Getting Innovation to Scale – Networks (part 2 of 3)

Through scaling, smart movers can quickly build substantial market shares – or define entirely new markets. To help understand scaling we have divided it into three main areas: Emergence, Networks, and Waves. This article is on Networks, the second in a series of three.

Part one of this series explored Emergence: a collective behavior; the phenomenon of patterns becoming apparent in complex systems of interacting agents. The first article can be found here.

We operate in business and societal environments that are complex, dynamic, and uncertain. This environment provides new challenges and at the same time great opportunities through scaling – which we have defined as the successful introduction of innovations that spread rapidly in non-linear fashion, seemingly self-propelled and with relatively little effort, resulting in an outsized impact.

Applying these new scaling techniques can be significantly more cost effective than traditional advertising or lobbying activities.

We have identified two dozen practical scaling tactics that can be designed into the concept during the concept development stage.

Successfully developing and introducing innovations is the lifeblood of any enterprise and requires a special kind of leadership: innovation leadership. Innovation leaders guide their organizations and employees to produce more creative ideas, products, services and solutions. They also recognize that for successful introductions, scaling needs to be addressed in the design phase, when new concepts are developed. We have identified two dozen practical scaling tactics that can be designed into the concept during the concept development stage. This should lead to accelerated diffusion and adoption upon introduction. Our research draws on scientific approaches such as Complexity TheoryBehavioral Economics and Systems Theory.  We have divided the topic into three main areas: Emergence, Networks, and Waves. Within these three areas, we have identified different tactics for leaders to benefit from scaling. We call these scaling frames. This article focuses on our seven Network scaling frames.

Networks spread ideas – if they have the right structure

Human behavior is strongly affected and shaped by the way people are connected together. Our life is full of networks. There are physical networks, as the neural network of brains, the electrical power grid, the phone call network, the internet and the World Wide Web. There are activity networks, as the civil aviation network or the global trade network. And there are social networks, which are defined by all different types of communities to which people can belong: friendship networks, professional networks, etc. It is this latter category of networks that is most relevant for scaling: both the physical version and the online version of social networks.

Innovation leadership leverages social networks for scaling. Possibly the most important aspect of networks when thinking of scaling is diffusion, e.g., the spreading of new products and technological innovation, but also of temporary trends of information and of social behaviors. Innovation leadership aims to spread new ideas rapidly through a web of connected nodes and overlapping networks. To do so successfully, it is important to understand the structure of a social network you may be targeting to leverage.

When a social network has centrally located clusters, messages or ideas also spread easier.

Each network consists of nodes and links that connect the nodes. In social networks, the nodes are people, the links are conversations through communication channels, such as email messages, telephone calls or tweets. Nodes with many connections are ‘hubs’ and thus can serve as ‘bridges’ to nodes with lower connectivity. When innovation leadership wants to use networks for diffusion of messages or new ideas, it works better in networks that have larger variance in connectivity, which means that some nodes have few links and others have many links. The intuition is that even a limited number of nodes with many links allow the transmission of the diffusion, working as ‘bridges’ between regions of nodes with lower connectivity. When a social network has centrally located clusters, messages or ideas also spread easier.

Networks also have components, basically independent sub-networks in the network with higher connectivity amongst the nodes. The largest component of many interlinking nodes – often called the ‘giant component’ – is often surrounded by smaller ‘isolated’ components of interlinking nodes. In general, it holds that beyond a certain base level of connectivity (when each node has on average more than one link) the higher the connectivity of the nodes becomes, the faster and more exponential the growth of the diffusion will be. The chances of the isolated components becoming connected to the centrally located ‘giant component’ increase. The size of the largest component continues to grow exponentially with previously isolated smaller component linking and thus the number of nodes that can be reached efficiently as well. This effect has important consequences for innovation leadership. One innovation leadership tactic for successful diffusion is providing network members in smaller isolated sub-networks surrounding the largest sub-network with platform, tools and motivation, to become more connected – odds are they will connect to the largest component. This is discussed in the frames 2.4, 2.5, 2.6 below. The overall effect is a highly non-linear and steep growth curve of messages or ideas spreading.

Another tactic as explained in frame 2.2 below is carefully identifying to whom the message or idea is seeded. If innovation leadership can spot the “right” people to start its launching campaign, the diffusion should go through much more easily. The diffusion will be larger if the seeds are hubs, meaning that they have many links – the super-connectors. Also, the more central the hub in the networks is, and the shorter the average path from node-to-node (popularized as “degrees-of-separation”), the easier diffusion will take place. A limited number of nodes (people) with many links can work as “bridges” between regions of nodes with lower connectivity. The example of transportation networks is meaningful: large airports, the aviation hubs, a few years ago were perceived as the fundamental means of transmission of the SARS epidemic.

The final notion to consider for diffusion in a network is clustering. For the adoption of a new product, as long as the adoption decision depends not just on personal preferences and evaluation, but also on a kind of “social” or “peer” effect, high clustering in a network makes diffusion easier. A consumer adopts with a probability that increases with the number of neighbors adopting. This notion is behind frames 2.1 and 2.3.

The seven scaling frames of Networks presented in this article provide innovation leadership with practical perspectives on how new products can spread rapidly leveraging the properties of networks.

2.1 Target hubs and amplifiers

Identify networks and communities, virtual and real-world, that align to your mission in some way. Target individuals and groups within them who control or support the message flow (hubs), and those who are able to magnify and accelerate the spread of network messages and asks (amplifiers).

2.2 Activate networks

Design your communications to convey the actions and behaviors you desire and to encourage people to spread them through their professional and personal networks. Ask people explicit to share your message, and make any other requests simple to execute.

2.3 Jump across networks

Actively make connections and foster social and professional interactions with individuals with whom you are only remotely associated and who have moved through different careers, industries, or academic disciplines. Network asks, messages, or actions passed through these individuals can spread extremely quickly across geographic and industry boundaries.

2.4 Infect with ideas

Design concepts to spread between people and across boundaries like a virus. Define the nature of the contact that is most likely to “infect” a large number of people within a network – channel, duration, repeated exposure, etc. Consider how the infection can be passed on, for example by people displaying visible signs that lead to discussions and further promotion.

2.5 Leverage network effects

Design your concept to incorporate network effects, whereby the overall value of the network and the utility to individuals increase with every additional user in a non-linear way. Do not forget that the initial uptake needs to reach a critical mass of users to make the concept viable.

2.6 Develop a community

Create and nurture a community focused on your core concept, supporting enthusiasts as well as passive followers, and adding both an enlarged experience of the concept and a group dynamic. Invest in community software, community managers, and community events to add substance to the community and to continue deriving benefits over time.

2.7 Gamify

Use games, simulations, rewards, and the sense of fun in general to offer an engaging platform for users to learn, process information, connect with others, or make decisions. Engage with people on an emotional and playful level, even for more serious topics.

The seven scaling frames on Networks offer innovation leaders different mechanisms and tactics to favorably influence the emergence of successful outcomes in systems characterized as networks. The right conditions and structures can fundamentally spread a new ideas or product in a non-linear fashion. Similarly, small design efforts of how to seed the product or which hubs to target can have an outsized diffusion as a result, both in terms of how far it spreads and how fast it scales.

In addition to this article Scaling 2/3 Networks, there are two more broad categories of Scaling Frames to consider: Scaling 1/3 Emergence and Scaling 3/3 Waves. These are explored in complementary articles.

  •  Emergence. Emergence is essentially collective behavior; it refers to the phenomenon of patterns becoming apparent in complex systems of interacting agents. Innovation leadership can look to make use of emergent collective behavior by designing openness into a system and designing rules for interaction, which allow successful behavior to surface and spread. We have distinguished 13 separate tactics or scaling frames that we have clustered under Emergence. More on this topic can be found in this article.
  • Networks. Innovation leadership can take advantage of the properties of networks, the structures and technology supporting networks, and the social conditioning that exists with network members to scale their innovations. We have identified seven distinct Networks scaling frames.
  • Waves. Waves are a naturally occurring phenomenon in complex systems. It is one thing for innovation leadership to be prepared to watch for waves and catch them when they appear. It is another thing altogether to create, nurture and sustain waves that are steered in the direction of your entrepreneurial vision. We have six Waves scaling frames.

Mark Turrell and Menno van Dijk recently published a book on the topic of Scaling. Read more about the book: Scaling – Small Smart Moves for Outsized Results.

By Menno van Dijk, Berend-Jan Hilberts, Mark Turrell

About the authors

Menno Van Dijk, Co-Founder and Managing Director of THNK. Before that he was former Director at McKinsey & Company, former board member of New Venture, NEMO and other organizations.

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With a background is in business strategy and innovation, Berend-Jan Hilberts has consulted internally and externally with companies on generating new ideas and creating new platforms for growth.

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Mark Turrell was nominated as a Technology Pioneer by the World Economic Forum and in 2010 became a WEF Young Global Leader. He is the Founder of Orcasci, a strategy and marketing agency focused on the science of spread, helping companies and NGOs design programmes to scale and spread products, ideas, and behavioural change

Sources

  • Barabasi, A.-L., & Reka, A. (1999). Emergence of Scaling in Random Networks. Science 286, 509 (1999), 286(286), 1-11.
  • Frenken, K., Izquierdo, L. R., Zeppini, P., Frenken, K., Izquierdo, L. R., & Zeppini, P. (2012).
  • Recombinant Innovation and Endogenous Technological Transitions Retrieved from http://cms.tm.tue.nl/Ecis/Files/papers/wp2012/wp1201.pdf
  • Scharmer, C. O. (2003). The Blind Spot of Leadership, (April), 1-11.
  • West, G. B. (2010). Focus on rethinking scale. Alliance, 15(2), 32-33.
  • This article was originally published on THNK.org.
  • Main image: Group of business people from Shutterstock.com
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