This case describes SAP's "Autism at Work" program, which integrates people with autism into the company's workforce. The company has a stated objective of making 1% of its workforce people with autism by 2020. SAP's rationale for the program is based on the belief that "neurodiversity" contributes to the company's overall innovative capabilities ("We believe that innovation comes from the edges.") Thus, the program is not viewed as a subsidized Corporate Social Responsibility activity but as a positive net benefit activity, as well as a way of addressing skills shortages by tapping into non-traditional pools of (considerable) talent. The case explores how SAP is also using the program to rethink and reengineer its Human Resource Management policies and processes to make them more inclusive and effective.

The Employee Provident Fund Scheme (EPFS) had been established as a social security scheme for the Indian industry and has established a huge corpus through its 42 million contributors. At a relatively risk-free rate of nearly 8.75% return, EPFS is recommended as a good retirement product in the debt portfolio. However, administration of the scheme had come under considerable criticism, which had resulted in changes in the regulatory norms around the scheme. The government's interest in promoting a defined contribution approach to retirement benefits appears to work at cross-purposes with the interest of the low-income employees. With recent regulatory changes in the minimum contribution level, the effect on bottom-of-the-pyramid employees covered by this scheme further reduces their net income. The case discusses the impact of changes in the regulatory scheme on all employees, but more specifically on the lower income workforce, the financial impact for organizations. It debates the efficacy of the current social security scheme in India and the options for organizations to design and administer variable compensation structures adapted to individual and life-stage needs.

Maxim, headquartered at San Jose in California, was founded in 1983 by Jack Gifford and other professionals with experience in semiconductor design and sales. The company posted $2.47 billion in sales in 2011, with 9,300 employees, and 35,000 customers worldwide. Maxim had developed expertise in designing and manufacturing highly integrated analog and mixed-signal semiconductors. Maxim set up a technology design center in Bangalore in 2006. The Bangalore center had grown over the years and moved up the value chain in terms of contributing to technology design at Maxim. Gopal Krishna, Head of India Operations, had joined Maxim in 2009. In mid-2011, Gopal Krishna was contemplating the new context that Maxim faced in India. India had been a location that contributed to design in Maxim while now India as a market appeared increasingly attractive. As a first step towards exploring this opportunity, Gopal decided to engage with the marketing faculty at Indian Institute of Management Bangalore who decided to examine the medical diagnostics space in India for value exchange opportunities. Interviews were conducted with healthcare professionals. The management team had to identify attractive market opportunities and develop a strategic plan to enter the Indian medical diagnostics market.

The case focuses on the dilemma faced by Dipak Mane, Bühler's President, South Asia as he pursues opportunities for sustainable growth in India's rapidly growing but competitive food processing industry. Buhler's corporate objectives, innovative technologies, superior quality, positioning as a premium global brand, competition and value chain requirements, determined its product - market strategies in India. Bühler was traditionally focused on the top-level market in several geographies that it served around the world. However, the company had experienced rapid growth during the last decade after it entered the mid-level market with new offerings and a value proposition tailored to the needs of the mill owners. Dipak's dilemma revolved around growing the business in India by consolidating in the mid-level market and/or targeting a new segment, namely the entry-level segment. The key issues relate to - Should Bühler target the entry-level segment? If yes, what adaptations will be needed to target customers in the entry-level segment? What will be the potential cannibalization in the mid-level segment where Bühler enjoyed a sizeable presence and reputation? What should be the differentiation strategy in the entry-level segment? What would be the go-to-market strategy for the entry level?

ScaleneWorks People Solutions LLP (ScaleneWorks), is a Bangalore-based talent management company, which commenced its operations in the summer of 2010 with a vision to build an organization of great value and be among the most respected talent acquisition solution providers globally. Sanjay Shelvankar, CEO of ScaleneWorks was considering the use of an analytical approach to predict renege. Past data from Indian IT companies revealed that 30% of the candidates did not join the company after offer acceptance, which significantly increased the overall cost of recruitment. Sanjay wondered if Analytics could possibly help in identifying the key drivers that influence a candidate in either joining/not-joining a company after accepting the offer, as it would largely help clients save both cost and time. However, there was a risk involved: any error in this prediction could turn out to be a costly affair, as the client could ''wrongly'' reject a potential candidate even without interviewing him/her.

ScaleneWorks People Solutions LLP (ScaleneWorks), is a Bangalore-based talent management company, which commenced its operations in the summer of 2010 with a vision to build an organization of great value and be among the most respected talent acquisition solution providers globally. Sanjay Shelvankar, CEO of ScaleneWorks was considering the use of an analytical approach to predict renege. Past data from Indian IT companies revealed that 30% of the candidates did not join the company after offer acceptance, which significantly increased the overall cost of recruitment. Sanjay wondered if Analytics could possibly help in identifying the key drivers that influence a candidate in either joining/not-joining a company after accepting the offer, as it would largely help clients save both cost and time. However, there was a risk involved: any error in this prediction could turn out to be a costly affair, as the client could ''wrongly'' reject a potential candidate even without interviewing him/her.

Flipkart, the poster child of Indian e-commerce, was an early entrant in the nascent Indian e-commerce market and quickly established itself as the leading company in this space. Flipkart has grown into an online retail giant, valued at over USD 15.2 billion as of 2015. Flipkart has been selling over 30 million products from more than 50,000 sellers in 70+ categories as well as has 30 exclusive brand associations with an in-a-day guarantee in 50 cities and a same-day guarantee in 13 cities. Flipkart was 33,000 people strong and had over 50 million registered users with over 10 million daily visits and 8 million shipments per month. Flipkart has been putting in much effort and emphasis on the use of Analytics in every aspect of decision making. Headed by Ravi Vijayaraghavan, the analytics team had over 100 data scientists in 2015. Customer churn is a major concern for Flipkart since it has direct impact on Customer Lifetime Value (CLV). CLV is an important measure to differentiate customers, which can further help the organization manage them effectively. The main challenge in calculating the lifetime value of customers of e-commerce companies such as Flipkart is that the exact life of the customer is unknown owing to data truncation, that is, the actual point in time of customer churn, which may not be identified in e-commerce since there would be no prior communication from the customer about the churn. Hence, traditional models of CLV calculation may not be appropriate for e-commerce companies such as Flipkart.

Flipkart, the poster child of Indian e-commerce, was an early entrant in the nascent Indian e-commerce market and quickly established itself as the leading company in this space. Flipkart has grown into an online retail giant, valued at over USD 15.2 billion as of 2015. Flipkart has been selling over 30 million products from more than 50,000 sellers in 70+ categories as well as has 30 exclusive brand associations with in-a-day guarantee in 50 cities and same-day guarantee in 13 cities. Flipkart was 33,000 people strong and had over 50 million registered users with over 10 million daily visits and 8 million shipments per month. Flipkart has been putting in much effort and emphasis on the use of Analytics in every aspect of decision making. Headed by Ravi Vijayaraghavan, the analytics team had over 100 data scientists in 2015. Customer churn is a major concern for Flipkart since it has direct impact on Customer Lifetime Value (CLV). CLV is an important measure to differentiate customers, which can further help the organization to manage them effectively. The main challenge in calculating the lifetime value of customers of e-commerce companies such as Flipkart is that the exact life of the customer is unknown owing to data truncation, that is, the actual point in time of customer churn, which may not be identified in e-commerce, since there would be no prior communication from the customer about the churn. Hence, traditional models of CLV calculation may not be appropriate for e-commerce companies such as Flipkart.

Consumer transactions will eventually go digital, but retailers and consumers alike need to learn how to make this work. Unlike most Millennials, most Boomers and Gen-Xers had to be coerced into switching to digital music. According to a recent consumer sentiment study on mobile usage, more coercion will be required before digital commerce reaches its potential. While more than 60 per cent of Americans have a smartphone, only 14 per cent surveyed prefer shopping online, and privacy concerns of customers limit the appeal of firms going digital. Such firms must make serious financial commitments, not to mention decisions about what platforms to bet the budget on. There is also a significant outlay of resources needed to train employees on how to use and maintain new systems and equipment. Much of the push to get retailers to invest in digital offerings has hinged on the value associated with compiling customer spending data, yet most retailers don’t know what to do with this data once it is collected. Businesses need to take advantage of the relatively slow adoption of digital transactions to first learn the new technology that they are deploying, and then use this expertise to serve their customers by helping them learn how to use their devices in new ways — while gaining more trust in their transactions rather than increased frustrations.

The case is set in May 2015 in Singapore, the regional headquarters of the UK-based travel metasearch firm, Skyscanner. After a successful launch as a start-up followed by a period of rapid expansion, the company is now facing the challenge of growth in Asia. In 2011, Skyscanner opened its regional headquarters for Asia in Singapore. The tech-savvy customers in Asia were gradually beginning to discover the Skyscanner service, but their behaviour in using the site was different from that of customers in Western markets. Many users were accessing the site through mobile devices and linking from social media sites, while Western market customers were traditionally searching from a computer using the Google search engine. Skyscanner traditionally worked closely with partners such as airlines and online travel agents to provide information, advertising, and data services. To help attract partners, Skyscanner allowed the partner to "own" the customer, by passing the consumer through to the partner site to complete the transaction. The partners got paid for click-through traffic or from advertising on the Skyscanner website. By May 2015, Skyscanner had created local websites for 14 countries in Asia Pacific, but the challenge was to scale up the business and get more customers using the site by meeting localised needs. How should it further adapt its local offerings and marketing strategies more effectively to better connect to the in-country users in Asia? How should Skyscanner change its internal organisation to be more nimble to respond to the market? This case targets participants who are interested in understanding the challenges associated with adapting an organisation and its business model for local market needs. The case is designed for use in postgraduate and executive education classes. It allows participants to better understand the Asian context and the challenges of growing a multi-national business in Asia.

It was April 2014, and Cadence Chong, a new analyst at YOB Bank Singapore's consumer banking department, is working on her first assignment. Chong has been hired to improve the bank's credit card business, as her manager believed that there was scope for the business to do better. A specific initiative that had been suggested was to enhance the bank's responsiveness to customer feedback on MyDiningDeals, a mobile application that offered special deals and promotions contingent upon customers using their YOB credit cards. Chong was tasked to apply analytical techniques to the user-generated data gathered by the application. She had to analyse the data in response to customer and internal feedback on the division's credit card offerings to investigate how the application could be made more user-friendly. Chong was eager to complete her task as she knew that her analyses and recommendations would help drive up profitability in the credit card division.

In December 2015, Angela Merkel, Chancellor of Germany and the de facto leader of the EU, faced the challenge of formulating an effective policy response to Europe's migration crisis. Merkel must decide whether Germany can continue to host large numbers of new refugees in 2016, keeping in mind that over a million had arrived in 2015. Merkel could continue Germany's relatively open refugee policy, but would need to decide how many more refugees to accommodate. Alternatively, Merkel could seek to significantly reduce the number of refugees, yet would need to formulate an effective set of international and domestic policy measures in order to achieve this objective. This case introduces students to the complex mix of economic and political considerations that guide policymakers seeking to regulate the cross-border movement of people. Students evaluate the labor-market, fiscal, and economy-wide consequences of different types of immigration flows, analyze how cultural prejudice and xenophobia mediate the political integration of immigrants, and study how electoral competition can give rise to right-wing and anti-immigrant movements that influence the overall direction of policymaking in democracies. This case also highlights the challenges faced by countries seeking to promote international cooperation in the domain of economic policymaking and highlights the role of national security, international law, and human rights norms in explaining policy contestation.

In June 1991, India was in the midst of a currency and balance of payments crisis the likes the country had not seen since independence in 1947. The country's foreign exchange reserves were barely enough to finance 13 days worth of imports. In the face of the crisis, India was forced to consider external help from the International Monetary Fund (IMF), which was accompanied by market-oriented conditionalities. The prospect of IMF support was a double-edged sword: on the one hand, restoration of finances and a viable path to economic recovery, but on the other, forced trade liberalization that would upend decades of centralized planning and inward-oriented growth. The IMF's adjustment plan would touch nearly every citizen, firm, and industry in the country. Liberalization, in theory, could stimulate long-term growth in the economy, yet it could also impose substantial adjustment costs in the form of firm closures and job losses. These economic reverberations would undoubtedly shake the country's political establishment, potentially jeopardizing the electoral fortunes of those in power. This case introduces students to Prime Minister P.V. Narasimha Rao's decision to liberalize the Indian economy. Students must pay attention to the domestic political actors-communist and right-wing parties, voter coalitions, and special interest groups-that played a central role in influencing Rao's policy positions. They must also evaluate the negotiation strategies of international institutions, national governments, and firms and industry groups in the context of trade liberalization. By applying political economy theories of trade and economic policymaking to the decision facing Rao, students learn about the complex linkages between domestic political factors and international economic pressures when developing countries integrate into the global economy.

Enabled by enterprise social software (ESS), online corporate communities are shaking up the management world by revolutionizing many core organizational activities. By creating new channels of interaction among employees, customers and managerial echelons, ESS solutions are democratizing the decision-making process. Many prominent companies see this favourably, which is why they actively use ESS platforms such as Yammer — a private social network that helps employees collaborate across departments, locations and business apps — to transform innovation, talent management, marketing and CSR practices. But democracy in business is a double-edged sword. And when it comes to empowering the corporate masses to heavily influence the decision-making process via ESS, it remains unclear when the C-suite benefits and when it doesn’t. <br><br> This article aims to raise awareness of the perils associated with decision democratization and help managers identify the conditions in which ESS platforms complement the decision-making process and those conditions in which online communities fall short in making a true contribution. We provide a framework to discuss the optimum role of ESS platform functionality for three different types of decision making: operational, tactical and strategic. Our research indicates that there is no question that ESS should indeed be exploited for some intra-firm decision making, but that companies need to be very wary of democratizing the strategic decision-making process.

When M Power Micro Finance was founded in 2009 in the Indian state of Gujarat, a number of challenges in the microfinance market made it difficult for the company to survive. Just months after M Power’s founding, the microfinance industry was hit by a repayment crisis that eroded both profitability and confidence in the industry. With public sentiment turning against microfinance institutions, M Power’s bright growth prospects suddenly disappeared and its CEO struggled to keep the business afloat. The flow of funding into the microfinance sector dried up, and the management of funds had to be closely monitored on a monthly basis. The CEO’s woes were not over: some of his business partners left the organization as the situation worsened. The company’s future was uncertain. As the industry began to show signs of recovery in 2013, though, the CEO hoped to secure a financing deal and persevere.

Mexican electric appliances company Mabe had grown from being a leading national firm in its field to an international company with presence in most of the Americas and Russia. It had ventured into emerging markets and intended to continue its expansion to other countries. The company gathered together five directors to form an Action Learning team that would evaluate its entry into India together with directors from its potential partner, Italian company Indesit. The Action Learning team had to analyze the company’s prospects and make its recommendations with respect to entering the Indian market. However, despite being a market with great potential, India also posed a series of problems, including a lack of transportation infrastructure, an excess of industry capacity for electric appliances and the cultural challenge of a multinational Mexican company marketing to Indian consumers. Should Mabe go ahead with its move into India? If so, what would be the best way to enter the market?<br><br><br><br>This case can be taught on its own, or in combination with Mabe: Learning to Be a Multinational (A) 9B13M042.

As one of the world’s largest OEM suppliers of electric massaging equipment, China’s Easepal has faced increasing challenges in its traditional OEM business over the course of two decades. Since the company’s inception in the 1990s, its founder has always had the ambitious goal of becoming more than just a supplier in the global electric massager market. Easepal’s mature research and development and manufacturing capabilities have the potential to deliver some valuable opportunities in both the Chinese and international markets. With the goal in mind of becoming the international market leader, how can Easepal systematically transform itself from an OEM supplier into a global brand?

in 2011, the senior management team at TransCanada Corporation in Calgary, Alberta, was stunned by the U.S. Department of State announcement that it was deferring its decision on a presidential permit, which was required for all construction of infrastructure crossing U.S. international borders. The infrastructure in question was the proposed Keystone XL pipeline, which would create a 2,735-kilometre direct route for Canadian crude from the Alberta oil sands to refineries in Oklahoma and the Gulf Coast. Because the pipeline would pass through environmentally sensitive landscapes, especially in the state of Nebraska, non-governmental organizations, climate change activists, citizens, celebrities and federal and state politicians pressured the Obama administration to halt the project. Company executives had initially seen the Keystone XL pipeline as a readily achievable, financially significant and strategically compelling venture but now wondered whether they had missed the indications and opportunities to avoid controversy. Extensive advertising campaigns and intensive lobbying in Washington did not seem to have improved the likelihood of the pipeline’s construction. What could be done now to increase the likelihood of permit approval and bring the Keystone XL pipeline to fruition?

Mexican electric appliances company Mabe had grown from being a leading national firm in its field to an international company with presence in most of the Americas and Russia. It had ventured into emerging markets and intended to continue its expansion to other countries. The company gathered together five directors to form an Action Learning team that would evaluate its entry into India together with directors from its potential partner, Italian company Indesit. The Action Learning team had to analyze the company's prospects and make its recommendations with respect to entering the Indian market. However, despite being a market with great potential, India also posed a series of problems, including a lack of transportation infrastructure, an excess of industry capacity for electric appliances and the cultural challenge of a multinational Mexican company marketing to Indian consumers. Should Mabe go ahead with its move into India? If so, what would be the best way to enter the market? This case can be taught on its own, or in combination with ""Mabe: Learning to Be a Multinational (A)""