought the help of his professor, John, to understand why the software rejected his application. Professor John explained to Ashraf the advantages and disadvantages of automation. In the process, Ashraf understood the significance and compelling need to address “Algorithm Bias,” a situation in which specific attributes of an algorithm cause unfair outcomes. The case place students in Ashraf’s position to help them understand the advantages and issues of applying automation through artificial intelligence.

The case suits graduate-level courses like business analytics, financial analytics and business intelligence.

Through the case, the students will be able to: Understand the role of algorithms in business and society. Understand the causes, effects and methods of reducing algorithm bias. Demonstrate the ability to detect algorithm bias. Define policies to mitigate algorithm bias.