Queen Essays

Source: How We Make Stuff Now: Turn Ideas into Products That Build Successful Businesses, 1st Edition ISBN: 9781260135855 Authors: Jules Pieri

2. WHERE DO GREAT IDEAS COME FROM?

No company or client wants to produce products for yesterday, or even today. They want "Wayne Gretzky" outcomes—to create products that can fulfill where the demand is going. Every product originates from an idea. And great product ideas often exhibit an uncanny prescience for solving a problem, like the "I just want to make a single cup of coffee" solution provided by Nespresso. Sometimes breakthrough products create brand-new behavior the way Fitbit did when it made it a social norm to count steps. Other times new products simply add joy and beauty to a routine activity, just as Method did when it gave pump soap products a contemporary makeover.

So how are these ideas born? How do people who are not professional designers get started?

During my years working at Playskool, advising the company on a product line and packaging overhaul, a trial attorney friend told me he could never do my job, saying, "Sitting down to face a blank screen or piece of paper every day would scare the crap out of me. How do you make something from nothing? Where do you get your ideas?" He envisioned my workday as a mysterious process of actively seeking stop-in-your-tracks lightning bolt inspirations. I told him I could never imagine succeeding in his job, which I simplified down to "getting paid to argue in front of strangers all day." I told my Perry Mason friend that when you are employed to generate good ideas, you develop a definitive and predictable process for being creative. Today people call that process "design thinking."

I will save you the trouble of researching design thinking as an abstract concept and boil it down to its essence:

Identifying opportunity. What is the business or customer area that needs attention? In the case of Fitbit, founders James Park and Eric Friedman saw an opportunity to help people improve their fitness with newfound access to individualized performance data. This breakthrough was made possible because of the advent of new, cost-effective miniaturized sensors.

Goals and constraints. Setting goals for a new product is an iterative process as the entrepreneur learns more via research. But a product like Fitbit could start with a list such as: "This solution must cost less than $100. It has to be convenient to carry at all times. It must be water resistant. It must not interfere with normal daily activities."

Research. Research involves studying the three Cs: customers, competition, and (internal) capabilities, as well as general cultural, social, technological, or natural trends that could influence the business or inform the product. For Fitbit the potential customer need was fairly vast: people who want to set and meet fitness goals. Investigation at the time of Fitbit's founding in 2007 would have yielded very little relevant competition, as existing solutions were cumbersome and required a customer to manually stitch together data from devices such as a pedometer, heart rate monitor, or calorie counter. Products that utilized the Internet to process data were barely emerging, such as SimpliSafe, an apartment security system that eliminated much of the cumbersome nature of existing services. Beyond technology advances, the founders could easily see that people were increasingly drawn to online communities and the gamification of ordinary activities—a big trend to draft off.

Ideation. This involves conceiving and quickly visualizing various concepts (you often see a ream of exciting raw sketches highlighted in the visual history of a product). Some founders draw their own concepts, while others engage a designer at this stage, but fancy renderings are not advised at such an early step. The original Fitbit was a thumb-sized clip, but it is likely that all manner of devices were conceived, such as necklaces, bracelets, credit card–sized devices to fit in a wallet, shoe inserts, and the like. Even if many of these ideas were not technically or economically feasible, the goal during ideation is to cast as wide a net as possible.

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Rough prototyping and feedback. Rapidly and roughly prototyping concepts to get customer feedback comes next. Early- stage prototyping for a device like the Fitbit could be as simple as a nonfunctional foam version of a clip presented alongside a static set of graphic screenshots to show the type of data the device could collect. In other words, early prototypes help express the idea to a potential user without needing to be fully functional. Fitbit would have been looking for feedback on core interest in these new capabilities, as much as for feedback on form and function.

Advanced prototypes. The entrepreneur repeats the last two steps enough times to commit to testable prototypes that help her lock down on a single idea. Advanced prototypes usually look like the real deal, even if they are not fully functional. But the more functional, the better.

There is nothing in that process that requires long walks on the beach, consuming hallucinogenics, or locking yourself in a dim room with Mozart playing. It's a rigorous and disciplined process you can do right in the middle of a fluorescent-lit office, or in your kitchen, or at a coffee shop. Anytime, anywhere.

There are two deep secrets to this process. Success lies not just in a designer's ability to generate concepts. First, great ideas are entirely hostage to the information and stimulation the designer (or aspiring Maker) gathers to provoke their gestation. In other words, it's all about the goals and research. You can think of this almost like cooking. The better the ingredients, the better the food. Ideas need to be fueled by great inputs.

For example, I was part of a consulting firm team that engineered the famous Reebok Pump shoe, which allowed a user to inflate an internal chamber for cushioning and support purposes. After its wild success we were subsequently engaged to propose ideas for shoes that could help a person jump higher. The research project included a huge range of athlete interviews and observations and then exploration of springy or reactive materials, mechanical systems, and natural systems. It even included the study of what enables the best rebounders on Earth—fleas—to jump 100 times their body height. (That would be like a person jumping over the Eiffel Tower.) Only after that wide-ranging exploration did our engineer, Eric Cohen, sit down and start sketching ideas.

The second critical building block to generating successful ideas actually precedes the research described above. As Eric explains it: "The first step is to define the problem you're trying to solve very clearly. The Harvard Business School professor Clayton Christensen calls this 'the job to be done.' This clarity then narrows down the field of possible solutions and brainstorming activities. If you just start brainstorming, you lack context for deciding which concepts are best. If you can clearly articulate the problem, often the solutions seem to magically appear and become obvious. But getting to that point of clarity is the real challenge."

In the case of step one, "identifying opportunity," Grommet Makers do not approach this step like an established business would. Why? Because they don't have an actual business just yet. They aren't noticing sales slipping, doing heavy R&D that yields opportunity, or responding to competitive threats. They are just going about their lives. As such, they tend to stumble into either (1) a problem that vexes them and needs solving or (2) an emerging technology or behavior that inspires them to improve it or apply it in a new area.

In fact, only 10 percent of Grommet Makers have any professional experience in the area where they end up building a product. In an interesting parallel, in my capacity as an entrepreneur in residence at Harvard Business School, I observe that a great number of the students pursue the well-known degree and credential as a giant, and admittedly expensive, career reset button. Makers often experience their businesses in much the same way. They throw over or work out of established careers to pursue an idea. The business is going to be epic in terms of effort and opportunity cost compared to other easier ways they might have collected a salary. But the idea becomes an itch that must be scratched, whatever the cost. The idea is often the fuel for all of the late nights, financial sacrifice, and occasional skepticism of friends and family.

CASE STUDIES

BluApple

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Prior to the 1960s and during cold winter months, produce was often stored in warehouses that were heated with kerosene. The heat kept the fruits and vegetables from freezing before they were shipped to market. As heat sources evolved, these warehouses became equipped with electrical heating systems. With that change came a surprising consequence for growers and commercial produce shippers: the fruit wasn't ripening. It turns out that kerosene gives off ethanol gasses, which help speed the ripening process.

Without the kerosene, fruit could last a bit longer in transit and in warehouses. And with the discovery of the unique relationship between kerosene and produce ripening came an understanding of how to slow the ripening process as well. If the ethanol gasses released from produce could be captured or absorbed, fruit sitting in a bin or box would ripen less slowly. So the cucumbers, lettuce, and peaches sitting in your fridge could last a bit longer if only the ethanol gas could be absorbed by something other than that same fruit or vegetable.

You may have seen those "eggs" that go inside produce bins, the ones that keep fruit and veggies fresher longer. Eric Johnson was part of the company that developed the egg-shaped gadgets that worked the magic. Inside the egg was a combination of naturally occurring elements that slowed the absorption of the ethanol gases and therefore slowed the ripening process.

The only downside was that the egg wasn't very popular; the shape was throwing off consumers. People were returning the eggs to the store, thinking they had mistakenly bought an Easter decoration. But Johnson knew there had to be interest in the actual function of the egg. He had hoped that the company would reconsider its design, but when that didn't happen, Johnson and his now cofounder and partner, Timmy Chou, started BluApple.

Johnson says he knew the components of the product—potassium permanganate, a bit of water, and volcanic ash—were essential: "It's a product everyone needs and no one knows about." Johnson and Chou designed their gadget as a small blue apple "because it's odd enough that it stands out. Your mind doesn't come across that very often," says Johnson. It's something people easily remember, and it certainly can't be confused with an actual fruit. Plus, Johnson says, "the apple is an iconic symbol, one that represents life, freshness, and growing."

Launched in 2009, BluApple is now in major retail stores such as the Container Store, Albertsons, and Bed Bath & Beyond, and in more than a thousand smaller shops that sell housewares. They sell nationwide in the United States, as well as in Canada and Australia. Johnson says the company is expanding internationally. "We do best where people are actually shopping," says Johnson, explaining that when people are rushing through a grocery store with a quick list they are less likely to stop and browse and consider a new product. Online sales are also growing. Johnson says the company started with just the simple BluApple and has grown to include other produce storage solutions. "We're looking for things in the same space; that is fruit and veggie storage," adds Johnson. The company is working on four other products to launch in the next few years.

Peeps

A self-described serial entrepreneur, Daniel Patton was working in the optic industry and knew about a carbon-based technology developed by NASA that was responsible for cleaning the camera lenses at the International Space Station. In space, it's impossible to use sprays because of zero gravity, low temperatures, and the fact that cloths often damage lenses. The technology became essential as standard cleaning options were a liability at best. If you destroy a lens in space, you're in pretty big trouble.

Working on product development within the optical industry, Patton knew there had to be a way to take the same technology developed by NASA and bring it to the everyday eyeglass wearer. There hadn't been a lot of changes in the optical cleaning world in about 30 years. After much research into how the carbon technology worked and how it could be translated into the consumer market, Peeps was born: it cleans glasses and lenses perfectly without any scratches, smudges, or the need for wiping away a wet solution.

The product was launched at the end of 2016 and is sold in nearly 30 countries and is considered the number one eyeglass cleaner sold in optical practices in the world, according to Patton. "The industry really supports us," he adds. Peeps is in more than 12,000 stores and thousands of Walmart Vision Centers.

The company is working with luxury brand eyewear companies for co-branding opportunities. And they can customize the Peeps product to match fashion glasses in texture and design. "Our revenue is in the 10s of millions annually," says Patton. The company later added mobile cleaning products: a small device to clean the screens of iPhones, laptops, iPads, and more. While Peeps has been exploding, Patton says the team is working more on marketing the newer device cleaner.

Nuheara

David Cannington had been an executive at Sensear, a hearing technology company that specialized in industrial headsets, the sort that looks like earmuffs with large coverings over each ear and a bulky headband. Only this one was unique because the headset blocked out loud industrial noise and amplified the relevant sound. The technology enabled people in industrial zones to remain situationally aware because dangerous and distractingly loud noises were filtered out.

The main customers of this product were mining, oil, and gas companies. The users were people in rugged, high-noise environments. "When we put this on people's heads, they could not believe it," says Cannington. "They said, 'I want to wear this in my personal life.' "

That's where the idea for Nuheara originated. Cannington quickly left his first company and created a new one, based in Australia and San Francisco. "We really did start the company to make an impact on people's lives." To him, it was just about selling to different consumers for a different reason. Nuheara consumers are primarily people with mild hearing loss, and the product enables them to separate speech from background noise. The other audience is people who simply love new technological innovations and want great earbuds.

"It makes an immediate improvement in your life," says Cannington. "There's a pretty compelling wow aspect." This was something Cannington saw firsthand while working on industrial headsets, so he knew the interest and the appeal of the product was there. He simply wanted to convert that big, bulky headset into earbuds, a complicated process. The first prototype for Nuheara was made in January 2016, and the product went to market in 2017.

CASE STUDIES

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Nuheara launched with one earbud and by April 2018 had brought to market a second version. The latest product allows users to do their own hearing assessment, and the buds adjust accordingly. There is an internal calibration system. "It's a huge evolution in the sophistication of wireless earbuds," says Cannington.

The company has taken off, and Nuheara is sold around the world, including in well-known shops such as Brookstone and Best Buy and through Amazon. The earbuds are also available through audiology clinics, and Cannington says they are constantly in talks to help expand into new markets. As for growth, the founder thinks constantly about ways to improve technology and user experience. "We have to continue to bring new hearing experiences to our audience."

CASE STUDIES

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chApter 2

Basic processes for innoVation, product, and

serVice deVelopment

For innovation to happen, it is not only of paramount importance to know what to do, but also how. Chapter 1 indicated how important innovations are, how important innovation management is for companies and engi- neers, and what types of innovation are distinguished. In between the con- ception of an invention or idea and the launch in the market, a product or service needs to be designed. This is generally called new product devel- opment or new service development. However, this term is relatively lim- ited because it is also possible to create innovations through improvement of existing products and services, which means that not all stages for new product or service development are followed. Therefore, some authors, for example, Hinckeldeyn, Dekkers, and Kreutzfeldt (2015, p. 480) and Riedel and Pawar (1991, pp. 321–22), indicate that engineering processes for new products and services may be better covered by the term product and service design and engineering. Sometimes, the text uses the term new product and service development, but this is almost always in the spirit of product and service design and engineering. Notwithstanding the different terms that it may cover, this chapter will look at the processes and methods (tools) necessary for the conversion of an idea into a product or service launched in the market.

To this purpose, this chapter will build on the concepts presented in Chapter 1 and goes into more detail about the processes for new prod- ucts and services design and engineering. Section 2.1 will briefly delib- erate on what engineering as a discipline covers; this includes basic cycles for generating new knowledge. Building on the contents of prod- uct design and engineering, Section 2.2 introduces the reference model for new product development that will be used throughout the book.

C o p y r i g h t 2 0 1 8 . M o m e n t u m P r e s s .

A l l r i g h t s r e s e r v e d . M a y n o t b e r e p r o d u c e d i n a n y f o r m w i t h o u t p e r m i s s i o n f r o m t h e p u b l i s h e r , e x c e p t f a i r u s e s p e r m i t t e d u n d e r U . S . o r a p p l i c a b l e c o p y r i g h t l a w .

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32 •   innovAtion MAnAgeMent And npd for engineers

It contains a primary design and engineering process and a secondary design and engineering process. After a case study, Section 2.3 presents some well-known methods for new product and service development; these methods are not an exhaustive list, but indicative for methods that can be used during product design and engineering. These tools and methods are part of the decision-making processes during new product and service development; to this purpose, Section 2.4 presents some methods for decision making. Next, Section 2.5 goes into more detail about the differences between new product development and new ser- vice development. Finally, Section 2.6 explores product and service platforms and product and service families with the related modular product configuration.

2.1  engineering As A discipLine

The first question arises what engineering exactly is. In the context of (new) products, services, and processes, it is a multidisciplinary disci- pline, whether it is civil engineering, electronic engineering, maritime engineering, mechanical engineering, or any other of its domains. Take a telecommunications satellite as a case in point:

• Keeping it in orbital position requires an understanding of the phys- ics of movements and propulsion systems.

• Communicating with a base station requires amalgamating knowl- edge from physics, transmission of signals, and software.

• Processing of telecommunications signals depends on knowledge from software, electronic circuits, and physics of microprocessor design.

• Thermal stability relies on thermodynamics (note that convection does hardly work in space) and control systems.

Knowledge from all these disciplines is integrated into the design of one satellite, but may also require tradeoffs between those disciplines to make it work together.

During the design of processes, products, and services, the approach of engineering is teleological. Teleological means that these processes are purpose-oriented, that is, each object that is created serves a purpose for the user, companies, and society. In systems thinking this is often associated with the term function as a more generic concept of purpose. A function is an abstract description of the purpose of an object.1 For example, the func- tion of a calculator is to perform calculations. However, using a calculator

1 For a more detailed description of function, see Dekkers (2017, pp. 127–30).

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innovAtion, product, And service deveLopMent   •  33

is not the only solution; there are also alternatives to perform calculations; cases in point are the abacus, the calculation ruler (also called a slide rule), pen and paper, and last but not least, the mind. All alternatives for a func- tion can then be evaluated against criteria. For the instance of performing calculations, these are accuracy, availability, cost, ease of use, and speed (but also portability could be used as a criterion depending on the circum- stances). Normally, the solution that is the best fit with the requirements is chosen; for the desk of a financial administrator, this may be a large electronic calculator, whereas a sales manager may opt to use a calculator application on a smartphone. This teleological thinking applies to com- plex products, assemblies, components and parts of products, or aspects of products, such as thermodynamics, strength calculations, materials, and dynamics, that need to be integrated to make it work. This brings about another characteristic of product and service design and engineering: only through realizing them, artifacts and objects can be evaluated against their expectations about performance. This points to a degree of trial and error, albeit purposeful. All this means that product and service design and engi- neering is purposeful (teleological), use multiple criteria for evaluating concepts and designs, and generate knowledge about products and ser- vices by using purposeful trial and error.

The latter, purposeful trial and error, indicates another character- istic of product and service design. The discipline of engineering is an inductive approach to science in two ways.2 The first is that, through trial and error, specific contingencies are investigated. An example is testing a design for extreme weather conditions. Outcomes of such testing, when not fulfilling requirements and expectations, may lead to adjustments of the design or even re-evaluation of alternatives that were discarded earlier. The second manner of using inductive research and experiments is the teleological evaluation of possible principle solutions or detailed designs against the functions and criteria, based on scientific and tech- nological knowledge. For movements, several principles can be used, for example electric, hydraulic, and mechanical propulsion; even magnetic levitation can be considered. An evaluation of these alternatives against criteria may lead to discarding alternatives or selecting the most appro- priate solution. Hence, scientific and technological knowledge is used in an inductive manner to select feasible alternatives based on criteria derived from requirements.

2 Inductive and deductive approaches are related to propositional logic. This is not to be confused with inductive and deductive reasoning (see Dekkers 2017, pp. 54–61).

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34 •   innovAtion MAnAgeMent And npd for engineers

The necessity to use scientific and technological knowledge points out the hypothetico-deductive approach in addition to the inductive approach. In this perspective, often a distinction is made between pure basic research, use-inspired research, and pure applied research, respectively, associated with the discoveries by Niels Bohr (atomic structures and the quantum theory), Luis Pasteur (vaccination, microbial fermentation, and pasteuri- zation), and Thomas Edison (inventor of devices, such as the phonograph, motion-picture camera, and light bulb); see Figure 2.1 for an overview, which is called the Pasteur’s quadrant (Stokes 1997, p. 73). The disci- pline of engineering falls into the quadrants of use-inspired research and pure applied research. In addition to the classification of approaches in the development of scientific knowledge, the continuous motion of knowl- edge in the technological domain is captured by Figure 2.2. The figure shows that tools and practices for product and service design are based on design principles and methods (pure applied research). These meth- ods are derived from theories in a teleological fashion (and integration of disciplines), which is use-inspired research in Pasteur’s quadrant. These

Figure 2.1. Pasteur’s quadrant for scientific research.

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Postulates

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Methodologies

Tools, practices

Feedback

Design principles

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innovAtion, product, And service deveLopMent   •  35

theories and methods are governed by methodologies based on postulates or assumptions; for example, a postulate is that software can fulfill more efficiently functions of control mechanisms that were previously embed- ded in electronic devices or mechanical artifacts. Feedback cycles com- plete this continuous development of technological knowledge. These cycles are instigated by assumptions or hypotheses that are consequently verified through deductive experiments and studies; this is called the hypothetico-inductive approach.

Consequently, innovation stems from the integration of disciplines, teleological character of product design, and engineering based on both inductive and hypothetico-deductive approaches for using scientific and technological knowledge. An example is the Dyson vacuum cleaner. Based on theories of vortexes to separate particles, this vacuum cleaner was developed into a commercially viable product. Using principles of undertaking research and development have led to basic concepts that were tested, to refinements implemented in the product design that led to further experimenting, and to conversion into a design appealing to customers. It should be noted that some of its claims, such as its sucking power, are better found in other designs, such as the Kirby vacuum cleaner. In the case of the Dyson vacuum cleaner, it most likely was the business model (see Section 1.3) that made the difference in terms of commercial success. For commercialization, Dyson exploited regular retail chan- nels, whereas Kirby relied on door-to-door salesman and word-of-mouth (direct sales, see Subsection 1.3.2 on business models); ultimately, this different approach to sales and marketing may explain the differences in market shares. This example demonstrates that the success of innovations is not only dependent on the right approaches to research and develop- ment, but also depends on how companies capture market shares through their business model.

2.2   reference ModeL for neW product  And service deveLopMent

Thus, characteristics for design and engineering are how scientific and technological knowledge is used for new products and services; to this purpose, this section will present a reference model for new service and product development that will be used throughout the book. This model also describes how these processes are connected to the production (and operations) and the use of goods and services; note that this model was developed for products initially (Dekkers, Chang, and Kreutzfeldt 2013,

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36 •   innovAtion MAnAgeMent And npd for engineers

p. 321). Hence, the next subsection shows the processes for production, and use of products and services before moving the primary and secondary processes of design and engineering (note that the modeling of processes is based on systems theories, particularly Dekkers [2017, pp. 117–30]).

2.2.1 PRoDucT (anD SeRvice) DeSign anD engineeRing aS infoRmaTion foR uTilizaTion

A function of the design and engineering processes for product and ser- vices is the provision of information to manufacturing, including supply of materials and services; see Figure 2.3. In the figure, the supply of assem- blies, components, parts, and materials for manufacturing is depicted, which is based on the bill-of-materials (see Subsection 1.1.2.2). These materials, parts, components, and assemblies are input to manufactur- ing processes that cover the production of parts and assembly of compo- nents, parts, and materials into products. These instructions for suppliers are provided in the form of drawing, specifications, and so on. Based on these instructions, purchasing (or logistics) departments obtain quotes from suppliers, and these are compared and evaluated before orders are awarded to a supplier. Usually, these decisions for non-standard compo- nents, parts, and materials are taken with the involvement of other depart- ments, such as the R&D department and manufacturing; certainly for more critical materials, parts, components, and for assemblies, this is usually done in established committees in which the relevant departments partic- ipate (these appear under various names, such as materials management board and buying committee). The selection of suppliers for more critical items is not always as straightforward as it may seem to be. This has to do with the incomplete and inaccurate information available during early stages of design and engineering (Shishank and Dekkers 2013), which does not make it possible to have full insight about all relevant aspects of such decisions. Hence, this output of the design and engineering process enables the supply of materials, parts, components, and assemblies for the subsequent manufacturing processes and informs manufacturing about which materials, parts, components, and assemblies to use and how to put them together into final products.

A second function of the design and engineering processes for product and services is the provision of information to distribution and logistics; see Figure 2.3. Such information may include instructions for packaging, handling, and storing of goods. In the perspective of this diagram, the dis- tribution also covers the delivery to (regional) distribution centers, whole- salers, and retail outlets, or any other agent involved in the sales of product

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innovAtion, product, And service deveLopMent   •  37

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38 •   innovAtion MAnAgeMent And npd for engineers

and services. For example, mobile telecommunications providers not only sell subscriptions to mobile services, but also handsets and other peripheral items to deliver these services to customers. Note that the information to distribution and logistics is related to a specific business model (see Section 1.3). This means that the second output of design and engineering processes is the information that enables products and services to be sold to customers.

A third function of design and engineering is providing information for the use, recycling, and disposal of products; see Figure 2.3. These instruc- tions need to be converted into manuals and user instructions; most often, the technical information is insufficiently accessible for users, mainte- nance engineers, and those involved in disposal and recycling. Certainly, as so-called sustainability, as environmental considerations, features higher on agendas than before (see Section 9.5 about sustainability). Design and engi- neering processes should not only include approaches to design for it, but also provide instructions for those further downstream how to recycle prod- ucts, assemblies, components, parts, and materials, or how to dispose them. An example is the coding of plastic components, so that the original mate- rial can be identified for recycling purposes. Whereas some might view this as not an essential task of engineering, it is important that the third output of product design and engineering processes reaches users, maintenance engi- neers, and those otherwise involved in recycling and waste management.

noTe • The supply of information to use, maintenance, disposal, and recy-

cling has been left out of the figures that follow, for the purpose of simplification and overview, notwithstanding their relevance.

• Also, the processes for distribution and logistics, which include deliveries to retailers and consumers, whether offline or online, have also been omitted in the next figures.

2.2.2 PRimaRy PRoceSS of PRoDucT (anD SeRvice) DeSign anD engineeRing

As one of the two main processes, the primary process of design and engi- neering converts customer requirements and technological knowledge into instructions for supply, manufacturing, utilization, maintenance, disposal, and recycling; see Figure 2.4. This is a staged process. First, customer requirements or elicited customer requirements together with scientific and technological knowledge are transferred into concepts for products and services. The second stage is engineering in which detailed specifica- tions of products and services are generated, including which assemblies,

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innovAtion, product, And service deveLopMent   •  39

Fi gu

re 2

.4 .

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io n

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d

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us e

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g

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40   •   innovAtion MAnAgeMent And npd for engineers

components, parts, and materials are needed for supply and manufacturing. The final stage is when these specifications are complemented by instruc- tions for supply, manufacturing, and distribution and logistics. These pro- cesses are characterized by incomplete and inaccurate information and iterations. Particularly, during early stages of new product and service development, not all detailed information about the product and services, assemblies, components, parts, and materials is available. This leads to decision making by engineers and managers that needs later to be revisited. When reviewing earlier decisions, that might also result in going back to earlier stages of design and engineering processes. These iterations might result in selection of other concepts, changes in the product configuration, and any other changes in assemblies, components, parts, and materials to be used for the products and services. Though by nature a linear process, more detailed information becoming progressively available during the primary process of design and engineering leads potentially to iterations.

The design of products and services might entail also the design and engineering of the processes downstream of design and engineering. For example, the use of a micro-fiber (inner diameter: 200 µ) in a medical diagnostic device required the development of a process that would bring substrates in a controlled fashion into the micro-fiber, something build- ing on the technological knowledge of the firm, but never before accom- plished. But, it might also be the delivery of the products and services to the customers that needs development. A case in point is the development of a website, where customers can download applications and config- ure those using their accounts. Thus, the design of products and services should also take into account the capabilities of the resources of down- stream processes, which could result in the development of processes and resources; this extends to the business model (see Section 1.3).

noTe • The iterations between the four stages have not been captured in the

figure for the sake of simplifying the overview. • This simplification has also been applied to the development of

operational processes in parallel to the design and engineering of products and services.

2.2.3 SeconDaRy PRoceSS of PRoDucT (anD SeRvice) DeSign anD engineeRing

The secondary process for design and engineering is also called engi- neering change management; see Figure 2.5. Note that this figure also

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innovAtion, product, And service deveLopMent   •   41

Fi gu

re 2

.5 .

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42 •   innovAtion MAnAgeMent And npd for engineers

includes a summary of the processes depicted in Figures 2.3 and 2.4. This secondary process complements the primary process. This additional process aims at resolving problems that appear downstream of design and engineering by looking at what corrections or redesigns need to be undertaken; such decisions could also affect suppliers. To this purpose, the input is feedback from the use of products and services, reclaiming processes, and manufacturing and supply processes. This feedback is evaluated against the expected performance of products and services and leads to proposals for redesigns and improvements of products, assem- blies, components, parts, and materials. These proposals will go through the regular stages of the primary process for design and engineering before revised information is supplied to the operational processes and users for products. Sometimes, this secondary process results in incre- mental innovations (see Subsection 1.1.2), because, generally speaking, the product configuration will remain intact for this type of innovation. Therefore, the secondary process of design and engineering complements the primary process by taking into account feedback from a broad scope of measurements related to the production of products and services and from their use in the widest sense.

This broad scope of measurements, probably from different sources, also implies that the evaluation of the feedback should take place in stages; this stage-wise evaluation is depicted in Figure 2.5 by the eche- lons on the right-hand side. The collection of data is of prime importance. Even when automated and supported by information and communication technologies, data does not lead right away to identifying the (root) cause. For example, an electric motor might fail and not function anymore. The quick response by an engineer to replace the motor with a new one might fix the problem, but not solve it at the same time. One of the following causes might have triggered the failure and will still result in a failure of the replaced motor: a design flaw in the control unit of the electric motor, a recurring manufacturing mistake, or a spike in the voltage supplied to the motor and control unit. To find out more, additional information is needed to establish what the cause is (this is called triangulation); only then, it can be established whether it is a matter of improved instructions to man- ufacturing (Echelon 1 in the figure) or substituting a component or subas- sembly (Echelon 2) or even redesign the product or service (Echelon 3). It could turn out that the technology for the motor and its control is out- dated, resulting in looking for an alternative technology (Echelon 4). In the reasoning so far, it has been assumed that the information supplied is univocal. In practice, this might be more difficult, as different people describing the same phenomenon will do so differently and not always,

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innovAtion, product, And service deveLopMent   •  43

the information is given in the same way (even the information carrier might differ, think about handwritten notes versus a dedicated recording in an automated system). A generic rule is that, in order to solve problems, you need to reflect on a higher level of aggregation than the occurrence of faults and failures (for the concept of aggregation strata, see Dekkers [2017, pp. 47–50]). Hence, the effectiveness of the secondary process for design and engineering depends on the quality of the information supplied from the different sources, triangulation during analysis, and stage-wise systematic evaluation using aggregation strata.

2.2.4 caSe STuDy: TuRBoPRoP aiRPlane

How important this secondary process is will be demonstrated through the case of an airplane manufacturer; to look into this matter was instigated by the costs of production of a turboprop airplane (see Figure 2.6), Fokker F50, exceeding the target labor costs for assembly by 30 percent. As all 150 planes, except one, were delivered on time to the customers and the quality of the final product should adhere to requirements for airworthiness (certification, FAA, etc.), the analysis was directed to the internal costs of assembly. Further initial analysis revealed that the cost of quality during assembly (inspections and corrections) constituted 25 to 30 percent of the internal production costs (supply of materials to assembly excluded); half of these were attributed to costs for recurring deviations from quality standards for components and instructions for assembly. Hence, the inves- tigation focused on the analysis of these deviations.

As a first step, the study looked at the internal quality performance and the processes for recovering from faults during assembly. As it appeared, the number of deficiencies occurring in assembled aircraft, called list of deficiencies, had decreased over the course of time; see Figure 2.7, and it seemed that spikes were mostly caused by the few deliveries of a spe- cific deviant type of the aircraft; the list of deficiencies was created at the time of the delivery to the customer and concerns points that are not affecting airworthiness. Note that, in Figure 2.7, the first three aircrafts are not listed, because these were produced for the certification and verifi- cation of all operational processes. Given the low number of deficiencies and improvements over time, combined with the on-time delivery per- formance, it could be concluded that the quality of the aircraft is not an issue. Therefore, the data from internal monitoring needed to be looked at. To support this analysis, the processes relevant to managing so-called non-conformance reports (NCRs) were depicted in Figure 2.8; these activities are the assembly of aircraft, production of parts, manufacturing

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44 •   innovAtion MAnAgeMent And npd for engineers

engineering, and detailed engineering. NCRs were filled out whenever there was a deviation of parts, processes, or assembly compared with the documentation supplied by manufacturing engineering. A so-called A-NCR was used when it concerned a fault concerning the aircraft, and a B-NCR, when it only concerned a specific component or part. Table 2.1 shows the recording of NCRs, compiled during a year, and a breakdown of the type of recovery actions undertaken based on the NCR (note that, this required decision-making and approval by a number of actors and could not be decided by assembly personnel themselves). Both lists of defi- ciencies and NCRs were recorded in a repository. Looking at more detail at the recorded NCRs during a year, it appeared that most led to addi- tional activities; see Table 2.1. In this table, repair means those actions

Figure 2.6. Fokker F50 (case study).

Figure 2.7. Number of items in lists of deficiencies plotted against aircraft delivered (by production number).

0

10

1284 16 20 24 28 32 36 40 43 47 51 55 59 63 67 71 75 79 83 87 91 95 99 10 3

10 7

11 1

11 5

11 9

12 3

12 7

13 1

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14 3

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20

30

40

50

60

70

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innovAtion, product, And service deveLopMent   •  45

Fi gu

re 2

.8 .

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d re

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ly sis

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46 •   innovAtion MAnAgeMent And npd for engineers

that bring the component or part back to predefined specifications, using non-previous approved methods, and therefore requiring design authority approval; rework indicates those actions that bring the product back within predefined specifications, using previously approved methods. Note that, in both cases, a new quality check is required. Rejected means, in this case, that during the process of decision-making, for example, after a test, the part was still airworthy (in other words, the claim in the NCR was rejected). Also, an analysis revealed that almost all NCRs were recurrent, albeit not for every aircraft. Looking into it with more detail indicated that 45 part numbers (10 percent of the total) caused one-third of the B-NCRs; this might indicate that preventive actions were hardly undertaken. A fur- ther check on this matter, pointed that only 11 percent of the NCRs could be connected to ongoing preventive actions. Hence, it could be concluded that the recurrence of NCRs in combination with a low number of pre- ventive actions caused additional labor and material costs for assembly, because of rework, repair, and replacement of parts together with the efforts needed for additional quality control and documentation (a prereq- uisite in the aerospace industry).

That relative few of these deviations, despite many of them being recurrent, resulted in preventive actions might be because of how requests for engineering changes are managed. Figure 2.8 gives a clue about these organizational processes. As it appeared, NCRs (and lists of deficiencies) were hardly evaluated and norms for acceptable levels of quality were also missing; thus, the integral costs of NCRs, including additional labor costs in assembly and production, were not considered for making decisions about revisions or other changes. Moreover, the requests for changes in design, parts, and instructions for assembly were not prioritized and managed; this design and engineering department focused on major changes in the design of the aircraft, sometimes ini- tiated by specific customers, and viewed these operational problems as less relevant in terms of prioritization. To resolve this, as a first step, an Engineering Review and Change Board was created to analyze the recur- rent NCRs (and lists of deficiencies) and to set out engineering changes together with a list of priorities, see Figure 2.9. Furthermore, capacity

Table 2.1. Classification of NCRs based on recordings for one year

NCR type Total

Percentage for specific actions Use as-is Repair Rework Return Scrap Rejected

A-NCR 1,482 18% 47% 35% B-NCR 1,163 1% 30% 59% 7% 3%

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innovAtion, product, And service deveLopMent   •  47

Fi gu

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.9 .

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48 •   innovAtion MAnAgeMent And npd for engineers

was allocated to requests for changes in design, parts, and instructions for assembly; this could be seen as a temporary solution, because, over the course of time, the number of deficiencies and NCRs should decrease, resulting in less work for the design and engineering department. The additional cycle of decision-making and capacity allocation resulted in a decrease of NCRs; this case study also shows the impact the absence of an appropriately managed secondary design an engineering process might have on downstream processes.

2.3   tooLs And Methods for product  design And engineering

This section will concentrate on a few of the many methods that are avail- able to designers and engineers during new product and service develop- ment. Note that these methods are not exclusive to each other; in other words, they can be used in conjunction. Some of these, such as the theory of inventive problem-solving, may lead to novel solutions.

2.3.1 TheoRy of invenTive PRoBlem-Solving

The theory of inventive problem solving, mostly known by its acronym TRIZ, is a tool developed by Genrich Altshuller that aims at solving prob- lems, particularly those with contradictions. He has written about this in a number of books, including some that are written in novel style (e.g., Altshuller 1996). The tools are based on solutions that have already been used successfully before. At the heart of the methods are 40 inventive principles for solving contradictions, rather than seeking a compromise or tradeoff; to this purpose, a contradictions matrix has been developed. This matrix has been derived from known and patented solutions; it lists 39 factors that could impact negatively on each other, and for each impact, there are a number of inventive principles, usually three or four out of the 40, that can be used to resolve it. Thus, the tool is based on analogous solu- tions for a problem. For more complex problems, a tool called algorithm of inventive problem-solving (ARIZ) has been developed, consisting out of 85 step-by-step procedures to do so. Some companies, among them Samsung, have adopted this tool and use it throughout the organization to support solving technological and organizational problems. The use of TRIZ, and some its complementary tools, for example, ARIZ, leads to principle, and sometimes innovative, solutions.

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innovAtion, product, And service deveLopMent   •  49

There are numerous examples of TRIZ. One well-known example is the detection of empty boxes on a packaging machine. An immediate reaction would be to use a visual detection system (manual or automatic). However, using relevant principles of TRIZ (e.g., taking out and anti- weight), one could come to the conclusion that the properties of the pack- aged product could be used, that is, there is a weight difference between a filled and empty box. Such can be measured by in real-time measuring by building a weighing station in the packaging machine, which may require an additional investment; a more inventive solution would be to use (com- pressed) air to blow away empty boxes, which would only call on mar- ginal expenses while being highly effective. Another would be predicting how many checkouts should be open depending on the flux of customers in supermarkets (although the self-service checkouts are resolving part of this challenge now). A simple indicator would be the number of carts and shopping baskets in use. Thus, applications of TRIZ can be found in solu- tions to everyday problems, as well as in more complex problem solving.

2.3.2 value engineeRing

Very differently from TRIZ, value engineering is a systematic method to improve the value of goods and services by considering its functions and the use of resources for its functions, usually expressed in costs. Value engineering dates back to the Second World War, when Harry Ehrlicher, Jerry Leftow, and Lawrence Miles developed its methods, due to short- ages of skilled labor, raw materials, and components. Alternatives could lead to reduced costs and improved products. To this purpose, value engi- neering identifies the function(s) and evaluates alternatives for that func- tion; see Figure 2.10. First, the function or functions of the product or service need to be identified, which is the input for generating principle solutions. This set of solutions is compared against constraints. Take for example, a student on a shoestring budget; such a student will not able to afford a helicopter flight to go to the university a few kilometers away, even though for transportation from the dormitory to the university, it is one of the possible solutions. The set of feasible solutions is evaluated on aspects. Looking again at the student, these might be comfort, weather conditions, time to reach the university, and so on. The final step is weight- ing of aspects and prioritizing the alternatives, ideally resulting in a cho- sen solution; this weighting might also be done by the value returned by the use of resources. In the case of the student’s transport to the university,

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50   •   innovAtion MAnAgeMent And npd for engineers

this is the effectiveness of the function of transport versus the cost. For example, using a bike might get a student closer to the teaching rooms, but might be less comfortable under certain weather conditions. And, the cost of a bike is less than the cost of a bus (despite requiring an initial investment). Depending on the weighting of the weather conditions, the bus might be the preferred option or the bike. Hence, value engineering allows maximizing the value for the customer against the resources used (most often taking the form of costs).

2.3.3 QualiTy funcTion DePloymenT

Extending on the concept of value engineering and combining it with concepts from quality management, quality function deployment (QFD) is a method that transforms consumers’ requirement into design targets and major quality assurance points to be used throughout the production phase; sometimes, it is referred to as the matrix product planning, decision matrixes, and customer-driven engineering. First developed in Japan in the late 1960s by Yoji Akao as a form of cause-and-effect analysis, QFD was brought to other countries in the early 1980s. Its early popularity was a result of numerous successes in the automotive industry. QFD is a struc- tured method that uses management and planning tools to identify and prioritize customers’ expectations; quality is a measure of customer satis- faction with a product or a service. The first tool, commonly denoted the house of quality, depicted in Figure 2.11, provides an overview of the most important attributes of a product or service. After prioritizing the attri- butes, QFD deploys them to the appropriate organizational department for performance measures and design of organizational processes, as shown in Figure 2.12; this shows that the cycle for this method consists of four stages, each using the house of quality: product planning, product design, process planning, and process control. Many QFD practitioners claim that using QFD has enabled them to reduce their cycle times for product and service by as much as 75 percent with equally impressive improvements in measured customer satisfaction. Some studies (e.g., Vonderembse and

Figure 2.10. Process for value engineering.

Generating principle solutions

Evaluating alternatives against aspectsSet of

principle solutions Function[s] (at defined aggregation stratum)

Set of feasible solutions

Unfeasible solutions Discarded solutions

Constraints Weighting of aspects

Chosen solution

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innovAtion, product, And service deveLopMent   •   51

Raghunathan 1997) into this matter point out that the product design and customer satisfaction improve, with only slight or modest gains for the time-to-market and costs. That QFD applies to design of services is noted by Bullinger, Fähnrich, and Meiren (2003, p. 279), and others have fol- lowed suit. Thus, QFD is the deployment of customer-driven attributes to

Figure 2.11. Basic principles for the house of quality (as part of quality function deployment).

C us

to m

er s’

r eq

ui re

m en

ts

W ei

gh tin

g

Correlations between functions or design features

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hm ar

ki ng

ag ai

ns t c

om pe

tit iv

e pr

od uc

ts o

r se

rv ic

es

Functions or design features

Technical evaluation of functions or features

Correlations

Figure 2.12. Phases of product development for QFD.

I Product planning

II Product design

IV Process control

III Process

planning

Customers’ requirements

Customers

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Concept design

Significant components

and parts Characteristics

significant components

and parts

Conceptual process design

Critical operations

Parameters critical

operations

Process control

requirements

Requirements maintenance

Procedures and training

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52 •   innovAtion MAnAgeMent And npd for engineers

the design of a process and services, and additionally, identifies how this product or service is best embedded in departments of an organization.

An example of QFD is given by Rawlings-Quinn (2005); it concerned the development of a heat-activated tape product by the Intertape Polymer Group. These tapes were used for packaging, among other applications. The team consisted of purchasers, marketeers, process engineers, research and development engineers, and quality engineers. During phase I (prod- uct planning), they conducted interviews and visited customer sites. This phase also included competitive analysis in terms of technological per- formance, cross-correlating these measures, establishing the difficulty for achieving them, and weighting requirements. In this case, the next phases (II: product design and III: process planning) were combined, because materials and process characteristics both influence the properties of the product. Using targeted experiments, the research and development engi- neers determined the combination of the most suitable ingredients and process conditions to achieve the requirements determined during the first phase. The second and third phases were complemented by asserting that properties of ingredients and process characteristics were measurable and controllable. The final phase (IV: process control) concerned the trans- fer of customer requirements into instructions for the shop floor, quality assurance, maintenance, and so on. For example, online weight control monitoring was established, troubleshooting guidelines provided, and a calibration schedule set. This example shows that the systematic develop- ment of a product can be enhanced by using QFD with its multidisciplinary approach, and that, this lead to products with improved performance.

2.3.4 faulT TRee analySiS

In addition to quality function deployment and value engineering, fault tree analysis (FTA) can be used for identifying root causes of failures of products, assemblies, component, and parts. It is a top-down, deductive failure analysis in which an undesired state of a system is analyzed using Boolean logic to link this failure to a series of lower-level events (in terms of product configuration, see Subsection 1.1.2); for deductive reasoning and systems, see applied systems theory (Dekkers 2017, pp. 55–58). This method is mainly used in the fields of safety engineering and reliability engineering to understand how systems can fail, to identify the best ways to reduce risk, or to determine (or get a feeling for) event rates of a safety accident or a particular system-level (functional) failure. It is used in the aerospace, nuclear power, chemical and process, pharmaceutical, petro- chemical, and other high-hazard industries; but it can also be applied in

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innovAtion, product, And service deveLopMent   •  53

other domains, such as social service systems and project management, for the identification of risk factors (see Section 6.5 for the application in project management). FTA is also used in software engineering for debugging and is closely related to the cause-elimination technique used to detect bugs. Thus, FTA is a principle method for design and engineering of products and services to increase the reliability through identification and assessment of failure modes.

2.3.5 failuRe moDe anD effecT analySiS

Akin to the FTA, failure mode and effects analysis (FMEA) is also a method for risk analysis during product and service design and engineer- ing; however, it starts with analyzing the impact of failure at lower levels of the product architecture. It was one of the first systematic techniques for failure analysis, developed by reliability engineers in the late 1950s, to study problems that might arise from malfunctions of military sys- tems. FMEA is often the first step of a system reliability study. It involves reviewing as many components, assemblies, and subsystems as possible to identify failure modes, and their causes and effects on the total system. For each component, the failure modes and their resulting effects on the rest of the system are recorded in a specific FMEA worksheet (there are numerous variations of such worksheets). FMEA might be a qualitative or a quantitative analysis. Sometimes, FMEA is extended to failure mode and effect criticality analysis (FMECA) to indicate that the probability of failure modes against the severity of their consequences is charted, too (in terms of critical failures). FMEA is based on inductive reasoning from a single point of failure and analyses the impact on the total system, which is also called forward logic; for inductive reasoning and systems, see applied systems theory (Dekkers 2017, pp. 58–61). It is used in reliability engi- neering, safety engineering, and quality engineering; quality engineering is especially concerned with applying FMEA to processes (production, manufacturing, and assembly).

2.3.6 caSe STuDy: SmaRT hoSPiTal BeD

A case for demonstrating the combined use of systematic design and risk analysis is the design of a smart hospital bed (Popescu et al. 2017); see Figure 2.13. The example is based on a collaboration that took place as part of the Transylvanian Furniture Cluster in Cluj-Napoca between the Technical University of Cluj-Napoca and a proactive furniture start-up

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54 •   innovAtion MAnAgeMent And npd for engineers

company. The challenges and opportunities on the market have led to the initiation of a smart furniture project with the aim of producing a new, advanced, and interactive hospital bed. Nicknamed HOPE (from Hospital- enhanced Patient Experience), the product was developed using a new product development approach that followed a cascading QFD approach supplemented by TRIZ and brainstorming. The hospital bed is designed with a self-care system that uses a tracking system and body temperature measurement; its versatility allows changing the position of the bed nat- urally. Another innovation is the use of composite materials with silver ions to reduce the risk of contamination. For the design, instead of FMEA an adapted method called success mode and effect analysis was used to identify factors that would facilitate commercialization of this innova- tion; see Table 2.2. This application to the smart hospital bed indicates that methods for product design and engineering can be used in differ- ent ways to enhance the design of product and services with their related business models.

2.4   product design And engineering As A  decision-MAKing process

All the methods in the previous section and also the processes in Section 2.2 point to design and engineering process being essentially decision-making; this covers what to include and what to exclude, principle solutions, design alternatives, integration, and tradeoffs for achieving the best results. To this purpose, this section looks at some basic approaches to decision- making; again, this is not an exhaustive list, but meant as an introduction for decision-making related to design and engineering.

Figure 2.13. Design of the smart hospital bed HOPE.

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innovAtion, product, And service deveLopMent   •  55

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56 •   innovAtion MAnAgeMent And npd for engineers

2.4.1 mulTiPle-cRiTeRia DeciSion-making

One of the most common approaches for decision making is multiple- criteria decision-making, sometimes called multiple-criteria decision analysis and multi-attribute analysis. This technique is used for compar- ing options and alternatives for achieving objectives. To this purpose, the first step is developing objectives that need to be achieved (or require- ments), followed by the generation of alternatives, options, and solutions.3 The alternatives are compared and weighted on criteria derived from the objectives. Subsequently, the option that scores best on all criteria or that achieves the highest overall score is selected. An example is the purchase of a car; such a purchase could be evaluated against purchase price, oper- ational costs (for example, fuel consumption and maintenance costs), comfort, image, transport capacity, and so on. It should be noted that in making the decision, there might not only very complex issues involving multiple criteria, but there are also multiple parties that are deeply affected by the consequences and might weight the criteria differently. Even for the purchase of the car, this might apply, when family members have differ- ent views on the purpose of a car and the weighting of the criteria. This means that even different parties or stakeholders may prefer a different optima solution. It should be noted that the appraisal of alternatives could be done quantitatively, semi-quantitatively, or qualitatively (it can even be combined). Hence, multiple-criteria decision-making aims at evaluating the options against criteria derived from objectives and allows subjective weighting of each to select the most appropriate solution.

An example of the method for multiple-criteria decision-making and the subjective weighting is found in a manual of the Department for Communities and Local Government (2009, pp. 90–101). It is about the case of appraising potential sites that could serve as repository for radio- active waste at the end of 1980s. Without going into much detail about the project, Table 2.3 shows the outcome of the evaluation for the site. The top rows show the criteria that inform the appraisal of the potential nine sites; from the original sites, only these nine were considered feasible. The base case represents the weighting of the group directly involved in the prepa- ration of the decision making after being informed by the various actors involved and the collection of data. The equal case was constructed to show the influence of weighting. The three right-hand columns display the

3 In this sense, it has similarities to value engineering, see Subsection 2.3.2. How- ever, value engineering uses functions for evaluation, rather than objectives or requirements as multiple-criteria decision-making does.

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innovAtion, product, And service deveLopMent   •  57

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58 •   innovAtion MAnAgeMent And npd for engineers

perspectives of the local communities, the environmental perspective, and the economic perspective. From the table, it can be derived that a number of options are very closely positioned to each other, across, and within perspectives. Ultimately, this means that such a decision might be based on other criteria than listed or subject to interpretations of data.

Principally, structuring complex problems well and considering mul- tiple criteria explicitly lead to more informed and better decisions. There have been important advances in this field since the rise of the multi- ple-criteria decision-making discipline in the early 1960s. A variety of approaches and methods, many supported by specialized decision- making software, have been developed for an array of disciplines, ranging from politics and business to the environment and energy. Over the course of time, some other approaches have been added, such the analytic hier- archy process and the use of fuzzy sets. The analytic hierarchy process converts subjective assessments of relative importance to a set of overall scores or weights; to this purpose, it asks actors involved in the decision making how important one criterion is to another. Note that some seri- ous concerns have been raised about the method and that extensions have been proposed and alternative methods propagated; however, it is beyond the scope of this book to go into more detail. Also, fuzzy sets for use in multiple-criteria decision-making has received criticism. Fuzzy sets are based on the membership of a set not being crisp, hence probability values are assigned. Whereas many methods and their extensions have been proposed, it is not clear whether the application of this mathematical approach will lead to better decision-making. Therefore, multiple-criteria decision-making is partially subjective, through the evaluation of alterna- tives on each criterion and the relative weighting of criteria; however, it is also sensitive to how it is performed, without or with specialized decision making software.

2.4.2 SaTiSficing

Whereas multiple-criteria decision-making aims at finding the optimal alternative, satisficing is an approach to decision making or cognitive heuristic that entails searching through the available alternatives until an acceptability threshold is met. The term satisficing, a combination of sat- isfy and suffice, was introduced by Simon (1959), although the concept appeared first in his book Administrative Behavior (1947). Simon used the concept of satisficing to explain the behavior of decision makers under circumstances in which an optimal solution cannot be determined. He pointed out that human beings lack the cognitive capabilities to optimize.

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innovAtion, product, And service deveLopMent   •  59

Rarely all outcomes can be evaluated with sufficient precision; usually, the relevant probabilities of outcomes are not known, and humans possess only a limited memory and limited cognition. Simon labeled this approach to decision making based on these limitations as bounded rationality. This means that bounded rationality as limitation to decision making might only exacerbate the choice for a non-optimal solution through satisficing; note that satisficing and bounded rationality are related, but separate concepts.

An example of satisficing and bounded rationality is the start of the development of the Airbus A350 in the beginning of the 2000s. When airlines pushed Airbus to provide a competitive airplane to the Boeing 787 Dreamliner, which had been a success before its deliveries, Airbus initially proposed the A330-200Lite; this concept was a derivative of the Airbus A330 featuring improved aerodynamics and engines similar to those on the Boeing 787 Dreamliner. This choice was based on the A330- 200 Lite being the first solution that would just meet the criteria from Airbus perspective to meet the customers’ demands; Airbus perspective of the customers’ requirements could be considered bounded rationality, as it only considered existing airframes without taking into account the impact of new technologies, and so on. The company planned to announce this version at the Farnborough Airshow in 2004, but did not proceed, and the next design proposals provoked negative reactions from potential customers. In 2006, the revised concept for the A350 became an almost all-new aircraft, with new wings, new engines, a new horizontal stabilizer, new composite materials, and new production methods. After its introduc- tion, this revised concept became a commercial success. Hence, at the end, Airbus managed to avoid the trap of satisficing and bounded rationality, though it can be reasoned that the intervention of customers was necessary to establish this.

2.4.3 caSe-BaSeD ReaSoning

In making decisions, lessons learned from the past and experience can play a role; in this sense, case-based reasoning is the process of solving new problems based on the solutions of similar past problems. This princi- ple of re-using existing solutions to new problems is apparent in daily life. For example, a car mechanic who repairs an engine by recalling another car that exhibited similar symptoms with its engine is using case-based reasoning. Also, a lawyer who advocates a particular outcome in a trial based on legal precedents or a judge who creates case law is using case- based reasoning. Essential to these examples is that applying case-based reasoning builds on a degree of similarity between the case under review

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60   •   innovAtion MAnAgeMent And npd for engineers

and previous cases, so that the solution is valid for the new problem, too.4 This implies that this similarity is investigated before putting the decision is taken to apply the existing solution to the new problem. The concept of TRIZ (see Subsection 2.3.1) is an example of case-based reasoning. So, too, is an engineer who copies working elements of nature as a data- base of solutions to problems; this is also called practicing biomimicry. Thus, case-based reasoning might also be a kind of drawing analogies to solve problems; see Dekkers (2017, pp. 65–67) for notes on analogies. It should be noted that, in the context of innovation, re-using existing solutions could be equated with incremental innovation (see Subsection 1.1.2). Therefore, case-based reasoning is a common practice, though those applying it should be well aware of its limitations.

2.4.4 conTRolleD conveRgence meThoD (SeT-BaSeD concuRRenT engineeRing)

Selecting solutions also appears in the controlled convergence method, originated by Pugh (1981); later, it was popularized by others, such as Ward et al. (1995), under the label set-based concurrent engineering. Pugh’s controlled convergence method is based on the subsequent nar- rowing down of alternatives to a final design; see Figure 2.14 for a sym- bolic overview. At each stage, progress of detailing concepts and design are set-off against criteria and requirements; with progressive insight these criteria become more detailed, too. The advantage of this method is that not an early selection of a specific design or concept leads to a lock-in that will cause problems downstream in new product and service development. The disadvantage is that, during early stages of product design and engi- neering, more parallel projects run in parallel, drawing on resources. For part, concentrating on essential challenges for each concept, rather than trying to do everything can circumvent this. Based on this understand- ing of the method, Frey et al. (2009, p. 56) contend that it is an effective method, especially for the stage of conceptual design, facilitates the focus on appropriate details, and also supports engineer teams to work together in a more objective fashion.

Even though this method of controlled convergence resembles multi-criteria decision-making, it differs from it by not using numerical

4 This means that the concepts of isomorphism and homomorphism (see Dekkers 2017, pp. 64–65) and the principles of generalization (ibid., pp. 50–52) should be applied in advance of declaring an existing solution from an old problem (or old problems) valid for a new situation.

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innovAtion, product, And service deveLopMent   •   61

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62 •   innovAtion MAnAgeMent And npd for engineers

or summary evaluation, but concentrates on reconciling tradeoffs, resolv- ing relevant outstanding issues, and sharing in teams; a hypothetical example in Table 2.4 demonstrates this. Suppose that an existing system based on steam for moving an object in combination with a mechani- cal contraption can be replaced with either an electromagnetic system or a hydraulic-powered system or a pneumatic-powered system. A basic, proven solution is called the datum in this approach; in this example, the steam-powered system is the datum. All alternatives are compared with the datum on their relative performance against criteria as indicated in the table. The evaluation of their comparative performance is then summarized at the bottom of the table. At this stage of the conceptual design in this case, the design and engineering team could decide to com- plete all data collection by focusing on the question marks in the table or to discard the solution of the pneumatic-powered system. Frey et al. (2009, p. 43) note that, in practice, this method is not a matter of clean-cut matrixes and tables, but that teams use this method with notes, memos, and other means in visual overviews. This corresponds with the notion that the controlled convergence method aims at keeping an overview during all stages of concept development, that it aims at shared decision making within a team, and that it supports setting out a plan of action to compare alternative solutions to a base case.

2.4.5 DialecTic DeciSion-making

Also a method that does not reach a decision right away is dialectic decision-making, aka the Socrates method. Perhaps, more applicable in

Criteria Electromagnetic Hydraulic Pneumatic Leverage of power S + – Auxiliary components + – – Weight + S + Reliability ? S S Costs ? + ? Comparative performance

2+ 2+ 1+ – 2–

+ Better performance as datum. – Worse performance as datum. S Same performance as datum ? Unresolved.

Table 2.4. Simplified example of the controlled convergence method

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innovAtion, product, And service deveLopMent   •  63

the social sciences, it aims at generating two or more competing propos- als. For each of the proposals, the underlying assumptions are identified, and the advantages and the disadvantages are determined. Consequently, the decision can be that one of the two alternatives is chosen or that a new proposal is generated or that a compromise is forged. For the latter, Dekkers, Chang, and Kreutzfeldt (2013, p. 330) observe for product design and engineering that in practice that managerialism seems to override the opinion of experts; especially in situations where management methodol- ogies, such as staged decision-making, are introduced, that appears to be more likely to happen; decision-making for and during new product devel- opment is influenced by the co-existence of two distinct cultures, the man- agement culture driven by performance objectives, and the engineering culture of finding optimal solutions and detailing to make these solutions work (for example, Schein 1996). However, in practice, it is very difficult to make decisions about design and engineering shaped by compromises.

2.4.6 concuRRenT engineeRing

Though not a decision-making method itself, concurrent engineering is a method for product and service design and engineering based on the parallel execution of tasks (i.e., performing tasks concurrently). It refers to an approach used in product and service development in which functions of design, engineering, manufacturing engineering, operations, and other functions are brought together in the design pro- cess to reduce the time required to bring a new product to the market; see Figure 2.15. For those who are interested, concurrent engineer- ing appeared first as simultaneous engineering (Kusiak and Park 1990, p. 1883), at the end of the 1980s. This modus operandi is in contrast to the more traditional approach of sequential engineering, in which the next phase only starts when the previous one is concluded. Hence, the main benefit is reduction of time-to-market, though increases of quality in the case of incremental innovation are also reported (see Dekkers et al. 2015, p. 327).

2.5  neW service deveLopMent

Although from a certain perspective, new product development and new service development carry similarities in their processes, approaches, methods, and tools, there are also vast differences; the first major dif- ference is that, for service, the design of operational processes should account for the principle that consumption = production. Whereas pro- duced goods can be stored awaiting purchase and consumption; in the

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64 •   innovAtion MAnAgeMent And npd for engineers

case of services, this is the hardly the case. This means that this principle also implies that there should be little delay as possible when the actual demand for a service is evoked. The companies delivering pizzas at homes and offices use this principle when they offer that the order arrives within a time limit, say 30’ or else your order is for free. Ultimately, this means that the channel for the delivery of services and the related business model (see Subsection 1.3.2) should have enough capacity to serve the expected customers, including accounting for variations and surges in demand.

In addition to the timeliness of services in comparison to goods, a second major factor is the intangibility of services; intangibility means that a service cannot be felt, heard, seen, or touched. The design of ser- vices should incorporate this intangibility, too, if possible, although not always easy to capture. This could range from simple things such as the indicator how much of a file has been downloaded to personal approaches to a customer. Generally, the intangibility of services puts the onus on the customer experience, and this means that the technological aspects should be enhanced to accommodate the customer.

This accommodation is found in the last relevant characteristic of new services design, which is the involvement of the customer in the delivery. Companies have four strategies to deal with customers in service contexts (see Frei 2006); these approaches have been depicted in Table 2.5. The approach called classic accommodation means that a firm relies on abun- dance of staff that is well-trained. More potential for innovation emerges in the low-cost accommodation strategies; it relies on automating tasks for employees and the self-service options, the latter requiring no special

Figure 2.15. Comparison of sequential engineering and concurrent engineering on time-to-market.

Sequential engineering

Concurrent engineering

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Conceptual development

Design

Engineering

Manufacturing engineering

Production

Conceptual development

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innovAtion, product, And service deveLopMent   •  65

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66 •   innovAtion MAnAgeMent And npd for engineers

skills and permitting customization. Another strategy is the classic reduc- tion, which limits the service provided in some way. That is done through reservations, the provision of off-peak pricing, limited service availability, limitation in the breadth of the service provided, and even the use of the capabilities of customers, supported by a reward and penalty policy. How- ever, this strategy might estrange customers. The fourth strategy, uncom- promised reduction, overcomes this disadvantage by targeting customers based on their requests, capability, motivation, and subjective preferences; the suggestions for further items when shopping online is an example of this strategy. Thus, these four strategies in combination with the other two characteristics—consumption = production and intangibility—influence the design of the services in addition to technological considerations.

2.6  product And service Architecture

Looking at the structure of products and services, the use of product and service platforms and modular design have become more common to balance product flexibility and standardization, to decrease lead-times for delivery of orders and to increase efficiency. Modular designs and platforms are specific product configurations (see Subsection 1.1.2.2) to achieve these objectives. To this purpose, the next subsection will discuss product and service platforms briefly. This is followed by a subsection about order entry points before modular designs are elaborated. An example of order entry points and modular designs concludes this section.

2.6.1 PRoDucT anD SeRvice PlaTfoRmS

A product or service platform is a collection of common elements, espe- cially the underlying core technology, that is implemented across a range of products and services. It is the foundation of a commercial product strategy because, in high-tech companies, many products are typically built from a core technology and related design. Known examples are found in the software industry and automotive industry; for example, a number of car models, sometimes across manufacturers, share a common chassis, powertrain, transmission system, and suspension, but differ in their silhouettes. Next generations of products and services build on the previous ones in the platform as incremental or modular innovation; for example, a new engine fitting in the platform is an example of modu- lar innovation. Accordingly, the key to a successful product family lies in properly balancing the inherent tradeoff between commonality and

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innovAtion, product, And service deveLopMent   •  67

distinctiveness: designers must balance the commonality of the platform with the individual performance (i.e., distinctiveness) of each product in the family. As a result, designing a product platform and corresponding family of products embodies all of the challenges of product design while adding the complexity of coordinating the design of multiple products in an effort to increase commonality across the set of products without compromising their distinctiveness. The selection of core technologies and commonalities used in product and service platform decisions is fre- quently irreversible and has a long-term impact for product and service development.

2.6.2 oRDeR enTRy PoinTS (aka oRDeR DecouPling PoinTS)

Product platforms—focusing on commonality—should not be confused with product families related to modular design of products; to this pur- pose, first, the concept of order entry points will be discussed. Order entry points are the points in the primary process of order processing that sep- arate what is already produced for no specific order from what is to be produced for a specific order; see Figure 2.16. For example, components are produced based on forecasts and stored as inventory, and once an order is accepted, the final product is assembled and delivered to the customer. Thus, this order entry point separates the production of the forecasted demand from the activities that only take place once an order is received. The concept of customer order entry points, as part of manufacturing and logistics, was originally introduced by Sharman (1984) for logistic control and by Wemmerlöv (1984) for manufacturing. This point is also known as the customer order decoupling point, the order penetration point, and the product configuration point (see Dekkers 2006, p. 4012). Based on this

Figure 2.16. Order entry point for scheduling of production processes.

Inventory (Assemblies/components/parts)

Raw materials Products (to customer)

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Delivery (Make-to-order)

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Forecast-driven Order-driven

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68 •   innovAtion MAnAgeMent And npd for engineers

order entry point, a distinction is made between make-to-stock, assem- ble-to-order, and make-to-order. Make-to-stock refers to products being produced on forecast, stored in inventory, and right away delivered to the customer once an order has been placed; this requires a company to have sufficient products available as the inventory, and therefore depends on the accuracy of forecasts. Assemble-to-order happens when sub-assemblies (and components and parts) are assembled from the inventory once an order is received; though it introduces lead-times for customers to deliver the order, it also offers companies to reduce inventory and be more flex- ible. A well-known example is Dell, one of the first large manufacturers of computers to base its business model (see Section 1.3) on this concept. Make-to-order goes even further and only starts with all processes for an order once it has been obtained; this could include purchasing materials, and so on, and for this reason, it is often associated with long lead-times. In the first instance, these customer order entry points are of consequence to manufacturing and logistic strategies.

In addition to the customer order entry point for manufacturing and logistics, Dekkers (2006, p. 4016) and Wikner and Rudberg (2005, p. 628) introduce the so-called order specification entry point to emphasize the impact of customer specifications on the engineering processes, and conse- quently the manufacturing process; some refer to this as engineer(ing)-to-or- der; for example, Gosling and Naim (2009, p. 741ff.), albeit from a supply chain perspective. Figure 2.17 shows the total processes for engineering, manufacturing, and logistics together with the order entry points. The order entry points for manufacturing and logistics are called customer order entry points (COEP) and the points for engineering order specification points (OSEP). There are five order entry points for manufacturing and logistics and four for design and engineering processes. The position of these points depends on which activities need to be undertaken once an order has been received; for example, OSEP-3 means that a conceptual design is available, but detailed design is still necessary. However, it could be that parts of the design are available, but that some other parts still need to be designed and engineered. This happens when airplanes are bought; the design of the air- frame is already set (OSEP-1), but the interior of the cabin still needs to meet specific demands of an airline (OSEP-3). Principally, the concept of the order entry points means that the customer order can be depicted on the dimensions of the engineering process and manufacturing process in the order entry matrix; see Figure 2.18. Note that some of the combinations in the figure are not possible in principle. A specific order may require differ- ent combinations in this matrix as indicated by the gray boxes in the figure. Thus, the order entry matrix summarizes the combined customer order entry

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innovAtion, product, And service deveLopMent   •  69

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70   •   innovAtion MAnAgeMent And npd for engineers

points and points for engineering order specification points for product fam- ilies. Note that, in general, there has been a tendency to increase product flexibility, which is reflected by a move toward COEP-1 and OESP-1; this requires not only flexibility in product design, but also responsive manufac- turing systems, which are flexible with regard to volume and product mix while keeping lead-times as short as possible.

2.6.3 moDulaR DeSign of PRoDucTS anD SeRviceS

This responsiveness is often facilitated by modular design of the prod- uct configuration; modularity links to product families consisting of stan- dardized assemblies, components, and parts. The sales and engineering processes should direct customers’ requirements to standard modules, standard option modules, and specials; see Figure 2.19. Products are configured using a basic module, from which only one is available, and standard modules, from which a limited range is available. Additionally, optional modules extend the functionality of the product. In case of unique customer requirements, special modules might be fitted, but these are only

Figure 2.18. Order entry matrix.

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P

Figure 2.19. Modularity of product families.

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innovAtion, product, And service deveLopMent   •   71

produced. By minimizing the use of special modules, the dilemma of variants and variety versus will be met. A popular example to explain the modular design is pizzas in fast-food chains. Basic modules are the tomato sauce and mozzarella cheese, whereas the base is a standard module; the base is not a basic module because it is usually available in varieties, such as size and crust. All ingredients for specific types of pizza are options. Most of these chains do not have a customer-specific module, but that could be an ingredient of the day or an ingredient the customer orders or brings along. The example shows that, with few components and parts, the delivery of a broad range of products is possible within a product family; moreover, this product flexibility is possible while still achieving relatively low lead-times (or delivery times) and a relatively high degree of efficiency.

2.6.4 caSe STuDy: manufacTuRing eQuiPmenT PRe-faB elemenTS

Shortening lead-times and achieving a higher degree of efficiency are also possible when customer orders seem to be very specific; the example of a manufacturer of equipment for concrete pre-fab elements (see Dekkers 2006, p. 4021) will demonstrate this. The company’s competitive advan- tage was to deliver custom-designed equipment, in contrast to the compet- itors that delivered modular designs in standardized sizes; an example of the design of subsystem for these factories is found in Figure 2.20. Typical lead-times for projects varied between 1.5 and 2 years. When reviewing the engineering and production processes, the initial process could be defined as a combination of OSEP-4 and COEP-5 (see Figures 2.17 and 2.18)

Figure 2.20. Long-line sleeper plant for pre-fab elements.

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72 •   innovAtion MAnAgeMent And npd for engineers

An analysis of five projects revealed that losses amounted to 20 percent per project due to an excess of engineering hours. This excess could be avoided by a more standardized operating procedure for the design and engineering of the products (based on small increments of 0.25 meter, thereby approaching a tailored design); this represented moving toward OSEP-1. A computer program based on this standardized design and modular components was developed to conduct the pre-design and initial stages of the engineering process. The proposal decreased the number of hours and decreased the lead-time, while still offering sufficient product flexibility to compete. Because of the low number of projects and their specific requirements, it was not possible to assess the exact improve- ments; estimates showed that the payback time for the standardized design and the implementation could be 1 to 1.5 years.

2.7  Key points

• Engineering as a discipline combines teleological, inductive, and hypothetico-deductive approaches to both generating and using sci- entific and technological knowledge. Although these methods dif- fer for both product and service design, they are complementary to advancing insight for engineering, and they constitute fundamental skills for engineers.

• The primary design and engineering process covers the integra- tion of scientific and technological knowledge into products and services that meet elicited customers’ requirements. It has as out- put instructions to the supply of materials, the production of parts, component and assemblies, the assembly of products, the commis- sioning of products, and the management of recycling.

• The secondary design and engineering process, complementary to the primary design and engineering process, uses feedback from downstream processes, such as manufacturing and use, to initiate improvements to the design of products and services. It does so by analyzing the feedback against performance improvements in a staged, aggregated manner. Key to an appropriate secondary design and engineering process is the capability for analysis and conver- gent thinking.

• The method of TRIZ aims at re-using knowledge about solutions that solved often-contradictory requirements for products, services, and so on. This knowledge has been derived from patents and other solutions. To aid this process, the method is based on 39 factors that

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innovAtion, product, And service deveLopMent   •  73

might influence each other and 40 principle solutions for resolving conflicts in requirements.

• Value engineering is a method to improve the value of goods or products and services by examining its functions. Value is defined as the ratio of function to usage of resources, which is most com- monly the cost. Thus, the value of a product or service can be increased by either improving the function or reducing the cost, according to this method.

• QFD is a method for the identification of critical attributes for customers of product and services, and the translation of user requirements or requests into designs and structure of processes that meet these specifications. The method consists of a number of steps supported by matrixes, from which the house of quality is most known.

• FTA is a tool for the identification of actual or potential failures of products and services; normally, it is followed by corrective or pre- ventive actions. The actual or potential failures are determined by a top-down approach from a system level to subsystems to elements.

• FMEA is a systematic, proactive method for evaluating products, services, and processes to identify where and how they might fail and to assess the impact of the (total) system. In contrast to the FTA, this method starts by looking at the elements and subsystems.

• Multi-criteria decision-making is a method that evaluates the prop- erties or performance of concepts, products, services, and processes against weighted aspects and criteria. As the consecutive selection of concepts, products, services, and processes might depend on the weighting of individual aspects, often, a sensitivity analysis is conducted.

• Satisficing is an approach to decision-making that aims for a sat- isfactory or adequate result, rather than the optimal solution. The satisfactory position is often seen as familiar, hassle-free, and secure, whereas aiming for the best-achievable result would call for additional costs and efforts, and might incur risks.

• Bounded rationality comes into play when individuals make deci- sions based on the rationality limited by the information they have, constrained by the cognitive limitations of their minds (in terms of knowledge), and constrained by the available time. This may lead to not all relevant aspects and information to be considered when a decision is taken.

• Case-based reasoning is developing solutions to unsolved prob- lems based on pre-existing solutions of a similar nature; it car-

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74 •   innovAtion MAnAgeMent And npd for engineers

ries similarities to experience. This means that the experience is embodied in a repository of past cases and feedback from these cases about performance.

• Concurrent engineering is a method of designing and marketing new products and services in which the design and engineering stages are executed in parallel, rather than sequential, often with the aim to decrease the time-to-market, to improve the quality, and to reduce the costs.

• By sharing technologies, components, and production processes across a platform of products (called commonalities), companies can develop differentiated products efficiently, and increase the flexibility and responsiveness of their manufacturing processes. For services, these platforms are usually associated with the deliv- ery that consists of an architecture with a set of components to this purpose.

• The objective of modular product and service design architecture is to distinguish subsystems that can be combined to create product families. These product families have a common and are more flex- ible toward meet the diversity of customer requirements. The prod- uct configuration of a product or service consists of basic modules, standard modules, standard option modules, and special modules.

2.8  references

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Dekkers, R. 2006. “Engineering Management and the Order Entry Point.” International Journal of Production Research 44, no. 18-19, 4011–25. doi:10.1080/00207540600696328

Dekkers, R. 2017. Applied Systems Theory, 2nd ed. Cham: Springer. Dekkers, R., C.M. Chang, and J. Kreutzfeldt.2013. “The Interface Between

‘Product Design and Engineering’ and Manufacturing: A Review of the Literature and Empirical Evidence.” International Journal of Production Economics, 144, no. 1, 316–33. doi:10.1016/j.ijpe.2013.02.020

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Frey, D. D., P.M. Herder, Y. Wijnia, E. Subrahmanian, K. Katsikopoulos, and D.P. Clausing, 2009. “The Pugh Controlled Convergence Method: Model-Based Evaluation and Implications for Design Theory.” Research in Engineering Design 20, no. 1, 41–58. doi:10.1007/s00163-008-0056-z

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Hinckeldeyn, J.,R. Dekkers, and J. Kreutzfeldt. 2015. “Productivity of Product Design and Engineering Processes—Unexplored Territory for Production Management Techniques?” International Journal of Opera- tions & Production Management 35, no. 4, 458–86. doi:10.1108/IJOPM- 03-2013-0101

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