At this stage in the process, both creativity and persistence are needed to move from a potentially good idea to a workable design. One product has commemorated the persistence of its design engineers in its company name. In 1953 the Rocket Chemical Company set out to create a rust-prevention solvent and degreaser to be used in the aerospace industry. Working in their lab in San Diego, California, they made 40 attempts to work out the water displacing formula, so they called the product ‘WD-40®’, which literally stands for Water Displacement, 40th attempt. Originally used to protect the outer skin of the Atlas Missile from rust and cor- rosion, the product worked so well that employees kept taking cans home to use for domestic purposes. Soon after, the product was launched with great success into the consumer market.
In fact, it’s not just persistence that is important in the innovation process – failure itself may be beneficial if organisations can spot potential. Sometimes, when a design fails, it represents an opportunity to rethink the concept itself. For example, Pritt Stick, the world’s first glue stick, was originally intended to be a super-glue, but product testing proved unsatisfactory. Henkel changed the product concept and successfully marketed the product as ‘the non-sticky sticky stuff’. Similarly, a group of chemists working for the pharmaceutical giant Pfizer developed a new drug called ‘Sildenafil’. Originally intended to help individuals with hypertension (high blood pressure) and angina, clinical trials of the drug proved unsuccessful, though doctors noticed a side effect of penile erection. Seeing the potential of this ‘failed’ innovation process, Pfizer marketed the drug as Viagra, for erectile dysfunction. In just two years, sales of Viagra had topped $1 billion and the product dominated the market.
Case example
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Prototyping and final design
Product prototypes include everything from clay models to computer simulations. For more service-dominant offerings, prototyping may involve the actual implementation of the service on a pilot basis. For example, a retailer may organise the piloting of new services packages in a small number of stores in order to test customers’ reaction to them. It may also be possible to ‘virtually’ prototype. For example, when designing a mass-transport hub, the behaviour and flow patterns of customers can be modelled using sophisticated simulation models, with impressive visuals that help to understand the effects of different layouts and volumes. In such simulations, safety is always an important objective, as would be efficient movement through the area. And although the means of prototyping may vary, the principle is always the same:
do whatever one can to test out the innovation prior to delivery.
Alpha and beta testing
A distinction that originated in the software development industry but has spread into other areas is that between the alpha and beta testing of a product or service. Most software prod- ucts include both alpha and beta test phases, both of which are intended to uncover ‘bugs’
(errors) in the product. Not surprisingly, alpha testing comes before beta testing. Alpha test- ing is essentially an internal process where the developers or manufacturers (or sometimes an outside agency they have commissioned) examine the product for errors. Generally, it is also a private process, not open to the market or potential customers. Although it is intended to look for errors that otherwise would emerge when the product is in use, it is, in effect, performed in a virtual or simulated environment, rather than in ‘the real world’. After alpha testing, the product is released for beta testing; that is, when the product is released for testing by selected customers. It is an external ‘pilot-test’ that takes place in the real world (or near-real world, because it is still a relatively small, and short, sample) before commercial production. By the time a product gets to the beta stage most of the worst defects should have been removed, but the product may still have some minor problems that may only become evident with user participation. This is why beta testing is almost always performed at the user’s premises without any of the development team present. Beta testing is sometimes called field testing, pre-release testing, customer validation, customer acceptance testing or user acceptance testing.
3.4 Diagnostic question: Are the resources for developing product and service innovation adequate?
For any process to operate effectively, it must be appropriately designed and resourced. Innovation processes are no different, so there are some strategic resourcing issues to consider – how much capacity to devote to innovation, how much of the innovation activity to outsource and what kinds of technol- ogy to use in the innovation process.
Is there sufficient innovation capacity?
Capacity management involves deciding on the appropriate level of capacity needed by a pro- cess and how it can be adjusted to respond to changes in demand. For innovation, demand is the number of new designs needed by the business. The chief difficulty is that, even in very large companies, the rate of innovation is not constant. This means that product and service design processes are subjected to uneven internal ‘demand’ for designs, possibly with sev- OPERATIONS PRINCIPLE
For innovation processes to be effective they must be adequately resourced.
innovation is needed. This poses a resourcing problem because the capacity of an innovation activity is often difficult to flex. The expertise necessary for innovation is embedded within designers, technologists, market analysts and so on. It may be possible to hire-in some expertise as and when it is needed but much design resource is, in effect, fixed.
Such a combination of varying demand and relatively fixed design capacity means some organisations are reluctant to invest in innovation processes because they see it as an underuti- lised resource. A vicious cycle can develop, in which companies fail to invest in innovation resources simply because many skilled design staff cannot be hired in the short term, resulting in innovation projects overrunning or failing to deliver appropriate solutions. This, in turn, may lead to the company losing business or otherwise suffering in the market-place, which makes the company even less willing to invest in innovation resources.
Should all innovation activities be done in-house?
Just as there are supply networks that produce services and products, there are also supply networks of knowledge that connect suppliers and customers in the innovation process; this is sometimes called the ‘design (or development) network’. Innovation processes can adopt any position on a continuum of varying degrees of design engagement with suppliers, from retain- ing all the innovation capabilities in-house, to outsourcing all the innovation work. Between these extremes are varying degrees of internal and external capability. Figure 3.11 shows some of the more important factors that will vary depending on where an innovation process is on the continuum. Resources will be easy to control if they are kept in-house because they are closely aligned with the company’s normal organisational structures, but control should be rel- atively loose because of the extra trust present in working with familiar colleagues. Outsourced design may give the impression of greater control, because of the use of penalty clauses for delay. Costs may also be seen in different ways depending on whether design is outsourced.
External innovation tends to be regarded as a variable cost. In-house innovation is more of a fixed cost. One inhibitor to open innovation is the fear of knowledge leakage. Firms become concerned that experience gained through collaboration with a supplier of design expertise may be transferred to competitors. There is a paradox here. Businesses usually outsource design primarily because of the supplier’s capabilities that are themselves an accumulation of specialist knowledge from working with a variety of customers. Without such knowledge ‘leakage’, the benefits of the supplier’s accumulated innovation capabilities would not even exist.
Figure 3.11 Some implications of the in-house–outsourced continuum In-house innovation
capability
Outsourced innovation capability
Close, but loose
Control of resource Distant, through contracts
Strong Weak in the short term,
potentially stronger in the long term
Familiarity
High Accessibility Low/limited
Fixed Cost Variable
Small Risk of knowledge leakage Great (potentially)
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Open-source innovation – using a development community
The implication of the model of innovation that we presented in Figure 3.9 is that innovation is largely an internal affair, with ideas and their subsequent development into marketable prod- ucts and services happening exclusively inside the organisation. However, in recent years there is evidence that some firms are more likely to widen their scope to include resources from out- side in the innovation process. This may be formalised and could include a wide community of individuals, suppliers, customers, research institutes (such as universities) and even commercial rivals. This is generally referred to as ‘open innovation’.9 And ‘openness’ can work in two ways.
What is sometimes called ‘inbound’ open innovation is where an organisation deliberately pro- motes external input from collaborators. ‘Outbound’ open innovation is where organisations permit unexploited ideas to go outside for others to use.
Arguably, the best-known examples of open innovation have come from the software indus- try. An open community, including the people who use the products, develops many of the software applications that we all use. If you use Google, Wikipedia or Amazon, you are using open-source software. The basic concept of open-source software is simple: large communities of people around the world, who have the ability to write software code, come together and produce a software product. The finished product is not only available to be used by anyone or any organisation for free but is regularly updated to ensure it keeps pace with the necessary improvements. The production of open-source software is very well organised and, like its commercial equivalent, is continuously supported and maintained. However, unlike its com- mercial equivalent, it is absolutely free to use. Over the last decade, the growth of open source has been significant with many organisations transitioning over to using this stable, robust and secure software. Open source has been the biggest change in software development for dec- ades and is setting new open standards in the way software is used. The open nature of this type of development also encourages compatibility between products.
More generally, open innovation has several other benefits:
• The exposure of an innovation can allow customers and competitors to explore alternative markets or applications for innovations.
• Products and services can be refreshed if partners are able to exploit underlying processes and technology.
• It helps establish an innovation community that can support customer engagement.
Crowdsourcing
Closely related to the open sourcing idea is that of ‘crowdsourcing’. Crowdsourcing is the pro- cess of getting work, or funding, or ideas (usually online) from a crowd of people. Although in essence it is not a totally new idea, it has become a valuable source of ideas largely through the use of the internet and social networking. For example, Procter & Gamble, the consumer products company, asked amateur scientists to explore ideas for a detergent dye whose colour changed when enough had been added to dishwater. Similarly, the LEGO Ideas platform allows users to submit their ideas for new LEGO sets. They can also vote and offer feedback for ideas that have been submitted. If an idea gets over 10,000 votes it is reviewed by LEGO, who then work with the idea’s originator. Other uses of crowdsourcing involve government agencies asking citizens to prioritise spending (or spending-cutting) projects.
Is appropriate technology being used in the innovation process?
Technology has become increasingly important in innovation activities. Simulation software, for example, is now common in the design of everything from transportation services through to
the actual product or service. Designers can work through the experience of using the service or product and learn more about how it might operate in practice. They can explore possibili- ties, gain insights and, most importantly, they can explore the consequences of their decisions.
Innovation technologies are particularly useful when the design task is highly complex, because they allow developers to reduce their own uncertainty of how services or products will work in practice. Technologies also consolidate information on what is happening in the innovation process, thus presenting a more comprehensive vision within the organisation.
Generative design
Like almost all aspects of operations and process management, product and service innovation is not immune from the increased use of technology. One particularly useful technology is the use of ‘generative design’ as an approach to exploring alternative designs. It involves design- ers specifying important design goals, parameters and performance requirements, after which generative design software explores all the possible permutations of a solution, from which it generates design alternatives. More advanced versions use artificial intelligence to learn from