I just wrote this for the UQ Business School Alumni publication:

Innovation is particularly important in turbulent economic times. As Scott Anthony points out in his upcoming book, The Silver Lining, nearly half of the current Fortune 500 companies were founded during recessions, including firms such as Bridgestone Tires, Digital Equipment Corporation, Enterprise Rent-A-Car, McKinsey & Co., and Whole Foods Market. The list encompasses everything from traditional manufacturing to cutting-edge electronics, from services to retail. It is important to understand now that one of the best possible responses to an economic downturn is to increase your innovation efforts, so that you are positioned well when things get better.

With the spread of initiatives such as open innovation, distributed Research & Development and customer-led innovation, the process of innovation has become increasingly dispersed over recent years. As we move from picturing the innovation process as consisting of a lone inventor working in a garage to these more distributed models of innovation, we need new ways to describe and measure the effectiveness of the process. In the current models of innovation, the connections that firms and people have throughout an industry value chain are at least as important as the quality of their ideas. Ideas have to be able to spread, and this is done through networks of communication. Consequently, if we want to understand the innovation process, we must understand the knowledge flows within firms and industries.

One way to do this is with network analysis. Social network analysis originated in the 1930s and was primarily used in psychology and sociology. Recent advances in network analysis have occurred in physics and economics, which has led to a broader adaptation of network thinking and measurement. Generally, when these tools are applied to business analysis they are referred to as ‘organisational network analysis’.

Organisational network analysis is used to measure intra- and inter-firm network structures. By asking people questions such as ‘who provides you with new ideas?’ or ‘who do you go to for help in solving problems?’ we can map the structure through which knowledge of different types flows through these networks. Once the network is mapped, there are numerous quantitative measures that are used to assess a network’s ability to assist information flow and knowledge co-ordination. The key issue is that increasing the number and density of connections usually makes it easier to communicate knowledge, but maintaining ties is costly – especially in terms of time. Therefore, managing an effective network becomes a question of trading off the cost of increasing the number of ties within the network against the benefits of doing so.

Looking at one network map can be informative, but this technique becomes really powerful when similar networks are compared with each other, or when the evolution of a particular network is mapped over time. Analysing a network at these levels allows us to devise interventions to improve the structure of the network. Current research strongly suggests that the structure of innovation networks has a substantial impact on the innovative performance of the people and firms within them.

Within the UQ Business School, we have several academics and students that use network analysis to analyse the innovation process. Professor Mark Dodgson, John Steen and Tim Kastelle won a grant from the Australian Research Council to measure innovation networks within project-based firms to assess the impact of network structures on innovation performance. We are working with a variety of firms on this project, and we have learned several important things already. One key finding is that the best possible structure for an innovation network will vary depending on the objectives of the network. Firms that are primarily focused on generating new ideas need to have relatively open networks, with dense connections between all of the various groups within the network. On the other hand, firms that are oriented towards executing ideas can have a network structure that is more hierarchical, with sparser connections.

As we learn more about these innovation networks within project-based firms, we will increase our knowledge about how to manage them most effectively. However, the importance of innovation network structure extends to all firms that are concerned with innovation performance. This in turn means that learning how to manage network structure and performance is becoming one of the key skills that firms and managers need to have. As the importance of innovation increases, so does the importance of knowing about innovation networks.

More information about organizational network analysis is included in ‘New Tools to Map and Manage Innovation Networks’ by John Steen, Sam MacAulay and Tim Kastelle in Inside the Innovation Matrix: Finding the Hidden Human Dimensions, published by the Australian Business Foundation.

Tim Kastelle is a Lecturer in Innovation Management in the UQ Business School. He provides a number of innovation related resources including talks, slides and a blog at the Innovation Leadership Network website.