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Consumer products companies were beset by changes on all sides during the 2010s. Customers were increasingly turning to ecommerce platforms rather than shopping in-store. Meanwhile, nimble, digitally-savvy competitors were gaining market share by capitalizing on the troves of newly available data on consumer preferences. Alibaba was the largest ecommerce platform company globally and operated in China, which was seen by many as an image of the future of western markets. In 2017, Alibaba launched the Tmall Innovation Center (TMIC) which provided a range of services to support innovation for companies selling through the Tmall business-to-consumer platform. These included robust consumer insights backed by data from across Alibaba and mechanisms to rapidly solicit customer feedback. Armed with the TMIC, consumer products companies were learning that effectively targeting consumer preferences required a new approach to product development which had far-reaching implications across roles, skills, and organizational structure.

In February 2020, Nick Dalton, executive vice president HR business transformation at Unilever, reflected on the changing nature of work marked by rapid advances in artificial intelligence, machine learning, and automation. Launched in 2016, Unilever's Future of Work initiative aimed to accelerate the speed of change throughout the organization and prepare the workforce for a digitalized and highly automated era. Despite the success over the last three years, the program still faced significant challenges in its implementation: How should Unilever, one of the world's largest consumer goods companies, adapt and accelerate the speed of change throughout the organization? Was it even possible to lead a systematic, agile workforce transformation across several geographies with local context differences? How could Unilever prepare and upscale its workforce for the future?

This case touches on the topics of project-based work, agile methodology, and skill and talent management through Catalant's evolution as a company. Catalant's journey to becoming a software platform and talent marketplace provides context for students to explore new models of work and ways companies are mobilizing talent internal and external to their organization. This case urges students to contemplate how these considerations might shape the critical decisions business leaders will need to make about how to manage their organizations and use their resources to capitalize on their own vision for the future. This case also provides valuable lessons for technology entrepreneurship, introduces students to important gig economy concepts, and asks students to consider the unique challenges facing companies like Catalant that are selling a gig platform as part of their product or service.

China's digital commerce platforms engage billions of consumers daily across a number of routine tasks from banking, retail purchases, travel, gaming, payments, and more. These platforms are the most sophisticated/informed and highest performing/capable in the world. While often business leaders refer to Amazon as a leader in digital exchange, this case highlights the vital areas where the Chinese platforms lead. Of special note is the merging of the retailers' on and offline capabilities into a unified consumer experience. Retailers like Walmart China have fundamentally altered their business model and federated with these Chinese platforms to build a better consumer experience, sell more, and manage costs and investment. While not all of these practices are globalizing, the non-china platforms are copying them fast to reach the new global standards. Leaders need to be informed and respond.

The nature of work is changing-and it is changing rapidly. Few days go by without industry giants such as Amazon and AT&T announcing plans to invest billions of dollars towards retraining nearly half of their respective workforces for jobs of the future. What changes lurking around the corner are Amazon and AT&T seeing? What tools do managers have to confront the accelerating change? How should talent management and workplace design evolve for the new landscape? This note summarizes the key drivers of change and offers a framework for managers to apply to their businesses.

Driven largely by advances in perception and situational awareness, robots in the 2010s were gaining functionality that allowed them to be applied to fundamentally new types of work. The expanding range of new types of tasks that could be completed by machines had significant implications for businesses, the workforce, and society. This primer grounds conversations about these implications by illustrating real-world examples of the new types of activities that robots were becoming able to perform. It describes the functionality limitations which dictated how earlier robots could be deployed and the advances in underpinning technology which have moved these boundaries and led to the current inflection point.

In late 2018, evidence emerged that many of Google's temporary help agency workers, vendors, and independent contractors ("TVCs") were unhappy with the company. TVCs, who reportedly made up 49.95% of Google's 170,000 person global workforce, had raised concerns of mistreatment, citing instances of pay inequity, social exclusion, and physical endangerment. "Flexible" workers, such as TVCs, were often seen as a key cog for Silicon Valley's IT companies: they made workforces scalable, they helped firms get access to specialized knowledge for temporary projects, and they boosted innovation by creating "knowledge spillovers" between firms. But, at the same time, many onlookers worried that flexible work arrangements were aggravating social inequality and making more jobs precarious. Google employees, major media outlets, and politicians demanded that the company change its policies on TVCs. One suggestion was that Google convert all of its TVCs to full-time status by early 2020. As tensions reportedly escalated between Google's workforce and its management team, some began to wonder if Google was still an employer of choice.

This case describes how caregiving responsibilities influence American employees, firms, and the broader economy. It details how sociodemographic trends in the late 20th century transformed the way that Americans balance their personal and professional lives, analyzing changes such as the evolving role of women in the economy, the rise of non-traditional households, the increasing cost and complexity of healthcare, and the aging and ailing of the U.S. population. The case then reflects on how such changes impact the productivity and profitability of the modern American company. It reviews survey data from employees and employers to understand how caregiving impacts individual careers and firms' profitability. The case concludes by asking readers to "rethink" how care might be provided by employers. It analyzes recent research on the return-on-investment of caregiving benefits, describes ways that firms are expanding their caregiving benefits coverage, and discusses the importance for managers to understand internal "care demographics" and promulgate a culture that supports caregiving.

By the late 2000s, rapid changes in the telecommunications industry forced AT&T's management team to take on a task that CEO Randall Stephenson called the "biggest logistical challenge" they had ever seen: retraining 100,000 workers by 2020. In 2012, internal company analyses found that AT&T's workforce would lack the skills it needed to fulfill emerging job requirements. AT&T responded by creating "Workforce 2020," a company-wide initiative that sought to address potential skill shortfalls. The initiative aimed to transform AT&T's workforce by implementing multiple changes, such as redesigning job roles, developing new educational curricula with Udacity, and incentivizing employees to retrain themselves for high-demand careers. Some gave high praise to the "Workforce 2020" model, going so far as to call it a new "social contract" between employers and employees. Others worried that the new program was systematically disadvantaging specific groups of workers. In 2018, AT&T rebranded Workforce 2020 to "Future Ready," signaling the company's commitment to retraining its workforce beyond 2020.

The founder of Osaro saw the potential of deep reinforcement learning to allow robots to be applied in a wide range of new applications. Osaro targeted warehousing, already a dynamic industry for robotics and automation, for its initial product - a system which allowed robotic arms to "pick and place" individual items into boxes for shipment to consumers. Despite receiving significant attention in the robotics space, the problem of universal "picking" had not been solved. Osaro believed deep reinforcement learning would provide the solution by allowing robots to handle the complexity involved in perceiving and grasping a wide range of objects. The case discussion will focus on the decision to choose the warehouse automation market, provide an overview of key machine learning concepts, and introduce students to some of the contours of competing in the machine learning space during the late 2010s. The case also introduces key concepts for thinking about how the combination of artificial intelligence and robotics will change work in the future.

In 2019, the retail and consumer product industries were undergoing a generational transformation. The consumer sector had gone through two other generational shifts in the past 50 years. During each shift, many legacy businesses lost share or outright failed. The businesses that survived and thrived had to grow new business models and competencies, while managing their pre-existing operations. The note explains the major transformations occurring to the global consumer sector in 2019 and how leaders reacted.

This primer provides a comprehensive exploration into the gig economy and how it is reshaping global business. It shows how the Uber driver, the freelancing programmer in India, and the independent corporate consultant are all different variants of the modern-day gig workers. In doing so, this document addresses the following questions: • What are gigs and who performs them? • What is the size of the gig economy? How big will it get? • What types of gig work are available, and how do they differ from one another? • What are major trends in the gig economy, and how could technology disrupt this space? • What are the key management and legal issues for companies that use gig workers? • What has been the recent legal and regulatory history of the gig economy? • How has the Covid-19 pandemic changed the gig economy?

Faced with intense competition from Amazon, in 2015 Walmart began a transformation of its operations and workforce. The goal was to create an omnichannel retail experience for customers that seamlessly joined online and offline shopping. This case explores Walmart's efforts to deliver this through investments in its workforce makeup and training, digital infrastructure, and automation technology.

In the face of a rapidly-changing economy, organiztions that wish to compete in the future of work must develop strategies for acquiring, retaining, and developing talent for their organizations. This primer reviews the major trends shaping jobs, workplaces, and worker demographics. It then discusses many of the largest weaknesses in traditional talent management systems. The case then closes by describing how firms can create "talent management pipelines." In this framework, firms' core asset - talent - is subjected to the same quality-management proceudres that revolutionized global supply chain practices in the 20th century.

Western Governors University (WGU) was a nonprofit institution of higher education whose online learning model served more than 100,000 students in 2019 and was scaling rapidly. President Scott Pulsipher wanted to expand WGU's reach to millions more with a plan called 10x Vision. 10x Vision called for scaling enrollment, creating new ventures to expand access to higher education that complement WGU's business model, and funding these ventures. Pulsipher believed WGU had a potential target market of 40 million people in the United States, as an increasing number of jobs required post-secondary education. How could WGU help these individuals participate in the higher education system and achieve upward mobility?

High-skilled immigration is dramatically transforming the tech sector in the United States. U.S. tech workers over age 40 have good reasons to be concerned. In addition to competing with greater numbers of skilled foreign workers, older tech workers are now also more likely than younger workers to lose their jobs when technical work moves overseas.

By December 2018, entrepreneur Joe DeLoss's fried chicken company, Hot Chicken Takeover, has opened three restaurants in Columbus, Ohio using an unconventional employment model that helps people with criminal records get back on their feet. DeLoss is proud of the supportive employment environment he has cultivated, but wonders how to scale it beyond Columbus.

This primer provides an overview of the implications of automation technology based on state-of-the-art "Artificial Intelligence" (AI) in the late 2010s: including the trends leading to the surge in AI, applications of AI categorized by the type of work performed, limitations of the technology, discussion about AI adoption, and key concerns the technology brought about.