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CHAPTER V - Conclusion

Large organizations face challenges in becoming more agile and innovative, and in attempting to shift from pursuing scalable efficiency as the best path to profitability to a commitment to scaling learning as a means of adapting to new circumstances. In a more stable world, developing reliable mechanisms that minimize costs while maximizing outputs made sense. But in a “whitewater world” of intense global competition and constant, rapid change, such an approach can lead to rigidity that hampers the ability to respond to unexpected problems or opportunities. Rather than simply getting better and better at doing the same things over and over, organizations need to support continuous learning as a necessary condition for remaining competitive. In addition, organizations that offer environments that are conducive to learning are also better positioned to attract top talent that is increasingly scarce and valuable.

The recent emergence of “exponential enterprises”—companies that have sustained high-speed growth and shown that they have kept the ability to keep innovating even as they have grown—poses a challenge, and in some cases, a direct threat, to existing organizations that have been operating according to more traditional rules. Think, for example, of Tesla, founded in 2003, whose market value at the beginning of 2020 was greater than that of GM and Ford combined, or Amazon that in just over 25 years single-handedly reshaped the retail landscape. Most of the companies that have remained highly innovative in terms of developing new products and even entering (or inventing) new markets as they have continued to grow are relatively new firms that are digitally based or digitally enabled. The number of traditional enterprises that have successfully made the “big shift” toward scaling learning and increasing agility remains small.

Participants in this Aspen Roundtable offered a number of promising ideas about strategies that can help established enterprises to adapt more successfully to the new environment, as well as examples of organizations that have actually done so. For example, Autodesk’s AI-based Generative Design software is providing a new way of creating novel products with characteristics that can depart radically from previous designs, and represents a more creative way for humans to interact with technology. Tom Malone’s notion of superminds suggests that leveraging the power of people working together, especially when augmented by AI-based tools, can substantially increase the value of individual contributions. The BetterUp study of the importance of meaning in work and how meaning is supported or stymied by organizations also points to a number of strategies for improving corporate performance by understanding human needs. And perhaps most concretely, the work of Michael Arena provides a practical roadmap for creating mechanisms that can allow large enterprises to overcome the resistance to accepting new and untested ideas that is typically innate to an organization’s core functions and to reap the benefits of entrepreneurial groups or activities that often operate on the periphery of an organization. The key is creating a middle ground—an adaptive space—that can resolve the impedance mismatch between two disparate cultures.

These approaches and strategies share two common premises. First, there are enormous gains to be had by understanding the potential of intelligent machines to supplement and augment human abilities rather than being a simple substitute for human resources. Instead of abolishing jobs, by automating routine functions, AI-based tools can free up human capacity to take on higher-level challenges and create new value. Second, there is growing evidence of the power of looking at organizations not in terms of their formal structure but rather by using the techniques of network analysis to reveal how influence flows and how decisions get made within an organization, which may differ dramatically from titles and positions. This shift in perspective also highlights the importance of building organization’s social capital—the way in which people are connected with and collaborate with each other—as well as its human capital which is typically measured in terms of the capability of each individual worker.

Finally, a new workscape calls for new kinds of workers. Shifting the priority from seeking individuals with specific skills to recognizing the value of more fundamental capabilities could enrich corporate workforces, as could tapping into underutilized talent pools, including millions of workers who are qualified to do higher level jobs but lack the traditional credentials used by many employers. To prepare young people for this new world of work, institutions like USC’s Iovine and Young Academy are pioneering innovative models of education that cross traditional disciplinary lines. Rather than relying on a store of knowledge accumulated during their formal education—the kind of knowledge whose half-life is increasingly short—these graduates can expect to keep learning as they tackle new challenges and generate new knowledge. And as they find themselves confronting increasingly complex problems, they will need to develop a pragmatic imagination that is a fusion of the traditionally distinct practices of the sciences and the humanities.

It is likely that most large enterprises, particularly in their core functions, will continue to march to the music of the standardization of operations in the pursuit of scalable efficiency. But new rhythms and new kinds of music are beginning to be heard that could be harbingers of novel forms of collaboration of people working together with each other and with technology in new ways. This new kind of music may be coming mainly from the edges of organizations where creativity and experimentation are more accepted, but perhaps the most significant trend is the development of practical strategies for integrating them more effectively with core operations. The real breakthrough will be when the two styles of music learn to play well with each other.

 
 
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