Determinants of New Product Launch Success in the Pharmaceutical ...

J Pharm Innov (2015) 10:175–189 DOI 10.1007/s12247-015-9216-7

RESEARCH ARTICLE

Determinants of New Product Launch Success in the Pharmaceutical Industry Minna Matikainen 1 & Tarja Rajalahti 2,3,4 & Marikki Peltoniemi 1 & Petri Parvinen 5 & Anne Juppo 1

Published online: 22 March 2015 # Springer Science+Business Media New York 2015

Abstract Purpose This study identifies key determinants of new product launch success, examines their role and impact on launch performance and links them to the different stages of product life cycle in the pharmaceutical new product launch context. Methods Survey data from pharmaceutical industry was analysed with multivariate data analysis using latent variable regression modelling followed by the calculation of selectivity ratios to reveal the most informative determinants. Results The results distinguish between the determinants driving financial new product launch success and those driving customer acceptance. Whereas financial success is driven by strategic choices and tactical decisions, the relationship approach is vital in fostering customer acceptance at different

phases of the innovation diffusion. Product advantage and relationship marketing activities contribute to achieving key opinion leaders’ acceptance in the early phase, while the accumulated market-based assets largely determine acceptance of a majority of other target customers in the later phase. Furthermore, launch performance is enhanced by a relationship-oriented company culture. Conclusions The study emphasises the significance of relational aspects in new product launches and provides both important theoretical insights and managerial implications for commercialising new pharmaceutical products. Keywords New product launch . Customer acceptance . Launch performance . Key opinion leader . Multivariate analysis . Selectivity ratio

* Minna Matikainen [email protected] Tarja Rajalahti [email protected] Marikki Peltoniemi [email protected] Petri Parvinen [email protected] Anne Juppo [email protected] 1

Faculty of Pharmacy, Division of Pharmaceutical Chemistry and Technology, Formulation and Industrial Pharmacy, University of Helsinki, P.O. Box 56, Viikinkaari 5E, FI-00014 Helsinki, Finland

2

The Norwegian Multiple Sclerosis Centre, Department of Neurology, Haukeland University Hospital, Bergen, Norway

3

KG Jebsen Multiple Sclerosis Centre, Department of Clinical Medicine, University of Bergen, Bergen, Norway

4

Department of Research and Development, Førde Central Hospital, Førde, Norway

5

Department of Forest Sciences, University of Helsinki, P.O. Box 27, Latokartanonkaari 7, FI-00014 Helsinki, Finland

Introduction The pharmaceutical industry places a heavy emphasis on research and development (R&D), delivering the highest ratio of R&D investment to net sales compared with other industrial sectors [1]. Thus, it has a vital reliance on new product launch (NPL) success [2–4]. In the changing business environment, pharmaceutical companies aim to launch a new drug onto the market fast [5–7], looking to achieve maximum market penetration and revenue in a limited timeframe before patent protection ends and generic competition begins. Moreover, the pharmaceutical industry has and continues to face a huge increase in the cost of developing new drugs while the number of approved drugs has declined [8–11]. Only two out of ten marketed drugs produce revenues that match or exceed their average R&D costs before losing patent protection [12], which typically lasts for 20 years [9]. The successful launch of a new drug will pave the way for a pharmaceutical company’s performance that enables R&D for new products

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in the future [9]. Under these circumstances, it is important to elucidate pharmaceutical NPLs and find new ways to manage this increasingly challenging and complex activity. The up-to-the-minute literature review reveals that pharmaceutical marketing literature has mainly focused on order of market entry and marketing mix, including 4Ps, i.e. product, price, place and promotion, related topics [13]. This review points out a vast research gap in comprehensive understanding of determinants of NPL success in the pharmaceutical industry. The mainstream of current pharmaceutical NPL-related literature emphasises product superiority compared with that of competitors [9] and suggests that the new drugs are commercialised through careful strategic decisions [14–17], supported by tactical marketing mix activities [15–17] and sales force management [4, 18]. These strategic choices and tactical decisions are considered key success factors in the general NPL literature [19–22], but their link to launch performance has not been studied specifically in the pharmaceutical NPL context. Only a limited amount of literature exists related to the relational aspects of pharmaceutical NPLs that emphasize the importance of customer relationships in NPL. This is surprising since relationship marketing has been one of the dominant paradigms in the industrial marketing research [23] and a common business practice in pharmaceutical sales [24–26]. The relational aspects are also reflected as the market-based assets, which represent the accumulated market and companyrelated assets, such as strong prior customer relationships, as the outcome of company’s operation in the market [27–30]. The importance of the relationship approach has been identified in the pharmaceutical industry and implicitly practiced for quite some time, however, arguing that more explicit adoption and demonstration is needed [26]. Furthermore, business scholars have recently devoted increasing interest to companies’ strategic orientations, which represent deeply rooted values and beliefs in an organization producing certain behaviours, which in turn impact company performance [31]. Product orientation emphasizes company’s product-centred organizational culture, whereby development and commercialisation of new and innovative products are considered key factors for success [31, 32] and the largely studied concept of market orientation focuses on customers’ needs and satisfaction as well as competitors [33, 34]. Instead, relationship orientation refers to an organizational culture that considers customer relationships a key driver of organizational performance [35, 36], being previously neglected but potentially a major contributor to NPL success. These company’s different strategic orientations play an important role in successful NPL [37, 38], but their role and relative impact on launch performance have not been examined in the pharmaceutical NPL context. A thorough evaluation of launch performance comprises both customer acceptance and financial NPL success perspectives. Customer acceptance refers to customer-related success that plays a key role in attaining the broader financial launch

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targets [39–41], whereas NPL success refers to the overall attainment of financial launch targets relating to sales, market share and profitability [20, 37, 42–44]. Since customer adoption of a new product is essential for improved financial success and poor customer acceptance, and is a reason for market failure [45], the role and impact of different determinants of NPL success on launch performance should be studied from both customer acceptance and financial perspectives [24, 46]. Furthermore, the measurement of customer acceptance is divided into two parts: key opinion leaders (KOL) and a majority of other target customers. KOL, representing external medical experts, have a significant influence in pharmaceutical sales and marketing. The existing studies indicate that the effective involvement of KOL is an important antecedent of market penetration of a new drug [47, 48]. A majority of other target customers refers to other physicians, who are potential prescribers of a new drug. By distinguishing between these early and mainstream market segments, this study aims to fulfil the additional research gap regarding the underresearched role of KOL in pharmaceutical sales and marketing as identified by Stros and Lee [13]. In sum, on the top of product, order of market entry and marketing mix, this study incorporates a broader set of determinants including relational aspects such as relationship marketing activities and accumulated market-based assets and company’s strategic orientations. In addition to examining the role and impact of these determinants on launch performance, this study links these determinants to the theory of innovation diffusion and the life cycle management perspective [49, 50] as requested by Stros and Lee [13]. This setting sheds new light to specifying and understanding which pharmaceutical sales and marketing activities are the most useful at the different product stages.

Methods Sample and Data Collection To obtain a comprehensive sample, the complete list of pharmaceutical companies licensed to operate in Finland selling and marketing pharmaceutical products was employed. Pharmaceutical contract research and manufacturing organizations and wholesalers were excluded. Target respondents for the survey were the key product, sales and marketing managers, and directors responsible for NPL in the selected companies. Suitable respondents were identified through Internet search, followed by direct contact with the target companies and qualified based on their familiarity with NPL-related practices. A description of the sample and respondents is presented in Table 1. The survey variables were based on the literature review and expert interviews or adapted from the existing scales where applicable [4, 36, 51–53]. The survey was piloted with seven

J Pharm Innov (2015) 10:175–189 Table 1

177

Description of sample and respondents

Demographics

Number*

Location of companies’ headquarters Finland 36 Outside Finland 72 Company size (revenue in Finland) 100 million euros 40 Company size (revenue outside Finland) 10 billion euros 44 Respondents’ department in their company Business development 2 Management 25 Market access/pricing 7 Marketing 53

%

33.3 66.7 38.1 23.8 38.1 25.3 23.2 7.1 44.4 1.8 22.9 6.4 48.6

Medical 5 4.6 Sales 14 12.8 Other 3 2.8 Respondents’ position in their company Director 29 26.6 Manager 75 68.8 Other 5 4.6 Respondents’ experience in the pharmaceutical industry (years) 1–5 5 4.6 5–10 20 18.3 10–15 34 31.2 15–20 20 18.3 >20 30 27.5 Respondents’ familiarity with new product launch related practices Very familiar 78 72.9 Quite familiar 29 27.1 Not at all familiar 0 0.0 *Total number of respondents in the sample is 109. Occasional empty answers in the background information section of the survey have been ignored here.

industry experts representing different types of company and respondent category in the sample, in order to confirm survey clarity and relevance to the present day industry context. The variables were assessed on 7 point Likert-type scales ranging from ‘strongly disagree’ to ‘strongly agree’. The financial NPL success measurement was used to evaluate how the selected NPL met sales, market share and profitability targets over 1- and 3-year periods, and was assessed on 11 point Likert-type scales ranging from ‘far below target: −5’ to ‘far above target: +5’ [39, 40]. The respondents were also requested to evaluate how successful the NPL was generally perceived [54]. This overall success measurement was also

assessed on 11 point Likert-type scales ranging from ‘very unsuccessful: −5’ to ‘very successful: +5’ [20, 22]. Appendix 1 summarises the variables employed in the survey. The survey was sent by electronic mail to 357 identified respondents, who were asked to complete the survey in relation to a specific product launch over the last 5 years in which they were most involved. The time frame of 5 years for launch newness was based on the previous NPL studies [20, 22]. The survey yielded 110 responses (including the pilots) following three reminders. After removing one response with several missing values, a total of 109 usable responses remained, representing a good 30.5 % response rate. As NPL represents the key level of analysis in the study, the key characteristics of the launched products, which were commercialised in 2008– 2012, are presented in Table 2. Table 2

Characteristics of the launched products

Characteristics

Number*

%

Type of product Prescription drug Over-the-counter drug

97 12

89.0 11.0

92 14

86.8 13.2

68 41

62.4 37.6

63 43

59.4 40.6

24 78

24.0 76.0

51 53

49.0 51.0

13 35 24

12.2 32.7 22.4

23 12

21.5 11.2

10 63 70 12 21 5

9.1 57.3 64.2 10.9 19.1 4.5

Proprietary product Generic drug Type of innovation Major/radical innovation Minor/incremental innovation Product novelty New to the market New to the company Launch territory Only in Finland Part of global/European/Nordic wide launch Market entry First in the market Not first in the market Sales target (million euros) 2 Primary target customer group for product General practitioners (GP)/primary health care Specialists/specialist health care Both GPs and specialists Consumers directly Pharmacists Veterinarians

*Total number of respondents in the sample is 109 but occasional empty answers in the background information section of the survey have been ignored here.

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Data Analysis The data set was subjected to multivariate data analysis using latent variable methods to reveal the most informative variables. The analysis was performed using Sirius version 9.0 software (Pattern Recognition Systems AS, Bergen, Norway). The variables were partitioned into predictor (input) and response (output) variables as presented in Appendix 1. Principal component analysis (PCA) was first performed to obtain an overview of the data and to reveal possible clustering, trends and outliers among the variables and respondents [55]. PCA confirmed that the data had no outliers. PCA also reveals that the overall success measurement describes well both 1- and 3-year financial success measurements and can thus be used to summarise the financial response measurements. Partial least squares (PLS) regression models were then calculated for each response variable separately [56]. The repeated double cross-validation was used to estimate the number of PLS components to obtain the PLS models with the best predictive performance [57]. In this procedure, one subset (here one seventh part of the observations) at a time is randomly removed from the training set. A PLS model is calculated using the remaining data and subsequently employed to predict the removed subset. This procedure is then repeated several (here 100) times. In this manner, all observations are utilised both for training and external validation and a measure of a model’s predictive performance is obtained. In order to improve interpretation of the PLS models, a target projection (TP) was performed [58]. In this projection, the predictor variables matrix is projected onto the PLS regression vector. The information in the predictor data unrelated (i.e. orthogonal) to the response variable is thus removed, and a single-latent variable (i.e. target-projected component) is obtained. The TP component represents the predictive information in the predictor variables for the investigated response variable. A detailed theoretical description of the method with illustrations can be found in the tutorial review written by Rajalahti and Kvalheim [59]. The calculation of selectivity ratios (SR) was used to reveal the most informative predictor variables for each investigated response variable [60, 61]. The SR is defined as the ratio between explained variance and residual (unexplained) variance in the target-projected component, and is calculated for each predictor variable. This ratio represents a direct quantitative measure of the importance of a predictor variable to explain and predict the response variable. Furthermore, by multiplying the SR with the sign of the corresponding loading on the target-projected component, the SR value reveals which response variables increase and which decrease with rising values of the predictor variables. The size of the SR ranks the most important predictor variables contributing to the different response variables. The predictor variables with a high

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(positive or negative) SR value are best at explaining the behaviour of the investigated response variables. In this study, the SR values were calculated for each predictor variable in each separate TP model (i.e. for all response variables separately). The response variables that increase with the increasing predictor variable provide positive SR while those decreasing with the increasing predictor variable provide negative SR. Furthermore, confidence intervals were calculated for each SR value based on the iterative crossvalidation procedure explained earlier.

Results Modelling Results PLS modelling results with two PLS components and the subsequent TP outcome are presented in Table 3. The explained variances for the models show the presence of a response-related factor in the predictor variables. The percentage explained variance in X (R2X) for the PLS and the TP models shows the information content in the predictor variables used to model the response variable y (PLS) and the information in the predictor variables specifically related to y (TP). The percentage explained variance in y (R2y) is used as one measure of the overall predictive performance of a model. All SR values and their confidence intervals are presented in Table 4. SR value is significant when the crossvalidated confidence interval does not include zero.

Respondent, Product Category and Company-Related Background Variables The SR values indicate the importance of the predictor variables in the interpretation of the results. The low SR values demonstrate that the respondent, product category, target customer group (i.e. general practitioner, specialist and pharmacist) or company-related background variables do not affect any response variables (see Table 4 and Fig. 1). The only exception includes the high negative SR value for the variable Table 3 Response

Summary of the modelling results A R2 (XPLS)% R2 (XTP)% R2 (y)%

Financial success 2 Customer acceptance by KOL 2 Customer acceptance by 2 majority of customers

29.61 28.75 29.20

11.71 13.98 14.42

52.14 56.85 55.12

A, number of PLS components; R2 (XPLS), explained variance in X for PLS model; R2 (XTP), explained variance in X for TP model; R2 (y), explained variance in y for PLS and TP models; KOL, key opinion leader

J Pharm Innov (2015) 10:175–189 Table 4 variables

179

Selectivity ratios and confidence intervals for predictor

Table 4 (continued) Financial success

Financial success

Customer acceptance of KOL

Customer acceptance of majority of customers SR

SR

CI SR (p=0.05)

CI (p=0.05)

SR

CI (p=0.05) RO9

Q1 Q2 Q3 Q4 Q5 Q6 Q7a Q7b Q7c Q7d Q7e Q7f Q8 Q9 Q10 Q11 Q12 Q13 C1 C2

0.006 0.011 0.000 0.002 0.000 −0.091 0.028 0.062 0.043 −0.020 0.000 0.013 0.076 0.035 0.072 0.024 −0.252 0.004 0.022 0.033 −0.091 0.056

0.003 0.020 0.009 0.015 0.007 0.009 0.002 0.005 0.018 0.007 0.018 0.008 0.042 0.006 0.008 0.020 0.043 0.018

C3 −0.078 0.025 MO1 0.165 0.030 MO2 0.092 0.024 MO3 0.419 0.058 MO4 0.291 0.064 MO5 0.144 0.027 MO6 0.171 0.032 MO7 0.090 0.026 MO8 0.253 0.047 MO9 0.280 0.050 MO10 0.096 0.029 MO11 0.168 0.036 PO1 0.083 0.033 PO2 0.000 0.009 PO3 0.091 0.034 RO1 0.068 0.032 RO2 0.037 0.024 RO3 0.045 0.028 RO4 0.016 0.016 RO5 RO6 RO7 RO8

0.083 0.170 0.081 0.286

0.036 0.053 0.034 0.074

0.003 0.002

0.006 0.004

0.000 0.004 0.000 0.002

−0.005 0.002 −0.080 0.000 0.002 0.024 −0.001 −0.084 −0.037 0.016 −0.015 −0.040 0.019 0.010 −0.073 0.031 −0.009 0.008

0.005 0.003 0.029 0.004 0.003 0.017 0.004 0.026 0.023 0.006 0.013 0.016 0.014 0.013 0.021 0.022 0.016 0.014

0.002 −0.003 −0.000 0.035 0.007 0.002 −0.012 −0.001 0.012 0.029 0.036 −0.002 −0.025 −0.005 −0.014 0.009 −0.087 0.048

0.003 0.007 0.004 0.012 0.005 0.006 0.008 0.004 0.008 0.009 0.016 0.006 0.014 0.007 0.011 0.012 0.028 0.027

−0.000 0.065 0.016 0.052 0.067 0.050 0.134 0.020 0.065 0.028 0.0672 0.0555 0.120 0.132 0.056 0.101 0.064 0.071 0.037

0.006 0.037 0.016 0.045 0.047 0.018 0.038 0.019 0.042 0.026 0.032 0.025 0.031 0.038 0.021 0.051 0.044 0.045 0.030

−0.003 0.021 0.068 0.145 0.034 0.077 0.219 0.031 0.170 0.194 0.132 0.129 0.011 0.000 0.016 0.188 0.147 0.178 0.071

0.006 0.026 0.036 0.061 0.030 0.023 0.043 0.022 0.056 0.074 0.049 0.050 0.015 0.007 0.015 0.074 0.070 0.075 0.046

0.108 0.217 0.159 0.359

0.052 0.077 0.063 0.111

0.224 0.480 0.290 0.708

0.067 0.145 0.107 0.153


CI SR (p=0.05)

0.251 0.060

CI (p=0.05)


CI (p=0.05)

0.241

0.074

0.520 0.096

RO10 PA1 PA2 PA3 PA4 PA5 PA6 STR1 STR2 STR3 STR4 STR5 STR6 STR7 TAC1 TAC2 TAC3 TAC4

0.334 0.006 −0.056 −0.028 0.002 0.049 0.052 0.280 0.427 0.478 0.130 0.163 0.347 0.157 0.275 0.295 0.490 0.545

0.085 0.013 0.024 0.017 0.007 0.028 0.018 0.051 0.098 0.073 0.048 0.051 0.076 0.040 0.042 0.063 0.106 0.100

0.317 0.601 0.233 0.258 0.455 0.588 0.195 0.037 0.168 0.204 0.306 0.253 0.503 0.241 0.007 0.222 0.041 0.151

0.091 0.151 0.082 0.089 0.094 0.140 0.040 0.030 0.076 0.066 0.092 0.073 0.104 0.085 0.016 0.065 0.038 0.067

0.367 0.091 0.003 0.003 0.083 0.241 0.157 0.181 0.124 0.388 0.453 0.239 0.599 0.297 0.117 0.283 0.077 0.313

0.074 0.051 0.015 0.015 0.039 0.090 0.041 0.075 0.064 0.107 0.094 0.057 0.110 0.095 0.056 0.074 0.036 0.119

TAC5 TAC6 TAC7 TAC8 SFM1 SFM2 SFM3 SFM4 SFM5 SFM6 RM1 RM2 RM3 RM4 RM5 RM6 RM7 RM8 RM9

0.060 0.231 0.526 0.259 0.027 0.032 0.070 0.031 0.122 0.060 0.004 0.004 0.005 0.094 0.014 0.107 0.041 0.082 0.191

0.019 0.062 0.104 0.045 0.016 0.022 0.032 0.018 0.041 0.030 0.010 0.007 0.008 0.031 0.012 0.033 0.019 0.022 0.031

0.048 0.237 0.156 0.042 0.169 0.252 0.370 0.145 0.115 0.084 0.383 0.526 0.488 0.649 0.217 0.358 0.173 0.185 0.196

0.020 0.066 0.066 0.030 0.044 0.081 0.107 0.048 0.043 0.041 0.113 0.142 0.135 0.120 0.078 0.080 0.049 0.062 0.042

0.043 0.285 0.234 0.119 0.085 0.143 0.329 0.160 0.112 0.164 0.091 0.123 0.088 0.447 0.077 0.386 0.235 0.148 0.223

0.019 0.078 0.094 0.059 0.028 0.054 0.088 0.043 0.046 0.044 0.038 0.047 0.040 0.100 0.040 0.080 0.050 0.053 0.042

MBA1 MBA2 MBA3 MBA4 MBA5 CA1

0.095 0.123 0.124 0.173 0.203 0.061

0.042 0.050 0.053 0.066 0.070 0.028

0.079 0.203 0.133 0.334 0.425

0.043 0.076 0.062 0.112 0.133

0.537 0.664 0.585 1.000 0.930

0.139 0.163 0.145 0.220 0.210

180

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Table 4 (continued) Financial success

SR


CI SR (p=0.05)

CA2

0.124 0.046

CA3 CA4 CA5 CA6 CA7

0.266 0.368 0.373 0.423 0.627

CI (p=0.05)

in building customer relationships (RO6), treatment of customers with both empathy (RO8) and with reciprocity (RO9), as well as trust between company and customers (RO10).


Sales and Marketing Activities and Product Advantage-Related Variables

CI (p=0.05)

The results reveal that the product advantage-related variables have the biggest impact on KOL acceptance compared with the other measurements (see Table 4 and Fig. 3). The highest SR values include the launched product’s unique customer benefits (PA1), superiority (PA4) and satisfaction of unmet market need (PA5). However, the product advantage-related variables do not affect financial success or the acceptance of a majority of target customers. The set of survey variables such as strategic choices, tactical decisions, sales force management and relationship marketing activities are the typical sales and marketing decisions and activities, which are executed in the commercialisation of a new drug. The results demonstrate that the SR values of the variables related to strategic choices, such as comprehensively gathered market intelligence (STR2) and clearly defined launch strategy (STR3), as well as tactical decisions such as appropriate pricing policy and price level (TAC3), well conducted promotion (TAC4), and proficiently executed marketing plan (TAC7), are more significant in terms of financial success than in terms of both perspectives of customer acceptance. However, timing of the product launch (STR6) seems to be the most important strategic variable for both KOLs’ and majority of customers’ acceptance. While sales force management and relationship marketing activities-related variables do not have impact on financial success, relationship marketing activities have remarkable effect on customer acceptance, especially on KOLs’ acceptance.

0.056 0.065 0.074 0.077 0.096

KOL, key opinion leader; SR, selectivity ratio; CI, confidence interval

of launch territory (Q10) indicating that a wider than national launch territory has a negative impact on financial success. Company’s Strategic Orientations-Related Variables The SR values show that the market orientation-related variables such as company’s objectives primarily driven by customer satisfaction (MO3), systematic and frequent measurement of customer satisfaction (MO4), targeting customers with competitive advantage (MO8) and rapid response to competitors’ actions (MO9) are linked to the financial success measurement more than to the customer acceptance measurements (see Table 4 and Fig. 2). Instead, the product orientation-related variables have low SR values in all performance measurements. The most significant SR values are linked to relationship orientation-related variables especially in terms of the acceptance of the majority of customers. The variables with the highest SR values include company’s willingness to invest Fig. 1 The SR values for respondent, product category, target customer group and company-related background variables (abbreviations for variables are explained in Appendix 1)

Q1 C3

0. 10

Q2

0. 05

C2

Q3

0. 00 C1

Q4

-0. 05 -0. 10

Q13

Q5

-0. 15 -0. 20 -0. 25

Q12

Q6

-0. 30

Financial success KOL Majority

Q11

Q7a

Q10

Q7b

Q9

Q7c Q8

Q7d Q7f

Q7e

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181 MO1

Fig. 2 The SR values for company’s orientation-related variables (abbreviations for variables are explained in Appendix 1)

RO10 RO9

MO2

0.7

MO3

0.6

RO8

MO4

0.5 0.4

RO7

MO5

0.3 0.2

RO6

MO6

0.1 RO5

Financial success MO7

0.0

KOL Majority

RO4

MO8

RO3

MO9 RO2

MO10 RO1

MO11 PO3

PO1 PO2

These variables, such as close interaction during product development process (RM1), identification and involvement of KOL (RM2), early market pro-activeness activities (RM3) and collaborative communication (RM4), deliver a significant impact on the customer acceptance of KOLs. The variables relating to market-based assets possess the ultimate SR values in the analyses, particularly in terms of the acceptance of the majority of customers. In particular, the SR values for company’s strong prior customer relationships (MBA4) and customers’ loyalty (MBA5) are significantly high, indicating their remarkable importance for customer acceptance in this customer group. Instead, marketbased assets-related variables have low SR values in terms of acceptance of KOL and have only a slight effect on financial success. Fig. 3 The SR values for product advantage, sales and marketing decisions and activities-related variables (abbreviations for variables are explained in Appendix 1)

Discussion Implications for Theory This study distinguishes between the determinants driving financial NPL success and those driving customer acceptance contributing to the pharmaceutical NPL literature (see Table 5 and Fig. 4). As the results show, certain strategic choices and tactical decisions drive the financial success of a new pharmaceutical product launch. This finding supports the previous studies presenting these determinants as the key elements in NPL success [13–15, 17, 19, 20]. Surprisingly, both strategic and tactical marketing activities, except the launch timing, have only moderate effects on customer acceptance. This finding calls for other explanations for determining customer acceptance.

MBA5 PA1 1.0 MBA4 MBA3 MBA2 0.8 MBA1 RM9

0.6

PA2

PA3

PA4 PA5 PA6 STR1

RM8

STR2 0.4

RM7

STR3

0.2

RM6

STR4 Financial success

RM5

STR5

0.0

RM4

STR6

RM3

STR7

RM2

TAC1

RM1

TAC2

SFM6 SFM5 SFM4 SFM3 SFM2 SFM1

TAC3 TAC4 TAC5 TAC6 TAC8TAC7

KOL Majority

182 Table 5

J Pharm Innov (2015) 10:175–189 Summary of the success drivers, key determinants, theoretical contribution and managerial implications

Success drivers Examples of key determinants

Acceptance by KOL

Acceptance by majority of customers

Financial success

• Product advantage • Relationship marketing activities • Launched product’s unique customer benefits, superiority and satisfaction of unmet market need • Identification and involvement of KOL • Early market pro-activeness activities • Collaborative communication with customers

• Market-based assets • Relationship orientation • Customers awareness of and preference for the company’s brand • Extensive existing customer base • Strong prior customer relationships • Customer’s loyalty to company • Company’s willingness to invest in building customer relationships • Treatment of customers with empathy and reciprocity

• Strategic choices • Tactical decisions • Comprehensive gathered market intelligence • Clearly defined launch strategy • Well-grounded pricing policy and appropriate price level • Well conducted promotion and marketing communication • Proficiently executed marketing plan • NPL-related literature

Theoretical reasoning • Product’s life cycle management [49] • Theory of innovation diffusion [50] Novelty/contribution Relationship approach to theory • Importance of product advantage and relationship marketing activities instead of traditional sales and marketing activities

Managerial implications

• Targeted and more effective product advantage focused relationship marketing activities • Traditional marketing mix practices do not affect KOLs

• Importance of accumulated market• When customer acceptance has based assets such as established and been achieved, strategic choices maintained customer relationships and tactical decisions have a instead of product advantage strong impact on financial • Relationship-oriented organizational performance culture should complement marketoriented ways of working • Fostering relationship-oriented • Financial performance can be organizational culture accelerated by a well-defined • Focus on business practices leveraging launch strategy, pricing, established customer relationships promotion and a proficiently implemented marketing pan

The results reveal that the relationship approach is vital in fostering customer acceptance, which is a fundamental prerequisite for successful NPL in the theory of innovation diffusion [50]. The critical role of the relationship approach broadens the extant pharmaceutical NPL literature, which largely neglects the role of customer relationships [13], although the importance of customer relationships, the relationship marketing concept, and consequently its link to improved financial performance are widely studied in the general business literature [62–64]. In order to analyse customer acceptance more deeply at the different phases of the innovation diffusion, two main customer groups, KOLs and majority of other target customers, were selected to illustrate the early and later phase of innovation diffusion [49]. In the early phase, the product advantage and relationship marketing activities are the key determinants of NPL success, demonstrating their utmost importance in achieving KOLs’ acceptance. KOLs appreciate product benefits and superiority over the competitor’s product that is logical, since product advantage is one of key factors driving the speed of innovation [50]. The study also demonstrates that the relationship marketing activities, which aim to leverage customer relationships, are more valuable for KOLs than traditional marketing mix and sales activities in the early phase of

launch. This finding contributes to the extant literature by demonstrating the significance and effectiveness of relationship marketing in this specific target customer group in the pharmaceutical NPL context [44, 65]. Thus, the effective engagement of KOLs is an important antecedent of market penetration of a new drug [47, 48]. In the later phase of innovation diffusion, the accumulated market-based assets such as company brand, strong prior relationships and loyalty to the company largely determine acceptance by a majority of other target customers representing the mainstream market segment. The rationale behind the differences in key success determinants between the early and late customer groups lies in the innovation diffusion theory, arguing that the domains of greatest value to the customers change from technology and product-related aspects to market and company-related aspects as a new product moves through its life cycle [49]. Interestingly, the role of sales force management-related activities is less significant than expected based on the previous literature [4, 18]. The same kind of phenomena can be seen in relation to the market access-related strategy and tactical activities such as advance notification documentation to key decision makers, health outcome toolkits and implementation tactics. They have a moderately low impact on NPL

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Fig. 4 The variables with the highest (over 0.4) SR values (abbreviations for variables are explained in Appendix 1)

success in this data set, although the role of market access has been noted as essential for a drug launch [66]. This study contributes to the pharmaceutical NPL literature also by demonstrating the role and importance of a relationship-oriented company culture on new product success. The strong effect can be seen in terms of all performance measurements, but the role of relationship orientation is significantly high in acceptance by the majority of target customers (see Appendix 1). This finding indicates that the broadly studied concept of market orientation emphasizing company’s focus on customer’s satisfaction and competitors [33, 34] is not sufficient as such in explaining the role of customer relationships in NPL success. In addition, some researchers have argued that the overemphasis on customers’ needs might decrease the company’s innovative competence and, therefore, only lead to marginally new products [31, 53, 67]. Thus, relationship orientation, as a company’s complementary strategic orientation, needs to be considered as a key success driver in the NPL research. Compared with the other strategic orientations, product orientation has in this data set the smallest impact on launch performance as a whole. This is contrary to the previous study demonstrating that product orientation has the biggest impact on new product commercialisation performance [38]. The rationale of the contrary finding might be explained by the fact that a company’s emphasis on development and commercialization of new and innovative pharmaceutical products is not solely enough for success without a proper attention to and leveraging of company’s customer relationships. From a methodological perspective, multivariate dataanalytical techniques are widely used in measuring and

modelling complex systems, and have a central role in the pharmaceutical R&D and manufacturing [68, 69]. At present, SR has been used successfully for variable selection and model interpretation in a diversity of biomarker analyses, pharmaceutical product development and manufacturing-related applications [70–74]. This study broadens the method’s usability also to sales- and marketing-related analyses. SR operates as a sensitive multivariate index to rank predictor variables according to their importance in the latent variable model [75]. The employment of latent variable modelling makes it possible to exclude noise from the variables and thus derive more robust models. The survey data comprise discrete variables that make it more difficult to create models with highexplained variance in the response variable. Thus, the explained variance of around 50 %, as seen in this study, implies a good model. As the data were collected retrospectively, that is the most common research method used in the previous NPL studies [20, 22, 42], some halo effect bias may exist, since the success or failure of each product launch was known prior to answering the survey. The subjective evaluation might result in an overoptimistic assessment of launch success. In order to minimize this limitation, the respondents were carefully selected representing those who are the most familiar with and involved in commercialization of a new drug. The objective verification of financial NPL success was not possible due to strict confidentiality restrictions. The data set was collected in one particular country that might limit generalizing the results. However, the common features and challenges in pharmaceutical marketing are global, even the health care system in a country is local. The results

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of this study are feasible in a country and market environment, where are the separate parties for decision-making (i.e. physician), paying (i.e. insurance company or national health insurance) and end using (i.e. patient) of a new drug. Furthermore, marketing of prescription drugs is allowed only to physicians and other health care professionals in the country of this study. The future studies could extend research focus across different countries and diversity of health care systems. Managerial Implications The differences between key success determinants identified in this study provide several practical implications for the commercialisation of a new pharmaceutical product. First, all personnel responsible for NPL should note the role and impact of the success determinants at the different phases of innovation diffusion. At the beginning, the identification and involvement of key opinion leaders are crucial since their rapid acceptance of a drug is a critical for success [3]. Preferably, close interaction should be initiated during the drug development phase [47] or even earlier in drug design phase. Utilizing expertise of KOL early enough, for example in formulary decisions, could help companies to avoid hurdles when competition with low margins exists. The early involvement of KOL could support companies to focus on superior product characteristics, such as unique customer benefits and fulfilling unmet market needs, and to achieve customer’s acceptance in this early market segment. In addition, relationship marketing activities including early market pro-activeness activities, such as building market awareness to arouse interest, product-related high-quality education and collaborative communication [48] are vital for success. However, regulatory approval aspects and the national Code of Practices needs to be taken into account when planning and executing relationship marketing activities to physicians and other healthcare professionals. In the later phase, management should focus on leveraging the strong customer relationships, which have been established and maintained during the company’s operation in the market. In practice, the company should strengthen customers’ awareness and preference regarding the company’s brand, extend the existing customer base and support customers’ loyalty to the company [76]. The proper leveraging of customer relationships is important to maximise outcomes from the accumulated company-specific market-based assets instead of overly stressing the product advantage. When customer acceptance has been achieved in the target groups, the strategic choices and tactical marketing activities have a clear impact on financial success. The managers launching a new drug should focus on comprehensively

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gathered market intelligence, a clearly defined launch strategy, well-grounded pricing policy and appropriate price level, well conducted promotion and marketing communications, and a proficiently executed marketing plan. The findings demonstrate that a company can effectively enhance commercialisation of a new drug through a relationship-oriented organizational culture. In practice, a relationship-oriented company is willing to invest time, effort, spending and resources in building stronger customer relationships and is committed to maintaining valued customer relationships. Furthermore, a relationship-oriented company treats its customers with empathy and reciprocity, and builds trust in its business practices. In sum, the findings call for a relationship approach to complement the traditional sales and marketing approach for NPLs. The pharmaceutical product launch should focus on appropriate sales and marketing activities conducted in a timely manner to achieve acceptance of both early market and mainstream market customers. The proper targeting of these activities is of considerable importance since major changes in the healthcare environment such as pressures for cost savings, access challenges to physicians and tightening regulations on promotion call for attention to pharmaceutical sales force effectiveness [4, 18]. As the sales force operation has been considered the most expensive pharmaceutical marketing activity [77], the relationship approach provides a new perspective on traditional sales and marketing, providing required effectiveness [9, 18].

Conclusion This study identifies key determinants of new product launch success, examines their role and impact on launch performance and links them to the different stages of product life cycle using the theoretical framework of innovation diffusion in the pharmaceutical NPL context. Multivariate data analysis employing selectivity ratios proved to be a useful method to identify and rank the most important determinants contributing to launch performance. The results reveal different success determinants for acceptance by key opinion leaders, a majority of other target customers, as well as financial success when launching new products. The findings call for a relationship approach to complement the traditional sales and marketing approach and suggest effective managerial implications for the successful commercialisation of a new pharmaceutical product. Acknowledgments D.Sc. (Econ.) Esa Matikainen Conflict of Interest The authors declare that they have no conflict of interest.

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Appendix 1 Variables Code

Variables

Background information Q1 In which function/department of the organization do you work? Q2 What is your position in the organization? Q3 How long have you been working in the pharmaceutical industry? Q4 How familiar are you with the new product launch related practices in your organization? Q5 Was the product launched a prescription or over-the-counter (OTC) drug? Q6 Was the product launched a proprietary or generic drug? Q7* What was (were) the primary target customer group(s) for the launched product at the time of launch? Q8 What kind of innovation did the product represent at the time of launch? Q9 What was the stage of the launched product novelty at the time of launch? Q10 Where was the product launched? Q11 What year was the product launched?

Type

x x x x x x x x x x x

Q12 Was the launched product the first of its kind on the market? Q13 What was the product’s sales target in the first 12 months after the launch in Finland? C1 Where does the company’s headquarter locate? C2 What is the size of the company in terms of revenue in Finland in 2011? C3 What is the size of the company in terms of revenue outside Finland in 2011? Market orientation MO1 We focused on gathering market intelligence pertaining to current and future customer needs MO2 All of our functions, not just sales and marketing, were responsive to market intelligence gathered on current and future customer needs MO3 Our company’s objectives were driven primarily by customer satisfaction MO4 We measured customer satisfaction systematically and frequently

x x x x x

MO5 Our business strategies were driven by our beliefs about how we can create greater value for our customers MO6 Our strategy for competitive advantage was based on our understanding of our customers’ needs MO7 Our top management regularly discussed competitors' strengths and strategies MO8 We targeted customers and customer groups in which we had or were able to develop a competitive advantage MO9 We had the ability to respond rapidly to competitors' actions MO10 Information on customers, marketing successes and failures were communicated across functions in the business MO11 All of our managers understood how everyone in our business can contribute to creating customer value Product orientation PO1 We believed the customer’s perception of product superiority with respect to quality, cost-benefit ratio or function relative to competitors is the key to new product launch success PO2 We believed that product innovativeness and uniqueness are the keys to new product launch success PO3 We endeavoured to offer the best products in our industry

x x x x x x x

Relationship orientation RO1 In our organization, retaining customers was considered a top priority RO2 Our employees were encouraged to focus on customer relationships RO3 In our organization, customer relationships were considered to be a valuable asset RO4 Our senior management emphasized the importance of customer relationships RO5 We believed that establishing and maintaining strong and long-term customer relationships is a key to success RO6 Our company was willing to invest time, effort, spending and resources on building stronger customer relationships RO7 Our company was committed to maintaining valued relationships with our customers and was willing to work on maintaining them RO8 Our company treated our customers with empathy (e.g. we saw things from each other’s point of view and cared about each other’s feelings) RO9 Our company treated customers with reciprocity (e.g. we kept our promises in every situation and repaid customers’ kindness) RO10 Our company and our customers trusted each others (e.g. we had confidence in each other’s reliability and integrity)

x x x x

x x x x x x x x x x x x x

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(continued) Code

Variables

Product advantage PA1 The launched product offered customers unique benefits PA2 The launched product was highly innovative PA3 The launched product was radically different from competitor products PA4 The launched product was superior (e.g. in terms of quality, cost-benefit ratio and/or function) to competing products PA5 The launched product satisfied a clear, unmet market need PA6 The launched product was compatible with the customer’s values and previous experiences Strategic choices STR1 Launch objectives and success measures had been clearly defined STR2 Market intelligence (e.g. market studies) on the product had been comprehensively gathered and utilized in decision-making STR3 Launch strategy (e.g. innovative and product advantage strategy; cost-oriented strategy) had been clearly defined STR4 Market segmentation had been carefully applied to identify an appropriate target market for the launched product STR5 The product had been carefully positioned in the target market taking all relevant competitors into account STR6 The timing of the product launch was successful STR7 Market access strategy (e.g. informing key decision makers involved in assessment and approval of drugs about clinical, organizational and financial implications of introducing the new product) had been well designed in a timely manner Tactical decisions TAC1 Product launch was supported by a well-designed marketing mix (4Ps; product, price, promotion and place/distribution) TAC2 Product branding was successful TAC3 Pricing policy was well grounded and the price level was considered appropriate (e.g. reimbursement was obtained as planned in the case of a prescription drug) TAC4 Promotion and marketing communication was conducted well TAC5 The whole supply chain (e.g. manufacturing plant, warehouse, wholesaler and customer) for the launched product ran smoothly and promptly TAC6 Marketing budget and marketing resources were sufficient and their allocation to various means and activities was conducted well TAC7 Marketing plan was executed proficiently TAC8 Market access activities (e.g. advance notification documentation, health outcome toolkits and implementation tactics) were successfully implemented in a timely manner Sales force management SFM1 Adequate sales resources had been allocated to the product launched SFM2 Sales people had received thorough training and were knowledgeable about the product SFM3 Sales people were motivated and enthusiastic about the product SFM4 Sales people were held accountable for the launched product targets, and their compensation and/or incentives were aligned with the targets SFM5 Sales people activities (e.g. processes, practices and techniques) were well managed during the launch period SFM6 Sales worked closely with marketing to make the launch a success Relationship marketing activities RM1 RM2 RM3

Our company had close customer interaction during the launched product development process (e.g. clinical trials) Key opinion leaders were identified and involved in the product launch Our company initiated early market pro-activeness activities (e.g. arousing of interest, market awareness, involvement of opinion leaders and product education) RM4 Communication with customers was collaborative including frequent sharing of tailored information RM5 We provided high-quality training (e.g. continuing medical education) for our customers RM6 Sales people and other personnel working at the customer interface recognized their role as relationship builders RM7 Our company had implemented effective key account management (KAM) practices RM8 Relationship-related market access activities (e.g. advisory board meeting, activities directed at decision-makers and payers) were successfully implemented in a timely manner RM9 Customer-related conflicts were managed effectively and resolved quickly Market-based assets MBA1 Customers were well aware of our company brand MBA2 Customers preferred our company brand to that of competitor companies

Type

x x x x x x x x x x x x x

x x x x x x x x

x x x x x x x x x x x x x x x x x

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(continued) Code MBA3 MBA4 MBA5

Variables

Type

Our company had an extensive existing customer base Our company had strong prior relationships with its customers Our customers were loyal to our company

x x x

Customer acceptance CA1 Customers were well aware of the brand of the launched product CA2 Customers preferred the launched product brand to competitors’ product brands CA3 The launched product was rapidly accepted by key opinion leaders (KOL) CA4 The launched product was accepted by the majority of the target customers CA5 Customers were satisfied with the launched product CA6 Customers were positively referring (word-of-mouth) the launched product to other potential customers CA7 Our company succeeded in increasing demand for the product through relational networking amongst our customers New product launch success NPLS1 How successful was the product launch in meeting its sales target? NPLS2 How successful was the product launch in meeting its market share target? NPLS3 How successful was the product launch in meeting its profitability target? NPLS4 How would you rate the overall success of your company’s selected product launch perceived as a whole?

x x x/y x/y x x x y y y y

x, predictor variable; y, response variable; * a, general practitioners (GP)/primary health care; b, specialists/specialist health care; c, both GPs and specialists; d, consumers directly; e, pharmacists; f, veterinarians

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