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thyssenkrupp Steel Europe, a major European steel company, operates a so-called push-pickling line (PPL) in Bochum, Germany. The PPL produces a particular type of steel strips that are sold to B2B customers, mainly in the automotive industry. In spring 2014, a senior vice president of thyssenkrupp Steel's production operations and one of his production managers notice that over the span of ten years the production facility regularly did not meet its planned production volumes. They set out to determine the drivers for the deviations from planned production figures with the ultimate goal to improve the production planning process at the Bochum PPL. Students will step into the shoes of Markus Schulze a production manager at thyssenkrupp Steel as he searches for performance drivers at the Bochum PPL and analyzes recent production data to build a forecasting model for production planning.

Faeyee Electronics was an electronics company that manufactured and sold smartphones including XS and XT types. The management of Faeyee wanted to pursue the maximum contribution margin as much as possible, especially since they were faced with limited resources. It was necessary to apply analytical tools and cost accounting concepts to study this case including cost-volume-profit analysis, learning curve analysis, regression analysis, definitions of competitive products, constrained non-linear optimization, and contribution margin.

The case uses business analytics tools and cost accounting concepts, including regression models and constrained optimization approaches, to study how to maximize business outcomes, such as contribution margin and profits when limited business resources are available. The company and individuals are disguised.

This case can be used in any junior-, senior-, masters- or MBA-level managerial accounting course. Students need to have at least one course of introduction to statistics or instructors review required statistics concepts or techniques before assigning this case. Students are exposed to the challenges of deriving learning curve models, using regression analysis to study collected data and allocating limited resources to maximize contribution margin.

Data used to develop the case included primary data from employees and supervisors of a commercial floorcovering manufacturing plant in Northwest Georgia. The case company is not disguised.

The survey was developed using existing instruments from the Organizational Behavior and Human Resources Literature. Instruments were listed in Exhibits 2 through 7. The survey administration had the support of the Vice President for Resources and Facilities, and employees and their supervisors were given time to complete the surveys. The data gathered was analyzed by the researcher using SPSS statistical software.

Established in 1957, J&J started as a family-owned business but had grown and diversified its product offerings by focusing on commercial flooring. It survived several economic downturns and remained competitive in a market dominated by more prominent flooring manufacturers. J&J Industries strived to empower its 800 employees with various incentive programs. Employees remained loyal to J&J; many had worked for the company for over 15 years. However, management wanted to measure the impact of empowering and initiatives on employee performance and satisfaction to determine the real power of employee incentive programs. The Resources and Facilities Vice President employed Professor Lopez, a Management Professor, to develop a survey to measure these constructs and analyze the data to guide future incentive programs. Data from the employee and supervisor survey was provided along with the statistical analysis results for interpretation and recommendations for VP Fordham.

The target audience for this case is primarily students in a research methodology course and students studying quantitative regression analysis and interpretation. The focus is predominantly on graduate-level students in Master of Business Administration or Master of Accounting programs in business. Graduate students should have completed courses in management or organizational behavior, business statistics or quantitative methods or data visualization and cleaning as background knowledge for this case. Specifically, students should understand regression analysis and know when and how the tool is used for managerial decision-making.

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

Operations Management Quality Management.

The case can be used in a number of course contexts, including undergraduate and graduate courses in operations management and quality management.

Central Tobacco Plant (CTP) is a tobacco processing and packaging company, operating in the Central America and Caribbean region. This case focuses on a waste measurement exercise conducted in the cigarette production department of CTP, which was commissioned by George Edwards, the Secondary Manufacturing Department Manager. The reason for the exercise was the announcement that CTP could possibly face a plant audit, where a poor result could cause the shifting of manufacturing of some products, or, in the worst case scenario, all of it product lines, to one of the larger, and more efficient manufacturing plants in the Central America and Caribbean region. The waste measurement exercise is carried out as a three-week student–industry project by two students pursuing an MSc programme at the local university, who are mentored by both Edwards and by a university supervisor. At the end of the exercise, Edwards needs to consider the appropriateness of the current waste measurement system, the quantities of waste produced and opportunities to reduce waste.

The case has four primary learning objectives: to illustrate the role of performance measurement in process improvement, to explore the perspective of lean manufacturing in waste management, to apply basic quality tools in the analysis of a manufacturing process and to identify opportunities for process improvement.

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 9: Operations and Logistics

Operations management.

This case can be used in a core course in production and operation management; process management and courses like design and planning of operations at the graduate level, preferably during or after the basic operations module of the course. The case focuses on the use of a process analysis that decomposes the problem into a number of easily solvable sub-problems, each of which could be distinctly analyzed and solved. The case can also be effectively utilized in elective courses on process reengineering, concurrent engineering/management, process management, capacity planning, etc. Ideally, this case can be discussed for 75 to 90 minutes.

The case describes the situation facing the operations supervisor, Sunil Mehta, of A-CAT Corp. in Vidarbha Region, Maharashtra, India. A-CAT Corp. was a mid-sized manufacturer and distributor of domestic electrical appliances, largely catering to the price-sensitive rural population. The firm operated two medium-sized facilities in one of the remote districts in Vidarbha, and these manufacturing units had been in operation since 1986. A-CAT manufactured a relatively wide range of electrical appliances for household use. Typical products from its stable included TV signal boosters, transformers, FM radio kits, electronic ballasts, battery chargers, voltage regulators, etc. The voltage regulators manufactured by A-CAT were used for many different purposes, although the focus was on its flagship product, VR500. The issue at hand for Sunil Mehta, operations supervisor at A-CAT, was to get data and act right; more often than not, this boiled down to critical information which everyone in the firm kept collecting but were too busy to use and utilize. The challenge was to select the right kind of data needed from the data-deluge that the company had in their databases. The eluding objective was to use it for the betterment of the firm. The challenge was to utilize the data that the workers and other operators kept logging in and, in the process of doing so, came up with some solutions to the problems faced on the operational front.

The case teaching and learning objectives are as following: to grasp the basics of process and process parameters; to understand the interrelationship between capacity, utilization, efficiency and productivity of a process; and to carry out process capacity analysis in assessing the performance of the firm on different metric drivers. The case also provides a very good foundation for understanding process parameters in a simple and lucid manner. To make right computations and not to use the terms and terminology in “cook book” or “strait jacketed” manner, students need to realize the parameters and their understanding changes from situation to situation.

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 9: Operations and Logistics.

This case was primarily researched using academic research papers, industry reports (Egg Industry Center and others), and finance databases including Standard and Poor’s Capital IQ. Regarding the cost and investment budgets, the case relies mainly on an experiment conducted by the Coalition for Sustainable Egg Supply, updated by the authors of this case.

Eggs produced by cage-free birds, while more expensive than conventionally produced eggs, are gaining in popularity among consumers who want only eggs that are produced more humanely. A number of major distributors, including Whole Foods, McDonalds and Starbucks have pledged to sell only cage-free produced eggs by 2025. Several states including California, Oregon and Michigan have passed laws limiting conventional egg production. The case provides costs and industry information and needed to project free cash flows and risk-adjusted opportunity cost of capital and perform break-even capital budgeting analysis of the two egg production alternatives.

This case is appropriate for graduate corporate finance courses. It is particularly appropriate for agribusiness finance courses. A preliminary exercise was used during the fall 2018 in a land grant university, just after the “Prevention of Cruelty to Farm Animals Act,” also known as Proposition 12, was passed in California in favor of cage-free egg production. The exercise was revised and used in the fall 2019 in the same class. This extended version of the case, was classroom tested in the fall 2020 in an agribusiness finance graduate class, with agricultural economics and business students enrolled.

Steel Corp has a large production capacity but a shrinking steel market in Europe. Reaching growing markets like China and U.A.E will be important to sustaining and growing revenue but is tough due to higher transportation costs. In this case, users must identify and use logistics data; logistics customer segmentation and related cost analysis.

The main theoretical models used in the instructor manual analysis are SWOT and institution-based view. Founder’s syndrome is also used as a foundation for analysis and discussion.

Primary source data acquired by the authors through one of the author’s actual experience working in the family business that is the subject of the case.

Classy Styles Ltd., Inc. is a small wholesaler of women’s apparel. It outsources production and sells to small retail stores. Classy Styles has grown steadily during its short existence, but is not on track to reach the CEO and majority shareholder’s profitability goal. The COO has determined that the only realistic way to achieve the goal is to shift manufacturing from North America to Asia. The decision creates tension between profitability and the CEO’s desire for tight supervision and control of the outsourced production shops.

Introductory undergraduate courses in general management would be sufficient, while a basic strategy course and/or entrepreneurial business course would be of benefit.

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.