# Managing Knowledge Needs during New Product Lifecycle Design on Quick-term Project Development
## QPD: Case Study of 24 Hours of Innovation – ETS Montreal

Luz-Maria Jiménez-Narvaez, Kimiz Dalkir, Mickaël Gardoni

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Luz-Maria Jiménez-Narvaez, Kimiz Dalkir, Mickaël Gardoni. Managing Knowledge Needs during New Product Lifecycle Design on Quick-term Project Development QPD: Case Study of 24 Hours of Innovation – ETS Montreal. 9th International Conference on Product Lifecycle Management (PLM), Jul 2012, Montreal, QC, Canada. pp.25-34, 10.1007/978-3-642-35758-9_3 . hal-01526160

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# Managing knowledge needs during new product lifecycle design on Quick-term Project Development QPD: *case study of 24 hours of innovation* –ÉTS Montreal

Luz-Maria Jiménez-Narvaez<fnref n="1" />, Kimiz Dalkir<fnref n="2" /> and Mickaël Gardoni<fnref n="1" />,<fnref n="3" />

**Abstract.** The research study analyzed the strategies used to managing knowledge during the definition of a new product, specifically, the conceptualization stage of preliminary product definition. This study analyzed knowledge needs and some performance conditions that R&D teams had to deal with within the context of QPD. The goal of this study was to understand the social and ICT factors that intervene during the process of product definition. A modified Benefit-Tools-Organization-Process-People (BTOPP) framework was used to describe the people, tools, processes and organization of R&D teams during the International Competition of “24 hours of innovation”. Results show that teams require a wide range of ICTs and a flexible knowledge support system.

**Keywords:** new product definition, knowledge needs, BTOPP framework, knowledge management of product lifecycle, Quick-term Project Development.

## 1 INTRODUCTION

In new product development, there is an implicit distributed interaction among different actors, particularly when R&D teams envision new product functionalities or new product life-cylce. An R&D team has to forecast more than 5 to 6 years into the future lifecycle of a new product. They must also integrate new user's needs and technological changes. It is a genuine challenge for organizations to capitalize on these knowledge sources by trying to predict how the new product will perform in an unknown context. From the social perspective, the challenge consists in sharing knowledge and interconnecting people that are imagining these future conditions. The team's distribution of ideas and knowledge can be observed: we can observe knowledge sharing among R&D agents, a distribution of the subject matter knowledge implicated and also a distribution of personal interests in the new product development, all of which are in turn related to the interaction between the expectations of consumers, producers and distributors.

<footnote n="1">¹ École de technologie supérieure, Automated Production Department, Montreal, Canada
luz-maria.jimenez.1@ens.etsmtl.ca, mickael.gardoni@etsmtl.ca</footnote>

<footnote n="2">² McGill University, School of Information Studies, Montreal, Canada
kimiz.dalkir@mcgill.ca</footnote>

<footnote n="3">³ INSA de Strasburg, Strasburg, France</footnote>
Table 1 shows the study conducted by Ulrich and Eppinger (2008) on the development of a new product which demonstrated that product complexity (number of pieces), organization team size (number of members in R&D implicated) and the time of development are all correlated. For a simple new product such as a screwdriver, at least three people are needed on the in-house team and three on the external R&D team (Ulrich & Eppinger, 2008). In a more complex product such as a Boeing 777, the internal design team is made up of 6,800 people and the external team and service suppliers consist of up to 10,000 people.

We can deduce that there also exists an interaction between different disciplinary knowledge fields with the result that contributions of each participant are interconnected to define the product lifecycle. The data also shows the role played by collaboration dynamics among the R&D staff and the main subjects for R&D, production and sales. The relationships between the size of design teams and variables such as product complexity - the number of pieces and the life cycle of a product - development time, sales lifetime, production investment and the sales price are also shown in Table 1.

<table><caption>Table 1 New Product resources comparison, by Ulrich and Eppinger (2008), p. 5</caption><thead><tr><th rowspan="2">Product Development Needs</th><th>Stanley Tools</th><th>Rollerblade</th><th>Hewlett-Packard</th><th>Volkswagen</th><th>Boeing</th></tr><tr><th>Jobmaster</th><th>In-Line</th><th>Deskjet</th><th>New Beetle</th><th>Boeing 777</th></tr><tr><th></th><th>Screwdriver</th><th>Skates</th><th>Printer</th><th>Automobile</th><th>Airplane</th></tr></thead><tbody><tr><th>Annual production volume (units/year)</th><td>100,000</td><td>100,000</td><td>4 million</td><td>100,000</td><td>50</td></tr><tr><th>Sales lifetime</th><td>40 years</td><td>3 years</td><td>2 years</td><td>6 years</td><td>30 years</td></tr><tr><th>Sales price</th><td>$6</td><td>$200</td><td>$130</td><td>$20,000</td><td>$200 million</td></tr><tr><th>Number of unique parts (part numbers)</th><td>3 parts</td><td>35 parts</td><td>200 parts</td><td>10,000 parts</td><td>130,000 parts</td></tr><tr><th>Development time</th><td>1 years</td><td>2 years</td><td>1.5 years</td><td>3.5 years</td><td>4.5 years</td></tr><tr><th>Internal development team (peak size)</th><td>3 people</td><td>5 people</td><td>100 people</td><td>800 people</td><td>6,800 people</td></tr><tr><th>External development team (peak size)</th><td>3 people</td><td>10 people</td><td>75 people</td><td>800 people</td><td>10,000 people</td></tr><tr><th>Development cost</th><td>$150,000</td><td>$750,000</td><td>$50 million</td><td>$400 million</td><td>$3 billion</td></tr><tr><th>Production investment</th><td>$150,000</td><td>$1 million</td><td>$25 million</td><td>$500 million</td><td>$3 billion</td></tr></tbody></table>

## ICT support needed for forecasting product lifecycle R&D or innovative teams

Despite the existence of an array of ICT services or knowledge toolboxes such as groupware options, extranet and intranet networks and databases that allow the knowledge exchange among R&D. The fact of adding communication tools did not alleviate the problem of effective exchange and communication in R&D teams. According with Gruber and Duxbury (2006) (cited by Dalkir, 2011), some possible causes are related to the difficulty of capturing knowledge that kind of forecasting knowledge, specially because the forecast information “is hard to find, there were different systems and no standards, the information was not where it should be, the tools were difficult to use and the database was difficult to access”(p. 234). It is not
enough to have modeling tools to support knowledge sharing, because satisfactory
team performance also depends on team dynamics: “training of knowledge retrieval,
to define a knowledge strategy that would categorize in a standard way, to standardize
the information technologies, and to create project web sites” (idem).

In the analysis of product lifecycle, we find approaches based in social demands as
client requirements (Forgues, 2006), consumers participation (Helander & Jiao, 2002)
or the product modelling with CAD technologies (Demoly, Monticolo, Eynard,
Rivest, & Gomes, 2010; Quintana, Rivest, Pellerin, Venne, & Kheddouci, 2010). We
observed that these approaches are complemented in a whole framework.

As the result of this reflection, we became interested in understanding and harness-
ing the complexity of managing knowledge needs of R&D teams: *What is the knowl-
edge acquired by a team when forecasting new lifecycle process? What types of tools
are needed create and share this knowledge?* We used the Benefits-Tools-
Organization-Process-People (BTOPP) framework, proposed by Morton (1975) in
*The Corporation of the 1990s*, and explained by Thorp (2012), to analyze the knowl-
edge needs to define the product lifecycle as a whole system. BTOPP describes the
benefits, the tools (information technologies), organization (structure and culture),
people (skills and experience) and processes (management practices, procedures)
(ibid, p. 72). Figure 1 shows an interpretation of BTOPP framework in defining the
knowledge management system. The BTOPP framework was used to analyze the
data collected in our case study/

<figure><img src="image_2.png" /><figcaption>Fig. 1. BTOPP Framework of Scott-Morton adapted for knowledge management system by Dalkir, 2011</figcaption></figure>

2 STUDY CASE DESCRIPTION

Our research team organized 24H, an international competition created by the
École Supérieure des Technologies Industrielles Avancées (ESTIA) in France and
sponsored by the École de Technologie Supérieure (ETS) in Montreal in partnership
with 400 members of the Specialty Vehicles and Transportation Equipment Manufac-
turers' Association (AMETVS). The objective is to develop innovative solutions
within the time frame of 24 consecutive hours. In the Fourth International competi-
tion, six universities participated, as shown in Table 2¹.

250 students, from a variety of design engineering disciplines and universities,
were divided into 40 teams of 5 to 10 members. Each team could freely select one
challenge<fnref n="2" />, to work on, given members' experience, knowledge and/or interests. They
then had to come up with an innovative solution to their problem. This solution has to
consider also all the product lifecycle process. The 24H teams developed complex
interactions through the knowledge acquisition process used to solve problems as well
as the knowledge that was shared to develop new products. Participants not only
needed to interact with co-located team members, but also with remote organizational
staff and industrial partners. In the early design stage, 24H teams searched for infor-
mation in order to understand the context of the new product. This information delimited the design problem and defined the goal/task to draft the new product concept.
Information was mainly through the Internet and distributed experts. They also made
use of support tools. During the competition, the research teams completed an online
questionnaire which captured biographical information and teamwork experience.
Open-ended questions were sent every two hours asking which design process stage
they were at, and what knowledge and tools they had needed and used. Participants
then completed and submitted a final user satisfaction questionnaire at the end of the
competition.

3 RESULTS

People: description of participants

Almost 250 students attended the competition and 142 agreed to participate in the research study. Each participant filled out the form every two hours only during periods in which they were working. On average, 50% completed and submitted the questionnaires. 57% were undergraduate students and 37% were Master's students. Approximately 73% said they frequently used from 1 to 5 groupware systems and 19% used more than 5 groupware systems. Most respondents were project development team members (69%) and 44% reported that had experience as a team leader. Students who had previously worked together tended to be on the same 24H team. 32% had not worked together for more than a year and only 19% responded that they had worked together for two years. 94% of participants reported that were comfortable working in teams. Table 2 shows how the teams were formed, including the number of members, the host university or institution and country of origin.

<footnote n="1">¹ For further information consult AMETVS's website:
http://www.transportail.com/en/nouvelles/nouvelle.asp?id=2230</footnote>

<footnote n="2">² For more details, please see: Montreal version:
http://etsinnovation.wordpress.com/2011/11/28/les-24-heures-de-linnovation-a-lets-les-gagnants-de-la-4e-edition-de-novembre-2011/</footnote>
<table><caption>Table 2. Team composition by participants and school</caption><thead><tr><th>Country</th><th>N.</th><th>Team</th><th>Participants</th><th>Institution</th><th>Domain</th></tr></thead><tbody><tr><td rowspan="10">Belgium</td><td>T1</td><td>Les Zips</td><td>5</td><td>ESA - Saint Luc</td><td>Industrial Design, Mechanical Eng.</td></tr><tr><td>T2</td><td>HEC-Ulg</td><td>6</td><td>HEC-Ulg</td><td>Bussiness</td></tr><tr><td>T3</td><td>ICW</td><td>5</td><td>HEC-Ulg</td><td></td></tr><tr><td>T4</td><td>Limitless conception</td><td>7</td><td>HEC-Ulg</td><td>Economics, MBA</td></tr><tr><td>T5</td><td>SAFEA's Troglodytes</td><td>8</td><td>HEC-Ulg</td><td>Economics, Bussiness Administration</td></tr><tr><td>T6</td><td>La fourmilière</td><td>4</td><td>HEC-Ulg</td><td>Finance</td></tr><tr><td>T7</td><td>ID-Brakers</td><td>5</td><td>HEC-Ulg</td><td>Economics</td></tr><tr><td>T8</td><td>Groupe1</td><td>5</td><td>HEC-Ulg</td><td>Finance</td></tr><tr><td rowspan="10">Canada</td><td>T9</td><td>Les zombilistes</td><td>3</td><td>ETS</td><td>Industrial and Electrical Engineering</td></tr><tr><td>T10</td><td>D-2913</td><td>6</td><td>ETS</td><td>Automatized Production Engineering</td></tr><tr><td>T11</td><td>15HP</td><td>7</td><td>ETS</td><td>Informatics IT, Mechanical Engineering</td></tr><tr><td>T12</td><td>INGénieuses</td><td>6</td><td>ETS, UTC TUBS</td><td>Mechanical Eng, Communications and Networks, Human Factors, Industrial Design, Aerospace</td></tr><tr><td>T13</td><td>Innov'UTC</td><td>9</td><td>ETS, UTC</td><td>Automatized Production Engineering</td></tr><tr><td>T14</td><td>Moonlight</td><td>3</td><td>ETS, UTC</td><td>Automatized Production Engineering</td></tr><tr><td>T15</td><td>MidgETS</td><td>7</td><td>ETS, UTC</td><td>Logistics and Operation Engineering</td></tr><tr><td>T16</td><td>Kandasamy</td><td>3</td><td>UNIV-MLV</td><td>Mechanical Engineering</td></tr><tr><td>T17</td><td>ESIPE-MLV</td><td>3</td><td>UNIV-MLV</td><td>Mechanical Engineering</td></tr><tr><td rowspan="10">France</td><td>T18</td><td>ESIPE 1</td><td>3</td><td>UNIV-MLV</td><td>Mechanical Engineering</td></tr><tr><td>T19</td><td>Purple</td><td>1</td><td>UNIV-MLV</td><td>Mechanical Engineering</td></tr><tr><td>T20</td><td>ESTIA-Zip</td><td>3</td><td>ESTIA</td><td>Mechanical Engineering</td></tr><tr><td>T21</td><td>Duck'y duck</td><td>2</td><td>UTBM</td><td>Design and mechanical Engineering</td></tr><tr><td>T22</td><td>Les 6 fantastiques</td><td>6</td><td>UTBM</td><td>Design and mechanical Engineering</td></tr><tr><td>T23</td><td>mécaZip</td><td>4</td><td>UTBM</td><td>Design and mechanical Engineering</td></tr><tr><td>T24</td><td>Les tuques</td><td>3</td><td>UTBM</td><td>Design and mechanical Engineering</td></tr><tr><td>T25</td><td>Les Woodchucks</td><td>6</td><td>UTBM</td><td>Design and mechanical Engineering</td></tr><tr><td>T26</td><td>Innov in the soul</td><td>4</td><td>UTBM</td><td>Design and mechanical Engineering</td></tr><tr><td>T27</td><td>The team of the time</td><td>5</td><td>UTBM</td><td>Design and mechanical Engineering</td></tr><tr><td>T28</td><td>Duck'y duck</td><td>4</td><td>ISA</td><td>Agro-research</td></tr><tr><td rowspan="10">Reunion Island</td><td>T29</td><td>Duck'y deck</td><td>7</td><td>ISEN</td><td>High Technology and Innovation Design, Agro-research</td></tr><tr><td>T30</td><td>Flo et les garcons</td><td>2</td><td>ISEN</td><td>High Technology and Innovation Design, Agro-research</td></tr><tr><td>T31</td><td>Barnique-veritas</td><td>6</td><td>ISEN</td><td>High Technology and Innovation Design, Electonics and Informatics, R&D</td></tr><tr><td>T32</td><td>Bazinga</td><td>4</td><td>ETS, Poly, UTBM</td><td>Design and mechanical Engineering</td></tr><tr><td>T33</td><td>Seven-Team</td><td>4</td><td>ISEN</td><td>High Technology and Innovation Design, Electonics and Informatics</td></tr><tr><td>T34</td><td>Team 1</td><td>5</td><td>Lycée Lislet Geoffroy</td><td>Electricotechnical</td></tr><tr><td>T35</td><td>Team 2</td><td>5</td><td>Lycée Lislet Geoffroy</td><td>Electricotechnical</td></tr><tr><td>T36</td><td>Team 3</td><td>5</td><td>Lycée Lislet Geoffroy</td><td>Electricotechnical</td></tr><tr><td>T37</td><td>Team 4</td><td>5</td><td>Lycée Lislet Geoffroy</td><td>Electricotechnical</td></tr><tr><td>T38</td><td>Team 5</td><td>5</td><td>Lycée Lislet Geoffroy</td><td>Electricotechnical</td></tr><tr><td>T39</td><td>Choc</td><td>5</td><td>Lycée Lislet Geoffroy</td><td>Electricotechnical</td></tr><tr><td>Senegal</td><td>T40</td><td>Teamud21</td><td>1</td><td>Université de Ziguinchor</td><td>Informatics</td></tr><tr><td></td><td></td><td>40 Team</td><td></td><td>187 Participants</td><td></td></tr><tr><td></td><td></td><td colspan="4">ESTIA-École Supérieure des Technologies Industrielles Avancées</td></tr><tr><td></td><td></td><td colspan="4">ETS- École de technologie supérieure,</td></tr><tr><td></td><td></td><td colspan="4">ISA - École de l'agriculture, l'agroalimentaire, l'environnement et du paysage à Lille</td></tr><tr><td></td><td></td><td colspan="4">ISEN- École d'ingénieur généraliste en haute technologie ingénieurs</td></tr><tr><td></td><td></td><td colspan="4">Poly-École polytechnique Montreal</td></tr><tr><td></td><td></td><td colspan="4">UNIV-MLV Université Paris-Est Marne-la-Vallée - Ecole d'ingénieurs par apprentissage des sciences et technologies</td></tr><tr><td></td><td></td><td colspan="4">UTBM-Université de Technologie de Belfort-Montbéliard-</td></tr><tr><td></td><td></td><td colspan="4">UTC-Université technologique du Compiègne</td></tr></tbody></table>

## B. Process of knowledge acquisition

Managing the process of product definition must be considered as a “focus on end-to-end service delivery” (Jiménez-Narváez et al., 2012, p. 73). It is related with how “management
practices and work procedures must be adjusted and changed to mesh with the major processes, such as product design and order processing" (idem). In this way, we identify a knowledge distribution in three axes constituted by three kinds of knowledge sources to achieve a new product development. First, we see the knowledge provided by the market and the valour chain: consumer expectations, distributors and sales information. Second, sharing knowledge provided by stakeholders and product designers, generally the information or briefing of a new product comes from sales, production and design departments. Third, knowledge about main technology or scientific knowledge involved in the new product conceptualization and the technological Watch results. R&D teams and partners have to integrate this variety of knowledge in a conceptual product definition. Figure 2 shows participants acquire knowledge to define a product from the Internet and search engines (45%) and from people or consumer information sources (27%). In the first stage of problem definition, 12% of the sources include external and internal experts and industrial constraints. The external expert also has a role at the end during the codification stage (14%). Industrial constraints are consulted 20% of the time during the conceptualization stage.

<figure><img src="image_3.png" /></figure>

<table><caption>Fig. 2. Information sources for product definition in the early design stage</caption><thead><tr><th></th><th>6H - n</th><th>%</th><th>14H - n</th><th>%</th><th>22H - n</th><th>%</th></tr></thead><tbody><tr><td>People - consumers</td><td>16</td><td>27,12</td><td>11</td><td>25,00</td><td>2</td><td>28,57</td></tr><tr><td>Internet - research</td><td>26</td><td>44,07</td><td>21</td><td>47,73</td><td>3</td><td>42,86</td></tr><tr><td>Clients - industrial constraints</td><td>3</td><td>5,08</td><td>9</td><td>20,45</td><td>1</td><td>14,29</td></tr><tr><td>External expert</td><td>7</td><td>11,86</td><td>1</td><td>2,27</td><td>1</td><td>14,29</td></tr><tr><td>Internal expert</td><td>7</td><td>11,86</td><td>2</td><td>4,55</td><td>0</td><td>0,00</td></tr><tr><td>Other</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr></tbody></table>

The open-ended questions identified the most important activities during the conceptualization stage, were: exchange of ideas about new technology development (including showing videos demonstrating existing technologies), brainstorming, discussions of different points of view on the prototype, use of different tools such as GoogleDocs so everyone could pool their ideas in one place, seeing commonalities, weighting ideas using criteria in order to identify the best idea and eventually achieving consensus on the unique solution. Participants used tools such as mind mapping,
post-its or flip charts to define users' needs and conceptualize a solution using meth-
odologies such as TRIZ<fnref n="3" /> or C-K<fnref n="4" />.

C. Organization

The structure of the organization is mainly related to teamwork dynamics and knowledge flow during the 24H session. At the beginning of event, as illustrated in Figure 3, Challenge Presentation (CP) stakeholders and Competition staff presented information using a PowerPoint presentation. This information was transmitted via a WebEx videoconference to participants in universities in France, Belgium and Senegal. Teams captured the knowledge needed to define a project using a knowledge toolbox that consisted of: search engines, patent database, and photos and videos (YouTube). The team also shared this information with some task and documents managers using Google groups, DropBox and email. Some participants used a LMS (Learning Management System) platform available to their universities. MS Project, MindManager, or Freemind were used to represent knowledge. This ICT richness decreased as the team defined the project more. Teams used paper-based tools in the second stage of Solution definition. Finally, ICT tools were only used for the Project Presentation (PP) stage, as shown in Figure 3. During this third stage, teams only used ICT technologies for a project outline, using standard design software and presentation tools (PowerPoint and MS MovieMaker).

D. Technology: use of ICT tools

As shown in Table 3, we assessed each team’s ability to identify tasks and tools used for knowledge acquisition in three phases: “identification, conceptualization and codification” (Dalkir, 2012, p. 117). We assumed that task activity and project were strongly correlated with ICT technologies and also with knowledge sharing processes (Gottschalk, 2005; Rao, 2005b). Koulopoulos & Frappaolo (2000) affirm that ICT technologies are important vehicles for knowledge sharing because they mediate the interaction (groupware), contribute to knowledge externalization: sharing and retrieving documents, knowledge visualisation (portals); they contribute to knowledge internalization by providing training and resources to connect novices and experts (Learning Modeling Systems LMS), and finally, ICT technologies support workflows and decisions.

<footnote n="3">³ TRIZ, from acronyme russian ARIZ (Altgoritm Reshenia Izobretatelskih Zadach) is the Theory of Inventive Problems Solving proposed by Genrikh Altshuller in 1946. Altshuller studied more of 1000 patents to identified the algorithme ARIZ and 40 principles of contradiction used by inventors. (Kolb, 1984)</footnote>

<footnote n="4">⁴ C-K, Concepts and Knowledge, is a method of reasoning on design to define the limits between the concepts and the knowlege of a new product. Method developed by Hatchuel and collaborators. (Hatchuel & Weil, 2002)</footnote>
<figure><img src="image_4.png" /><figcaption>Fig. 3. ICT tools in knowledge acquisition during project development</figcaption></figure>

R&D teams responded that they required tools to “critical” to realize the project definition” (see Table 3). To assess these critical tools, we used the definition of “critical” need by Collins (2007), cited by Rao (2005a), who defines five levels of critical need “*critical, must have, important, nice to have and non-critical*” to sustain team performance.

<table><caption>Table 3. Critical tools to be used during a new product development</caption><thead><tr><th>Project Stage</th><th>Activities</th><th>ICT-based Tool</th><th>Non ICT-based Tool</th></tr></thead><tbody><tr><td rowspan="5">Problem definition</td><td>Inspiration</td><td>Internet Engine</td><td rowspan="5">Simulations and body language</td></tr><tr><td>Watch technology</td><td>Patents Database</td></tr><tr><td>Art state</td><td>Youtube</td></tr><tr><td>Sharing links and files (Sharing content)</td><td>Google docs<br/>Google groups<br/>Dropbox</td></tr><tr><td>Brainstorming – collective idea production</td><td>Brain, Freemind</td></tr><tr><td rowspan="3">Discussion</td><td rowspan="3">Communication tools</td><td>e-mail</td><td>Paper-Pencil</td></tr><tr><td>Skype (audioconferencing)</td><td>Board – markets</td></tr><tr><td>Webex (videoconferencing)</td><td>Post-it</td></tr><tr><td rowspan="4">Solution definition</td><td>Definition</td><td>Internet Engine<br/>Google docs<br/>MS-Word</td><td>Images<br/>Paper-Pencil<br/>Excel</td></tr><tr><td>Idea definition</td><td>Catia, Rhinoceros<br/>MS-Power Point<br/>Blackboard</td><td>Drawings, plans,<br/>models</td></tr><tr><td>Discussion</td><td>e-mail</td><td>Paper-Pencil</td></tr><tr><td>Communication tools</td><td>Skype (audioconferencing)<br/>Webex (videoconferencing)</td><td>Board – markets<br/>Post-it</td></tr><tr><td rowspan="2">Project definition</td><td>Idea definition</td><td>Catia, Rhinoceros,<br/>Solidworks<br/>MS-Power Point<br/>MS Movie-maker</td><td>Drawings, plans,<br/>models</td></tr><tr><td>Communication Tools</td><td>Dropbox<br/>Skype (audioconferencing)<br/>Webex (videoconferencing)</td><td>Co-presence or<br/>remote: verbal<br/>notations</td></tr></tbody></table>
## E. Benefits

When R&D teams use KM practices, they profit from a “benefits flow” (Jiménez-Narváez et al., 2012). They improve their knowledge acquisition by consulting creative or innovative sites, particularly at beginning of problem definition. This activity consists of searching of images, photos and videos through Internet-search engines and innovation or technology websites. This allows teams to develop an effective strategy to envisage an innovative evaluation (e.g. through technology watch or functional analysis methods). Table 4 shows the Internet was used on average 25% to support this process. Contrary of the widespread belief on the importance of CAD software, R&D teams, at least at beginning of project definition, did not report extensive use of CAD until the conceptualization stage to define measures, establish volume/material or technical constraints. 15% used CAD for conceptualization and 17% used CAD for codification and presentation of the project. This demonstrates that R&D needs involve a wide range of ICT tools.

<table><caption>Table 4. Variation of use of ICT Tools during Project development</caption><thead><tr><th rowspan="2">Software Used</th><th colspan="2">Problem definition</th><th colspan="2">Conceptualization</th><th colspan="2">Codification</th></tr><tr><th>6H - n</th><th>6H - %</th><th>14H - n</th><th>14H - %</th><th>22H - n</th><th>22H - %</th></tr></thead><tbody><tr><td>Skype - Webex - video conference</td><td>5</td><td>6%</td><td>4</td><td>6%</td><td>6</td><td>11%</td></tr><tr><td>Concept maps - mind mapping</td><td>5</td><td>6%</td><td>7</td><td>11%</td><td>2</td><td>4%</td></tr><tr><td>Drawing - Paint</td><td>14</td><td>17%</td><td>16</td><td>25%</td><td>7</td><td>13%</td></tr><tr><td>Internet - Search engine</td><td>25</td><td>31%</td><td>16</td><td>25%</td><td>13</td><td>25%</td></tr><tr><td>Photos, images or videos</td><td>16</td><td>20%</td><td>9</td><td>14%</td><td>9</td><td>17%</td></tr><tr><td>CAD</td><td>6</td><td>7%</td><td>10</td><td>15%</td><td>9</td><td>17%</td></tr><tr><td>Innovation sites - Methods</td><td>8</td><td>10%</td><td>2</td><td>3%</td><td>4</td><td>8%</td></tr><tr><td>Other</td><td>2</td><td>2%</td><td>1</td><td>2%</td><td>3</td><td>6%</td></tr></tbody></table>

## 4 CONCLUSION

Our goal was to model the process of knowledge acquisition and the use of KM tools for new product development and to describe the kind of knowledge management and resources (BTOPP framework) that can support the definition of a new product and its lifecycle so teams may be more effective in sharing ideas during a QPD project. We conclude that innovation tasks require knowledge acquisition tools that allow designers to easily manage information found on the Internet. R&D teams also need a flexible system of knowledge acquisition and sharing because the knowledge flow is variable and it depends on the design stage.

In this study, we demonstrated how the knowledge is distributed in different fields or disciplines. R&D teams work to compile the knowledge using a wide range of strategies and ICT-based tools. The BTOPP framework can be used to profile an integrated system of knowledge sharing between ICT-based tools and social dynamics.

In future research, we will focus on defining the causal relationships between the knowledge distribution, the use of Internet and the knowledge management system that could join together participants' knowledge production and sharing activities.
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