NILab
Network Innovation Lab
Where do good ideas come from?
From idea generation to value creation
Leveraging external connections to bring new knowledge inside the organization and innovate
Increasing the global innovation footprint: moving to where new knowledge is and back
Micro environments in the broader organization
The social structure of innovation
Giuseppe Soda
Scientific Director
Generating innovations is the result of a collective effort based on individuals’ ability to contribute, integrate, transform the knowledge they have to obtain something new. Surprisingly however, the ongoing debate surrounding the generation of innovation and new technologies focuses primarily on technical aspects leaving its “social underpinnings”, that is, what individuals collectively do to achieve it, relatively unexplored.
The main objective of this research project is to study what drives the development of innovation by bringing the human component back into the picture. Historically, research on industrial economics has suggested that, holding everything constant, higher investments in R&D translate in greater innovative outcomes. In our study of innovation and new technology development we would like to reverse this paradigm and ask instead, holding the amounts invested in R&D constant, what makes an organization more innovative?
We seek to find the answer to this question by studying how scientists, researchers, managers, and engineers, pool together their knowledge, expertise, know-hows and backgrounds towards the overriding objective of inventing new products, services and technologies.
From idea generation to value creation
Pier Vittorio Mannucci
Scientific Directorr
The path that leads from initial concept to final product can be long and perilous. Even in organizations that pride themselves on rapid iteration and experimentation, many truly novel ideas either stall out at some point in development or lose their originality along the way. How do we help creative ideas successfully complete the journey from idea generation to value creation?
How can we prevent ideas from dying “an early death”? Answering these questions requires understanding the different needs of the four stages of the idea journey generation, elaboration, championing and implementation –and identifying the collaboration and communication patterns and networking behaviors that better match these needs.
Moreover, it requires understanding how organizations can help individuals identifying these “best patterns” and adjusting their collaborative behaviors as an idea progresses in its journey.
Leveraging external connections to bring new knowledge inside the organization and innovate
Marco Tortoriello
Scientific Director
To generate innovations, organizations rely primarily on the knowledge that they produce internally. Often, however, scientific or technological advancements that become available outside the boundaries of the organization, hold the potential to significantly increase the ability to innovate. Particularly, when these external inputs are successfully merged with the knowledge the firm already has. Accessing and leveraging external knowledge, can significantly boost innovative capabilities of organizations.
However, how is external knowledge recognized and accessed? Are collaborations with other research institutions or other organizations enough? What facilitates the integration of external and internal knowledge? Formal and informal connections with the external environment are a powerful means to increase innovativeness.
Using the network paradigm to study where, with whom, and how these relationships form and evolve can significantly increase our understanding of how knowledge is used to innovate
Where do good ideas come from?
Alessandro Iorio
Assistant Professor
Scientific Director
A well-establishing finding in academic research is that good ideas do not generally originate from the hard work of lone geniuses, but rather they are a consequence of a social system of actors that amplify (or stifle) each other’s creativity.
The key question, therefore, is the following: how to design social network structures that can optimize groups’ ability to generate good ideas? In this respect, social network analysis has emerged as an extremely powerful approach that can help us tackle questions of this sort. For example, we know that social brokers, that is, people who sit at the interface of unconnected groups have an advantage when it comes to generate good ideas. In a similar vein, we know that “small-world” systems―networks with highly cohesive subgroups of people in which the average distance between people is very short—have generally a positive impact on innovation.
This is because the presence of multiple subgroups allows a number of distinct ideas to emerge, which can then potentially flow from one subgroup to another, thus facilitating cross-fertilization and recombination between them.
Yet, structures of this sort do not automatically translate into superior outcomes. Indeed, unlike electric networks in which switches allow bits of information to move effortlessly, the flow of ideas and information does not occur automatically.
This brings a number of follow-up questions: How can we maximize subgroups’ ability to generate different, valuable ideas? And how can we make sure that such ideas move freely among clusters? Studying informal networks allows us not only to understand the structural underpinnings of good ideas, but also to devise potential interventions that organizational decision-makers can put in place to maximize the risk of “productive accidents.”
Increasing the global innovation footprint: moving to where new knowledge is and back
Marco Tortoriello
Scientific Director
A typical debate in innovation management is about centralization vs. decentralization of R&D activities. On the one hand large, centralized R&D laboratories offer scale and scope economies, critical mass, opportunities for synergies, easier access to resources, proximity with key decisions makers, etc.
On the other hand, moving R&D activities directly where a new technology is developing and emerging setting up smaller local operations, can give a first mover advantage, securing access to key human capital or technology, allowing to act faster, and to be more focused, away from the rigidities of central planning. Both models have advantages, both have drawbacks.
Hence, it is rare for large global companies to rely exclusively on one or the other. It is often a matter of degree rather than an either/or. This begs the question, how do we integrate the agility and focus of decentralized research activities, with the critical mass of knowledge and applications that are produced centrally? And how do we bring the novelty generated in the periphery of an R&D network closer to the core, while bringing the best practices developed in the core, closer to the periphery?
For a hub-and-spoke R&D structure to work well, understanding how knowledge, expertise and capabilities travel from the core to the periphery and back becomes critical to reap the advantages that each model has, avoiding duplications and inefficiencies. Studying the formal and informal networks among different laboratories can allow us to identify best practices about the internal structuring of R&D activities to increase innovative capabilities.
Micro environments in the broader organization
Ronald Stuart Burt
Scientific Director
The work environment of an organization is a combination of the many micro work environments that individual managers create around themselves. At one extreme are managers who create an open environment of energy, excitement, growth, and innovation. At the other extreme are managers who create a closed environment of obedience to numbing routine. To be sure, these micro environments are shaped in part by the kind of work a manager does, but past research shows that micro environments vary widely between managers doing similar kinds of work — and work quality varies with them, for the individual manager, subordinates, and colleagues.
Research has been limited by the lack of precise, continuous data on these micro environments.
This project is a search for reliable, productive network metrics on micro environments using an exploration of 20 million email messages and HR data, over four and a half years, for 800 employees in an organization going through substantial change.