Our study utilises a solid theoretical foundation: market orientation (MO) theory [19]. MO focusses on determinants and processes of the successful implementation of marketing, and how these activities are coordinated and used across entire organisations: “[…] [MO] is the organization wide generation of MI [market intelligence] pertaining to current and future customer needs, dissemination of the intelligence across departments, and organization wide responsiveness to it.” ( [19]: p. 6) MO was first popularised by Kohli & Jaworski in 1990 and has been repeatedly, and recently, associated with positive performance of new products [20] [21] [22] [23] and entire organisations, also in the healthcare-pertinent pharmaceutical, [24], biotech [25] and food industries [26]. For more detail regarding the study-relevant components of MO, see Appendix 12.

To improve the validity of our study, we continued interviewing until we reached data saturation. If no new concepts were mentioned in two consecutive interviews, we considered saturation to have been achieved [28] [29]. Following the recording and transcription of interviews, a summary was shared with the interviewee, for their review (member-check). This helped us verify if we had correctly interpreted their elaborations and, thereby, improve the reliability of our analysis [30].

Analysis was performed by the first and second authors. Interview transcripts were evaluated using thematic analysis, which provides for a structured approach to extract and cluster data from textual evidence [31] [32] [33]. Analysis involved the following steps: creation of initial codes based on the MO framework, familiarisation with the data and assigning codes to text passages we deemed relevant, (sub-)theme review, summary and refinement of themes (3 iterations), and report production. In total, 21 codes were used to identify relevant passages in our data. We used computer-assisted qualitative data analysis software (Atlas.ti, version 8.4.4) to assign codes and export data in a tabular format. We then summarised similar extracts of text and grouped them into sub-themes and repeated the process until we had identified top-level themes.

In June 2017, we invited 80 individuals via email. 16 responded and offered to participate. From 21 June to 1 August 2017, 14 interviews (duration: ~45 minutes) were conducted face-to-face (n = 2), or by phone (n = 12). All respondents permitted us to record the interviews. The participation rate was 17.5%. Eight participants were associated with SMEs (5 pharma, 3 biotech), five with Big Pharma, and one with a service provider (consultancy). All participants were, or recently had been senior managers, vice-presidents or chief-operating officers and had extensive experience (~29 years) in marketing and/or R&D. Central data about our interviewees are shown in Table 1, and Appendix 3. Data saturation (86 unique concepts, see Appendix 4) was achieved by the end of the 12th interview, see Figure 1. Two further control interviews were conducted but no further concepts identified.

After concluding thematic analysis, we stratified our findings by stakeholder. Subsequently, we re-clustered, visualised and discussed our data several times. During this iterative analysis stage, we identified overarching themes, which we

AU: Australia, BD: Business Development, CA: Canada, CCO: Chief Commercial Officer, CEO: Chief Executive Officer, CSO: Chief Scientific Officer, Dir.: Director, Ex.: Executive, SG: Singapore, Sr.: Senior, SME: Small and Medium-sized Enterprises, US: United States, VP: Vice President.

mapped against the main stages of the SIVC, see Figure 2. Furthermore, we identified a similar analytical pattern that respondents consider for stakeholder stratification (reasoning and value), see Figure 3.

Various studies have found a positive correlation between a company’s degree of MO and its product and organisational performance, for both first-to-market and late-entrants [22]. Evidence suggests that the sooner innovators increase their degree of MO, the more sustainable their stakeholder and market alignment (and competitive advantage) is [34]. Our findings even suggest that the Pareto principle applies to market research: rapid (and early) review of easily accessible resources can provide substantial and relevant decision information. As market analysis plays such an important role for improving the potential societal value of new health interventions, it is all the more surprising that there exists paucity of market research direction for innovators in the biopharmaceutics sector. Our study addresses this important gap in the current body of MO literature and provides actionable guidance to reduce information discrepancy between innovators and their target market needs.

Being able to readily map our results against six out of ten stages of the SIVC has facilitated their meaningful stratification across a novel and pertinent innovation framework. It also emphasises, once again, the high degree of market information fragmentation across diverse stakeholders involved in the innovation process, as also observed by others [15]. A recent study found that even basic definitions of unmet needs are not identical across stakeholders [35]. This is problematic as concerted efforts based on shared understanding, awareness of and alignment towards needs and preferences of relevant actors, are required to maximise the value of interventions for society. On a more encouraging note, one of our respondents mentioned that one regulator liaises with providers and patients to identify unmet needs, and with companies to assess regulatory time-lines and the compassionate use of medicines in clinical trials. We contend that policies to incentivise the system-wide overall increase of MO should be more thoroughly explored for all relevant stakeholders, irrespective of if they add value to new interventions by, for example, vetting the safety and quality, or covering the costs, thereof. Systematic support (and empowerment) of all stakeholders to this end could lead to various benefits. For example, the long-term reduction of information fragmentation could contribute to strengthening and streamlining collaboration in healthcare innovation processes. However, to be effective, support must be nuanced and acknowledge the specific role and contribution of individual stakeholders, and stakeholder:stakeholder interfaces to de facto increase overall MO.

In addition to providing an analytical sequence of data per stakeholder, our stratification model is well-suited to inform and complement the population of decision support systems in the healthcare sector. Multi-criteria decision analysis (MCDA), which takes into account diverse, and potentially conflicting, criteria and requirements, is being used for reimbursement prioritisation in market access decisions [36] [37]. Recently, MCDA has been investigated as a decision tool for regulators assessing applications [38], but also suggested as a payer decision prediction tool for R&D organisations [39]. If innovators had, across various markets, access to stakeholder MCDA requirement profiles, which could be elicited and structured based on our stakeholder stratification model, the burden of MI collection and barriers for intervention improvement could be, potentially significantly, decreased. In addition, such profiles could improve the level of detail of needs for better segmentation of markets, group markets with similar stakeholder and need profiles, etc., and reduce resource consumption for MI.

Our findings also relate to a range of key factors of successful innovation as identified in a recent study for probiotics [15], further indicating the relevance of MI and orientation across industries in the broader healthcare sector with differential pain points and requirements. First, regarding early phases of technical development, our interviewees stated the importance of incorporating considerations relating to stakeholder value and decision-points at an early stage. In addition, our respondents highlighted that, to improve resource allocation and collecting evidence for applications with regulators and payers, it is important to align as closely as possible TPPs (target product profiles) with provider and patient preferences. The key factors of successful innovation, however, do not include payers, which is not surprising as probiotics usually do not require an intermediary institutional payer. Second, when designing early market introduction strategies, our interviewees (primarily referring to prescription interventions) indicated that interactions with leaders in the field can facilitate collaborations and help establish or increase awareness of the medical need and potential intervention(s) among healthcare providers. In addition to said interactions, the key factors of successful innovation include issues related to determining sales channels and strong competition on retailer shelves (for functional foods). Although of secondary nature, this was also a theme in our data pertinent to OTC products sold by pharmacies. Nevertheless, innovators in the biopharmaceutics industry should have a clear understanding of how their product will be classified and accessed, and who will be the payer. A timely example of novel classifications, in this case for the hospital-market, is CAR-T therapy in Australia: on one hand, it is regulated as a biologic and not a prescription medicine and, on the other, reimbursed as a medical service rather than a pharmaceutical [40] [41]. Third, while the key factors of successful innovation highlight the importance of good manufacturing practices (GMP), GMP was not a central theme in our data. This is surprising, as in particular in the biopharmaceutics industry, GMP and the specific quality standards that underpin GMP are mandated and monitored by regulators in essentially all markets, and indeed GMP standards can be identified by market research. [42] However, this might be due to the fact that the implementation of GMP is not primarily a marketing-related activity. Nevertheless, this once again shows that market research informs and aligns various stages of development or, in this case, manufacturing and evidence needs respectively with market requirements. Finally, our interviewees stated the importance of eliciting and responding to market feedback by improving their interventions and engagement strategies to better match customer needs. Regarding responses to market feedback, the key factors of successful innovation focus on inference of future customer needs from market feedback. Our respondents, on the other hand, emphasised the extrapolation of future needs by monitoring competitor pipelines and potential changes in regulator and payer priorities. Forecasting is an important function of MO and our stakeholder information and decision pathway model is suited to guide innovators in their assessment of the (future) needs and activities of diverse stakeholders, and indeed of the other above-mentioned factors.

By focussing exclusively on senior executives and marketing experts of the biopharmaceutics sector, our study provides evidence particularly pertinent to academic entrepreneurs developing new medical interventions. Our sample ranged from both consolidated as well as highly dynamic markets increasing the degree of external validity. In line with other works [29], we reached data saturation at the end of the 12th interview. This confirms that we asked a specific research question to a specific group of stakeholders. Additionally, the use of a consolidated theoretical framework and two researchers working in tandem improved the validity of data collection and analysis. This study provides a clear overview of the factors that are important primarily for prescription drugs because it was the type of intervention respondents alluded to most frequently. It is conceivable that for OTC drugs different aspects play a role, especially with regard to payers. Future studies could therefore explore differences between prescription and OTC interventions. Moreover, to fully understand the extent to which different factors resonate in society, a quantitative follow-up study could investigate, if priorities exist in our results across various stakeholders.

Above, we have primarily appealed to innovators to perform market research. Funding models can readily support innovators with market research, especially those developing interventions that promise step improvements in disease management. Importantly, a decreased dependence on private funding, for which incentives can be misaligned with unmet need, [43] with access to a market research toolbox, such as the one proposed here, could persuade innovators to invest more resources in market research. Issuers of public tenders, and in particular seed funds that can have a major impact on the sustainability of growth of (biotech) start-ups [44], are in a unique position to incentivize market research activities as early as possible [45]. In addition, some funding consortia, e.g. European Innovation Council [46], also offer coaching services that can include access to MI via partner networks [47]. They can thereby support innovators in, first, appreciating that market research is not merely an academic exercise but rather, serves to fundamentally inform them of the value judgements of their target audiences, and options to improve their interventions and the societal impact they are, in all likelihood, seeking; and, second, understanding which potential barriers they might face if they do not align their developments with the needs of stakeholders. Naturally, with available product-specific market research data, funders would have better grounds to evaluate the probability of new developments meeting the requirements of stakeholders and take decisions on further funding, and, over time, establish a baseline of experience with MI data facilitating differential decision outcomes. Funding models could also include earmarked budgets: first, limited funding for innovators to conduct basic market research (pre-application)—to inform the funding decision; and second, should development funding be approved, more substantial financial support for thorough market research—to align interventions with the needs of market(s).

Because our study is exploratory, it can be considered a starting point for future, more targeted research into the impact of different MI aspects on development timelines, health technology assessment, commercialisation success, etc., of therapeutic interventions. For example, although analysts might agree that certain MI considerations are important, it might not be clear which specific considerations and to which degree contribute to the success of interventions. Moreover, as alluded to above, besides MI a host of determinants exist that can drive the success of new interventions, and their utility for society. Similarly, future research could assess and quantify the relative contribution, and hence value, of each of these innovation drivers. Thereby, an overview of innovation policy blind-spots and corresponding priorities could be created to inform innovator support strategies.