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The case is meant to be used in an introductory course on Data Visualization or Analytics in either a business school or any other context where students have had some exposure to management topics. This case primarily focuses on introducing students to the basic philosophy and techniques of exploratory data analysis (EDA). The Steaming Mug, a US based hot beverage chain is provided as a context for engaging in a hands-on exploratory data analysis exercise to understand the strengths and weaknesses of the company's operations and performance. The learning from exploring this case will help students understand that many different insights can be drawn from the given data. The students will understand that there is no “one correct path” for this analysis. The values of getting multiple groups to present their findings is that students realise that there are many other angles that could have been explored, than the path they had gone down.

Data Services provides flexible, scalable data processing and information storage to the fast-food industry. Sales have grown steadily, but the company has operated at a loss since its founding five years ago. Data Services management is enthusiastic about the company's prospects. The chief executive of Armistead, the insurance company that owns Data Services, is under pressure from corporate officers to slough off the subsidiary. A business analysis is done not only to help the CEO decide whether to continue investment in Data Services, but also to determine if the company is well managed. Information includes the day-to-day operations of Data Services, its sales process, profit and loss statement, revenue and expense analysis, and cost allocations.

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.

Management of Innovation and Technology/Management Information Systems.

Information Systems.

SER (Sugar, Energy & Rum) was a company belonging to the Grupo Pellas Corporation. The company operated in four countries, had six subsidiaries, employed more than 25,000 people, had more than 43,500 manzanas of sugarcane crops in Nicaragua alone and had global annual sales of more than US$400m. In 2008, due to the negative effects of the crisis on the company’s business model (increasing costs due to higher prices for fuel and decreasing income because of low international sugar prices), the company decided to implement a business intelligence (BI) system to optimize its processes to reduce costs and increase productivity. At that time, the company had more than 100 years of data, information systems that fed into their main business processes and a culture that appreciated data as the basis for decision-making. However, there were inconsistencies among data systems, users received highly complex reports in Excel or green screens and process monitoring happened long after the tasks had been completed. As a response, SER used extract–transform–load to collect and clean data that would be used in the BI system (the case leaves the questions regarding the systems selection unsolved for discussion). Based on their business model, they selected the most critical processes and defined key performance indicators to measure the impact of changes in those processes. They considered graphic design as a tool to make the system more accepted by users and worked together with users so that reports only offered the most important information. The result was improved costs and productivity. They decreased manual time spent by 14 per cent, automated time spent by 10 per cent, and eliminated 1,556 hours of dead time for equipment in the field, which allowed them to increase productivity by US$1m just in sugar. They saved 20,000 trips from the fields to the factories, which represented more than US$1m in savings by monitoring the weight of wagons loaded with sugarcane in real time. They improved client perceptions about the company both locally and internationally by implementing a sugar traceability system.

The case “Business Intelligence at the Grupo Pellas SER Company” has as its objective to respond to the question: How does a company make its BI system implementation successful? As such, the case: Discusses what a BI system is and what it provides to a business analyses challenges, benefits and context when implementing a BI system; analyses success factors and recommendations in the BI system implementation process; analyses the process of implementing a BI and highlights the importance of the system priority questions and technological alternatives.

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

Acme Inc, a large retailer, explores the use of Data warehouse for addressing their decision support infrastructure Challenges. Acme plans for a pilot study to assess the feasibility and evaluate the business benefits of using Data warehouse. The focus of this case is to ascertain the steps involved in design, development and implementation of a Data warehouse.

The case fosters discussions on basic concepts of entrepreneurship that include building a minimum viable product before launching a finished product, the importance of doing market research for early-stage startups, challenges in understanding an unfamiliar domain or industry and understanding the dynamics of business to business market.

Team Arnetta’s founders were interviewed in relation to the case. After the initial round of interviews, a product demonstration was given by Arnetta. Follow up interviews were conducted to delve-deeper into the problem while secondary research was conducted to understand the market dynamics and competitive landscape at the point in time in the case.

The four founders of Arnetta Technologies debate go-to-market timing for Integrated Breeding and Research Management Software, a data handling software for the R&D process followed by seed enterprises in India. The founders had spent over US$75,000 on the product development on which they had been working for more than one year. Two of the founders had given up their full-time jobs to work dedicatedly on the venture. The product was being customized to the requirements of their only client. Product development was taking longer than anticipated. To add to the challenges, international competitors had started capturing the Indian market. The founders had two options. First, they could wait and finish the product development before reaching out to their prospective clients – leading to delays and losing out on the market. Second, they could reach out to prospective clients and convince them to use the work-in-progress version of the product – which could turn out to be a deal breaker. The founders had to come to a consensus soon.

The case is intended for students in undergraduate or graduate-level courses related to entrepreneurship, new venture creation, innovation management and business management.

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 deals with marketing research study undertaken to introduce a new product in the market. The company was planning to introduce Cerenity, a toilet seat sanitizer for women who frequently use shared restrooms. The case discusses the conclusive study undertaken involving quantitative marketing research. The research team carried out quantitative survey and collected the data. It applied various quantitative research methods such as factor analysis, multiple regression, cluster analysis and conjoint analysis for analysis the collected and drawing managerial inferences.

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.

In 2013, ‘Fashion Destination’, a well-established clothing retailer considered setting up a clothing and accessories rental service. They hired a market research agency ‘Wright & Company’ to conduct a research on the sustainability and profitability of such a business model. The consultants collected primary data and did an extensive analysis for Fashion Destination. Based on the secondary research, expert interviews, extensive qualitative and quantitative research the consultants recommended the management to start a clothes and accessories rental service but suggested that the product offering be limited to formal clothes only and offer accessories. Vishal had doubts despite of the go-ahead signal from consultancy. He wondered what recommendations should he accept and which needed further verification.