Biology remains the most extensive and complex information network on the planet. This chapter examines the nature of biological networks, including their inherent stability and risks to their resilience. After a general introduction exploring networks and biological systems, this chapter reviews (1) the evolution of biological networks; (2) principles that govern biological networks; and (3) measures of stability, productivity, and efficiency in biological networks. The authors use examples from food (energy) transfer in rainforests and coral reefs, as well as the creation of a biological network through colonization in Darwin’s Finches of the Galapagos Islands. Research shows that while large biological networks are inherently unstable, some are more stable than others.

Although networks in key business areas such as communications, supply chains, R&D, and sales are designed to improve the flow of information, people, or goods, they can also be used to improve the “peripheral vision” of the organization. In this chapter, the authors examine how networks can be used by organizations to scan, sense, and adapt to new and important signals from the organization’s strategic environment beyond its core focus. The first part of the chapter emphasizes the importance of peripheral vision in helping organizations not being blindsided by threats while seeing new opportunities sooner. The authors examine some key obstacles to using networks to better mine the periphery for early insight. They then explore how extended networks can help the organization be a responsive open system adapting faster to changes in the environment. They examine to what extent network constructs such as centrality, hierarchy, self-healing, distributed intelligence, multihoming, and latency can be used to improve organizational networks for scanning the periphery. The last section explores some of the leadership challenges associated with using networks to detect weak signals sooner.

As terrorist organizations such as Al-Qaeda have been transformed from hierarchical organizations to more fluid networks, countering terrorism requires an understanding of networks. These networks evolve rapidly in response to actions to thwart them, leading to an ongoing struggle of terrorist and antiterrorist networks. In this chapter, Boaz Ganor examines the evolving threat of terrorist networks and network-based responses. As he notes, “it takes a network to beat a network.” He also examines direct and indirect implications for business organizations.

Artificial intelligence (AI) offers computational methodologies for modeling systems, which can be valuable in understanding networks. In this chapter, the author examines several types of applications of these methods in exploring how the behavior of individual agents leads to outcomes across networks. For example, he considers how one system, based on a Prisoner’s Dilemma that provides a higher payoff for players who don’t cooperate, can result in a surprising outcome in which cooperation dominates after many rounds of play. He also considers agent-based models--including turtles in a pond, showing discrimination effects; and sugar and spice trading, showing interactions through trading. Finally, he explores applications to ant colony optimization and swarming optimization of flocks of birds or schools of fish. He concludes that computational models offer important insights into networks, and the procedures used in modeling have a significant impact. The discussion also demonstrates that “networks matter,” affecting outcomes in sometimes unpredictable ways.

What can we learn about networks from ants, honeybees, and other animals with evolved social structures? The impact of information and communications strategies on network dynamics did not arrive with the emergence of computers, cell phones, and the Internet. This chapter describes communication networks selected from among many that have been studied in communities of nonhuman organisms. It explores the extent to which communication linkages have controlled the development of those networks. In some of those networks, developmental histories are manifest as evolved body plans and gender roles not represented in human communities. Many of those networks are founded on efficient exchange of information via pathways of which humans are almost fully oblivious.

This chapter provides an overview of social networks, the basic discipline from which ideas and terminology are drawn when characterizing popular phenomena such as “social networking” Internet sites like Facebook. The authors offer the reader a flavor of the theoretical and empirical research conducted by social network scholars since the 1930s. They explore how researchers have used social networks to generate and test economic, sociological, and organizational theories. They also examine broad insights from this research, as well as management implications in areas such as advertising, brands, loyalty, authenticity, and segmentation. The overriding message is that as power shifts from firms to social networks, companies have less control over their own destinies and need to pay more attention to networks.

Global networks of firms are rapidly replacing top-down, hierarchical organizations. Such networks, thanks to information technology and global communications systems, can respond to changes in international demand faster and more flexibly than rigid corporate organizations of the past. But by drawing together diverse cultures and individuals, these networks present new challenges to leaders. Traditional styles of leadership are not enough for this emerging environment. The kind of leadership style that leads to efficient execution in these global networks is different from the “do it and do it now” approach that might work in hierarchical organizations. Based on the author’s experience in the leading global accounting firm Touche Ross, serving as dean of the Wharton School, and heading his own corporate investment firm, this chapter discusses leadership in a networked, global environment.

Most companies realize the need to “look outside” for innovation. However, few have a clear understanding about how they can make such a shift toward network-centric innovation--an innovation strategy that is centered on external networks and communities. Managers need more than anecdotal success stories about externally focused innovation, and they need more specific guidance than the “one size fits all” prescriptions of open innovation. The authors argue that every firm needs to find its own roadmap for tapping the “Global Brain”--the creative potential of the world outside its four walls. There are many different approaches and opportunities for network-centric innovation, based on the nature of the innovation space and the nature of network governance. In this chapter, the authors present a framework for structuring the landscape of network-centric innovation. They describe four models of network-centric innovation--Orchestra, Creative Bazaar, Jam Central, and MOD Station--and outline how companies can select, prepare for, and pursue the approach that best fits their particular business and innovation context.

Managers often must make decisions that depend on decisions in other parts of the organization. These interactions create a network of interdependent choices and make strategizing difficult. In this chapter, the authors explore the intersection between organizing and strategizing. Motivated by real examples that run contrary to conventional wisdom, the authors examine how firms organize themselves to strategize well. In particular, they examine “premature lock-in”--how a firm’s strategizing efforts can become stuck in a web of conflicting constraints prematurely, before managers have explored a wide enough range of possibilities. A key role of organizing is to free strategizing efforts and encourage broad search. At the same time, organizing must ensure that strategizing efforts stabilize after the firm discovers an effective set of choices. Balancing search and stability, the authors argue, is a central challenge of organizing. They explore this challenge with an agent-based simulation that shows (1) how a change in organizational structure[md]for example, a shift from decentralization to integration[md]may reflect not a reversal of early mistakes but an effective sequence of organizing; and (2) why firms may benefit from unnecessary overlap between departments. They conclude that a period of decentralization and unnecessary overlap can be seen as organizational mechanisms to ensure the broad, early search that a firm needs in order to cope with interactions among strategic decisions.

As manufacturing supply chains have moved from vertically integrated factories to diffused networks, manufacturers need to manage complex, global webs of suppliers. In this chapter, Netessine examines supply networks in two industries in particular: automobiles, and aerospace and defense. He explores how different strategies and technologies have helped companies manage, organize, and capitalize on their networks of suppliers. He discusses how Japanese automakers have used partnerships to outperform their U.S. rivals, who have taken a more adversarial approach to their suppliers. He also considers how companies such as Airbus and Boeing have used technology to coordinate and integrate far-flung networks. While Netessine notes that the formal study of network-based supply chains is just emerging, he offers insights from research and practice on the growing importance of supply networks and strategies for managing them successfully.