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In this return on investment (ROI) for customer relationship management (CRM) case scenario, students must calculate the ROI for analytic CRM enabled by an enterprise data warehouse. The case is based upon a real-life consulting engagement with a major Fortune 100 telecommunications company. In this case the executive management team's strategic objective is to grow the customer base by 5 percent annually by customer acquisition. The internal rate of return calculated from the data given in the case is more than 800 percent for one year, and sensitivity analysis shows this is a robust projection, suggesting it should be funded without question. However, the strategy of the firm is customer acquisition in an environment of high customer churn. As a result of these dynamics, the revenues and net income of the firm are actually decreasing by hundreds of millions of dollars each year. A better solution would realize that the executive team has the incorrect strategic objective. Customer acquisition is the wrong approach in an environment of high customer churn and executives should focus on customer retention and cross-sell and up-sell to high-value customers. The case discussion therefore takes students beyond CRM ROI to focuses on the key strategic concepts of customer relationship management.

Students learn how to calculate return on investment (ROI) for analytic customer relationship management (CRM) initiatives. The case also discusses in detail the difference between operational CRM and analytic CRM. The case solution is relatively straightforward with a very good ROI. However, the true learning of the case is for students to understand the strategic context of analytic CRM and to question assumptions in any ROI model.

Technology projects are inherently risky; research shows that large IT projects succeed as originally planned only 28 percent of the time. Building flexibility, or real options, into a project can help manage this risk. Furthermore, the management flexibility of options has value, as the downside risk is reduced and the upside is increased. The case is based upon real options analysis for an enterprise data warehouse (EDW) and analytic customer relationship management (CRM) program at a major U.S. firm. The firm has been disguised as Global Airlines for confidentiality reasons. The data mart consolidation or EDW marginally meets the hurdle rate for the firm as analyzed using a traditional net present value (NPV) analysis. However, different tactical deployment strategies help mitigate the risk of the project by building options into the project, and the traditional NPV is expanded by the real option value. Students analyze the different deployment strategies using a binomial model compound option Excel macro, and calculate the volatility using Monte Carlo analysis in Excel. A step-by-step tutorial is provided to teach students how to accomplish the real options analysis for a simplified project, and this tutorial is easily generalized by students to the case scenario. In addition to the tactical options, the case also has the strategic growth option of analytic CRM. Students must therefore analyze both the tactical and strategic growth options and make a management recommendation on funding the project and also recommend an optimal deployment strategy to manage the project risk.

The case teaches real options for technology projects. Students learn how to calculate real option values, where the key input of volatility is obtained by Monte Carlo analysis in Excel. Students also learn that the real option value is “real,” resulting from active management mitigating the risk of the project and improving the upside. Most important, students understand the difference between tactical vs. strategic growth options and the important management issues to consider.

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.

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 demonstrates the use of strategic management tools such as pros and cons analysis, SWOT analysis, strategy canvas, the four-action framework and the eliminate–reduce–raise–create grid to create a Blue Ocean.Through a discussion of the case, students will be able to:▪ conduct pros and cons analysis to objectively understand a situation;▪ conduct SWOT analysis to understand the internal and external ecosystem;▪ understand non-customers and paths to reach them;▪ demonstrate the role of strategy canvas and the four-action framework in designing a new offering; and▪ explain how to create a Blue Ocean market space, by implementing the concept of value innovation.

This case describes a situation in which Dr Vishal Sardeshpande (Sardeshpande), a first-generation entrepreneur in the agro and food processing industry, started Sarvaay Solutions to provide technological solutions for the sector, especially for the small/medium-sized farmer. Such farmers did not have access to technology and the markets to create value addition on their farm produce, and hence were at the mercy of the middlemen or the large farmers. After years of experimentation from 2006 till 2018, Sardeshpande made a resource-efficient jaggery manufacturing process (REJMP) in Pune to enable and empower the farmer to produce quality jaggery using their own sugarcane, which otherwise was sold to the middlemen. Sardeshpande knew the industry and was aware of the challenges faced by the farmers, traditional jaggery producers and cooperative farming bodies. In June 2022, while sitting in his house, Sardeshpande was struck with an idea that the key to success of REJMP is to empower farmers or traditional jaggery producers or cooperative farming bodies to create value from agriculture produce and wondered the way forward. The purpose of this case is to provide an opportunity for the participants to use management tools such as strategy canvas, four-action framework, Pros and Cons analysis and SWOT analysis to understand noncustomers and paths to reach them and understand new industry creation. Participants need to take into consideration the data given in the case and make realistic assumptions to understand how new industries are created.

The case engages the participants in deciding a suitable course of action for Sardeshpande to decide the Blue Ocean strategy. It helps them to delineate the challenges faced by an entrepreneur to select a route for the new market space.The case is ideal for undergraduate, postgraduate or executive education students and can be used in the following courses of a business management, agri business management or entrepreneurship programs:▪ creating new industries;▪ Blue Ocean strategy; and▪ strategic management.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

On completion of this case study, students will be able assess new venture opportunities by properly allocating expansion fund in growing the business; analyzing various scaling-up options; applying the Ansoff matrix for growth and expansion; designing a framework for scaling up; and using the business model canvas.

Mr Sreeram established Eruvaka Technologies in Vijayawada, Andhra Pradesh (India), in 2015 to provide products and services related to aquaculture. The company was founded with the goal of assisting prawn farmers who had trouble keeping up with the demands of the industry. Eruvaka Technologies created risk-reducing and productivity-boosting on-farm diagnostic devices for aquaculture growers. The company developed low-cost monitoring and automation solutions for aquaculture by merging sensors, mobile connection and decision tools. Eruvaka’s primary objective was to offer reasonably priced, technologically advanced goods and services to farmers. Eruvaka matured into a promising startup over time, attracting $5m in funding. Sreeram and his team had to detail their plan to their investors about how they intended to use the money from each funding rounds toward growing the business, how the company planned to achieve sustainable and competitive advantage while providing value to its consumers and how they would address critical issues including product acquisition cost, supply chain problem and customer anxiety.

This case study can be taught as part of undergraduate- and postgraduate-level courses and Master of Business Administration courses.

Teaching notes are available for educators only.

CSS 11: Strategy.

The learning outcomes of this paper are as follows: to understand the context of seaport logistics and supply chain design structure, to apply Monte Carlo simulation in the interface of the supply chain and to analyze the Monte Carlo simulation algorithm and statistical techniques for identifying the key seaport logistics factors.

It was 9:00 p.m. on November 10, 2020, and Nishadh Amonkar, the CEO of OCTO supply chain management (SCM) was glued to the television watching the final cricket match of the Indian Premier League, 2020. Amonkar’s mobile phone rang and it was a call from Vinod Nair, a member Logistics Panel of Ranji Industries Federation. Nair informed Amonkar that it was related to the rejection of several export consignments of agricultural products from Ranji (in the western part of India). The rejection was due to the deterioration in the quality of the exported agricultural products during transit from Ranji to various locations in Europe.

This course is suitable at the MBA level for the following courses: Operations research (Focus/Session: Applications on Monte Carlo Simulation). SCM (Focus/Session: Global SCM, Logistics Planning, Distribution Network). Logistics management (Focus/Session: Transportation Planning). Business statistics (Focus/Session: Application of Hypothesis Testing).

Teaching Notes are available for educators only.

CSS 9: Operations and logistics.

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.

In this case study, the alternative route designs were observed to significantly decrease transportation costs and the total distance traveled. This decrease in logistics requirements almost halved the annual number of shipments and the time needed for operation and documentation activities. In addition, reduced carbon emissions made this an environmentally friendly transportation model, in line with trends in society.

The basis for this case study was the analysis of Whirlpool Turkey’s transportation system for materials used in the production of white goods. Data obtained through fieldwork and cooperation with company consultants showed that some suppliers have high annual logistics costs. This inefficiency causes time loss and increases the total distance traveled and thus carbon emissions. In the case study, the current application created inefficiency in cost and time management, and therefore, after determining the factors that increase costs, different transportation solutions were developed accordingly.

This case is particularly designed for undergraduates in the final semester of management courses that specialize in supply chain and operation management.

Teaching notes are available for educators only.

CSS 9: Operations and logistics.

Entrepreneurship, Innovation Management, Bringing Technology to Market, International Growth Strategy from Emerging Markets, Russia, B2B Marketing.

MBA and executive education programs, technology management programs and electives.

The case investigates the 20-years growth story of ABBYY, one of the most successful Russian technological companies in a global market. It covers the company’s roots, development of unique technology, evolution of products, market development and globalization and discusses a strategic threat from Google Translate to the company’s sustainable position and its business model.

The expected learning outcome is to discuss the key issues associated with establishing, growing and globalizing technology-driven business in an emerging market: bringing technology to market, defining customer value proposition, entering overseas markets from Russia, building partnerships, developing organizational structure to fit growth, financing rapid growth and solving “Innovator’s Dilemma”.

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 3: Entrepreneurship.