Aligning R&D to Business Strategy A Longitudinal ... - Semantic Scholar

Proceedings of the 39th Hawaii International Conference on System Sciences - 2006

Aligning R&D to Business Strategy A Longitudinal Study from 1997 to 2002 Frances T.J.M. Fortuin and S.W.F. (Onno) Omta1 Department of Business Administration, Wageningen University P.O. Box 8130, 6700 EW Wageningen, The Netherlands

Abstract The present paper addresses the important issue of the alignment of corporate R&D to business strategy, by presenting the CUSVALIN model (Customer Value Learning in INnovation). This empirical model typically assesses the gaps between the self perception of the R&D staff and that of their internal BU customers on the dimensions: strategic alignment, responsiveness, timeliness, R&D-BU communication, and perceived R&D performance. The CUSVALIN model has been tested in a longitudinal survey from 1997 to 2002 (696 R&D and BU responses) in a large technology-based industrial company (+/- 30,000 employees world-wide). It is concluded, that the CUSVALIN model can be used to monitor R&D-BU perception gaps, and that the regular feedback provided by this monitoring leads to better alignment of R&D to corporate strategy.

1. Introduction In today’s markets, characterized by fierce global competition and increasing customer demands, attaining product superiority by conducting superior R&D (Research and Development) is an important strategy for survival and growth. Watson [20] emphasizes this by stating: ‘Companies that want to compete successfully must offer quality beyond competitors, technology before competitors and cost below competitors’. Consequently a number of authors have developed methodologies to assess and improve the quality of the R&D process [e.g. 3, 6, 7, 10, 15, 18, 22]. However, most of the R&D management literature so far is based on industries characterized by relatively short product life cycles, such as the computer industry. Companies in long life cycle industries, such as pharmaceutics and aviation, are typically confronted with a long time span between the emergence of a novel idea and the final launch of the product to the market, sometimes more than 10 years later. Being so far ahead, this often results in a gap between the perception of the corporate R&D lab and 1

its internal customers, what may result in a lot of tension, R&D being criticized of not being aligned to business needs. In R&D management literature spends is relatively little attention for this important issue. Many of the above cited studies either ignore the customer perception (by only focusing on the R&D staff's opinion [e.g. 7] or focus on ex-post analysis of success or failure of the newly developed products and processes [6]. It is the aim of the present paper to fill up this gap by addressing the issue of R&D performance from a customer value perspective [19]. This study is part of a larger research program aimed at comparing the R&D management metrics used in short and long life cycle industries. The main research questions we want to address in this paper are: 1. Is it possible to device an instrument to monitor R&D performance, by evaluating the perception gaps regarding R&D quality between the corporate R&D staff and their internal business unit (BU) customers? 2. If so, can the feedback provided by such an instrument, be used to improve the alignment of R&D to corporate strategy and ultimately to higher R&D performance, as perceived by the internal customers? We have structured the paper as follows. Section 2 describes how the CUSVALIN model monitors customer value in an R&D environment. The different dimensions of the CUSVALIN model: strategic alignment, responsiveness, timeliness and R&D reporting and perceived R&D performance, are introduced. In addition, the longitudinal application of a questionnaire, based on the model, leading to improved R&D management metrics is discussed in this section, as well as the (theoretical and empirical) background of the different propositions. Section 3 describes the research methods and the methods of data collection. Section 4 presents the empirical results of the longitudinal application of a questionnaire, based on the CUSVALIN model in the corporate R&D laboratory of a multinational company (+/30,000 employees’ world wide) in a long life cycle industry from 1997 to 2002 inclusive. Finally, in section 5 the main

[email protected], and [email protected]

0-7695-2507-5/06/$20.00 (C) 2006 IEEE

1


results are discussed in the light of the management metrics taken by the R&D management, and the general measures taken by the corporate head office in the same period, and the effectiveness of the CUSVALIN model is evaluated.

2. Theoretical Framework The CUSVALIN model (see figure 1) is based on the customer value map developed by Haar et al. [12] who adapted model is the definition of R&D quality in terms of the comparison of the delivered value as perceived by the corporate R&D lab and the received value as perceived by the customer [13]. Depending on the width of this gap the customer is satisfied or not. Therefore, in the present study the self-assessment of different aspects of quality by the corporate R&D staff is compared with an assessment of the same aspects by the most important internal customers in the Business units (gap analysis). It is hypothesized that there are gaps between the two, based on a number of misinterpretations during the R&D delivery process, which can be bridged by regular R&DBU communication, e.g. by using a structured questionnaire, based on the CUSVALIN model. From this we derive at the main proposition of the present study. Main proposition: Regular feedback from the internal BU customers, as provided by the CUSVALIN model will diminish the gap between the BU assessment and the R&D self assessment of R&D performance and will eventually raise R&D performance, as perceived by the BU customer. CORPORATE R&D

Intended Value

Gaps

Strategic alignment Responsiveness

Design gap

Designed value

R&D reporting

Timeliness Perceived performance

Figure 1. Gaps between the value maps of the corporate R&D staff and the internal BU customers, bridged by structured R&D-BU communication (ļ)

the SERFQUAL model of Zeithaml et al. [21] to assess the value of innovation services. It is based on the observation that companies deliver value, and customers choose that value that best fits their needs, i.e. that provides the best trade-off between benefits and sacrifices, such as cost and time spent [e.g. 8, 9, 14]. However, this trade-off is complicated by differences in the value perception between the deliverer and the receiver. This is even more pressing in an R&D environment. Therefore, the basic feature of the CUSVALIN Figure 1 shows the value maps of the R&D staff and the internal Business Unit customer, as well as the gaps between these maps, as they develop in the successive stages of the innovation process. The term value map is used to indicate that the customer value of a product or service consists of several dimensions, which all play a role in the customer's overall quality perception. The dimensions of R&D quality we use in the present study are strategic alignment, responsiveness, timeliness, R&D-BU communication, and perceived R&D performance. Burgelman [in 17] argues that experience with ("performing") a strategy will have feedback effects on the set of organizational capabilities. In the case of the CUSVALIN model this works as follows: the feedback provided by its application at time T0 enables R&D management to address specific problems with targeted metrics. The subsequent measurement with the CUSVALIN model at time T1 will provide information on the effect of these metrics, and will lead to adjustments or new metrics, the effect of which can be measured at time T2 etc. It is proposed that as the INTERNAL CUSTOMER R&D-BU communication improves over time the regular feedback will lead to a learning loop that will Desired Value lower the gap between the R&D and BU assessment. We propose that the reduction over time of the Compromise gap R&D-BU perception gaps will not be evenly distributed over the different phases of the Expected value R&D process, because of practical constraints that build up during the course of this process. At the initial phase from idea conception to inclusion into the corporate R&D portfolio, getting alignment between R&D and corporate business strategy is critical [1, 2, 5]. In the stage of R&D project inclusion, the pace the R&D centre is able to incorporate the most promising BU requests into the R&D portfolio becomes an important value aspect (responsiveness to BU requests'). When an innovative idea has to be materialized into an R&D project it has to compete with a

2


number of other ideas that deserve attention, and are interesting to be included into the R&D portfolio. In this stage improved R&D-BU communication by use of the CUSVALIN model can assure that the gap between the desired value by the business units and the intended value by the corporate R&D lab (see figure 1) will be closed for a substantial part, leading to improved strategic alignment of R&D to business needs. We therefore propose that: Proposition 1: Improved R&D-BU communication by use of the CUSVALIN model in the course of the investigation period will considerably reduce the R&D-BU gap, and will considerably improve the BU assessment on the strategic alignment of R&D. As Goldman and Nagel [11] indicate in the execution phase agility is crucial to reduce R&D lead-time and to capture market opportunities. They identify the twin characteristics of agility to be flexibility and speed. Where flexibility is captured in responsiveness, speed is captured in 'timeliness of project execution' in the present study. In this phase speed of project execution may be seriously hampered by design problems, either of a technical nature, or concerning lack of the necessary competencies and capabilities, which may cause the project to be (severely) delayed or even stopped. It is also possible, that the practical design constrains will lead to (major) changes in the R&D project. If this is not adequately communicated to the BU customers this may lead to a gap between the designed value by R&D and the expected value by its internal BU customers [12], hence adequate ‘R&D reporting’ is very important in this stage. If well informed, the BU consumer will have understanding for the design problems that R&D has encountered (the design and compromise gap, see figure 1 [12]). Finally, after the delivery of the project results to the Business Unit customers, they can give their assessment of R&D performance. It is expected, that their perceived performance will be a resultant of the previous gaps. We therefore propose that: Proposition 2: improved R&D-BU communication will moderately reduce the R&D-BU gap, and will moderately improve the BU assessment on timeliness, and R&D performance.

3. Research methods and data collection Table 1 provides an overview of the operationalization of the different dimensions used in the present study. To assess the performance of corporate R&D, respondents from the R&D lab and their customers in the BUs were asked to indicate the relative importance of a number of R&D objectives, ranging from basic research via applied research to engineering. Then the respondents were asked to assess the lab's performance on each of these objectives. To assess the items reflecting the dimension of strategic R&D alignment the respondents were asked how well the R&D projects aligned with important technologies and with market needs. Responsiveness was captured by the lab’s flexibility to

incorporate new R&D projects into the corporate R&D portfolio, and the pace of starting-up these projects. Table 1. Operationalization of the dimensions of the CUSVALIN model

Strategic alignment (4 questions using seven-point Likertscales ranging from strongly agree to strongly disagree, Cronbach Į = 0.85) - Strategic alignment of R&D to corporate strategy in terms of technologies and market needs. Agility: Responsiveness (2 questions using seven-point Likert-scales ranging from strongly agree to strongly disagree, Cronbach Į = 0.73) - Ease of incorporation of Business Unit's requests in the corporate R&D portfolio and start-up time lag of R&D projects. Agility: Timeliness (3 questions using seven-point Likertscales ranging from strongly agree to strongly disagree, Cronbach Į = 0.68) - The number of projects which are perceived to be delivered before or conform the agreed date. - The average project cycle time; - The time lag to answer technical questions. R&D reporting (9 questions using seven-point Likert-scales ranging from strongly agree to strongly disagree, Cronbach Į = 0.64) - Customer communication, i.e. regular project progress reports and information meetings between the laboratory and customers to assess - Market and competitor information; - Quality aspects and analysis of complaints; Staff exchange; - Project communication improvement. Perceived performance (2 x 6 questions using five-point Likert-scales ranging from strongly agree to strongly disagree, with no verbal labels for the intermediate scale points, Cronbach Į = 0.72) - Relative importance of R&D’s objectives: 1. expanding the company’s technology knowledge base 2. Developing new technology in a product/process area. 3. Offering new technology for cost reduction. 4. Translating existing technology in a new product or process area. 5. Developing new product or process tests. 6. Contributing to the improvement of product or process designs. - The lab’s perceived performance per objective. - Objective weighed performance, the lab’s achievements weighed for the relative importance of its objectives. Timeliness was measured as the average cycle time of R&D project execution, the number of projects delivered at promised

3


date and the time lag to answer technical questions. The aspect of R&D–BU communication was assessed on a number of communication aspects around R&D project execution and project reporting as well as in terms of the respondents’ opinion on the importance of R&D-end user communication. The items representing the various dimensions were generated by expert inquiry to form the initial pool for the questionnaire. The process resulted in the generation of 61 items (approximately 12 items per dimension). These 61-items were subjected to two stages of data refinement. The first stage focused on condensing the instrument by retaining only those items capable of discriminating across respondents having different value perspectives, and examining the dimensionality of the scales and establishing the reliabilities of its components. The second stage was primarily confirmatory in nature and involved re-evaluating the condensed scale’s dimensionality and reliability by retesting the scale. Some further refinements occurred in this stage. In the 5 years that the longitudinal study was conducted the core of the questionnaire has remained unchanged, although some minor changes have been introduced. The questionnaire uses five-point Likert-scales for the R&D objectives and the R&D performance dimensions, and sevenpoint Likert-scales for the other dimensions, ranging from strongly agree to strongly disagree, with no verbal labels for the intermediate scale points. The construct validity is acceptable, the Cronbach Alpha of the five dimensions ranged from 0.64 to 0.85 (see table 1), within the generally accepted guidelines for measuring organizational attributes. Several items were negatively worded to reduce response tendencies by the respondents [4]. These items were reverse-scored for use in the analyses, in order to ensure that a higher assessment in all cases reflects a more positive judgement of the item at issue. Best fitting curve analysis was conducted, using linear and second order polynomial trend approximation. For the analysis of the gaps between the assessments given by respondents from the Business Units and the self-assessments given by the R&D staff, two-tailed t-tests were used. Non-parametric analyses of group means, using the Kruskal-Wallis test, did not alter the conclusions.

30,000 employees worldwide, working at 83 production sites in 24 countries. The annual sales volume in 2002 amounted to about US$ 5 billion, with an operating profit margin of about 8%. In 1997, 1998, 2000 and 2002 the CUSVALIN Questionnaire was sent to the staff of the corporate R&D laboratory and those staff members of the business units, who are in (regular) contact with this lab. Table 2 shows the number of respondents per year, as well as the response rates of BU staff and staff of the R&D laboratory. The total study population consisted of 696 respondents, with an average of 174 respondents per year. The average response rate was 48%, although the response rate was clearly going down, probably because of questionnaire fatigues.

4. Results As was described in section 2, the CUSVALIN model works as follows: the feedback provided by the questionnaire at time T0 enabled R&D management to address specific problems with targeted metrics. The subsequent measurement at time T1 provided information on the effect of these metrics, and led to adjustments and new metrics, the effect of which were measured at time T2 etc. In this section the results of these measurements are presented. The management metrics taken after each measurement are discussed in section 5. For the sake of clarity of presentation, we selected per variable one item that is most representative for the outcomes on that variable. The authors are still working on more detailed analyses of the longitudinal dataset.

4.1 Strategic R&D Alignment Product and process alignm ent

5.60

1997 BU 147 (63%) R&D 69 (70%) Total 216 (65%)

1998 189 (48%) 67 (70%) 256 (51%)

2000 102 (36%) 44 (67%) 146 (43%)

2002 45 (28%) 33 (70%) 78 (38%)

% = number of respondents divided by number of questionnaires sent out The data were collected in a multinational supplier company of technology-based industrial components for different industries, especially automotive. The company employs about

5.71

y = -0.0817x 2 + 326.66x - 326682 R2 = 0.9746

5.40

5.52

5.46

5.33

5.20 5.00

Table 2. Number of R&D and BU respondents and response rates, 1997-2002

5.84

5.80

5.00 y = -0.0618x 2 + 247.37x - 247693 R2 = 0.9757

4.80 4.60 4.40 4.26

4.20 4.00 3.90 3.80 1996

1997

1998

1999

2000

2001

2002

2003

Figure 2. Strategic alignment of corporate R&D to BU needs, product and process alignment Blue line = perception of corporate R&D staff Red line = perception of BU customers

4


As can be seen in figure 2 and Table 3, the BU assessment regarding the strategic alignment of the corporately funded R&D projects improved considerably over time, and the gap between the BU's assessment and the R&D self assessment has totally disappeared in 2002. Both findings support Proposition 1: Improved R&D-BU communication by use of the CUSVALIN model in the course of the investigation period will considerably reduce the R&D-BU gap, and will considerably improve the BU assessment on the strategic alignment of R&D. Table 3. Strategic alignment of R&D to BU needs, mean and standard deviation (between brackets) 1997 1998 2000 2002 R&D 4.03 (1.53) 4.17 (1.42) 5.02 (1.02) 4.64 (1.03) BU 3.33 (1.31) 3.49 (1.34) 4.60 (1.04) 5.02 (0.99) PG 0.70 *** 0.68*** 0.42* - 0,39 p: * < 0.05; ** p < 0.01, *** p < 0.001

4.2 R&D Responsiveness The results on R&D responsiveness show a similar pattern as those for strategic alignment, namely a clear tendency of rising Business Unit assessment, and closing of the gap between Bu and R&D assessment. In the item shown in table 4 (ease of incorporation of BU projects in the corporate R&D portfolio), the gap between the BU and the R&D assessment has even reversed, indicating that The BU customer assessment has become higher than the R&D staff self assessment. This means, that it has become much easier for BU customers to get their projects incorporated in the R&D portfolio. These findings are stronger than expected in Proposition 2: Improved R&D-BU communication will moderately reduce the R&D-BU gap, and will moderately improve the BU assessment on responsiveness, timeliness, and R&D performance. Table 4. R&D responsiveness, ease of incorporation of R&D projects, mean and standard deviation (between brackets) 1997 1998 2000 2002 4.25 (1.53) 4.75 (1.47) 4.58 (1.55) 4.58 (1.80) 3.87 (1.66) 3.96 (1.60) 4.49 (1.54) 4.80 (1,85)

PG

0.39

0.8 ***

0.09

The results on timeliness show a positive, but much weaker effect than on the former aspects. Table 5 shows a representative item: the assessment of R&D project cycle time. The trend in the Business Units assessment clearly indicates that the feed back has had its positive effects, but the improvement is only moderate, as was expected in proposition 2. The gap between the BU and R&D assessment however, has become wider over time, caused by the fact that the self assessment of R&D staff has risen more strongly than that of the BU customers. This finding is in contrast with proposition 2. Possible explanations for this unexpected effect are discussed in section 5. Table 5. Timeliness of Project Execution, R&D cycle time, mean and standard deviation (between brackets)

R&D = R&D self perception; BU = BU perception (both on 7point Likert-scales); PG = Perception gap (R&D perception – BU perception)

R&D BU

4.3 R&D timeliness

-

- 0.22

p: * < 0.05; ** p < 0.01, *** p < 0.001 R&D = R&D self perception; BU = BU perception (both on 7point Likert-scales); PG = Perception gap (R&D perception – BU perception)

1997 1998 2000 3.50 (1.77) 4.33 (1.64) 5.34 (1.48) 2.89 (1.25) 3.40 (1.40) 3.78 (1.65) PG 0.61** 0.94*** 1.57*** p: * < 0.05; ** p < 0.01, *** p < 0.001 R&D BU

2002 5.21 (1.52) 3.89 (1.57) 1.32***

-


4.4 R&D - BU Communication This variable comprises of questions assessing the importance of direct contact of R&D staff with both internal (BU) and the external (end user) customers. The results show two distinct trends: the divisions clearly value regular contacts with the R&D Center, and their opinion on staff exchange as a means to foster communication has improved over the years (see table 6). Table 6. R&D-BU communication, the importance of staff exchange, mean and standard deviation (between brackets) 1997 1998 2000 R&D 3.50 (1.77) 4.33 (1.64) 5.34 (1.48) BU 2.89 (1.25) 3.40 (1.40) 3.78 (1.65) PG 0.61** 0.94*** 1.57*** p: * < 0.05; ** p < 0.01, *** p < 0.001

2002 5.21 (1.52) 3.89 (1.57) 1.32***

-


5


Table 7. Importance of regular discussion of corporate R&D with end users, mean and standard deviation (between brackets) 1997 1998 2000 R&D 5.97 (1.16) 5.82 (1.41) 5.73 (1.17) BU 5.18 (1.74) 5.18 (1.75) 5.29 (1.74) PG 0.79*** 0.64** 0.43 p: * < 0.05; ** p < 0.01, *** p < 0.001

2002 5.97 (1.10) 4.64 (1.88) 1.33***

-

customers, and the R&D staff self-assessment remained constant. This means, that after four successive surveys, the gap between the BU assessment and the R&D staff selfassessment has gradually disappeared. Both findings are in line with proposition 2. Table 8. Overall perceived performance of the corporate R&D Lab., mean and standard deviation (between brackets) 1997 1998 2000 3.26 (0.44) 3.38 (0.56) 3.37 (0.42) 2.87 (0.82) 2.91 (0.78) 3.14 (0.46) PG 0.39*** 0.47*** 0.23** p: * < 0.05; ** p < 0.01, *** p < 0.001

2002 3.40 (0.51) 2.95 (0.81) 0.45**


R&D BU

In contrast to this, table 7 shows, that in the case of direct communication of the R&D staff with the end-users, the gap between the R&D Center and the BU’s widens over time. The BU’s are clearly not in favor of the idea of R&D staff having regular contact with end-users, independent of the Business Units, their main fear being, that R&D staff will offer solutions to end users, before a commercial price can be negotiated.


4.5 Perceived R&D performance As was explained in section 3, the variable performance is composed of two elements: an assessment of the importance of different R&D objectives, and the assessment of the perceived performance on each of these objectives. The results on the importance of the R&D objectives show a clear decline in the gap between the self-assessment of the R&D staff and the BU’s assessment. The gap has shrunk from very significant on 2 of the 6 objectives in 1998 (‘translating existing Technology in New Product/Process Design’ and ‘Contributing to the Improvement of Product/Process Design’) to no significant differences in 2002. Interestingly, the opinion of the BU’s concerning the importance of fundamental research and technology development increased over time. Apparently, the perceptions of the BU’s and the central R&D lab. have gradually converged. The data show that the BU assessment of the laboratory’s performance has gradually gone up since 1997 on most objectives. Longitudinal analysis of the gaps between the lab’s self-assessment and the judgement of the BU’s show that the R&D lab’s staff has acquired a more realistic self-image of its performance in 2002, where in the first years the lab’s staff’s self assessment was clearly higher than that of the BU’s on all 6 objectives, and these differences were all very significant except one (‘Expanding the company’s Technology Knowledge Base’), in 2002, the only significant gap between the lab’s assessment and that of the BU’s was a gap on the two design items, where the lab’s self assessment was even lower than that of its customers. Table 8 combines these data in the overall perceived performance. The longitudinal data show a steady progress in the laboratory’s overall performance as perceived by its

-

5 Discussion and Conclusions The presentation of the results of the four CUSVALIN measures led to intensive discussions at the corporate R&D Centre, first at the management level and then in the quality circles. The feed back on the gaps between the Business Units assessments and the lab's staff self-assessment proved to be a powerful tool to motivate the R&D staff to change its attitude towards its customers. Where in the first surveys the BU assessment on many items was rather low (below 3.5 on a 7 point scale), and in the comments section of the questionnaire many BU respondents complained about the 'head-in-thecloud' mentality of Corporate R&D, the results of the later surveys show, that together with the disappearance of the gap, the BU's appreciation for the R&D Centre did clearly improve. The results of the successive surveys provided the feedback on the effects of the former actions and input for further actions. After each survey a number of improvement actions were introduced. After the first survey it was decided to set up a global benchmark study to identify best practices in R&D management used by the leading companies in other long life cycle industries, and to compare them with the R&D management metrics used in short life cycle industries. Based on the results Corporate R&D decided to include new management metrics which were already common in short life cycle industries, such as Technology Road Mapping and the Balanced Score Card, including financial and non-financial indicators [see 16]. There were also some other management metrics taken by the Corporate headquarters of the company. The most important of these were the change in R&D funding from 100% corporate funding in 1997 and 1998 to a mixed system of 50% corporate and 50% Business Unit funding from 1999 onwards. Furthermore a severe reduction of the R&D staff as part of a major employee reduction policy in order to

6


reduce costs was conducted in 2000 (see also table 2). The questionnaire, based on the CUSVALIN model, was used to monitor the (positive or negative) consequences of these management metrics on a longitudinal basis. We will now elaborate on the three phases of the R&D process, separately. Regarding the idea phase, the results on strategic alignment (figure 2) show a clear tendency of increasing BU customer appreciation of the alignment of the R&D projects with corporate strategy, both concerning the development of important technologies, and concerning alignment to (future) market needs, and a clear closing of the gap between the BU and the R&D assessment. Concerning the inclusion of R&D projects into the corporate R&D portfolio (responsiveness, table 4), the results show an over-closing of the gap, resulting in a reverse gap in BU and R&D assessment on the item of ease of incorporation of BU requests into the R&D portfolio. Perhaps this effect can also be attributed to one of the above described metrics: the change in R&D project funding, which changed from a 100% corporate funding structure in 1997 and 1998 to a mixed system in which 50% of the R&D project funds was allocated by the Business Units, and 50% by the headquarters of the company, from 1999 onwards. Interestingly, the figures on strategic alignment after 1999 show a clear improvement of the BU assessment not only for the BU funded projects (as could be expected after the change in funding structure), but also for the corporately funded projects. This means, that apparently the possibilities to include BU ideas into the corporate R&D’s portfolio has clearly improved over time. These outcomes provide strong support for the proposition that in the initial phase of the R&D process regular feedback from internal customers, as provided by the CUSVALIN model, combined with the incentive provided by 50% direct BU funding, will strongly diminish the gap between the BU assessment and the R&D self assessment of strategic R&D alignment, and will lead to considerable improvement of BU satisfaction with R&D alignment. The results on timeliness (table 5) are closely in line with the expectations based on the CUSVALIN model that feedback in the execution phase of R&D, where the constraints of budget and resources way heavily on project execution, will have less effect than in the idea phase. We think that the widening of the gap is a clear indication of the stronger influence of resource constraints in this stage of the R&D process: since 2000 a considerable reduction of R&D staff has taken place. The relatively high R&D self assessment can very well be explained by the fact that the R&D staff is content that they have been able to maintain such a high level of efficiency, despite the staff reduction. It must be remarked, that the items concerning R&D reporting (tables 6 and 7), represent the assessment of the importance of communication, not the actual perceived quality of the communication as it takes place, and as such do not specifically fall under the proposed relationships. However, they do provide a clear indication of the respondents’ feelings on the topic of communication, a critical element of the

CUSVALIN model as a whole. As such they indicate that all participants agree on the importance of communication of R&D staff with its customers, but that the opinion on whether this should be the internal or the external (end user) customer is divided: the Business Units are opposed, and get more opposed over time, the R&D staff is positive and becomes more positive over time. This result is very interesting, for it indicates that there is some competition between the customer oriented staff in the BUs and the R&D staff concerning direct end user contact. Seen in the light of the importance of R&Dcustomer orientation, headquarters of companies in long life cycle industries should put clear management attention into this important topic. The expectation that the results on performance (table 8), being an expression of the perceived quality of the whole R&D process, will behave as the resultant of the preceding dimension seems to be fully supported by the outcomes. We therefore conclude that structured feedback, based on the CUSVALIN model forms an effective instrument to monitor and bridge the gap between corporate R&D and its internal customers in a company in a long life cycle industry, and that this longitudinal feedback leads directly as well as indirectly (via the management metrics based on it), to better alignment of R&D to corporate strategy and ultimately to higher R&D performance, as perceived by the internal customers. This final conclusion leads to the question whether this improved perceived R&D performance ultimately led to improved business performance. Sales figures 2 years after the respective surveys indicate that this has indeed been the case (a rise of 22% from 1999 to 2004), although such figures have to be interpreted with some care, for the obvious reason that they are influenced by many more factors than R&D to business alignment alone. Looking at the study as such, it can be concluded, that the longitudinal approach is a strong point, because it enabled the researchers to follow actual effects of feedback and management metrics over time. As weak points the reduction of response rate in the last years, and the lack of a control group have to be mentioned. We therefore suggest for further research on the subject of strategic alignment between R&D and BU customers, that other types of companies are studied using the same method, to see if the findings of the present are confirmed. Furthermore, in follow-up studies the link between R&D to business alignment and business success should be studied more in detail.

6. References [1] Bessant, J.; Managing Advanced Manufacturing Technology: The challenge of the fifth wave. Oxford/ Manchester: NCC-Blackwell, 1991. [2] Brown, S., R. Lamming, J.Bessant, and P. Jones; Strategic Operations Management. Oxford: Butterworth-Heinemann, 2000.

7


[3] Brown, W.B. and D. Gobeli; “Observations on the measurement of R&D productivity: a case study,” in IEEE Transactions on Engineering Management, vol. 39, pp. 325-331, 1992. [4] Cooper, D.R. and C.W. Emory; Business Research Methods, Richard D. Irwin, Homewood, IL, 1995. [5] Cooper, R. and E. Kleinschmidt; Nezo Products: The key factors in success. Chicago: American Marketing Association, 1990. [6] Cooper, R.; "The invisible success factors in product innovation," Journal of Product Innovation Management, Vol. 16, pp. 115-133, 1999. [7] Foster, R.N, L.H. Linden, R.L. Whiteley and A.M. Kantrow; ‘Improving the return on R&D I and II,’ Research Management, Vol. 28, pp. 2-17 and Vol. 29, pp. 13-22, 1985. [8] Gale, B.T.; Managing Customer Value: Creating Quality and Service That Customers Can See, New York: The Free Press, 1994. [9] Gallagher, R.; Returning To Your Customers, Customer Value Management New Zealand Ltd., December 1997, http//www.cvm.co.nz/paper1.html. [10] Gerritsma, F. and S.W.F. Omta; ‘The Content Methodology. Facilitating performance measurement by assessing the complexity of R&D projects,” in Management of Technology, Sustainable Development and Eco-efficiency, Pergamon, Elsevier Science Ltd, Amsterdam etc., pp. 101-110, 1998.

[16] Omta S.W.F. and J. Bras; “Design and Implementation of the Balanced Scorecard in Industrial R&D,’’ in The Key to Prosperity in the 3rd Millennium. Proceedings of the 9th Int. Conference on Management of Technology [CD-ROM], eds.: T. Khalil and L. Lefebvre, Miami, Fl. IAMOT, February 2000. [17] Rosenbloom, R. and R. Burgelman; “Technology Strategy: An Evolutionary Process Perspective,” In Research on Technological Innovation, Management and Policy, Vol. 4, , 1989. [18] Szakonyi, R.; “Measuring R&D effectiveness I,” Research.Technology Management, Vol. 37, pp. 27-80, 1994. [19] Subramanian, A. and S. Nilakanta; "Organizational Innovativeness: Exploring the Relationship Between Organizational Determinants of Innovation, Types of Innovations, and Measures of Organizational Performance," Omega, International Journal of Management Science Vol. 24 (6), pp. 631-647, 1996. [20] Watson G. H.; Strategic Benchmarking, How to Rate your Company’s Performance against the World’s Best, New York, John Wiley & Sons, 1993. [21] Zeithaml, V.A., A. Parasuraman and L.L. Berry; Delivering Quality Service: Balancing Customer Perceptions and Expectations, New York, The Free Press, 1990. [22] Zirger, B.J. and M.A. Maidique; “A model for new product development: an empirical test,” Management Science, Vol. 36, pp. 867-883, 1990.c

[11] Goldman, S.L., Nagel, R.N.; ‘Management, technology and agility: the emergence of a new era in manufacturing,” International Journal of Technology Management, Vol. 8 (1/2), pp. 18-38, 1993. [12] Haar, J.W. van der, R.G.M. Kemp and S.W.F. Omta; “Value that can’t be copied. Assessing customer value in service creation at a large R&D intensive company,” Industrial Marketing Management, Vol. 30, No. 8, pp. 627-637, 2001. [13] Hauser, J. R. and D. Clausing; “The House of Quality,” Harvard Business Review, Vol. 3, pp. 63-73, 1988. [14] Kim, W.C. and R. Mauborgne; “Value Innovation: The Strategic Logic of High Growth,” Harvard Business Review, Jan.-Feb., pp. 103-112, 1997. [15] Morbey, G.K.; “R&D: Its relationship with company performance,” Journal of Product Innovation Management, Vol. 5, pp. 191-200, 1988.

8