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2023 | OriginalPaper | Buchkapitel

14. Specifying the Product

verfasst von : Marco Cantamessa, Francesca Montagna

Erschienen in: Management of Innovation and Product Development

Verlag: Springer London

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Abstract

In order to support the design of a product or service, it is necessary to translate the outcomes of Chap. 13 in technical terms, deriving precise requirements and specifications. This chapter discusses the approaches and methods that can be used to this purpose, with a special focus on customer-centered design methods, and on the definition of target costs, taking into account a lifecycle perspective and estimating experience economies.

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Vorheriges Kapitel From Market Research to Product Positioning

Nächstes Kapitel Designing Products and Services

If one thinks about a simple product such as the remote controller for a TV set, a user need elicited during market research may be “I don’t want to have to put my eyeglasses on when operating the remote control”. The firm may therefore decide to cope with this need by asserting the following requirement ‘button labels must be readable in 50 lx (dim light) by a user having a visual impairment of −1 diopters’. The requirement may then be translated into a specification such as ‘characters for button labels must be between 6 and 8 mm tall and must be color-contrasted with their background’.

In the remote controller example, it is up to the company to decide on the degree of readability of button labels with respect to illumination level and the degree of visual impairment, and to decide whether 6 mm tall and color-contrasted characters would adequately meet such requirement.

When defining character size for button labels, the designer is assuming that the remote control will be operated with physical buttons, which is only one of the many possible technical solutions allowing the required functions to be carried out (for instance, a remote control might be conceived with a touch screen-based interface).

For instance, suppose users of a high-end digital camera ask for a ‘reliable’ product, where ‘reliability’ implies a defined number of years before the product fails and has to be replaced. The manufacturer will probably view a connection between this need and the expected lifetime of the mechanical shutter, expressed in thousands of actuations. However, it will be possible to connect the requirement to a specification only if the manufacturer correctly defines the ‘mission profile’ of the camera. In this simple example, the product brief might recite: ‘this camera is aimed at photography enthusiasts and professionals who need a stand-in product along to their main camera’. The manufacturer will therefore have to define the number of yearly shutter actuations that can be expected to be made by the customers belonging to these two segments.

User-centered Design actually merges three different Design approaches, and namely Cooperative Design, from the Scandinavian tradition of Design of IT artifacts (Greenbaum and Kyng 1991), Participatory Design*, by the North American Design school (Schuler and Namioka 1993), and Contextual Design*, that connects customer-centered design to the actual circumstances surrounding the ‘use situation’ (Beyer and Holtzblatt 1997). User-centered design has become a formalized procedure through the ISO standard: the “Human-centred Design for interactive systems” (ISO 9241-210 2010).

As a reminder, in Chap. 13 we made the example of a persona such as ‘Marie, 35-year old IT professional, mom of two children (4-year old Susie and 2-year old Jean). She is the wife of Robert, an airline pilot who is often away from home. They live in an apartment in the XV Arrondissement of Paris’. To the family, one may add ‘Jeanne, Robert’s 70-year old mother, who lives close to Robert and Marie and sometimes borrows their car to visit her friends during the weekend’.

For example, a scenario associated to Mary’s usage of the family car might be ‘Mary has collected her kids from school and now is in the grocery store’s parking lot, having to move items from the shopping cart to the trunk of the car’. This scenario can be further split into a best-case scenario such as ‘the sun is shining, the kids are happy and singing a song’, and the worst-case scenario ‘it’s raining heavily, the kids are crying and a phone call is coming from Singapore, where Robert is minutes away from taking-off for a long-haul flight’.

A distinction can be made between slips and mistakes, the former being errors in the execution of appropriate actions, the latter being errors associated to the very action to be taken. For instance, a slip occurs if a user that must press a button presses both the right one and—inadvertently—another one that is located too close. It would be a mistake if the user pressed the wrong button, having misunderstood the functions associated to it.

For instance, commonly available lane departure warning systems (classified by SAE as ‘level 0’ devices in their classification of driving automation) augment drivers’ perception by providing feedback if the vehicle leaves the lane, for example, by making the steering wheel vibrate. Note that these devices provide feedback that is directly tied to the human control, thus making it easy to interpret (e.g., a buzzer would not fully meet this criterion), and still allow the driver to override them by force, thus allowing to control the car in case of emergency. The situation is different for lane centering systems (SAE levels ‘1’ and above) in which the car can automate, though under given conditions, the task of driving.

The bias emerges because product developers usually have a technical competence and an inclination for technology that is far superior to users. Moreover, the target customer segment can be significantly different from the one that the product development team is used to consider (e.g., a team that has to develop a new car model for a geographical market in which the team has no prior experience).

These average ratings should not be computed on the entire sample used for market research, but only on the subset of respondents that can be associated to the customer segment the product is being targeted to.

For instance, in a passenger car it makes sense to specify maximum speed and acceleration, but not engine horsepower and torque, which would be the corresponding specifications at engine level.

For instance, a firm may set the price of a product by computing the annual savings or profits P it determines on a customer firm and hypothesizing that customers will purchase it if its price PR ≤ P PBT, where PBT is a payback time.

For instance, parametric models can be based on rules, such as ‘surface treatment X costs 22 €/m²’, or ‘with technology Y, the cost of producing parts like this is about 12 €/cm³, adding 2 € per each geometric feature to be machined’.

For instance, a die used in an injection molding process will be a fixed cost up to a given production level. After that threshold is passed, the firm will have to invest in a second die.

For instance, if the cost driver used is direct labor hours, the firm will first compute the total annual cost of the overhead cost pool, TAC, and the total labor hours worked, TLH. It will then determine an ‘overhead rate’ of TAC/TLH €/hour, which will be added to the direct costs of the product.

A difference is sometimes made between learning effects and curves (Wright 1936) and experience effects and curves (Henderson 1974), the former related to labor productivity and the latter to overall efficiency. The two phenomena follow mathematical models that are equivalent, and we will therefore consider the two interchangeably in the following discussion.

For a review of learning curve models, readers may refer to Anzanello and Fogliatto (2011).

When dealing with continuous improvement projects, it is customary to say that it is easy to ‘pick low-hanging fruit’ at first, but that things become quite harder as time goes by. Following on this analogy, exponential learning would be as if fruit had already fallen on the ground, and one simply had to find it hidden in the grass.

For example, if customers are unwilling to pay a higher price for a system that has very low maintenance costs, a producer might find it highly profitable to start leasing it. This is especially true if the producer is able to secure finance at low interest rates, while customers base their purchasing decisions on short-term criteria such as Payback Time.

More precisely, ISO 14000 standards define LCA as the “compilation and evaluation of the inputs, outputs and potential environmental impacts of a product system throughout its life cycle”.

Public databases are often used to this purpose. For instance, a washing machine manufacturer may wish to compute the energy consumed to produce the casing of each machine. The team will multiply the weight of steel used in each machine times a standard parameter that expresses the specific energy that goes in each kg of steel (kWh/kg). To this, they will add the kWh used internally to stamp and weld the steel casing of each machine.

In the previous example, the firm may translate the kWh/unit in terms of CO₂ emissions, based on the country’s energy mix (again, using publicly available data).

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Titel: Specifying the Product
verfasst von: Marco Cantamessa
Francesca Montagna
Verlag: Springer London
Buch: Management of Innovation and Product Development
Print ISBN: 978-1-4471-7530-8

Electronic ISBN: 978-1-4471-7531-5

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-1-4471-7531-5_14

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