In 2017, Constellation Brands, the U.S. based beverage company, acquired a 9.9% equity interest in the Canadian marijuana company, Canopy Growth. In 2018, Constellation announced a subsequent investment in Canopy-taking its ownership interest to 37%. However, Canopy's performance had been volatile and net losses had increased since the investment. In an effort to get into the cannabis market early, had Constellation Brands been too early?
After spending more than 50 years creating a diversified industrial conglomerate that Fortune Magazine described as "arguably the most profitable conglomerate in America" in 2014, UTC's CEO Greg Hayes was under pressure from activist investors (Dan Loeb and Bill Ackman) to break the company into three standalone businesses in the spring of 2018. The activists claimed that a breakup would create at least $20 billion of incremental value (on top of a current market value of approximately $100 billion) and possibly a lot more. Hayes must decide whether a breakup makes sense-will it create value and, if so, how much value and why? What factors determine whether a conglomerate trades at a discount or a premium, and how big are those discounts and premiums likely to be?
For decades, Chile enjoyed the stability of being the world's largest producer of copper. Keynes would have advised that this period of growth would have been the time for the government to save, that "the boom, not the slump, is the right time for austerity at the Treasury." If this wisdom has proven true on multiple occasions since Keynes's statement in 1937, why do countries continue to conduct procyclical fiscal and monetary policies? Economists have documented this phenomenon across countries and found that particularly for emerging markets, capital inflows tend to coincide with expansionary macroeconomic policies while periods of capital outflows correspond with contractionary policies. Why is it so difficult for governments of emerging market countries to save during economic booms? By analyzing economic and social factors that contributed to unrest in Chile, students will wrestle with economic and ethical questions about balancing the needs of current and future generations.
After losing market share to low-priced competitors such as Harry's and Dollar Shave Club for several years, Gillette decided to fight back by launching new products and increasing advertising. When these efforts failed to stem the losses, Gillette decided to cut the prices on its razors and blades in April 2017. Bonnie Herzog, an equity analyst at Wells Fargo, must assess how the recently announced price cuts are likely to affect Gillette's earnings and its parent company's earnings (Procter & Gamble owns Gillette). As part of her analysis, Herzog must estimate the price elasticity of demand for Gillette's razors and blades. The case contains scanner data which allows students to calculate both price elasticities for a sample of Gillette products, and sufficient data to estimate the financial impact.
This case focuses on Purple Innovation Inc. (Purple), a company that started out in the Direct to Consumer (DTC) mattress space. After a successful launch and IPO, with sales predominantly originating from its website, in late 2018 Purple was looking to sustain its growth momentum by partnering with traditional bricks & mortar players, such as Mattress Firm and Bed Bath and Beyond. Although the move had the promise of expanding the relevant customer base, it presented a marketing challenge: Could the company continue to rely on its previous digital advertising approach to drive offline sales? If so, how, and, if not, what other media outlets and messaging should be considered? The case forces students to analyze the digital strategy the company had previously used to generate hundreds of millions of dollars in online sales, and then propose a communication plan for generating 30% of sales offline. In doing so, students grapple with delineating the customer journey for buying a mattress online and in stores. The case can also serve as a vehicle to discuss the scaling challenges many disruptor DTC brands face.
In mid-2019, a year after German conglomerate Bayer Group closed its acquisition of U.S.-based seeds giant Monsanto, the leadership of Bayer's Crop Science division (which absorbed Monsanto) is reflecting on the opportunities ahead. Some observers have questioned Bayer's decision to buy Monsanto, citing potential reputational and financial liabilities; in the last year, Bayer's stock price has suffered. However, the leadership team expects the combination of Monsanto's and Bayer Crop Science's seed, crop protection, and digital agriculture technologies and expertise to deliver huge value to farmers and shareholders. A key focus is The Climate Corporation, Monsanto's (and now Bayer's) digital agriculture unit, which collects data from farmer-customers' operations and uses it to provide tailored farming advice and to inform internal research and development. Bayer Crop Science is digitizing its entire R&D operation in order to fast-track innovation, with the goal of producing the game-changing products needed to feed the growing global population while protecting the environment. The Bayer team aspires to lead the digital transformation of agriculture. Is this achievable, and is Bayer the right firm to lead it? Will farmer distrust, competition, merger-related challenges, or other hurdles prove insurmountable?
This case introduces students to the history of women in the venture capital industry. It explores the impact of gender diversity on both company performance and fund returns, describes the lack of funding for female founders, and highlights examples of women-led venture capital firms.
Recently booming academic interest in digital transformation aims to provide continuous support to managers in dealing with this important issue. However, as with all new fields, the scholarly literature is characterized by increased variability and diversity of topics covered, constructs used and relationships between them, resulting in an unclear and blurry understanding of the whole of digital transformation. Our article closes this gap by identifying distinctive digital transformation strategies in terms of two critical dimensions: usage of digital technologies and readiness of a business model for digital operation. The result is a typology of four generic digital transformation strategies that essentially differ in the primary motivation and target of transformation, leadership style, importance of skills like creativity and entrepreneurial spirit among employees, risks and challenges faced in the process, consequences of potential failure and available tactics for improvement. By providing heuristics and a systematic basis for comparison of different strategies, it is our belief that the proposed framework will be useful to researchers and managers responsible for and interested in digital transformation.
With digital technologies shaping competition in many industries, predicting the future of potentially disruptive technologies becomes an essential task of business leaders concerned with the survival and success of their organizations. Looking into the future of disruptive technologies requires a philosophical stance and a practical method that accommodates the inherent uncertainty and nonlinearity of the path of disruptive innovations. Unfortunately, much of the current thinking in relation to adoption and diffusion of innovations is rather linear and deterministic. This article proposes a set of philosophical principles, together with a practical brainstorming method, for glimpsing into the future of disruptive technologies. The method of alternative histories is based on the traditional brainstorming techniques and the philosophical ideas of Imre Lakatos, Roy Bhaskar, Bruno Latour, and Nassim Taleb.
With the rapid development of digital technologies, many supply chain professionals are wondering how to move forward. Three technologies are poised to change supply chain business processes: robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), and blockchain. Based on interviews with supply chain professionals in 14 large, mature manufacturing and service organizations, we outline the promise of each process and forecast their broad-scale adoption potential. Organizations should take the following measures to ensure their readiness to adopt and effectively use one or more of these technologies: (1) identify a supply chain technology visionary who can lead through the maze of technologies and the changing digital landscape, (2) develop a digital technology roadmap for their supply chain processes, and (3) update foundational information systems.
Digital transformation encompasses an organization's ability to adapt, respond, and position itself for success in the face of rapid technology evolution. A critical structure in achieving successful digital transformation is the digital project team, yet there is little research to study how they are created and developed. Much of the focus has been on agile methodologies and processes but there is less research to inform organizations on digital team dynamics such as roles, empowerment, learning, and leadership development. This article describes our findings from a multi-level study of the IT function of 60 companies, including fieldwork at 5 company sites involving more than 130 semistructured interviews with senior level IT professionals. We identify four essential team-based levers that enable digital transformation: (1) diverse and targeted team composition, (2) iterative goal setting, (3) continuous learning, and (4) talent management. Using company examples and practices, we describe how digital leaders are using these levers to propel their organizations forward in the journey toward digital transformation.
Recruiting talent has moved from a tactical HR activity to a strategic business priority. This has been driven by shifts in the source of firm value and competitive advantage and the critical role of human capital in those shifts. Technological advances have moved digital, AI-enabled recruiting from a peripheral curiosity to a critical capability. However, we know little about candidates'reactions to AI-enabled recruiting. Consequently, in this study, we examine the role of social media use, intrinsic rewards, fair treatment, and perceived trendiness on the intentions of prospective employees to engage with and complete digital, AI-enabled recruiting processes. The positive relationships between these factors and candidates'engagement with AI-enabled recruiting have several important practical implications for managers. We also examine the larger implications and make general recommendations to firms about using AI-enabled recruiting technology and tools.
Artificial intelligence (AI) is emerging as a potential growth area for facilitating the improvement and development of teams in the workplace. AI, as used in the team context, is currently underdeveloped and limited, thus reducing the wide-scale adoption and implementation of AI to improve team effectiveness. The use of AI to provide team diagnostics and improvements represents a significant shift in the approach organizations currently use to facilitate and strengthen effective teamwork. We describe the challenges involved in developing team effectiveness in organizations and the potential application of AI to improve teamwork. Further, we report on our experiences using AI in business school student project teams, the important advantages and disadvantages that emerged from this, and insights for future consideration when adopting and implementing AI in the workplace. Based on our use of AI and our experience training high-performing teams, we propose a multistep process for analyzing and improving teams in organizations.
Technological progress-including the development of online channels and universal access to the internet via mobile devices-has advanced both the quantity and the quality of data that companies can acquire. Private information such as this may be considered a type of fuel to be processed through the use of technologies, and represents a competitive market advantage. This article describes situations in which consumers tend to disclose personal information to companies and explores factors that encourage them to do so. The empirical studies and examples of market activities described herein illustrate to managers just how rewards work and how important contextual integrity is to customer digital privacy expectations. Companies' success in obtaining client data depends largely on three Ts: transparency, type of data, and trust. These three Ts-which, combined, constitute a main T (i.e., the transfer of personal data)-deserve attention when seeking customer information that can be converted to competitive advantage and market success.
Digital transformation recently converged on organizations as a new paradigm-a must-have exemplar-to enable competitive advantage. While the effects of digital transformation and their analytics, along with platform technologies, are becoming pronounced in companies, there is still a need to examine their implications on higher education. In light of the dynamics of digital transformation, how can higher education better manage the shift toward newer competencies and the need for innovation presented by the emergence of digital technologies? In this article, I examine the issues around the need for this balance-often defined in strategy as ambidexterity, or the need to address both competency with innovation-by outlining the historical trajectories that led to this problem in higher education, identifying three common pitfalls that higher education programs and administrators face, and tying these issues to higher education's absorptive capacity. To resolve these pitfalls, this article builds upon absorptive capacity frameworks for education practitioners and strategies as a prospective change management tool.
As the underlying technology of bitcoin, blockchain is expected to create a new economic system by revolutionizing the way we communicate over the internet. Blockchain seeks to improve information security and transparency by sharing encrypted data among peer-to-peer (P2P) networks. Due to its emphasis on security and trust, there is increased demand for blockchain's application in a variety of business sectors. The decentralized nature of blockchain creates the new concept of a token economy in which the community's revenue can be allocated to the actual content producers and service users who create value. This article looks at how blockchain technology and cryptocurrencies are evolving and interconnected, creating a token economy through different business models. Blockchain is expected to be a key technology that enables new protocols for the establishment of a token economy in the future, leading to a new economic paradigm.
Chatbots are used frequently in business to facilitate various processes, particularly those related to customer service and personalization. In this article, we propose novel methods of tracking human-chatbot interactions and measuring chatbot performance that take into consideration ethical concerns, particularly trust. Our proposed methodology links neuroscientific methods, text mining, and machine learning. We argue that trust is the focal point of successful human-chatbot interaction and assess how trust as a relevant category is being redefined with the advent of deep learning supported chatbots. We propose a novel method of analyzing the content of messages produced in human-chatbot interactions, using the Condor Tribefinder system we developed for text mining that is based on a machine learning classification engine. Our results will help build better social bots for interaction in business or commercial environments.
As companies become increasingly digital, growth hacking emerged as a new way of scaling businesses. While the term is fashionable in business, many executives remain confused about the concept. Even if firms have an idea of what growth hacking is, they may still be puzzled as to how to do it, creating a strategy-execution gap. Our article assists firms by bridging the growth hacking strategy-execution gap. First, we provide a growth hacking framework and deconstruct its building blocks: marketing, data analysis, coding, and the lean startup philosophy. We then present a taxonomy of 34 growth hacking patterns along the customer life cycle of acquisition, activation, revenue, retention, and referral; categorize them on the two dimensions of resource intensity and time lag; and provide an example of how to apply the taxonomy in the case of a fitness application. Finally, we discuss seven opportunities and challenges of growth hacking that firms should keep in mind.
Due to its intrinsic characteristics, artificial intelligence (AI) can be considered a general-purpose technology (GPT) in the digital era. Most studies in the field focus on the ex-post recognition and classification of GPT but in this article, we look at a GPT design ex-ante by reviewing the extreme and inspiring example of IBM's Watson. Our objective is to shed light on how companies can create value through AI. In particular, our longitudinal case study highlights the strategic decisions IBM took to create value in two dimensions: internal development and external collaborations. We offer relevant implications for practitioners and academics eager to know more about AI in the digital world.