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Interorganizational Relations in New Product-Service Systems Development

The Role of Complementary Capabilities

Published onJun 20, 2023
Interorganizational Relations in New Product-Service Systems Development
·
Luís Irgang1*, Henrik Barth1, Magnus Holmén1,
1Department of Engineering and Innovation, School of Business, Innovation and Sustainability – Halmstad University
*E-mail of corresponding author: [email protected]

Abstract

This study explores the complementary capabilities in PSS development by MedTech firms and how it drives interorganizational relations. The findings indicate three categories of complementary capabilities: health-related, data-driven, and social capital capabilities. They are attracted with formal contracts and additional benefits, remote support, and exploration of partners’ networks.

Keywords 

Product-Service System, Complementary Capabilities, New Product Development, Interorganizational Relations.

Background

The use of digital technologies such as Internet of Things, Big Data Analytics and artificial intelligence (AI) is changing how manufacturing firms create new value propositions, which may shift their business models from traditional product suppliers towards product-service systems (PSSs) providers consisting of design and development of integrated systems of products, services, and software (Kohtamäki et al., 2020; Agarwal et al., 2022). In the medical technology (MedTech) industry, PSS development rely on the reconfiguration of firms’ processes, structures, and routines to promote the early engagement of patients, practitioners, and suppliers in the design of new value propositions, and to extend the firm’s involvement and responsibility in the final stages of consumption and usage of solutions (Yip et al., 2014). Much work is grounded on the logic that value is co-created by the exchange of resources, skills and knowledge among patients, end-users, hospitals, and firms (Ciasullo et al., 2017).

Traditional MedTech firms face overlapping challenges to adopt the PSS logic in the business model (Pereira et al., 2019). The development of PSS solutions in healthcare relies on the combination of multidisciplinary capabilities such as engineering and data science, health sciences (Mathews et al., 2019). These are complementary capabilities for the traditional product-oriented MedTech firms, in the sense that to create value, MedTech firms existing capabilities, such as knowledge management and process management, need to be combined with complementary capabilities to create and deliver value to customers and users. However, these firms do not routinely pursue such capabilities, which means that they must develop them internally, by training or recruitment processes, or by involving external actors such as suppliers, customers, end-users and competitors (Martin et al., 2019; Li et al., 2022). More precisely, to create value for customers and users, firms must identify which complementary capabilities need to be integrated in the development of PSS value propositions, what actors pursue these capabilities, and which strategies firms can use to attract these actors (Kolagar et al., 2022; Huikkola et al., 2022).

Today, not much is known of these complementary capabilities for MedTech firms when diversifying from product markets to PSS solutions. In particular, to the best of our knowledge there are not any studies highlighting which ones are essential during different phases of PSS development. This is problematic because the nature of the complementarities affects how a focal firm aligns its activities with other stakeholders to successfully develop and exploit necessary capabilities to create and capture value (e.g., Jacobides et al., 2018). Here, complementary capabilities can be understood as the degree to which two or more actors are able to fill out, or complete, each other's performance by supplying distinct competences, knowledge, and resources (Jap, 1999).

Although prior literature has addressed how the imminence of PSS have triggered profound transformations on stakeholders’ relationships in value chains (Ayala et al., 2017), little is known about how MedTech firms design new configurations of complementary capabilities when developing and commercializing new PSS offerings (Szwejczewski et al., 2015; Kamalaldin et al., 2020).

Against this backdrop, this study aims to answer the following research question: what is the nature of complementary capabilities in PSS development and how does this drive interorganizational relations? We draw on the literatures on PSS (e.g., Mont, 2002; Tukker & Tischner, 2006), strategic capabilities (e.g., Grant, 1996; Teece, 2007), and innovation ecosystems (e.g., Adner, 2017; Jacobides et al., 2018) to identify the nature of the complementary capabilities in new PSS development and to explore how an established MedTech firm formulates, creates, or attracts complementary capabilities to develop new PSS value propositions.

Method

We conducted a single-case study with an embedded case study research design (Yin, 2018) of four PSS value propositions of a MedTech firm. According to Scholz and Tietje (2002), embedded case studies allow the interpretation, organization and integration of sets of knowledge originated from a complex case by analyzing its sub-units. Embedded case studies are suitable to explore the diversity of paths for the development of capabilities within and across an organization (Jovanovic et al., 2019), and allow to understand the complexities and contingencies of relationships that drive the co-creation of value in innovation processes (Ponsignon et al., 2011).

As a research setting, we selected a large leading MedTech company which manufactures sterilization equipment for the healthcare sector. Moving away from a focus on MedTech products, the company is transitioning its business model to become a PSS supplier. The company has more than 25,000 customers in more than 130 countries, with net sales approximating 2.1 billion dollars in 2022. The company has three business areas named acute care therapies, surgical workflows, and life science. Similar to De Toni and Pessot (2021), we selected four cases of PSS development as sub-units (see Table 1), with value propositions in different phases of development, i.e., need phase, solution seeking, solution development, solution realization, solution support, and solution closure (see Isaksson et al., 2011) to increase the representativeness of the findings.

The data collection is based on workshops, exploratory interviews and semi-structured interviews. First, we conducted two workshops with business directors, product managers, and external partners to get an overview of the company’s business models across business units, and identify opportunities and challenges related to the transition from a traditional product manufacturer to a PSS provider. Second, we conducted four exploratory interviews with product managers between March and June 2022. The interviews outlined how the PSS offerings are developed and commercialized. Last, we conducted semi-structured interviews between November 2022 and May 2023 (see Table 2).

We used a thematic analysis technique following a hybrid approach of inductive and deductive coding and theme development (Fereday & Muir-Cochrane, 2006). First, we identified the problems that drive the need for complementary capabilities (drivers). We then clustered them and linked to first-order complementary capabilities. Last, we clustered similar first-order complementary capabilities around high-order dimensions, and we then formulated aggregating labels according to their meaning and representativeness (see Figure 1).

To triangulate the data, we used documents such as project plans and reports, informal conversations, and follow-up interviews.

Table 1. Overview of the four cases.

Product area

Description

Phase of PSS development

External partners involved

Alpha

The project aims to develop and commercialize a software that optimizes the sterile supply workflow and helps hospitals to automatize the sterilization process.

Solution support: the solution is being commercialized and the company is focused on identifying opportunities to provide updates, add new features to the solution, and increase the sales.

- 1 university

- 1 hospital

Beta

An AI-based solution that reduces the incidence of surgical site infections. The solution is focused on the improvement of the air quality in operating rooms by monitoring and controlling environmental, procedural, and behavioral aspects during surgeries.

Solution development: together with its partners, the company is collecting data to test and analyze the functionality of the solution.

- 1 university hospital

- 1 university

- 1 IT company

- 1 research institute

- 1 medical device manufacturing company

Gamma

Development of a managerial solution (machine learning) to improve the workflow and use of resources in operating rooms by planning, scheduling, documenting, and tracking of surgeries.

Solution realization: the solution is launched on the market and the company is seeking for potential clients.

- 1 consultancy company

- 1 university hospital

- 1 hospital

Delta

Development of a predictive maintenance solution (machine learning) of machines and devices in use in hospitals.

Need phase: the company identified an opportunity to provide a solution for unmet end-user needs. Ideas are being elaborated and discussed, but no action towards the development of the solution has been taken.

- 1 university

- 1 hospital

Table 2. Descriptive information of data collection procedures.

No.

Case

Respondent - Formal position

Date

Dur. (min)

Stage 1: Workshops

1

Beta

Multiple participants

15-Dec-21

120

2

Alpha

Director of Product Management and Business Development

18-Aug-22

48

*

Director of Product Launches

*

Product Support Manager

Gamma

Product Manager

Stage 2: Exploratory interviews

1

Beta

Vice President Global Product Mangement

18-Mar-22

60

2

*

Director of Product Launches

28-Mar-22

60

*

Product Support Manager

3

*

Director of Product Launches

02-May-22

60

*

Product Support Manager

4

Alpha

Director of Product Management and Business Development

03-Jun-22

52

Stage 3: Semi-structured interviews

1

Gamma

Product Manager

21-Nov-22

48

2

Gamma

Data Scientist

24-Nov-22

45

3

Alpha

Director of Product Management and Business Development

07-Dec-22

65

4

Delta

PhD Researcher

08-Mar-22

49

5

Delta

Senior Director Open Innovation

29-Mar-23

47

6

Alpha

Product Manager

29-Mar-23

49

7

Delta

Director of Product and Solutions Management

30-Mar-23

53

8

Beta

PhD Researcher

30-Mar-23

52

9

Delta

Service Group Manager

18-Apr-23

58

*Professional who works in more than one case.

Figure 1. Data structure.

Preliminary Findings

Our preliminary findings indicate that the complementary capabilities in PSS development can be described in three aggregating dimensions: health-related capabilities, data-driven capabilities and social capital capabilities.

Health-related capabilities refer to the knowledge, skills and competences inherent to healthcare professionals and that are related to the provision of healthcare services. The company has limited technical knowledge in the health and medical area, but has chosen not to hire professionals with this expertise due to the associated costs with human resources, but especially because the company believes that it is more valuable to rely on the knowledge and experience from hospital practitioners, since they are potential users of the solutions and can share insights about the efficiency of the solution and the need for adaptations and improvements. To keep a strong relationship with this community and benefit from feedback on current solutions and new ideas on how to integrate new services into traditional product-oriented solutions, the company invests in periodic visits to hospitals by service technicians, after-sales calls, and multiple channels for remote support.

While in cases Alpha and Gamma medical doctors and biomedical technicians participate as end-users to collaborate with the improvement of the efficiency of the solution, in case Beta they are in the center of new PSS development, as they not only serve as source of ideas, but are responsible for managing the data collection and data analysis activities based on the events inside operating rooms. Moreover, they assist data scientists and engineers with understanding technical concepts and variables, as well as sensemaking the data, thus helping to turn technical medical knowledge into accessible information.

Data-driven capabilities

Data-driven capabilities are the skills and abilities related to the harnessing the power of data to explore business opportunities while ensuring cybersecurity and coping with data protection laws and regulations.

Ensuring cybersecurity crucial in the MedTech industry, and it is a top priority for hospitals when purchasing technological solutions from MedTech firms. In this regard, the company relies on IT consultancy companies to conduct penetration tests with solutions from cases Alpha and Gamma. To avoid any kind of biases, the company prioritizes formal contracts with experienced and reputed consultancy companies.

Similarly, the company relies on external actors to ensure data protection. As dealing with patient-related data is a very sensitive issue, the collection and analysis of data from hospitals is most of the time restricted to devices and equipment, as per in case Delta. In cases Alpha, Beta and Gamma, where there is direct or indirect collection and analysis of human-related data, data sharing between hospitals and the company for the development and improvement of PSS solutions is limited to encrypted data, while data storage is done exclusively by hospitals. In addition, data management is governed by very strict contracts, which somewhat limits the scalability of new products and services.

Unlike the medical knowledge that the company prefers to obtain from external stakeholders, the company understands that keeping in-house data analytics capabilities is essential after launching the solutions in the market. However, our findings show that during early phases of PSS development, data analytics capabilities are outsourced. Case Beta counts on the participation of data management experts from an IT consultancy company, while in case Delta the company relies on a university partner to develop and train machine learning algorithms.

Social capital capabilities

Social capital capabilities refer to the abilities of leveraging business relationships to create value and achieve strategic goals. Our findings indicate two types of social capabilities: networking capabilities and legitimation capabilities.

As a leader in the MedTech industry, the company seeks to be at the forefront of developing innovative solutions. Therefore, collaborating with universities and research institutes is essential to identify new opportunities arising from scientific discoveries. Although the company is well known and has a good reputation, it still depends on external actors to find suitable stakeholders. In this sense, respondents state that the company depends on the networking capabilities of its partners (often hospitals and universities) to find collaboration opportunities with new partners and public sponsors of innovation projects.

Legitimation capabilities refer to the set of competences that an individual or organization possesses that guarantee them a status of being reliable. Our preliminary findings indicate that partnering with hospitals helps the company to attest the usefulness and cost-benefit relation of PSS solutions. In this sense, respondents argued that well-known hospitals and medical doctors use their good reputation to test and validate the solutions, and to endorse the credibility and reliability of the solutions, thus helping the company to approach new customers and enter new markets.

Final Remarks

This study explored the nature of complementary capabilities in PSS development and understand how it drives interorganizational relations. Our preliminary findings indicate that the complementary capabilities in PSS development by MedTech firms can be described in health-related capabilities, data-driven capabilities and social capital capabilities.

The findings indicate that, to attract complementary capabilities, MedTech firms rely on negotiations and formal contracts, additional benefits to current clients, after sales contact and remote support, and exploration of partners’ networks and reputation.

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