Elsevier

Technovation

Volume 24, Issue 7, July 2004, Pages 553-561
Technovation

Complexity and learning behaviors in product innovation

https://doi.org/10.1016/S0166-4972(02)00121-9Get rights and content

Abstract

Successful product innovation and the ability of companies to continuously improve their innovation processes are rapidly becoming essential requirements for competitive advantage and long-term growth in both manufacturing and service industries. It is now recognized that companies must develop innovation capabilities across all stages of the product development, manufacture, and distribution cycle. These Continuous Product Innovation (CPI) capabilities are closely associated with a company’s knowledge management systems and processes. Companies must develop mechanisms to continuously improve these capabilities over time.

Using results of an international survey on CPI practices, sets of companies are identified by similarities in specific contingencies related to their complexity of product, process, technological, and customer interface. Differences between the learning behaviors found present in the company groups and in the levers used to develop and support these behaviors are identified and discussed. This paper also discusses appropriate mechanisms for firms with similar complexities, and some approaches they can use to improve their organizational learning and product innovation.

Introduction

Product Innovation is now accepted as a key requirement for business success. It is also generally accepted that product innovation is a process within firms and, therefore, can be managed by manipulating the influences at work (Johnston and Ireland, 1999). In the last fifteen to twenty years, companies have experienced considerable pressure to improve both the quality and speed of product innovation. One of the main consequences of this focus was the emergence of product innovation models almost totally focused on the management of the New Product Development (NPD) process. Integration among different phases of an NPD project and autonomy of the project team were considered synonymous with best practice product innovation. Concurrent engineering was thought to represent a long-lasting paradigm for product innovation management.

In the early 1990s, a new stream of studies emerged which enlarged these perspective. These studies demonstrated how focusing on single projects is not enough to sustain competition. Success is also dependent on exploiting synergy among projects; for example, by fostering commonality and reuse of design solutions over time (Wheelwright and Clark, 1992, Meyer and Utterback, 1993). In this perspective, attention progressively shifts from single projects to a project family (Meyer and Utterback, 1993, Sanderson and Uzumeri, 1995) and to the process of learning and knowledge transfer and consolidation (Imai et al., 1988, Lynn et al., 1999, Bartezzaghi et al., 1997a). Many of these studies, however, still considered product innovation as occurring only within the boundaries of the product development process. Downstream phases in the product life cycle were still important for innovation but only as long as they represented valuable sources of information or constraints that should be anticipated and considered during development (Clark and Fujimoto, 1991). Recent evidence suggests that other phases in the product life cycle may actually represent additional opportunities for direct contribution in product innovation. This is a consequence of increasing pressure for more rapid product development and decreased time to market. Several companies, especially in rapidly shifting environments, purposely release to market products that are not fully optimized, followed by a rapid almost continuous stream of enhanced releases (e.g., software industry).

Thus, the boundaries of product innovation are changing dramatically. Customer- and supplier-sourced information and opportunities coming in from the field installation and use phases are not only stored for informing next-generation product development projects, but can also provide valuable opportunities for product innovation within a product life cycle. These two dimensions are combined in the model of Continuous Product Innovation (CPI) proposed by Bartezzaghi et al. (1997b). CPI embraces not only NPD (Concept, Product, & Process design and Product launch), but also the subsequent phases in a product life cycle (Improvements in Manufacturing, Customization in Sales and Installation and Enhancements and Upgrading during Product Use). CPI also moves the traditional perspective from a single product to a product family, and thus includes all the interactions between the different products in the family. Hence, innovation may concern a product that is in its development phase, a product that has been already released to market, or a transfer of solutions between products. All of these interactions have a very strong potential for learning and innovation that can be exploited only through active design and implementation of mechanisms to enable the required transfer and consolidation of knowledge. Successful knowledge transfer and consolidation can be fostered by particular enablers whose effectiveness strongly depends on the actors involved and their influence on the process, and on the typology of knowledge that is managed.

Section snippets

Knowledge management in product innovation

Managing innovation in a CPI perspective implies shifting attention from the product to the process of knowledge creation, sharing, and transfer. The product becomes a vehicle for knowledge embodiment and transfer rather than the final outcome of a company’s efforts. The structure itself of the product should be conceived and designed differently in order to be flexible enough to enable knowledge exchanges and incorporate improvement throughout its life cycle. Fostering learning and knowledge

Complexity in product innovation

In rapidly shifting environments, Aram and Noble (1999) argue that information is often incomplete and ambiguous and the consequences of people’s actions are highly unpredictable. This is part of the organizational complexity that results from complexity in technologies, products, and customer interfaces as well as other sources in business organizations. In many product innovation processes the interface between employees and customers is becoming increasing complex as it requires detailed

Research methodology

Drawing on the literature in the broad areas of product innovation, knowledge management, and continuous improvement (CI), an exploratory model was developed to describe the CPI process in terms of a set of inter-related variables. This exploratory model for CPI was initially produced from a combination of the CI Maturity model (developed by Bessant et al., 1994) and the intra- and inter-project learning model proposed by Bartezzaghi et al. (1997a) with input from most of the significant

Analyzing complexity

In collecting data on aspects of complexity the company managers surveyed were provided with definitions of terms and specific Likert Scale statements to ensure they had a clear understanding of the concepts. The four aspects of complexity were investigated through the following statements and questions.

Product Complexity

How complex are the majority of your company’s products?

Likert response statements ranged from 1 to 5 with the two extremes being:

1. Very few distinct components are needed,

Analysis of levers and learning behaviors

An analysis of the levers used to encourage learning behaviors results in several useful findings. In particular, human resource management policy levers such as personnel rotation, departmental assessment and development plans, reward systems, and any type of empowerment programme were the least used by all companies regardless of the complexity of the company or the type of learning behavior. The only instance where low-complexity firms made substantially more use of a lever than

Conclusion

The need for high-complexity firms to firstly encourage learning behaviors is evident across the learning behaviors examined in this research. Furthermore, our results indicate that apart from minor variations, high-complexity firms used a greater variety of levers than low-complexity firms and in most instances they used levers more frequently than low-complexity firms. The most disturbing trend is the low use of human resource management policies (Lever 4) across all firms in this study. It

Ross Chapman has been employed at the University of Western Sydney, for the last 15 years, and is currently the Director, Research Management and Training for the College of Law and Business (which includes seven key Schools across these discipline areas). He is also Coordinator of the InCITe (Innovation & Continuous Improvement Technologies) Research Group. Ross has spent 10 years in private industry in technical, QC/QA and R&D management positions, working for several companies including ICI,

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    Ross Chapman has been employed at the University of Western Sydney, for the last 15 years, and is currently the Director, Research Management and Training for the College of Law and Business (which includes seven key Schools across these discipline areas). He is also Coordinator of the InCITe (Innovation & Continuous Improvement Technologies) Research Group. Ross has spent 10 years in private industry in technical, QC/QA and R&D management positions, working for several companies including ICI, Monsanto and North Broken Hill Holdings. Since 1985, he has taught and researched predominantly in the areas of Quality Management; Continuous Improvement; Operations Management; Innovation and Technology Management. He has also undertaken several large consultancy projects in the areas of quality systems development; TQM implementation; organisational change and process re-engineering. Ross is author or co-author of 3 books and over 45 journal and conference papers in the above areas, plus a further 15 articles on technical and scientific studies and 2 worldwide patents produced prior to 1987. He is currently Associate Editor or Editorial Review Board Member for several international journals including the International Journal of Entrepreneurship and Innovation Management (IJEIM), the TQM Magazine, and Managing Service Quality. He is a Foundation Member, and Member of the Board, of CINet (the Continuous Innovation Network - a global network established to bring together researchers and industrialists working in the field of Continuous Innovation—a new way of thinking about the integrated management and organisation of day-to-day operations improvement and learning, and innovation and change. See: http://www.continuous-innovation.net)

    Paul Hyland joined the Faculty of Business and Law at CQU in January 2002 as an Associate Professor in Management in the School of Management. He has an active interest in applied research that helps firms better understand their business environment and improve their management systems and processes. Paul is an associate member of the Australian Expert Group in Industry Studies (AEGIS). AEGIS’ research seeks to develop an understanding of industrial development and innovation that is critical to Australia’s future economic success and well-being. He was deputy Director of InCITe (Innovation and Continuous Improvement Technologies) Research Centre at the University of Western Sydney from 1996-2001, and has been a key researcher in several projects including: the CIMA (Continuous Improvement in Product Innovation Management) project, the Mapping CI maturity an AusIndustry funded project and the continuous improvement survey. The CI survey was also an international project and resulted in a widely acclaimed book. Paul is active in CINet (the Continuous Innovation Network), which is a global network of researchers and industrialists pursuing the underlying idea that in the near future businesses will rely more and more on individuals and on their commitment to learning and diffusing innovation at all levels and in all parts of an organisation. Paul is currently working on an ARC funded project with Prof Jane Marceau, and Dr Terry Sloan, this project investigates the role of knowledge-generating institutions and knowledge-intensive business services in industrial clusters in Australia. He is also working on knowledge management and management models in Australian manufacturing.. He has worked on consultancies for many organisations including Sydney Water, Surf Life Saving Australia Hawker de Havilland, MM Cables, Macarthur Region of Councils, Western Suburbs’ Rugby League Club Alstom IT and Pilkingtons.

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