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DEVELOPING A MATURITY MODEL FOR PRODUCT-SERVICE
SYSTEMS IN MANUFACTURING ENTERPRISES
Alexander A. Neff, Institute of Information Management, University of St.Gallen (HSG),
Switzerland, [email protected]
Florian Hamel, Institute of Information Management, University of St.Gallen (HSG),
Switzerland, [email protected]
Thomas Ph. Herz, Institute of Information Management, University of St.Gallen (HSG),
Switzerland, [email protected]
Falk Uebernickel, Institute of Information Management, University of St.Gallen (HSG),
Switzerland, [email protected]
Walter Brenner, Institute of Information Management, University of St.Gallen (HSG),
Switzerland, [email protected]
Abstract
The constantly rising fraction of industrial services reveals the structural economic change that is changing
the manufacturing industry landscape. Manufacturing firms have more and more problems to find the
appropriate information technology (IT) solution for planning and execution as they are confronted with the
strategic challenge of reducing operating costs while at the same time meeting ever-increasing industrial
service demands. Despite the existence of some standardization efforts dealing with product-related services,
there is no common understanding of product-service systems and the corresponding processes and IT
systems among manufacturing companies. This paper addresses this need by developing a maturity model
capturing the key requirements for the information systems (IS) support of product-service systems based on a
multiple case study. Further, we confronted these requirements with scientifically recognized maturity models
and standard specifications developed by the German Standards Institute. The development of the maturity
model is grounded in the design science research approach and is evaluated by managerial experts.
Keywords: Service Science, Information Systems, Product-Service Systems, Maturity Model, Design
Science Research.
1 INTRODUCTION
Nowadays, the manufacturing industry is undergoing significant structural economic changes (Vargo
& Lusch 2004; Wölfl 2005). In the German mechanical engineering sector, the total turnover related
to industrial services has made significant advancement from 16.8% in 1997 to 22.5% in 2000, while
the fraction in the electrical engineering industry has almost doubled in this period (Stille 2003). On a
European scale, services account for almost half of the profits of manufacturing companies with a
average annual profit growth of five percent (Strähle et al. 2012). The constantly rising fraction of
industrial services in all Organisation for Economic Co-operation and Development (OECD) countries
except Luxembourg (OECD 2011) results in the need for product-service systems to be supported with
the appropriate IT solution. Manufacturing firms have more and more problems to find the appropriate IT
solution for planning and execution as they are confronted with the strategic challenge of reducing operating
costs while at the same time meeting ever-increasing industrial service demands. (Dietrich 2006). While
legacy systems need to be replaced, expensive proprietary systems and highly customized standard
solutions must be maintained to serve the service component (Günther et al. 2009; Thomas et al.
2008). Notably, firms encounter problems in the maintenance function of product-service systems
(Thomas et al. 2008) and in supporting the managerial accounting (Dietrich et al. 2008). Moreover,
one of the major difficulties lies in the detail and accuracy of status information on the service
execution process, which is required by different hierarchy levels in the company.
The situation is even more challenging in business segments that are characterized by numerous and
strongly diverging production processes and highly versatile products. This holds particularly true for
the manufacturing industry, typically involving batch processes in press plant, highly automated
production lines, and assembling activities with load and balancing requirements. Service research has
traditionally concentrated on the front stage of service delivery, studying phenomena such as provider-
client relationships, co-creation of value, service quality, service encounters, and service experiences
(Glushko & Tabas 2009; Teboul 2006). However, there is a lack of research studies on the back stage
of service systems (Becker et al. 2011; Glushko & Tabas 2009). The authors apply an information
systems research perspective of service science. In view of the foregoing, a concept is needed allowing
a holistic support for such broad design and transformation tasks. Being successfully implemented in
the software engineering domain (Paulk et al. 1993), maturity models represent an established means
to support effective management for complex, heterogeneous phenomena (Ahern et al. 2004). Our
objective is to develop a maturity model that is capable of holistically assessing the IT support of
product-service systems in the manufacturing industry and that is based on highly relevant
requirements. Hence, we address the following research questions (RQ):
(1) What maturity models are capable of holistically assessing the IT support of product-service
systems in the manufacturing industry?
(2) What could a product-service system specific maturity model targeting key requirements of
multinational manufacturing enterprises look like?
In order to address these research questions, the authors conducted a multiple case study analysis with
leading manufacturing firms from the capital equipment goods industry. The authors contribute to the
body of knowledge by identifying requirements that are not covered holistically in existing maturity
models. Based on the identified requirements, the research gap is addressed with the development and
evaluation of a holistic maturity model. The following paper is divided into four parts. The first part
lays the foundation by considering the central terms and the research gap studied in this paper. The
second part describes the selected research approach. The third part answers RQ.1 by exploring
unaddressed requirements and analyzing existing maturity models and publicly available
specifications (PAS). The fourth part is concerned with the development and evaluation of the
maturity model (RQ.2). Finally, we conclude with our major contribution, supplemented with a critical
reflection and an outlook on future research.
2 RELATED WORK AND RESEARCH GAP
Academics as well as practitioners hold an ongoing debate on services and related products. Scholarly
literature considers service science from distinct academic perspectives, e.g. information systems,
marketing, management and operations management (Bardhan et al. 2010; Beverungen 2011; Maglio
& Spohrer 2008; Rai & Sambamurthy 2006; Spohrer & Kwan 2009). Service concepts heavily depend
on the academic imprint of the researchers. In accordance to the service dominant logic (Vargo &
Lusch 2004), IS scholars define services as the application of competence and knowledge with the aim
of creating value between providers and receivers (Spohrer et al. 2007). Lately, the notion of the
“service system” has been put forward as the basic abstraction of the new discipline service science,
management, and engineering (SSME), representing “a dynamic value co-creation configuration of
resources, including people, organizations, shared information […], and technology, all connected
[…] by value propositions” (Maglio et al. 2009). In view of the broad conception of a service system,
extant literature in operations management tries to combine products and industrial services in terms
of bundles (Oliva & Kallenberg 2003), solutions (Davies et al. 2006; Tuli et al. 2007) and systems
(Goh & McMahon 2009).
The authors apply the definition of product-service systems, since it achieves most hits in a literature
search (among the three terms: bundles, solutions and systems) and fits best with the manufacturing
focus by adding the life cycle aspect (Neff et al. 2012). The definition recalls the “customer life cycle
oriented combinations of products and services, realized in an extended value creation network”
(Aurich et al. 2006). Although scholarly literature tries to consolidate the theoretical views on services
(Sampson & Froehle 2006), no consensus has been reached on a general definition of services
(Metters 2010). Present research in SSME focuses on customer value, such as value creation in service
economies, service marketing issues or service encounters, as well as value co-creation with customers
(Clarke & Nilsson 2008). Unfortunately, the existing research has not provided deeper insight into
business processes (Glushko & Tabas 2009), enterprise systems and software applications that are
required to integrate manufacturing and service processes in service systems. Although exchanging
information is accepted as one of the key challenges in SSME (Chesbrough & Spohrer 2006), the
literature falls short of outlining how IT artifacts have to be designed in order to make the appropriate
information accessible through the life cycle stages (Becker et al. 2011). In conclusion, there is a clear
need for an integrated solution with selected information exchange. Rather than analyzing transaction
cost economies, the authors focus on the requirements of product-service systems and the
corresponding IS / IT implementations. In particular, some producer stakeholders only supply physical
goods, whereas other producer stakeholders provide services in interaction with customers, thereby
fitting the front stage (i.e., services) and back stage (i.e., manufacturing carried out in the technical
core of operations) together into a seamless value network. Integrating service and manufacturing
processes is a challenging effort, as manufacturing processes and service processes require different
management approaches and are built upon different IT artifacts. For instance, service processes, as
opposed to manufacturing processes, are, due to their very nature, conducted in cooperation with the
customer as a co-creator of value (Tuli et al. 2007). Furthermore, customers often perceive “their
solution” to be inseparable (Bardhan et al. 2010), while manufacturers and service providers are faced
with the need to coordinate disparate business processes and resources to create this integrated service
experience.
Being defined as “the state of being complete, perfect or ready” (Simpson & Weiner 1989), the term
maturity implies an evolutionary progress in the demonstration of a specific ability or in the
accomplishment of a target from an initial to a desired end stage. IS scholars refer to a measure for the
evaluation of corporate capabilities (Rosemann & De Bruin 2005). Tying up in this line of
argumentation, Becker et al. (2009) explain that a maturity model serves as a tool for designing and
using IT effectively and efficiently. In essence, these models consist of multiple archetypal levels that
together represent the evolution of a certain domain (Fraser et al. 2002; Rosemann & De Bruin 2005).
The user, e.g. an organization, applies maturity models to benchmark and continuously improve
enterprise capabilities (Paulk et al. 1993). Assuming a strong link between the maturity level of a
particular capability and the effectiveness of the IT providing that capability, maturity models describe
how the value gained from IT increases along the evolutionary path (Urwiler & Frolick 2008).
3 RESEARCH APPROACH
In order to construct a maturity model and thereby address the RQs of this paper, we selected the
design science research (DSR) approach (Hevner et al. 2004; Peffers et al. 2007). This form of
research is widely accepted among IS scholars for addressing real-world problems and simultaneously
contributing to the body of scientific knowledge (Baskerville & Myers 2009). DSR strives to build and
evaluate “artifacts” with the aim of overcoming existing capability limitations (Hevner et al. 2004).
These artifacts represent the outcomes of the DSR process (Peffers et al. 2007). Using DSR, we argue
that maturity models are reference models (Herbsleb et al. 1997) and hence artifacts that show “an
anticipated, desired, or typical evolution path” (Becker et al. 2009).
Problem identification Iterative model development Model evaluation
· Problem identification and
motivation
· Conceptualization of maturity
levels (as in Paulk et al. 1993)
· Definition of structural dimensions
· Multi-perspective approach
(following Frank 2006)
· Multiple evaluation rounds
· Reflection on evaluation results
· Exploratory case studies
· Literature review
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1 3 4
· Section 2 (Related work and
research gap)
· Table 1 (Case study participants)
Ou
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rela
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Comparison of existing maturity
models
· Deduction of maturity model
requirements
· Identification of existing maturity
models
· Evaluation of existing maturity
models
· Exploratory case studies
· Literature review (following vom
Brocke et al. 2009)
· Likert-scale ranking of MMs
2
· Section 4.1 (Analysis)
· Table 2 (Results of the keyword
search)
· Table 3 (Model fit assessment)
· Iteration 1: Content analysis of case
study reports
· Iteration 2: Model adoption
mechansims (vom Brocke 2007)
· Iteration 3: Focus group analysis
(Tremblay et al. 2010)
· Section 4.2 (Synthesis)
· Table 4 (Maturity model for
product-service systems)
· Focus group workshop
(Tremblay et al. 2010)
· Self-assessment of manufacturing
companies
· Section 4.3 (Evaluation)
· Table 5 (Profile of focus group
members)
· Table 6 (Self evaluation of
manufacturing companies)
· Iteration 1: Conceptualization of
maturity levels (as in Paulk et al.
1993) & definition of structural
dimensions
· Iteration 2: Integration of
requirements
· Iteration 3: Model refinement
Figure 1. Procedure model based on Becker et al. (2009)
We are aiming to investigate heterogeneous phenomena with a homogeneous model, and a maturity
model is well-suited for this analysis of product-service systems in the manufacturing industry. The
development of maturity models within the IS field is not new, and has been popular for quite some
time (De Bruin et al. 2005); literature scholars have counted numerous models (Becker et al. 2010b;
Mettler et al. 2010). In contrast to the large number of maturity models, the research on how to
develop these models is rather sparse (Becker et al. 2009). Additionally, most authors seldom
demonstrate their development process. During our literature review (Chapter 4.1), we encountered
only a few development procedure models, and the results suggest that there are two popular models
(Becker et al. 2009; De Bruin et al. 2005) among IS scholars. We decided to apply Becker et al. (2009)
to develop our maturity model, since this provides a stringent as well as a consistent development
process that is subject to the DSR guidelines (Hevner et al. 2004). Becker et al. (2009) propose an
eight-step development process for maturity models which we adapted slightly (Figure 1). In order to
reduce the complexity of the model and to align the procedure process with the structure of this paper,
we merged three process steps (conception of transfer and evaluation, implementation of transfer
media and finally the evaluation) into one, the evaluation step. Nevertheless, we follow the steps
proposed by Becker et al. (2009) within the evaluation step. Transfer media represent hereby the
media which are used to communicate and illustrate the maturity model. Since DSR refers to a
problem-oriented approach, the development of the maturity model is usually initiated either by a
“need and require” intention or by opportunity-based innovation (Järvinen 2007). In light of this, our
approach starts with problem identification (step 1). We specified the research problem, provided
practical relevance and justified the value of the artifact. Since the boundaries between service and
manufacturing processes and their contexts, i.e. the service systems in which they are embedded, are
not clear, case study research is well suited to guide our research (Yin 2009). Over a period of 3
months, from April 2012 till June 2012, a team of two researchers conducted seven exploratory case
studies at worldwide leading manufacturing firms (Table 1). Based in the high-wage countries of
Germany and Switzerland, the manufacturing firms rely heavily on innovation and customer service
for achieving efficiency synergies. Although data was collected using a variety of methods, semi-
structured interviews were our primary method of data collection. Scholarly literature emphasizes the
benefits of the multiple case study approach in terms of enhanced validity (Eisenhardt & Graebner
2007). Multiple researchers can improve the creative potential, while the convergence of observations
strengthens confidence in the findings (Eisenhardt 1989). After writing down the interview transcripts,
the authors complemented the interview-based data collection by further analyzing system landscapes
and process maps. The final results were documented and triangulated in a case study report, which
was consecutively reviewed and approved by the industry partners. The second step, comparison of
existing maturity models (2), builds on the problem identification (1) and the identification of
shortcomings or lack of transferability in the analysis of existing maturity models. As part of this step,
we conducted a structured literature review in accordance with vom Brocke et al. (2009) to identify
existing maturity models devoted to the same or similar domains. Subsequently, we analyzed the
maturity models according to their domain and functionality as well as their capability to address the
research problems we had outlined. During the iterative maturity model development (step 3), we used
model adoption mechanisms (i.e., configuration, instantiation, aggregation, specialization, analogy
(vom Brocke 2007)) in a rigorous creation of a maturity model (structure and content). For the next
step, model evaluation (step 4), we combined the conception of transfer and evaluation, the
implementation of transfer media and the evaluation into one step (Becker et al. 2009).
Case company
[Industry]
Employees
> 10k
Turnover €
> 5 Billion
Interview
partner
Number of
interviews
ALPHA
[Industrial]
Process Automation IS
Manager 2
BETA
[Industrial] -
Vice President Service
Division 2
GAMMA
[Construction] - - CIO & Head of Processes 2
DELTA
[Industrial] - CIO 1
EPSILON
[Industrial] -
Head of IT Strategy &
Transformation 1
ZETA
[Utility] CIO 2
ETA
[Industrial]
Head of Corporate
Solutions & Technology 1
Table 1. Profile of the case study participants; numbers are based on the fiscal year 2010
4 MATURITY MODEL DESIGN
During the interviews, the authors were confronted with a large number of specific challenges and
requirements for product-service systems. After analyzing all of our data thoroughly, the authors
aggregated and consolidated the aforementioned requirements and discussed them in workshops with
experts (Tremblay et al. 2010). This process resulted in the derivation of a list of seven highly relevant
requirements. In order to create a holistic perspective and to identify the critical levers, we structured
our findings according to three segments (strategy, process, and information systems) (Österle 2010).
The intensive interviews with experts from different manufacturing corporations revealed the fact that
there is neither a common definition nor a standardized business model classification of the product-
service systems available. From a strategic perspective, these firms have developed their firm-specific
terminology, including classification approaches for business models. A similar thing holds true for
analytical objectives and performance indicators. The process perspective showed that mature
instantiations of installed base management and mobile solutions take advantage of valuable
operational and customer-centric data. Analyzing the cases from an information systems perspective,
we encountered a wide spectrum of system approaches. The system spectrum ranges from legacy
systems, through loosely coupled proprietary systems, to fully integrated enterprise systems. Applying
the most pragmatic approach of using proprietary systems was criticized by participants due to the
high level of software development and integration effort. Added to this problem, a high risk of low
data quality has a serious impact on the effectiveness and efficiency of the product-service system.
Furthermore, service processes need to be supported by a flexible and global service infrastructure.
According to our case study participants, the following aspects are not fully covered by existing
industry models and standards such as the PAS developed by the German Standards Institute (referred
to from here on as the DIN):
· (R1) Business model: The business model influences the service portfolio and hence the
business processes. However, all case study participants acknowledge that keeping capital
equipment goods operating at the customer site is essential to succeed in the service business.
The IS manager of ALPHA stated that “the ALPHA group distinguishes three business model
stereotypes: spare parts, life cycle service and full service. Each of them requires different
business processes for realization.”
· (R2) Service quality: Since the value of industrial services arises when the business customer
applies it, the service quality has to be ensured along the entire value chain, including external
vendors. For that reason, the following methods have been applied: roll-out global service
processes, establishing audits and certifications, and performance indicators. The CIO of
DELTA outlined that “we rolled out standardized service processes worldwide. Once a year,
the service locations are checked in a comprehensive audit program.”
· (R3) Installed base management: Managing the installed base is salient as it presents valuable
customer knowledge and creates critical insights about the machines in operation. The
following elements characterize this requirement: collecting and updating historic data after
repair and maintenance events, use of condition monitoring for preventive maintenance, and
optimizing the customer processes including equipment investment goods from competitors.
As stated by the manager of BETA, “the application of emerging technologies such as remote
setup, repair, and maintenance can help to keep up the operation condition with efficient
resources.”
· (R4) Mobile solution: There is a clear need to support service technicians during the customer
visit. The main purpose is to provide master data, historical data, service catalogues, access to
the knowledge base, and to trigger the billing and accounting processes. The manager at
EPSILON reported “on a mobile solution that guides the service technicians during repair
and maintenance activities. However, expensive proprietary systems serve as a technical basis
for the mobile support of our service technicians.”
· (R5) Enterprise integration: Most of the case companies primarily produce in their European
home market, while local entities are responsible for sales and service activities. Larger
production entities, smaller service entities and local subcontractors form a comprehensive
service network that requires appropriate architectural solutions. The resulting complexity
provides additional challenges to the IT architecture. As specified by the manager of ALPHA,
“locations with production and service hubs require substantially more information systems
support than smaller locations with a smaller budget. Cloud-based information systems
present a contemporary approach for such small entities.” The manager of GAMMA refers to
expensive customization projects for adapting enterprise systems to the service-specific needs.
· (R6) Data quality & integration: Ensuring high efficiency in the service processes requires
substantial investment in corporate data quality to establish standards. A set of profound and
reliable master data is crucial for automated service processes. Five case study participants
clearly indicated that service and product businesses are separated organizationally and that is
reflected in a separation of the adjacent information systems. As a result, product and service
components are covered by distinct data models. However, efficient contract management
requires an integrated view of product and service objects. The manager of BETA mentioned
that “the service level is specified as long text in the product object.”
4.1 Analysis
Based on the exploratory findings, we analyzed the existing literature that seemed promising for
addressing the discussed requirements. The selection of existing maturity models and DIN PAS was
based on the structured literature review approach (vom Brocke et al. 2009). We present below (Table
2) the results of the keyword search in which, using relevant keywords from literature reviews
(Bardhan et al. 2010; Berkovich et al. 2011; Beverungen 2011; Neff et al. 2012; Spohrer & Kwan
2009), we performed the searches of certain databases (EBSCOhost, ProQuest (ABI/INFORM),
Emerald, ScienceDirect, Web of Science, and AISeL) (vom Brocke et al. 2009). We limited our search
to title, abstract, and keywords, and it resulted in 57 matches for in-depth analysis. After the actual
content analysis, 53 articles were excluded, since they did not include maturity models in the targeted
domain or they referred to previous models instead. The findings can be narrowed down to four
articles. Since these maturity models do not even mention two of the relevant requirements (R4 and
R6), we continued the literature search with a forward / backward search that yields four DIN PAS;
deriving, in total, 8 articles for analysis.
Database
AN
D
“Stage model” OR “maturity model”
“Information technology” OR “information systems”
“Service
science”
“Product
service
bundle”
“Product
service
system”
“Product
service
solution”
Net
hits*
EBSCOhost 7 (33) 0 (9) 2 (8) 0 (1) 9
ProQuest 6 (73) 0 (8) 4 (37) 0 (5) 10
Emerald 6 (70) 2 (16) 6 (28) 1 (6) 15
ScienceDirect 0 (2) 0 (12) 1 (12) 0 (3) 1
Web of Science 3 (42) 1 (2) 3 (82) 1 (10) 8
AISeL 12 (49) 0 (0) 3 (3) 1 (7) 16
Net hits* 57
Legend: *) Double counts are removed manually
Table 2. Results of the keyword search (before in-depth analysis)
The keyword search yields four existing maturity models. This selection was also confirmed by two
conceptual publications in the product-service context (Becker et al. 2010a; Pöppelbuß et al. 2009).
Hildenbrand et al. (2006) break down the strategic service management of industrial organizations into
five stages, each of which reflects a distinct degree of service orientation. While Nägele and Vossen
(2006) focus on the integration of the customer into the service development, Oliva and Kallenberg
(2003) outline the transition of the corporate focus from product to service in a procedural model.
They claim that new organizational structures and business processes become necessary for the
adequate support of this transition. Spath and Demuß (2006) describe in their maturity model the
different roles that industrial service can obtain through the combination with physical goods in the
manufacturing industry.
The forward / backward search provides four standard specifications (i.e., DIN PAS) that outline
particular requirements. Special requirements are given through the integration of heterogeneous
service and product components, properties of the life cycle management, innovative business models,
customer integration and regulatory compliance. In accordance with DIN PAS 1094 (2009b), three
additional DIN PAS have been developed to deepen particular aspects. While DIN PAS 1082 (2008)
presents a standardized process for the development of industrial services in networks, DIN PAS 1091
(2010) encompasses interface specifications for the integration of product-service systems. DIN PAS
1090 (2009a) is concerned with IS requirements that are developed for the mobile support of the
technical customer service.
In order to derive the appropriate dimensions for the maturity model, the authors mapped the explored
requirements with the identified maturity models and the DIN PAS (Table 3). We used a five point
Likert scale to rank every article for every requirement according to the degree of coverage from 1
(very low) to 5 (very high). This method has been widely applied to IS research, e.g. by Alavi (1984).
The evaluation of coverage was conducted by the research team focusing on quantifying the
conceptual differences of the analyzed models. In the next paragraphs, we will outline examples that
illustrate the ranking process and the mentioned imperfect coverage of the requirements by the
existing industry models. None of the existing models covers can be called holistic as no model
addresses all requirements at the same time.
Framework [Source] Orientation Requirements
Standard Maturity R1 R2 R3 R4 R5 R6
Hildenbrand et al. (2006) - 4 3 1 1 3 1
Nägele & Vossen (2006) - 4 3 1 1 1 1
Oliva & Kallenberg (2003) - 5 1 4 1 2 1
Spath & Demuß (2006) - 4 3 3 1 1 1
DIN PAS 1082 (2008) - 3 1 1 2 2 3
DIN PAS 1090 (2009a) - 1 1 1 4 4 1
DIN PAS 1091 (2010) - 3 3 1 1 1 3
DIN PAS 1094 (2009b) - 4 3 3 1 1 2
Average 3.5 2.3 1.9 1.5 1.9 1.6
Legend: Degree of coverage: 1 very low; 2 low; 3 medium; 4 high, 5 very high
Table 3. Model fit assessment
The business model requirement (R1) achieves the highest average of all the requirements
investigated. Most attention in literature is directed towards the strategic debate about the appropriate
business model in the “servizitation” (Neely 2008) of the manufacturing industry, resulting in seven
articles for analysis. After dealing with transaction-based services, manufacturing firms recalibrate
their focus towards relationship-based activities such as professional services and sophisticated
maintenance (Oliva & Kallenberg 2003). They claim that new business models such as spare parts, life
cycle service and full service become necessary to support this strategic transition. Hildenbrand et al.
(2006) break down the strategic service management of industrial organizations into five stages, each
of which reflects a distinct degree of service orientation, but neglect the full service conception.
Nägele and Vossen (2006) posit a customer-oriented view from a purchaser to a partnering role in the
service development and hence they lack the provisioning function of a manufacturing firm. Spath and
Demuß (2006) consider the organizational capabilities to realize customer-individual solutions that
arise in the transition from product to service business. However, they focus on design and mechanical
engineering issues. DIN PAS 1082 emphasizes the development phase of product-service systems in
networks, while the need to develop an innovative business model is only outlined. DIN PAS 1091
addresses component-based interface specifications for supporting controlling, sales and organization
but neglects the implications for business models. DIN PAS 1094 rather provides an overview and
remains on a very generic level. Summing up, although particular publications achieve a relatively
high coverage of R1, the average resides on a medium to high level (3.5).
The lowest coverage was achieved by the mobile solution requirement (R4). The IS requirements
specified by DIN PAS 1090 are based merely on a particular case study analysis and, hence, lack
validity (Thomas et al. 2007). Furthermore, the document does not address billing transactions, refers
to custom-built software for the service technicians of the construction industry and does not
incorporate the latest technological shifts such as cloud computing. The authors, hence, conclude with
a very low to low coverage (1.5) of the mobile solution requirement that is addressed in three articles.
Summing up, the analysis revealed that the majority of maturity models only partially address these
requirements, while the DIN specifications make up a broader set but remain very generic.
4.2 Synthesis
In view of the unsatisfactory coverage of the relevant requirements, the development of a new
maturity model is preferable to the evolution of an existing model. Nonetheless, our maturity model
adopts the well-established dimensions, elements, levels, and functions of the investigated maturity
models. We developed the maturity model in three iterations. In the first iteration, we defined the basic
characteristics and structure of the model. Drawing from popular maturity models such as the
capability maturity model (CMM) (Paulk et al. 1993), we conceptualized five levels: prepared,
engaged, established, managed and optimized. For structural purposes, we employed the dimensions
strategy, process and information systems (Österle 2010) to collect together the exploratory identified
requirements. Whilst the first iteration satisfies the need for relevance through the content analysis of
the case study reports, the second iteration ensures rigour by assessing the requirements against
existing models and standards. As a result, we integrated the elements of analytical objectives (based
on R1 & R2), installed base management (based on R3), mobile solutions (based on R4), data
integration (based on R5 & R6) and data quality (based on R6). The element data integration
addresses R5 implicitly, since e.g. [C.1.4] refers to “data integration with major business entities”. In
this light, the second iteration is concerned with the alignment and specification of the maturity model.
Confronted with the lack of coverage of the analyzed maturity levels, we extended the scope to the
DIN PAS to specify the maturity levels further. The third iteration, which refers to a focus group
analysis, yielded the element business model (R1) as well as the specifications for the installed base
management and mobile solution maturity levels. The focus group (comprising a senior researcher and
two case study participants) allowed us to slightly adapt and balance the model in terms of details and
wording. Finally, we consolidated the contributions of the discussion and aligned the model (Table 4).
Since it lies beyond the scope of this paper to describe all the maturity levels in detail, we focus on the
two extreme levels of the developed model. Level 1, product-service systems prepared, implies that, in
addition to the capital equipment goods, only rudimentary services such as spare parts sales are offered
[A1.1]. There are no key performance indicators (KPIs) in place [A.2.1]. Regarding the business
processes, neither an installed base management [B.1.1] nor a mobile solution [B.2.1] is adequately
covered in the IS landscape. The data necessary for the analytical functions and sophisticated business
processes are gathered on an ad hoc basis [C.1.1], while a consistent quality assurance has not been
implemented [C.2.1]. Forming a clear contrast to Level 1, Level 5, product-service systems optimized,
describes a customer-driven, highly integrated and real-time organization. Instead of managing
particular functions associated with the installed base, the firm extends the business model by
managing the entire customer operation [A.1.5]. In order to integrate the customer’s needs, the
organization gathers a balanced set of financial, non-financial and customer-oriented KPIs [A.2.5].
Efficient processing and velocity in managerial decision-making is ensured by permanent and real-
time monitoring of the customer’s operation [B.1.5]. Moreover, fully integrated mobile devices are
deployed for the service technicians’ use, allowing them to perform create, delete, update and insert
(CRUD) operations for the installed base management, to trigger billing transactions, and to access the
knowledge database [B.2.5]. These aforementioned business processes require substantial investments
into the information systems landscape. Data from the production and service divisions need to be
automatically integrated on a real-time basis [C.1.5]. However, efficiency and effectiveness in the
product-service system depend on consistent data quality (e.g. master data, operational data,
transaction data, and knowledge base data) encompassing vertical and horizontal reconciliation
[C.2.5]. Intermediate levels are designed to be clearly distinguishable, so that a higher level
corresponds to additionally offered features. In the mobile solution element, e.g., this translates into a
clear add-on criteria sequence. On Level 2, access to customer data is provided [B.2.2], on level 3 the
access extends to a knowledge database (including CADs, construction plans, experience reports, etc.)
[B.2.3] and on level 4, the system allows for automatic billing of the service provided [B.2.4].
Dimension Element Level 1 Level 2 Level 3 Level 4 Level 5
[A]
Str
ate
gy
[A.1
.]
Bu
sin
ess
mo
del
[A.1.1]
Rudimentary
spare parts
sales
[A.1.2]
In addition
to[A.1.1],
reactive
maintenance
[A.1.3]
In addition to
[A.1.2], predictive
maintenance
[A.1.4]
In addition to
[A.1.3],
performance
contracting
[A.1.5]
In addition to
[A.1.4],
managing the
customer’s
operations
[A.2
.]
An
aly
tica
l
ob
ject
ives
[A.2.1]
There are no
specific KPIs
in place
[A.2.2]
Focus on
financial KPIs
[A.2.3]
In addition to
[A.2.2], non-
financial KPIs are
added
[A.2.4] In addition
to [A.2.3],
financial and non-
financial KPIs are
balanced
[A.2.5] In
addition to
[A.2.4], KPIs are
adjusted
regularly to
customer needs
[B]
Pro
cess
[B.1
.]
Inst
all
ed b
ase
ma
na
gem
ent
[B.1.1]
No
coordinated
interaction
[B.1.2] Basic
electronic
reports are
exchanged
[B.1.3] In addition to
[B.1.2], remote calls
on machines are
supported
[B.1.4] In addition
to [B.1.3],
continuous
monitoring based
on sensory data is
established
[B.1.5] In
addition to
[B.1.4],
maintenance for
competing
brands is done
[B.2
.]
Mo
bil
e
solu
tio
n
[B.2.1]
No mobile
support
[B.2.2]
Access to
customer data
is provided
[B.2.3] In addition to
[B.2.2],
access to knowledge
database is provided
[B.2.4] In addition
to [B.2.3],
transactions of
billing are
provided
[B.2.5] In
addition to
[B.2.4], full
integration of
mobile devices
is given
[C]
Info
rma
tio
n
Sy
stem
s
[C.1
.]
Da
ta i
nte
grati
on
[C.1.1] Data
is collected
on an ad-hoc
basis without
an integrated
approach
[C.1.2] Data
collection is
done manually
with basic
integration
applications
[C.1.3] In addition to
[C.1.2], data
collection is partially
automated with
partial data
integration (e.g.
intranet-based web
tool)
[C.1.4] In addition
to [C.1.3], data
collection is fully
automated, data
integration with
major business
entities (e.g. MIS)
[C.1.5] Data
integration is
fully automated
and optimized as
real-time
integration for
the whole
enterprise
[C.2
.]
Da
ta q
ua
lity
[C.2.1] No
data quality
assurance in
place
[C.2.2]
Rudimentary
quality
assurance
(plausibility
checks)
[C.2.3] In addition to
[C.2.2], quality
assurance includes
horizontal integration
(e.g. between
product and service
division)
[C.2.4] In addition
to [C.2.3], quality
assurance involves
vertical integration
(e.g. between
operative &
analytical systems)
[C.2.5] In
addition to
[C.2.4], data
quality is part of
a continuous
improvement
process
Table 4. Maturity model for product-service systems (after iteration 3)
4.3 Evaluation
A substantial element of DSR is the evaluation step that demonstrates the “utility, quality, and efficacy
of a design artefact” (Hevner et al. 2004). To conform to these requirements, we followed a multi-
perspective approach. As previously outlined, maturity models are particular instances of reference
models. Hence, we employed the four evaluation perspectives of Frank (2006) to structure and
document our evaluation findings. Further, we conducted a focus group workshop with representatives
of four additional manufacturing companies in order to make a confirmatory investigation of the
maturity model (Tremblay et al. 2010). The focus group was asked about comprehensiveness, validity
in self-assessment and the capability of supporting the development of a roadmap. The results were
structured according to the aforementioned evaluation perspectives.
The economic perspective suggests an evaluation based on the criteria of cost, benefit, and
coordination. Cost and benefits have rarely been measured due to the lack of cases in which the model
has been applied. The model by itself does not generate direct benefits. However, it helps to align the
service initiatives of manufacturing firms by framing the analysis of the situation and outlining the
required activities for advancement in maturity. The maturity model can also foster inter-
organizational standardization, since it supports the establishment of a unified terminology that is
compatible with the DIN PAS and existing maturity models. Further, it provides a better
understanding of the requirements of product-service systems not only for the industry but also for
software vendors to allow them to develop standardized support tools. Since improvement activities
can be easily identified by analysing the capabilities at the next higher level, the maturity model was
found particularly useful as a foundation for the development of a preliminary roadmap serving as a
basis for investment decisions.
The deployment perspective is subject to understandability and appropriateness criteria that are
confirmed by the managerial practitioners. Applying the business engineering framework (Österle
2010) and the DIN PAS, they agreed that the model presents a holistic and integrated approach to
assessing and improving organizations that implement product-service systems. Moreover, it provides
the first insights into developing a reference model to map the functional requirements with the
appropriate IT support.
From an engineering perspective, the intended purpose of the maturity model (defining and
explaining) and the application domain (capital investment goods industry) are aligned with the
research approach. The requirements are mapped to the elements of the maturity model. The model
was confirmatory investigated in a focus group workshop with representatives of four additional
manufacturing companies (Tremblay et al. 2010). The two hour focus group workshop took place in
October 2012 and was made up of five managerial practitioners as participants (see profile in Table
5), a senior researcher as moderator, and a junior researcher as observer. The focus group was asked
about comprehensiveness, validity in self-assessment and the capability of supporting the development
of a roadmap. Summing up, the general reactions to the presented model were positive. The mix of
business-related and technical items supports the comprehensiveness of the model. Nonetheless, two
managerial practitioners criticized the absence of a human-centred dimension. In particular, they
argued for addressing factors such as skill or specialisation.
Regarding the self-assessment, all participants were able to position their organisation by applying the
maturity model. Most of the managers located their product-service systems between maturity levels 2
and 4 (see Table 6). As a result, the total average across all manufacturing companies was 2.6. The
individual elements of the maturity model varied between a maturity level of 1.8 and 3.3. [B.1]
“installed base management” turned out to be difficult to implement and hence achieved the lowest
average of 1.8. However, one managerial expert in the focus group positioned his company at level 4.
He justified that self-assessment level by stating that “today, we are able to remotely monitor the
installed base at the customers’ plants. Our solution continuously analyses the sensory data and
informs the service staff, when problems occur. By doing so, we are not only able to ensure an
immediate replacement of the correct defect product [one assembly line can be driven by dozens of
capital equipment goods], but also provide accurate predictions on the remaining lifetime. The
customer value lies in the reduced downtimes of production facilities. As a consequence our sales went
up, while the company saved money by streamlining and accelerating the service processes”. [C.1]
“data integration” had the highest average of 3.3. One of the focus group participants put this down to
the large data warehousing and business intelligence projects which had happened in recent years. In
this light, he outlined that “we realized that our databases contain much valuable information on the
products deployed at the customer's place when we consolidate our services and systems. By means of
combining pieces of data from several data warehouses, it is possible to find out which customer
possesses which product at which location.”
Company
[Industry]
Employees
> 10k
Turnover €
> 5 Billion Function of the participant
Number of
participants
THETA
[Industrial] -
Head of IT Services for Sales
Head of Customer Service 2
IOTA
[Industrial] - - Director of ERP Systems 1
KAPPA
[Industrial] CIO 1
LAMBDA
[Industrial] - Head of IT Strategy 1
Table 5. Profile of the focus group participants; numbers are based on the fiscal year 2010
The epistemological perspective is concerned with the scientific value and the fulfilment of scientific
requirements. The development of the maturity model uses a combination of numerous scientifically
accepted approaches. The literature review is based on an established literature review framework and
ensures sufficient coverage of the existing maturity models. The research methodology takes case
study research to explore the requirements, follows an established procedural model for the
development of maturity models that is embedded into the design science approach, and critically
evaluates the artifact in accordance with approved evaluation perspectives and approaches. The
contribution to the scientific body of knowledge comprises the application of the maturity model
approach to the IS support of product-service systems in the manufacturing industry. For managerial
practitioners, in turn, the contribution lies in the assessment of their organization and the identification
of capabilities that serve as levers for corporate improvement. Managers are able to draw a preliminary
roadmap to increase the performance of the product-service systems within their organizations
according to their individual requirements.
Dimension Element Level
Average 1 2 3 4 5
[A]
Strategy
[A.1] - #2 #1 #1 - 2.8
[A.2] - #3 #1 - - 2.3
[B]
Process
[B.1] #1 #2 - #1 - 1.8
[B.2] - #3 #1 - - 2.3
[C]
Information
System
[C.1] - - #3 #1 - 3.3
[C.2] - #2 #1 #1 - 2.8
Total 2.6
Table 6. Self-assessment of four manufacturing firms
5 CONCLUSION
This paper aims to develop a maturity model for the IS support of industrial product-related services.
Contrary to the traditional focus on customer value such as co-creation with customers in SSME, we
adopt the perspective of manufacturing firms offering an integrated product-service portfolio. The
maturity model can be used as a management instrument to analyze the current set-up in order to
determine the key levers for improvement. The overall goal is the reduction of the effort needed to
unleash the full potential of the product-service system and the corresponding information systems
support. Accordingly, this paper addresses this need by answering two RQs in line with the DSR
approach. The first part of this paper investigates “what maturity models are capable of holistically
assessing the IT support of product-service systems in the manufacturing industry” [RQ.1]. For that
reason, the authors conducted a multiple case study to elaborate key requirements which serve as a
reference baseline for investigating whether existing maturity models are capable of holistically
assessing the IT support of product-service systems in the manufacturing industry. Using a structured
literature review framework (vom Brocke et al. 2009), we analyzed the coverage of those requirements
in current managerial and scientific frameworks. The findings indicate that existing maturity models
and DIN PAS only partially address the exploratory identified requirements, and hence that none of
the models is capable of assessing the problem holistically. For that reason, the authors develop a
maturity model in the second part of this paper. The model and its evaluation address the second
research question “what could a product-service system specific maturity model targeting key
requirements of multinational manufacturing enterprises look like” [RQ.2]. The model we developed
is based on the structure of existing maturity models and inherits conceptualizations and
methodologies from extant literature in IS, operations management, marketing, and general
management. Consistent with the fundamental principle in DSR of addressing real-world problems
and simultaneously contributing to the scientific and practitioners’ body of knowledge, it was the
researchers’ aim to produce consumable results for literature scholars and managerial practitioners.
Moreover, the maturity model benefited from a multi-perspective evaluation according to a
scientifically well-accepted approach (Frank 2006). The focus group workshop outlines the model’s
capability in terms of comprehensiveness, validity in self-assessment and supporting the development
of a roadmap. In particular, the self-assessment then offers further insights into the current state of four
additional manufacturing companies. The model is differentiated from existing maturity models not
only through its holistic coverage of the requirements, but also through its exclusive focus in the IS
domain.
The case selection might be described as a possible limitation of the study presented. A generalization
of the results could be enhanced by examining more cases and more industries. The utilization of a
quantitative research design might help to validate the findings. Another limitation is the focus on
multinational German and Swiss companies. The requirements derived are influenced by the
multinational setting of the firms which have, for example, a strengthening effect on the global service
infrastructure requirement. Additionally, the success of knowledge management initiatives heavily
depends on the managerial ability to make customers and employees contribute (Kankanhalli et al.
2005). Future research can investigate the validity of the model for local firms. The maturity model
presents an important step in understanding to what extent manufacturing firms struggle with the IS
implementation of product-service systems and how they apply proprietary systems. Following this
line of argument, we posit the development of a functional reference model (mapping the functions
with the IS support) with the aim of forming building blocks and identifying the standardization
potential of existing solutions.
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