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The term 'innovation' is particularly ambiguous and lacks either a single definition or measure. The UK Department of Trade and Industry's (DTI 1998) defined innovation as, 'the successful exploitation of new ideas'. Innovation is defined as the invention and commercialization of new products or services based on the application of technological and/or market knowledge (Hitt & Ireland, 2000)
A considerable literature has accumulated on the subject of innovation, which is widely seen as the basis of a competitive economy (Porter and Ketels 2003)
Quantifying, evaluating and benchmarking innovation competence and practice is a significant and complex issue for many contemporary organizations (Frenkel et al. 2000). An important challenge is to measure the complex processes that influence the organization's innovation capability, in order that they can be optimally managed (Cordero 1990).
Innovation is central to organisational growth and competitiveness (Terninko et al., 1998; Zairi, 1999; Tidd et al., 2001). It can result in changes to the products, processes or services that an organisation offers and on occasion all three together (Roberts, 2002).
CHALLENGES IN MANAGING INNOVATION
There are several challenges affecting the innovation process these occur from the idea generation stage to the commercialisation of the idea. This paper will consider a few of those challenges.
One of the major barriers to innovation is creativity. Large corporations lack the motivational capacity of small companies to nurture or motivate innovative people who have new, creative and break-through ideas. However, some companies rely upon historical experience to help them solve their problems and come with solutions (Marnix, 2006). Creativity in new product development can be approached in different ways, such as technology driven product development or in some cases companies have been successful through a thorough understanding of the customer needs (Mahesh & James, 2008, p.1021).
The level of priority given to the innovation process in an organisation affects its implementation and contributes to its achievement. Many organisations itemise innovation as part of its goals but without the necessary steps to put it into action (Wladawsky, 2008; Kuczmarski, Middlebrooks & Swaddling, 2000, p21).
Without fail risk aversion is the most frequent barrier to innovation. Most companies inform employees that they simply will not tolerate failure. The challenge of balancing the need for success with the need to accept risk can be daunting (Kuczmarski et al., 2000, p23). Knight (1971) suggests that innovation is risky because innovative actions aimed at the future always confront uncertainty. Innovation can create human resource risk. Henrik (2007) found that there was an ever-present risk of losing key people especially technically skilled personnel; this is due to the fact that certain projects maybe neglected to assist the companies in reaching their innovative goals. He also found that there was a risk of senior employees retiring with essential skills because of the pressure to train and learn new customs at a later stage in their careers than they expected.
According to Marnix (2006), managers cannot predict exactly the outcome and reactions of the market, resulting to uncertainty. Uncertainty makes it hard to obtain long-term internal support and resources. A framework was developed by Pearson is used for analysing and understanding uncertainty in the innovation process. The framework developed due to research in case studies in technological innovation with companies like 3M, Pilkington's float glass process and Sony's walkman, Pearson divided uncertainty into two: Uncertainty about ends and uncertainty about means (Trott, 2005, p.79)
USING MODELS TO MANAGE INNOVATION
Early models regarded innovation as a linear process driven either by technology push or market pull, later models recognised that success was highly dependent on coupling these two forces together with feedback loops (Tidd, 2006). Following further research on Japanese automobile companies, integrated or parallel models began to be developed that involved significant functional overlaps between departments and/or activities (Hobday, 2005, p. 124). Observations made during the 1980's and 1990's of an increase in corporate alliances, partnerships, R&D consortia and joint ventures of various kinds led to the systems integration and network models (Jim, 2007, p.228).
The linear models provide a justification for additional research and development spending by firms as this would lead to greater innovation and, in turn, faster economic growth. These models treat innovation as a sequential process that takes place in discrete stages (Hobday, 2005, p.124).
The linear models facilitate manager's creative ability, having the necessary technology and understanding the market needs allow for proper direction of research investments toward those needs and fosters the new product development in an organisation (Mahesh & James, 2008, p.1020)
According to Rothwell (1992), the fifth generation approach was brought about by time pressures on leading edge innovators. These models helps managers solve the challenge of isolation it emphasises on the learning that goes on within and between firms, suggesting that innovation was generally and fundamentally a distributed networking process.
In addition, Beer's System model consists of four levels or subsystems, each of which represents common and necessary elements of the model. The only requirement (and a necessary one) is that System I must produce something of value such that in its own right it could be a viable system all the other systems (system II, system III, and system IV) exist only to support the teams and groups that make up System I. According to him if system I does not create something of value to its marketplace or society, then there is no purpose for the others- and hence, by definition, no viable system. (Bean & Radford, 2001, p.41)
Allenna, (2008, p.646) notes that Beer's model aid managers in identifying the task of employees and how each system supports the previous system, making it possible for each system to perform its role although challenges arise in making systems cooperate during the process. Understanding the relationship between both systems is critical to managing innovation. System three provides operational direction, resolves conflicts, and allocates resources in cases where System two needs help or clarification.
Also, system four deals with a broader, more encompassing challenge than those addressed in system three and previous systems, which are distinctly operational. This system also facilitates managers with envisioning the future and acting so that threats can be avoided and opportunities seized (Bean & Radford, 2001, p.41).
Furthermore, other models include the waterfall model which is a staged model often used in product development processes where the steps to completion are very well known a well-defined project goal, timeline, and project plan. This model is often called a stage-gate model which provides a framework for development projects providing business models for product sales, a pool of experience, and engineering and manufacturing knowledge within the field to solve the majority of technical problems. At the end of each stage, the project moves through a gate, or review process, to the next phase (Jeremy, Mason, Kline & Bunch, 2005, p.4)
Dubinskas (1993, p.135), asserts that the funnel and vat models are very similar in nature but processes for product development are not necessarily strictly defined like in the waterfall model because there is a narrowing of potential possible solutions toward a known outcome. The vat model, compared to the funnel model, allows for more ambiguity through the development cycle.
These two models have a linear time component like the waterfall model. As time progresses one singular goal remains in mind and, eventually, possibilities are narrowed to an outcome originally defined at the projects initiation (Jeremy et al, 2005, p.4).
WEAKNESS OF THE MODELS
Vasconcellos, Bruno, Campanario, & Noffs, (2009, p.171) stated that models cannot provide rigid normative guidelines on how to produce efficacious constructs in innovation management. This implies that models may not essentially guarantee growth of the firm.
The linear models are an overly orderly 'rational' process implied; no recognition of alternative pathways; human decisions and choices underplayed and has been widely criticised by many observers for their linear, sequential nature and for oversimplifying the innovation process with little to say about what goes on within each stage (Hobday, 2005).
Coupling models are a major improvement on earlier models, and explicitly and/or implicitly attempt to address some of the weaknesses of the linear models because it allows feedback from the post-innovation diffusion stage is recognised and with it the need for firms to adapt new products to competition by improving quality and product features and reducing costs (Hobday, 2005).
Also there is little evidence to demonstrate that firms have adopted the fourth and fifth generation models (integrated, system integration & network models), or that adoption of information technology (IT) leads to the benefits proposed (Rothwell, 1992)
The Beer's system model may find each system competing in order to cut cost, an example of the advertising department in competition with the sales department because the support systems attempt to standardize service and thus cut costs to avoid conflict with their direct customers (Bean & Radford, 2001, p.43).