The Cyclic Nature of Innovation: Connecting Hard Sciences with Soft Values: Volume 17

Innovation requires change, i.e. change in the way we think and the way we act. These changes may be small or big. Fig. 1 schematically shows our business development view on this matter (Berkhout, 2005).

Sustained modern economic growth is less than 300 years old. Most of the human experience has been a Malthusian one – brief periods of relative plenty for some, followed by collapse due to famine, drought, or other exogenous factors, or due to internal factors such as war or excessive population growth that outstripped the resource base. In all cases, general productivity growth was short term and minimal and each society's well-being was tied inexorably to the condition and stock of natural resources.

In order to understand today's innovation models, we need to look at the historical development of these models. This chapter describes the succession of the R&D management generations and discusses the innovation models in each generation (Section 2). The shortcomings of these models and the requirements for improved versions are summarized in Section 3. In Section 4, we will explain why new models of innovation should be circular and multi-layered.

Innovation models should give insight into the success and failure of generating new business. Considering the high degree of complexity, it is proposed to view such models at different levels of abstraction. It is also proposed to make feedback an essential property of the process model. The result of this line of thinking is an integrated environment for the creation of new business. In this multi-layer environment, innovation is positioned as the interconnecting activity between the development of new technology and business, and the involved process model is represented by a circle of change.

Donald Stokes’ approach to map the names of prominent scientists onto adiagram showing their impact on fundamental science and applied science is adopted and expanded to illustrate the dynamic interactions of the four nodes of the Cyclic Innovation Model (CIM). Tagging names of prototypical role models onto the four nodes and cycles of CIM increases the meta-level understanding of the fundamental concepts depicted by this innovation model. It also serves as a tool to validate the completeness of the model.

The duration of an innovation process, from new idea to new business, may take many years. This makes it necessary to incorporate a vision of the future. The Cyclic Innovation Model (CIM) shows that aspects such as multiplicity (looking at multi-fold futures) and multidimensionality (looking at different aspects of the future) should be taken into account. Looking at the different actors involved in CIM, the future should be researched with an open mind (meaning that the transition path to the future should be kept wide open) and different time horizons should be taken into account.

The ability to predict the market potential of product concepts at an early stage is of great importance to many organizations. In terms of Cyclic Innovation Model (CIM), this activity occurs in the lower right part of the cycle. Standard approaches to predict the market potential like concept testing and need assessment, and the assumptions that are required to use these methods will be described in Section 2. A problem is that these assumptions are usually not met in the case of products based on breakthrough technologies. Alternative approaches will be described in Section 3. How market analysis can benefit from using CIM will be discussed in the last section.

Intellectual property (IP) and the legal protection thereof are of paramount importance in innovation. IP plays an important role in each of the four fundamental nodes of the Cyclic Innovation Model (CIM). While no one can claim property rights on knowledge in the science node, intellectual property rights (IPR) are essential in the development of new technology-based products (technology node and product node), because it prohibits competitors who did not incur the cost of R&D from unauthorized copying.

In the telecommunication industry we observe trends such as unbundling, convergence, and new business models. To accelerate innovation, mobile telecommunication companies are more and more working together with companies from other industrial sectors (such as media and IT). The Cyclic Innovation Model helps to understand all those activities in this rather chaotic business environment. This particularly applies to mobile telecommunication companies that are developing mobile data innovations (such as Lucio). All those innovations are steps along a transition path towards a wireless future.

Thixomolding® refers to a new technology to mold a magnesium alloy in elaborate forms. The actors that introduced this technology in the Netherlands first operated on a regional level. With the support of the Cyclic Innovation Model (CIM), the innovation system was able to evolve by developing new innovations, although initially Class 1 and 2 type of innovations. In the future, the Thixomolding® innovation system will compete on a European scale, and it is expected that products will be developed for many different industries.

The Cyclic Innovation Model is applied to a new process for the production of fine chemicals and pharmaceuticals using a combination of ionic liquids and supercritical carbon dioxide. This multi-value innovation combines economic growth with environmental concerns and social value. The most important obstacles in the implementation of this new technology are the successful life cycle management of current production plants, the linearity of current innovation thinking, and a perceived high risk of adoption.

We think that problems 2 – 5 can be explained by realizing that current innovation models fail to bring in the business context of innovation in an explicit manner (see Figs. 2.11 and 2.2). Innovation should lead to new business and, therefore, innovation models should be an integral part of some business development framework. Stand-alone innovation models are not very useful in the practice of business.