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This B case is a supplement to HBS case no. 717-404 "BlackRock (A): Selling the Systems?"

This (C) case is a supplement to HBS case no. 717-404 "BlackRock (A): Selling the Systems?"

The Cost Variance Analysis note was written to provide students with fundamental concepts and methods for the analysis of cost variances. This note focuses on the decomposition of cost variances into price, quantity and mix variance components, an approach that allows students to identify the root causes of differences between expected and actual costs.

The purpose of this case is to look at Autodesk's cultural and technological challenges as the company faces a changing industry. With various innovations such as the cloud, the Internet of things, and various new manufacturing processes affecting every aspect of the company's future, students will be introduced to the various decisions and challenges a corporation has to face in order to remain ahead of massive industry disruption. The case analyzes Autodesk's three major branches: (1) Architectural and Engineering, (2) Manufacturing, and (3) Media & Entertainment and how all three branches are adjusting to meet the future. Of particular focus is the shift to a subscription business model, the cultural ramifications of such a shift, the arrival of activist investors to the company's stock, and the various disruptive innovations in Autodesk's markets.

This case follows Jenica Fletcher as she rebuilds her company's guitar strings division from the ground up. Convinced that she could turn the division around if given complete independence from corporate headquarters, Fletcher relocated the group, rebranded it as Malenti Strings, repositioned the guitar strings as high-performance products, and transformed Malenti into a fast-growing, profitable business. The case traces Fletcher's key steps in rebuilding the organization, including the development of a team of committed, interdependent employees. Students learn about Fletcher's values and unique management philosophy, as well as her managerial practices and daily activities. The case also discusses the role and development of the partnerships that helped solidify and grow the business. Coming off its high-end success, Malenti must now decide whether to move into the mid-priced market with a new line of electric guitar strings called True.

This case describes a situation in which Vivek Vyas and Vimal Popat conceive an idea to start an online obituary advertising platform. Vyas and Popat then discuss the possible ways to start an online obituary advertisement platform. The purpose of this case is to provide an opportunity to step into the shoes of Vyas and Popat and explore the best possible option to offer an alternate solution to print obituary advertisement. The case provides the context for students to examine alternate options for the print obituary advertisement amidst lack of entrepreneurial experience of Vyas and Popat.

Supplement to case W16649.

Delhi Metro Rail Corporation Ltd. (DMRC), a government-owned enterprise in India, was responsible for building, operating, and managing the metro rail network in the National Capital Region of India. Delhi's reliable, punctual, clean, and green metro services began operation in 2002. By 2016, DMRC had transformed peoples' lives and become an essential form of transit for an average of 2.5 million commuters per day. In terms of customer satisfaction, DMRC was ranked in a global online survey as the second-best metro system in the world. But management at DMRC knew that to maintain that level of customer satisfaction, it had to be conscious of the gap between performance and customer expectations, which were increasing with demands from DMRC's assertive and ambitious millennial commuters. In addition, the government was embarking on strategies to induce commuters to switch from private to public transit. DMRC needed to evaluate its strategic service priorities while continuing to deliver value to its stakeholders. Should DMRC focus on enhancing customer experience with augmented services or invest in measures to reduce operational costs? Was DMRC's culture of customer delight sustainable?

Hope Blooms was a social enterprise based out of Halifax, Nova Scotia, that grew its own garden produce and manufactured and sold a line of herb dressings. For a small social enterprise, it was remarkably successful. Hope Blooms had appeared on CBC's Dragons' Den and was constantly selling out of its products in local markets. In addition, it had secured placement in a national grocery retailer and was continuing to fulfill its social mission of empowering marginalized youth by providing education on food, sustainability, and entrepreneurship issues. These successes started to create a series of problems associated with production and capacity shortfalls associated with using a youth volunteer workforce, stock outs, and potential mission drift. As the executive director of Hope Blooms prepared for the final board of directors' meeting in 2015, she wondered how to solve two of the organization's fundamental problems: How could the retail operations provide stable employment for its youth members? How could Hope Blooms increase its profits to continue to expand its activities?

This sequel accompanies case number 1999 (HKS766). This case looks at public-private partnership (PPP) between the Health Ministry for the government of Lesotho and a private consortium headed up by Netcare, a South African company, to build and operate a new referral hospital and four feeder clinics in Maseru, the nation's capital. The project was one of the first efforts to design a PPP in Africa for the construction and the operation of a major hospital plus the clinical services. The project is perceived by the International Finance Corporation as a major success. The case focuses on three issues: 1. the steps taken by the government, IFC, and the private parties to form a workable public-private partnership; 2. the design and implementation of the key performance indicators contained in the contract; and 3. the sustainability of the project in light of higher than anticipated costs and lower quality health services in other areas of the country, which have resulted in a demand for services from the new clinic and hospital far in excess of the numbers originally forecast. Case number 1999.2

This case study outlines the strategic, regulatory, and broader issues that confront the venture capital and tech startup ecosystem in China; as the country continues its reforms towards a more domestically driven market economy.

The case is set in June 2014, when Lau Wing Chew, Chief Transformation Officer (CTO) at Alexandra Health System (AHS) in Singapore was highlighting the achievements of the data analytics initiative made by the Health Analytics Unit (HAU) at AHS to his management team. Although the initiative was still in its initial stage, multiple medical and administrative areas had been improved with the help of data analytics. The journey to develop the data analytics initiative had commenced in 2011, when Lau reviewed a set of data presented by the Accident & Emergency (A&E) Department, and realised that non-emergency cases at A&E were taking up too much of hospital resources. He also noted other pressing resource-related issues, such as acute bed shortages and patients not showing up for their appointments at specialist outpatient clinics, causing a sub-optimal utilisation of critical resources like doctors and appointment rooms. Lau knew that given the right metrics, predictive analytics could improve the situation. In the following three years, the HAU had leveraged the capabilities of data analytics to roll out initiatives such as population health and ageing-in-place programmes, and implementing solutions into patient medical billing and operating theatre dashboards. Although these unremitting efforts were showing results, the challenges ahead were significant. The HAU team not only needed to get buy-in at an operational level with different business units, but also needed to increase health awareness in patients. How could AHS improve the data analytics initiative further, and plan its resources optimally? Students will gain an understanding of the critical success factors and challenges faced during the implementation of analytics projects, as well as learn how to operationalize such a project within an organisation.

Supply Chain Risk Management Tools for Analysis, Second Edition, is an eight-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author explores the growth of global supply chains as well as the risks associated, such as political unrest and natural disasters. He highlights the importance of managing risk in a supply chain and outlines the categories of risk that managers must consider. He presents several quantitative tools and methods for risk management with extensive real-world examples and detailed models that have been updated in the new edition. Chapter 1, Introduction (10 pages), explores the benefits of supply chains as well the inherent risks. While the increased global connections in a supply chain can provide greater cost efficiency, they also expose the system to a greater risk from disruptions like piracy, natural disasters, and epidemics. The author explains that, since a supply chain is often based on a "just-in-time" delivery, a problem in one section can throw off the entire process. Thus, he advises managers to incorporate flexibility into a supply chain, by methods such as diversified product sourcing, multiple transportation routes, and other contingency planning. He highlights the importance of anticipating unexpected consequences and categorizes risks into internal (such as government regulations and organizational delays) or external (such as market trends and political events). He provides a detailed discussion of examples in each risk category.

Supply Chain Risk Management Tools for Analysis, Second Edition, is an eight-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author explores the growth of global supply chains as well as the risks associated, such as political unrest and natural disasters. He highlights the importance of managing risk in a supply chain and outlines the categories of risk that managers must consider. He presents several quantitative tools and methods for risk management with extensive real-world examples and detailed models that have been updated in the new edition. In Chapter 2, Supply Chain Risk Management Process (18 pages), the author describes how modern supply chains have evolved in complexity due to the growth of global competition and technological change. He contends that the importance of risk management has grown accordingly, becoming part of part of organizational strategy and planning. He presents a basic model for risk management in four steps: identification, assessment, avoidance, and mitigation. He describes how risk mitigation focuses on the source of risk and outlines four areas of risk: supply, demand, products, and information, and provides examples for each. He also considers four methods of supply chain coordination, including Vendor-Managed Inventory (VMI) and continuous replenishment. He highlights examples of supply chain disruption due to natural disasters and provides nine coping strategies, including postponement, economic supply incentives, and dynamic assortment planning.

Supply Chain Risk Management Tools for Analysis, Second Edition, is an eight-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author explores the growth of global supply chains as well as the risks associated, such as political unrest and natural disasters. He highlights the importance of managing risk in a supply chain and outlines the categories of risk that managers must consider. He presents several quantitative tools and methods for risk management with extensive real-world examples and detailed models that have been updated in the new edition. In Chapter 3, Risk Matrices in Supply Chain Risk Management (14 pages), the authors discuss how to use a matrix planning tool and rating system. He considers risk identification and present an enterprise risk management framework to assist managers in approaching different risk types, such as legal, market, and operational. He explains how a risk matrix can help a manager determine the probability of success and identify areas that need attention. He demonstrated the matrix, reviews the challenges in using it, and then presents detailed analysis of several examples of decision-making with a matrix.

Supply Chain Risk Management Tools for Analysis, Second Edition, is an eight-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author explores the growth of global supply chains as well as the risks associated, such as political unrest and natural disasters. He highlights the importance of managing risk in a supply chain and outlines the categories of risk that managers must consider. He presents several quantitative tools and methods for risk management with extensive real-world examples and detailed models that have been updated in the new edition. Chapter 4, Supply Chain Selection Decisions (18 pages), reviews how to organize decision-making criteria when selecting sources, channels, or routes in a supply chain. The author reviews the creation of a value hierarchy to assess the risks involved in supply chain selection decisions. He considers decisions made on multiple criteria and explains each step in a simple multi-attribute rating theory (SMART). He illustrates this technique through a detailed example of a sourcing decision. He also provides examples of the supplier segmentation process and product design selection.

Supply Chain Risk Management Tools for Analysis, Second Edition, is an eight-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author explores the growth of global supply chains as well as the risks associated, such as political unrest and natural disasters. He highlights the importance of managing risk in a supply chain and outlines the categories of risk that managers must consider. He presents several quantitative tools and methods for risk management with extensive real-world examples and detailed models that have been updated in the new edition. In Chapter 5, Simulation of Supply Chain Risk (16 pages), the author outlines basic concepts in modeling risk. When risks can be based on probability, he advises managers to use a Monte Carlo simulation and provides an example based on a military supply network. He demonstrates how to use Net Present Value (NPV) model and presents an example where levels of funding are uncertain. He also consider risk management for inventory systems and models a basic simulation using Crystal Ball to analyze data.

Supply Chain Risk Management Tools for Analysis, Second Edition, is an eight-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author explores the growth of global supply chains as well as the risks associated, such as political unrest and natural disasters. He highlights the importance of managing risk in a supply chain and outlines the categories of risk that managers must consider. He presents several quantitative tools and methods for risk management with extensive real-world examples and detailed models that have been updated in the new edition. Chapter 6, A Simulation of Supply Chain Risk Models (12 pages), focuses on a Monte Carlo simulation used to manage the risks of selecting supply vendors. The author uses vendor data to demonstrate in detail how a simulation can frame the uncertainties in the decision-making process. He also explains the need for a program such as Crystal Ball in the simulation. He explains how to use the Value at Risk (VaR) Concept to determine risk exposure in a supply chain and provides an example of a vendor selection model. The chapter ends with a real-world example of a furniture supply chain.

Supply Chain Risk Management Tools for Analysis, Second Edition, is an eight-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author explores the growth of global supply chains as well as the risks associated, such as political unrest and natural disasters. He highlights the importance of managing risk in a supply chain and outlines the categories of risk that managers must consider. He presents several quantitative tools and methods for risk management with extensive real-world examples and detailed models that have been updated in the new edition. In Chapter 7, Optimization Models in Supply Chain Risk Management (22 pages), the author presents linear programming as a tool for operations management. He reviews different model types, such as product mix, blending, and transportation, and the corresponding variables, functions, and constraints. He provides detailed analysis of the components in linear programming through an example of a petroleum shipping supply chain, reviewing the solution, assumptions, and complications of the model. He also explores the metals production industry to show the potential of optimization models and outlines two real-world examples. First, how one company built a decision support system (DSS) to minimize costs. Second, how a mixed integer programming model optimizes medical supply transportation.