The term innovation means a new way of doing something. It may refer to incremental, radical, and revolutionary changes in thinking, products, processes, or organisations. A distinction is typically made between Invention, an idea made manifest, and innovation, ideas applied successfully (Mckeown, 2008). In many fields, something new must be substantially different to be innovative, not an insignificant change, e.g., in the arts, economics, business and government policy. In economics the change must increase value, customer value, or producer value. The goal of innovation is positive change, to make someone or something better. Innovation leading to increased productivity is the fundamental source of increasing wealth in an economy.
Innovation is an important topic in the study of economics, business, technology, sociology, and engineering. Colloquially, the word "innovation" is often used as synonymous with the output of the process. Since innovation is also considered a major driver of the economy, the factors that lead to innovation are also considered to be critical to policy makers.
Those who are directly responsible for application of the innovation are often called pioneers in their field, whether they are individuals or organisations.
While innovation typically adds value, innovation may also have a negative or destructive effect as new developments clear away or change old organizational forms and practices. Organizations that do not innovate effectively may be destroyed by those that do. Hence innovation typically involves risk. A key challenge in innovation is maintaining a balance between process and product innovations where process innovations tend to involve a business model which may develop shareholder satisfaction through improved efficiencies while product innovations develop customer support however at the risk of costly R&D that can erode shareholder return.
Innovation has been studied in a variety of contexts, including in relation to technology, commerce, social systems, economic development, and policy construction. There are, therefore, naturally a wide range of approaches to conceptualizing innovation in the scholarly literature. See, e.g., Fagerberg et al. (2004).
Fortunately, however, a consistent theme may be identified: innovation is typically understood as the successful introduction of something new and useful, for example introducing new methods, techniques, or practices or new or altered products and services.
"An important distinction is normally made between invention and innovation. Invention is the first occurrence of an idea for a new product or process, while innovation is the first attempt to carry it out into practice" (Fagerberg, 2004: 4)
It is useful, when conceptualizing innovation, to consider whether other words suffice. Invention – the creation of new forms, compositions of matter, or processes – is often confused with innovation. An improvement on an existing form, composition or processes might be an invention, an innovation, both or neither if it is not substantial enough. It can be difficult to differentiate change from innovation. According to business literature, an idea, a change or an improvement is only an innovation when it is put to use and effectively causes a social or commercial reorganization.
Innovation occurs when someone uses an invention or an idea to change how the world works, how people organize themselves, or how they conduct their lives. In this view innovation occurs whether or not the act of innovating succeeds in generating value for its champions. Innovation is distinct from improvement in that it permeates society and can cause reorganization. It is distinct from problem solving and may cause problems. Thus, in this view, innovation occurs whether it has positive or negative results.
A convenient definition of innovation from an organizational perspective is given by Luecke and Katz (2003), who wrote:
Innovation typically involves creativity, but is not identical to it: innovation involves acting on the creative ideas to make some specific and tangible difference in the domain in which the innovation occurs. For example, Amabile et al (1996) propose:
For innovation to occur, something more than the generation of a creative idea or insight is required: the insight must be put into action to make a genuine difference, resulting for example in new or altered business processes within the organization, or changes in the products and services provided.
A further characterization of innovation is as an organizational or management process. For example, Davila et al (2006), write:
From this point of view the emphasis is moved from the introduction of specific novel and useful ideas to the general organizational processes and procedures for generating, considering, and acting on such insights leading to significant organizational improvements in terms of improved or new business products, services, or internal processes.
Through these varieties of viewpoints, creativity is typically seen as the basis for innovation, and innovation as the successful implementation of creative ideas within an organization (c.f. Amabile et al 1996 p.1155). From this point of view, creativity may be displayed by individuals, but innovation occurs in the organizational context only.
It should be noted, however, that the term 'innovation' is used by many authors rather interchangeably with the term 'creativity' when discussing individual and organizational creative activity. As Davila et al (2006) comment,
The distinctions between creativity and innovation discussed above are by no means fixed or universal in the innovation literature. They are however observed by a considerable number of scholars in innovation studies.
Innovation = Creativity * Risk Taking
Using this inventory it is possible to plot on axis where individuals fit on their Risk Taking and Creativity.
Joseph Schumpeter defined economic innovation in The Theory of Economic Development, 1934, Harvard University Press, Boston.
According to Regis Cabral (1998, 2003):
Market outcome from innovation can be studied from different lenses. The industrial organizational approach of market characterization according to the degree of competitive pressure and the consequent modelling of firm behavior often using sophisticated game theoretic tools, while permitting mathematical modelling, has shifted the ground away from an intuitive understanding of markets. The earlier visual framework in economics, of market demand and supply along price and quantity dimensions, has given way to powerful mathematical models which though intellectually satisfying has led policy makers and managers groping for more intuitive and less theoretical analyses to which they can relate to at a practical level. Non quantifiable variables find little place in these models, and when they do, mathematical gymnastics (such as the use of different demand elasticities for differentiated products) embrace many of these qualitative variables, but in an intuitively unsatisfactory way.
In the management (strategy) literature on the other hand, there is a vast array of relatively simple and intuitive models for both managers and consultants to choose from. Most of these models provide insights to the manager which help in crafting a strategic plan consistent with the desired aims. Indeed most strategy models are generally simple, wherein lie their virtue. In the process however, these models often fail to offer insights into situations beyond that for which they are designed, often due to the adoption of frameworks seldom analytical, seldom rigorous. The situational analyses of these models often tend to be descriptive and seldom robust and rarely present behavioral relationship between variables under study.
From an academic point of view, there is often a divorce between industrial organisation theory and strategic management models. While many economists view management models as being too simplistic, strategic management consultants perceive academic economists as being too theoretical, and the analytical tools that they devise as too complex for managers to understand.
Innovation literature while rich in typologies and descriptions of innovation dynamics is mostly technology focused. Most research on innovation has been devoted to the process (technological) of innovation, or has otherwise taken a how to (innovate) approach. The integrated innovation model of Soumodip Sarkar goes some way to providing the academic, the manager and the consultant an intuitive understanding of the innovation – market linkages in a simple yet rigorous framework in his book, Innovation, Market Archetypes and Outcome- An Integrated Framework.
The integrated model presents a new framework for understanding firm and market dynamics, as it relates to innovation. The model is enriched by the different strands of literature – industrial organization, management and innovation. The integrated approach that allows the academic, the management consultant and the manager alike to understand where a product (or a single product firm) is located in an integrated innovation space, why it is so located and which then provides valuable clues as to what to do while designing strategy. The integration of the important determinant variables in one visual framework with a robust and an internally consistent theoretical basis is an important step towards devising comprehensive firm strategy. The integrated framework provides vital clues towards framing a what to guide for managers and consultants. Furthermore, the model permits metrics and consequently diagnostics of both the firm and the sector and this set of assessment tools provide a valuable guide for devising strategy.
Innovation by businesses is achieved in many ways, with much attention now given to formal research and development for "breakthrough innovations." But innovations may be developed by less formal on-the-job modifications of practice, through exchange and combination of professional experience and by many other routes. The more radical and revolutionary innovations tend to emerge from R&D, while more incremental innovations may emerge from practice – but there are many exceptions to each of these trends.
Regarding user innovation, rarely user innovators may become entrepreneurs, selling their product, or more often they may choose to trade their innovation in exchange for other innovations. Nowadays, they may also choose to freely reveal their innovations, using methods like open source. In such networks of innovation the creativity of the users or communities of users can further develop technologies and their use.
Whether innovation is mainly supply-pushed (based on new technological possibilities) or demand-led (based on social needs and market requirements) has been a hotly debated topic. Similarly, what exactly drives innovation in organizations and economies remains an open question.
More recent theoretical work moves beyond this simple dualistic problem, and through empirical work shows that innovation does not just happen within the industrial supply-side, or as a result of the articulation of user demand, but through a complex set of processes that links many different players together – not only developers and users, but a wide variety of intermediary organisations such as consultancies, standards bodies etc. Work on social networks suggests that much of the most successful innovation occurs at the boundaries of organisations and industries where the problems and needs of users, and the potential of technologies can be linked together in a creative process that challenges both.
When an innovative idea requires a new business model, or radically redesigns the delivery of value to focus on the customer, a real world experimentation approach increases the chances of market success. New business models and customer experiences can’t be tested through traditional market research methods. Pilot programs for new innovations set the path in stone too early thus increasing the costs of failure.
Stefan Thomke of Harvard Business School has written a definitive book on the importance of experimentation. Experimentation Matters argues that every company’s ability to innovate depends on a series of experiments [successful or not], that help create new products and services or improve old ones. That period between the earliest point in the design cycle and the final release should be filled with experimentation, failure, analysis, and yet another round of experimentation. “Lather, rinse, repeat,” Thomke says. Unfortunately, uncertainty often causes the most able innovators to bypass the experimental stage.
In his book, Thomke outlines six principles companies can follow to unlock their innovative potential.
Thomke further explores what would happen if the principles outlined above were used beyond the confines of the individual organization. For instance, in the state of Rhode Island, innovators are collaboratively leveraging the state's compact geography, economic and demographic diversity and close-knit networks to quickly and cost-effectively test new business models through a real-world experimentation lab.
Once innovation occurs, innovations may be spread from the innovator to other individuals and groups. This process has been studied extensively in the scholarly literature from a variety of viewpoints, most notably in Everett Rogers' classic book, The Diffusion of Innovations. However, this 'linear model' of innovation has been substantinally challenged by scholars in the last 20 years, and much research has shown that the simple invention-innovation-diffusion model does not do justice to the multilevel, non-linear processes that firms, entrepreneurs and users participate in to create successful and sustainable innovations.
Rogers proposed that the life cycle of innovations can be described using the ‘s-curve’ or diffusion curve. The s-curve maps growth of revenue or productivity against time. In the early stage of a particular innovation, growth is relatively slow as the new product establishes itself. At some point customers begin to demand and the product growth increases more rapidly. New incremental innovations or changes to the product allow growth to continue. Towards the end of its life cycle growth slows and may even begin to decline. In the later stages, no amount of new investment in that product will yield a normal rate of return.
The s-curve is derived from half of a normal distribution curve. There is an assumption that new products are likely to have "product Life". i.e. a start-up phase, a rapid increase in revenue and eventual decline. In fact the great majority of innovations never get off the bottom of the curve, and never produce normal returns.
Innovative companies will typically be working on new innovations that will eventually replace older ones. Successive s-curves will come along to replace older ones and continue to drive growth upwards. In the figure above the first curve shows a current technology. The second shows an emerging technology that current yields lower growth but will eventually overtake current technology and lead to even greater levels of growth. The length of life will depend on many factors.
Programs of organizational innovation are typically tightly linked to organizational goals and objectives, to the business plan, and to market competitive positioning.
For example, one driver for innovation programs in corporations is to achieve growth objectives. As Davila et al (2006) note,
In general, business organisations spend a significant amount of their turnover on innovation i.e. making changes to their established products, processes and services. The amount of investment can vary from as low as a half a percent of turnover for organisations with a low rate of change to anything over twenty percent of turnover for organisations with a high rate of change.
The average investment across all types of organizations is four percent. For an organisation with a turnover of say one billion currency units, this represents an investment of forty million units. This budget will typically be spread across various functions including marketing, product design, information systems, manufacturing systems and quality assurance.
The investment may vary by industry and by market positioning.
One survey across a large number of manufacturing and services organisations found, ranked in decreasing order of popularity, that systematic programs of organizational innovation are most frequently driven by:
These goals vary between improvements to products, processes and services and dispel a popular myth that innovation deals mainly with new product development. Most of the goals could apply to any organisation be it a manufacturing facility, marketing firm, hospital or local government.
Research findings vary, ranging from fifty to ninety percent of innovation projects judged to have made little or no contribution to organizational goals. One survey regarding product innovation quotes that out of three thousand ideas for new products, only one becomes a success in the marketplace. Failure is an inevitable part of the innovation process, and most successful organisations factor in an appropriate level of risk. Perhaps it is because all organisations experience failure that many choose not to monitor the level of failure very closely. The impact of failure goes beyond the simple loss of investment. Failure can also lead to loss of morale among employees, an increase in cynicism and even higher resistance to change in the future.
Innovations that fail are often potentially ‘good’ ideas but have been rejected or ‘shelved’ due to budgetary constraints, lack of skills or poor fit with current goals. Failures should be identified and screened out as early in the process as possible. Early screening avoids unsuitable ideas devouring scarce resources that are needed to progress more beneficial ones. Organizations can learn how to avoid failure when it is openly discussed and debated. The lessons learned from failure often reside longer in the organisational consciousness than lessons learned from success. While learning is important, high failure rates throughout the innovation process are wasteful and a threat to the organisation's future.
The causes of failure have been widely researched and can vary considerably. Some causes will be external to the organisation and outside its influence of control. Others will be internal and ultimately within the control of the organisation. Internal causes of failure can be divided into causes associated with the cultural infrastructure and causes associated with the innovation process itself. Failure in the cultural infrastructure varies between organisations but the following are common across all organisations at some stage in their life cycle (O'Sullivan, 2002):
Common causes of failure within the innovation process in most organisations can be distilled into five types:
Effective goal definition requires that organisations state explicitly what their goals are in terms understandable to everyone involved in the innovation process. This often involves stating goals in a number of ways. Effective alignment of actions to goals should link explicit actions such as ideas and projects to specific goals. It also implies effective management of action portfolios. Participation in teams refers to the behaviour of individuals in and of teams, and each individual should have an explicitly allocated responsibility regarding their role in goals and actions and the payment and rewards systems that link them to goal attainment. Finally, effective monitoring of results requires the monitoring of all goals, actions and teams involved in the innovation process.
Innovation can fail if seen as an organisational process whose success stems from a mechanistic approach i.e. 'pull lever obtain result'. While 'driving' change has an emphasis on control, enforcement and structure it is only a partial truth in achieving innovation. Organisational gatekeepers frame the organisational environment that "Enables" innovation; however innovation is "Enacted" – recognised, developed, applied and adopted – through individuals.
Individuals are the 'atom' of the organisation close to the minutiae of daily activities. Within individuals gritty appreciation of the small detail combines with a sense of desired organisational objectives to deliver (and innovate for) a product/service offer.
From this perspective innovation succeeds from strategic structures that engage the individual to the organisation's benefit. Innovation pivots on intrinsically motivated individuals, within a supportive culture, informed by a broad sense of the future.
Innovation, implies change, and can be counter to an organisation's orthodoxy. Space for fair hearing of innovative ideas is required to balance the potential autoimmune exclusion that quells an infant innovative culture.
The OECD Oslo Manual from 1995 suggests standard guidelines on measuring technological product and process innovation. Some people consider the Oslo Manual complementary to the Frascati Manual from 1963. The new Oslo manual from 2005 takes a wider perspective to innovation, and includes marketing and organizational innovation. Other ways of measuring innovation have traditionally been expenditure, for example, investment in R&D (Research and Development) as percentage of GNP (Gross National Product). Whether this is a good measurement of Innovation has been widely discussed and the Oslo Manual has incorporated some of the critique against earlier methods of measuring. This being said, the traditional methods of measuring still inform many policy decisions. The EU Lisbon Strategy has set as a goal that their average expenditure on R&D should be 3 % of GNP.
The Oslo Manual is focused on North America, Europe, and other rich economies. In 2001 for Latin America and the Caribbean countries it was created the Bogota Manual
Many scholars claim that there is a great bias towards the "science and technology mode" (S&T-mode or STI-mode), while the "learning by doing, using and interacting mode" (DUI-mode) is widely ignored. For an example, that means you can have the better high tech or software, but there are also crucial learning tasks important for innovation. But these measurements and research are rarely done.