Mahindra Trucks and Bus Division (MTBD) of Mahindra & Mahindra is at an interesting stage of its evolution. Having gone through a bad patch with a product that was not quite up to the mark, it appears to have got the product right by early 2018 and truck sales had been going up in the country for the previous four years. While Mahindra & Mahindra as a company is a large firm with revenues of more than USD 15 billion, MTBD itself is a small player (INR 2400 crore , USD 350 million) within the firm and in an Indian truck industry that is dominated by goliaths, Tata Motors and Ashok Leyland that between them had more than 81% market share and a customer mindset that was loath to leave the comfort of a known brand. The case provides data on product specifications, prices, marketing communication, channels, positioning, the context and competition. The intention is to use the case to go through the steps involved in evaluating and developing and creating a marketing plan for MTBD to increase its market share from the 4% in 2018 to an intended 8% in 2022.
AWARD-WINNING CASE - African Business Cases Category, 2019 European Foundation for Management Development (EFMD) Case Writing Competition. In 2014, an entrepreneur in Cape Town, South Africa, started SweepSouth with her husband. Their mission was to enable dignified home cleaning work for the most vulnerable blue-collar workers, and they offered several services to empower them. When the company struggled to meet the demand for domestic services over the December holiday period, the founders realized the extent of the market’s need to connect domestic workers with potential clients. Given the entrepreneur’s business acumen and her husband’s skills and experience in software development, they created a digital platform that was often labelled the Uber of domestic services. SweepSouth employed 40 staff members and had 8,000 contractors (referred to as “SweepStars”) on the company’s platform. In 2018, the two founders wanted to scale up the business for greater social impact and had to choose among expanding the business to other African countries, expanding the service offering to office spaces, or remaining focused on serving the home and adding new services such as gardening and plumbing.
On September 30, 2017, the general manager (GM) of Uber Technologies Inc. (Uber) for sub-Saharan Africa, arrived in Nairobi, Kenya, and paid for his Uber service with cash. This functionality of the Uber app represented a new business model for Uber. The GM had to convince global management of the business case for offering cash payment options in Africa; he did so by conducting experiments and showing data that indicated rider numbers had tripled with adoption of the cash payment option. Uber’s driver-partners were concerned about safety when they transported passengers who paid by cash, both because credit card payments offered Uber rider identification and because the driver-partners were concerned about driving around with large amounts of cash. In spite of their concerns, the rationale for introducing a cash payment option was relevant, and it had to be considered carefully in the context of African locations with high crime rates. The GM considered various initiatives for utilizing data from their technology platform to safeguard their riders and drivers. They needed to address local needs in Africa while adhering to global Uber standards.
AI-driven text mining, a relatively new business analytics tool, allows users to unlock troves of information contained in documents and make them searchable by content and metadata. The ability to analyze documents requires a number of intricate steps. First, optical character recognition must be used to convert a document image into machine-readable text. The text must then be converted to a format in which it can be analyzed. Finally, information must be extracted from the documents. This case takes students through some of the theory behind and examples of text analysis. This case is a companion to Evisort: An AI-Powered Start-up Uses Text Mining to Become Google for Contracts (Case ID: CU251)
OpenSky.tv was founded in 2016 with the objective of getting people back to watching video content on television. The founder wanted all video content to be accessible through an Internet connection on the viewer's television. His company's platform located and brought together programs and videos that were of interest to each viewer, so viewers could have their own personalized video channel. One full year after its launch, OpenSky.tv wanted to focus on the Cantonese market, and then concentrate on Mandarin and English audiences. The founder was wondering what his platform's business model should be. How could he achieve his initial objective of creating a business-to-consumer (B2C) recommendation platform?
In June 2018, an intern at an investment firm was given the task of assessing the financial condition of Bon-Ton Holdings, Inc. (Bon-Ton), a leading US department store chain. In January 2018, it had entered into forbearance agreements with some of its lenders and announced store closures at 42 locations as part of its rationalization program. On February 4, 2018, it filed a voluntary petition for protection against bankruptcy and for reorganization. With the US retail industry already having witnessed more than 15 bankruptcies in 2017-the most in the last six years-would Bon-Ton survive? What measures could the company take to fight bankruptcy? What actions might put the company back on track?
In 2018, California-based Tesla Inc. (Tesla) seemed to be gaining momentum after a series of setbacks in the production of its mass-market Model 3 car. Tesla's partnership strategy, guided by founder and chief executive officer Elon Musk, had been key to its success, yet Tesla did not appear to be succeeding as a stand-alone firm. It continued to command a small portion of overall vehicle sales, it had not mastered mass-production techniques, and it had not solved its sales dilemma by receiving permission to bypass the car dealership network in the United States. Tesla would continue to need partners for growth even as the nature of its partnerships changed. The challenge was to determine Tesla's partnership strategy in the short to medium term.
In early April 2017, the newly-appointed business account manager at the Confederation Bank of Canada's branch in London, Ontario, was reviewing a long-term loan request for CA$1,500,000. The president of Yates Control Systems (YCS), an engineering company focused on providing automation solutions for manufacturing companies, had requested the loan to fund the purchase of a new facility for her company as part of a strategic expansion plan. YCS's president was a long-time client of the bank and was expecting a decision to be made about the loan within the next few days; otherwise, YCS's expansion could be delayed. However, the bank manager would have to ensure that granting the loan request would be financially feasible for the bank and that YCS's $50,000 line of credit, not used in several years, would still be sufficient.
Argus Farm Stop is a year-round farmers market store in Ann Arbor, Michigan. The owners launched the business with a mission to improve support for local farmers and offer the community better access to locally-produced food. The Argus model is a consignment arrangement so that farmers and other local producers can sell more directly to customers and retain more of the profit. However, though growing in revenue and having opened a second store location, Argus is not profitable. How can this business be scaled while still adhering to its mission?
This note provides a framework for addressing the classic chicken-or-egg dilemma facing entrepreneurs launching nascent multi-sided platforms. There are several conditions that lead to a difficult chicken-or-egg problem: strong network effects, high multi-homing costs, limited differentiation, and high other barriers to entry. To overcome this challenge and create competitive advantage by reaching critical scale in network size, there are three categories of solutions to the problem: increasing value, decreasing cost, or subsidizing value for the platform participants. For a multi-sided platform, there are also dynamic considerations for addressing whether to stage one side of the platform first or build both simultaneously.
The case covers events leading to the hostile bid for AkzoNobel by PPG in 2017, the market response that it prompted, and Akzo's takeover defenses including the divestment of a division and large cash payout. Various scenarios (as a standalone; after an asset sale) are considered for the valuation of AkzoNobel, as is the rationale behind the various takeover bids by PPG. The role of activists in triggering the takeover process is highlighted. Alternative payout mechanisms (capital repayment, dividend payment, share buyback) are discussed.
WeWork has seen a decade of growth with a disruptive new service business model in a rapidly transforming industry: shared office space for start-ups (and increasingly for big companies) thanks to its understanding of workplace trends such as the 'gig' economy, the rise of millennials and Generation Z in the workforce, more collaborative office work and tech-enabled mobility of employees. It caters to freelancers and multinationals alike, all members of the 'co-working' community, as well as an ecosystem of likeminded entrepreneurs. The case allows discussion of customer-centricity in a B2B service context, and of how companies optimize - digitalize - the customer experiences by leveraging data. WeWork relies on analytics and artificial intelligence (AI) to mine data from its global customer base for insights and deep learning that feed into next-gen office design and usage. Customers perform a job-to-be-done analysis using a means-end ladder to understand how WeWork creates an outstanding customer experience in a competitive, commoditized market. The case offers learning about service blueprinting and customer journey mapping when designing new services and/or improving existing ones. To deliver on its customer promise WeWork integrates the key building blocks of a superior business model, for example, alliances with strategic partners secure unique resources and distinctive competences, achieving cost-effective service excellence. Discussion culminates in future growth avenues following a corporate rebranding and reorganization into three business units under the umbrella "We" brand.
At the BMW Group, Gregor Gimmy, a serial entrepreneur and former consultant, introduces the Venture Client (VCL) model to engage with start-ups and boost corporate innovation. The case discusses its initial success at BMW and the rationale that drove Gimmy to establish a new model of external corporate venturing (ECV). It also provides background information on the key forces shaping the auto industry today, the challenges faced by legacy automakers as technological developments accelerate, and the emergence of new rules and new players.
In August 2018, Felicia Wong, Chief Investment Officer at 88 Capital, the investment arm of a Hong Kong family office, was considering investing in a bike-sharing company. The bike-sharing business was booming in China, with the two dominant players Mobike and ofo rapidly expanding. Mobike had been acquired for US$3.4 billion by Meituan Dianping, a food delivery company. ofo also had unicorn status with a roughly US$3 billion valuation. The bike-sharing industry could potentially disrupt the transportation industry. Bikes had the advantage of being able to bypass gridlocked streets and were more environmentally sustainable than private cars. In addition, the use of bikes promoted a healthier lifestyle and offered a prospective solution to the last mile problem for commuters who used public transport. But despite the many advantages of using dockless bikes, the practice brought about problems as these bikes were parked indiscriminately on pedestrian walkways and pedalled on busy roads. The industry also had too many players in China. In addition, bike-sharing companies were not yet profitable. Companies had prioritised gaining market share over making profits to increase the value of their respective platforms. It was expected that the industry would become more valuable should city planners approve plans to redesign transport networks to accommodate bikes. As at August 2018, the low rental fees and high capital expenditures were proving to be unsustainable. Mobike was the largest player in China and were likely to survive the industry's consolidation phase. The firm had strategic partnerships to help it reach critical mass and improve its service offerings. Wong wondered if it was worth investing in Mobike at this stage.
BotGo was started in 2007 by Ravi Panchal, an engineer, after he lost motivation to continue at a managerial role at his job. A hands-on technical person, Panchal was inspired to create an underwater tank-cleaning robot. He started BotGo by bootstrapping it with his savings and roped in his friends for key positions in the company. He also started workshops for robotics education in colleges in order to sustain the company; he called this initiative BotLearn. In 2009, BotGo was incubated and Panchal started franchises for BotLearn as part of his growth plans. This led to a crisis within the company, escalating to a point where Panchal was forced to consider options. This case highlights the importance of a product-to-market fit and examines the decision to franchise in view of the case facts. The case also points towards the mistakes in crisis management, with particular emphasis on channel management. Towards the end of the case, Panchal is faced with a dilemma on whether to continue with the franchises or close them down. The dilemma is further accentuated since Panchal's decision would ultimately affect the growth of BotGo as well as directly challenge his intention to franchise.