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The learning outcomes are as follows: to understand why talent management is a vital component of a company’s broader strategy for long-term operational excellence; to understand the impact of generation, life stage and career stage on an employee’s professional needs, goals and expectations of their firm; to understand how organisational culture contributes, in this case, to ineffective people management practices; and to develop a talent management strategy: new policies, processes or practices that will address the identified issues and create a sustainable pipeline of talent.

This case finds the successful agro-processing firm Namib Mills in a state of internal tension in April 2019. As Namibia’s premier supplier of staple food products, Namib Mills is performing well in a struggling economy. Then yet, CEO Ian Collard is concerned that his senior management team is not exhibiting the kind of leadership and strategic management needed to take the company into the future. As Ian examines the issue further – with the aid of a report from an external consultant – he begins to see that the weaknesses of his senior managers, who are prone to micromanaging and poor communication, are part of a bigger issue of talent management in the firm. The junior employees, who are energetic and ready to innovate, are growing restless as they wait for career growth and promotion opportunities. The rising leaders in middle management are also struggling to break through. Ian must confront how organisational culture and generational diversity within this family-owned business have created talent management barriers and develop a strategy for sustainably developing employees into the leaders of the future.

This case is designed for a master’s level management program and is well-suited for courses that deal with organisational behaviour, people management or human resources management. Specifically, the case is aimed at students interested in talent management, generational diversity and organisational culture.

CSS 6: Human Resource Management.

From 2002 to 2011, coffee-machine manufacturer Keurig Incorporated had grown from a privately held company with just over $20 million in revenues and a plan to enter the single serve coffee arena for home consumers, to a wholly owned subsidiary of Green Mountain Coffee Roasters, Inc., a publicly traded company with net revenues of $1.36 billion and a market capitalization of between $8 and $9 billion. In 2003 Keurig had introduced its first At Home brewer. Now, approximately 25 percent of all coffee makers sold in the United States were Keurig-branded machines, and Keurig was recognized as among the leaders in the marketplace. The company had just concluded agreements with both Dunkin' Donuts and Starbucks that would make these retailers' coffee available for use with Keurig's specialized brewing system. The company faced far different challenges than when it was a small, unknown marketplace entrant. John Whoriskey, vice president and general manager of Keurig's At Home division, had to consider the impact that impending expiration of key technology patents and the perceived environmental impact of the K-Cup® portion packs would have on the company's growth. Whoriskey also wondered what Keurig's growth potential was, and how the new arrangements with Starbucks and Dunkin' Donuts could be leveraged to achieve it.

Sondologics, a manufacturer of video, audio, and gaming accessories products, was experiencing pricing and distribution problems in its channels. Numerous retailers were complaining about unfair price competition from unauthorized retailers, i.e., gray marketers, on standalone websites or Amazon's Marketplace, offering discounts of up to 30% off list price.

The company estimated that about 10% of its retail volume in the United States was being generated by unauthorized retailers. Compounding the problem, gray marketers and authorized retailers alike were selling at below-list prices, which violated the Sondologics MAP (minimum advertised pricing) policy.

Sondologics was considering numerous initiatives to address the MAP and gray-market problems, including retaining a third-party service to monitor pricing and distribution in the channel. Students are asked to develop recommendations that would promote sales while protecting the name-brand image and price points of Sondologics' products.

In late 2019, Dr. Hiroaki Kitano, the president and director of research at Sony Computer Science Laboratories (Sony CSL), had decided he would be stepping down from his position soon. Sony CSL, a small blue-sky fundamental research facility funded by Sony, had always operated on the strength of the trust between Sony's CEO and the lab's director. Sony had been hands-off in its management, leaving Kitano to hire, fire, fund, and evaluate the lab's researchers and project portfolio at his own discretion. Now that he was stepping down, however, he worried that Sony CSL could not withstand his departure. Kitano wanted to make a transparent plan for the organization's future before he handed off Sony CSL to his successor. That plan involved three key decisions. First, what should be the optimal structure and governance of Sony CSL? Should it maintain its independence and autonomy, or should it align more closely with Sony's business priorities? Second, how could Sony CSL scale its impact on Sony and society at large, given its small size? Finally, should Sony CSL establish some standard methods of measuring project success and strength of the portfolio? In making these decisions, Kitano wanted to ensure that he preserved the unique culture that had allowed Sony CSL to pursue path-breaking research and innovation.

In the fall of 2014, Chad Kartchner, senior manager of marketing and product management at Honeywell Aerospace (HA), pondered how technology could transform the way aircraft were maintained. He had heard a lot of buzz about cognitive analytics, an artificial intelligence term referring to the use of computer models and algorithms to simulate human thought through self-learning systems, data mining, pattern recognition, and natural language processing. The sheer volume of parts and the time-sensitive nature of repairs in the aviation industry made it complicated to identify problems and address them quickly.

Kartchner contemplated the options for updating HA's ground-based maintenance system. Should he emulate HA's state-of-the-art on-board system for an entire aircraft or try something new? Emulating the on-board system, which HA developed internally, would be an easy sell to leadership given internal buy-in and satisfaction with the on-board system, but he contemplated new approaches because he did not want to overlook rapidly emerging technologies. The latter could include crowdsourced features that leveraged the abundance of knowledge among HA's customers' technicians or a cognitive analytics approach. Even if he could persuade leadership to try a new cognitive analytics approach, should HA partner with an established entity or work with a relatively unproven startup who promised lower cost, better features, and quicker turnaround to develop a new system?

Students will step into the shoes of Kartchner as he leads the internal discussion on whether and how to tap into the benefits of cognitive analytic solutions for Honeywell Aerospace and its customers.