Value Co-Creation in Data-Driven Services: Towards a Deeper Understanding of the Joint Sphere

Abstract

While the co-creation of value between provider and customer(s) is a common theme in service research, continued theoretical conceptualization is required to guide more effective design of services. In order to advance understanding of value co-creation, we have conducted a pre-study consisting of 16 interviews in the application domain of data-driven services-services that support the decision-making process of customers through the provision of data and analytics. Adopting the theoretical lens of joint spheres, we present empirical evidence that the proportions of the joint sphere can vary with differences in interaction, access to customer processes or behaviors and decision power. As a next step, we propose a final case study phase to further explore factors that influence the proportion of joint sphere and, thus, the provider's real value creation. Understanding how real value creation is impacted by the resource integration of provider and customer(s) will ultimately enable the purposeful design of data-driven services for effective value co-creation.

Full text

Value Co-Creation in Data-Driven Services
Fortieth International Conference on Information Systems, Munich 2019 1
Value Co-Creation in Data-Driven Services:
Towards a Deeper Understanding of the
Joint Sphere
Short Paper
Ronny Schüritz
Karlsruhe Institute of Technology
Kaiserstraße 89, 76133 Karlsruhe,
Germany
ronny.schueritz@kit.edu
Killian Farrell
MIT Sloan School of Management
100 Main St, Cambridge, MA 02141
USA
killianf@mit.edu
Barbara Wixom
MIT Sloan Center for Information
Systems Research
100 Main St, Cambridge, MA 02141
USA
bwixom@mit.edu
Gerhard Satzger
Karlsruhe Institute of Technology
Kaiserstraße 89, 76133 Karlsruhe,
Germany
gerhard.satzger@kit.edu
Abstract
While the co-creation of value between provider and customer(s) is a common theme in
service research, continued theoretical conceptualization is required to guide more
effective design of services.
In order to advance understanding of value co-creation, we have conducted a pre-study
consisting of 16 interviews in the application domain of data-driven services—services
that support the decision-making process of customers through the provision of data and
analytics. Adopting the theoretical lens of joint spheres, we present empirical evidence
that the proportions of the joint sphere can vary with differences in interaction, access to
customer processes or behaviors and decision power.
As a next step, we propose a final case study phase to further explore factors that influence
the proportion of joint sphere and, thus, the provider’s real value creation. Understanding
how real value creation is impacted by the resource integration of provider and
customer(s) will ultimately enable the purposeful design of data-driven services for
effective value co-creation.
Keywords: value co-creation, joint sphere, smart services, data-driven services
Introduction
In recent years, new ways to collect and transmit large volumes of data have emerged and advancements in
computational power have created the ability to analyze them (Chen et al. 2012; Turner et al. 2014). This
technology evolution enables a liquefaction of resources in which knowledge and its transfer is decoupled
from physical objects and their movement (Lusch and Nambisan 2015). This creates resources (such as
knowledge and information) that flow instantly and seamlessly among actors. As a result, these actors—for
instance, a provider and its customer—can interact and engage with each other digitally (Lusch and

Value Co-Creation in Data-Driven Services
Fortieth International Conference on Information Systems, Munich 2019 2
Nambisan 2015). Our understanding of such digital interaction and engagement is still unfolding and
requires refinement of the very nature of value co-creation (Nenonen and Storbacka 2018).
The need for a more nuanced conceptualization of value co-creation becomes evident in the context of data-
driven services, defined as the use of data and analytics by a provider to support a customer’s decision-
making process with the intent to create value for the customer; the data and analytics can stand alone as
an offering or be bundled with an existing product or service offering (Beverungen et al. 2019; Davenport
2013; Schüritz and Satzger 2016; Wixom and Ross 2017). This concept is not completely new: FedEx
introduced data-driven services in the late 80’s when the company added package delivery tracking to their
transportation services. FedEx customers used this tracking information—such as current shipment status
and predicted delivery time—to better manage their shipments (Baldwin 2013). Since that time, myriad
companies across a diverse range of industries have launched data-driven services that analyze data, guide
users through insights, and/or even automatically act on behalf of the user. In financial services, banks
developed financial spending dashboards and alerts to help customers manage their budgets and cash flow
(e.g., Alfaro et al. 2018). Heavy equipment manufacturers developed algorithms that predict parts failure
to help customers proactively maintain equipment and reduce operational downtime (e.g., Porter and
Heppelmann 2015). In these data-driven services contexts, our existing understanding of value co-creation
through actor-to-actor interaction (Grönroos and Voima 2013) is challenged because actors can be deeply
integrated in other actor’s processes and because interactions can take place through automated algorithms
(Storbacka et al. 2016).
Inspired by the proliferation of data-driven services and by the interesting new provider-customer
relationships and interactions that they represent, we sought to explore the co-creation of value in data-
driven services contexts. This research aims to contribute towards a more nuanced conceptualization of
value co-creation and resource integration. Specifically, we investigate factors that influence the space in
which providers and customers interact to co-create value, called the joint sphere (Grönroos and Voima
2013).
To do this, we conducted an initial research phase to examine the level of provider-customer integration
across a diverse set of 36 data-driven services examples. We analyzed the examples and interviewed a subset
of 16 executives of service providers associated with eight of those examples to refine our analysis. We
learned that in data-driven services contexts, the proportions of the joint sphere are determined by
interaction, access to customer processes and behaviors, and decision power. Only in the joint sphere can
the provider purposefully integrate resources to affect real value creation—that is, the value a customer
realizes in the use (value-in-use) of a service (Grönroos and Voima 2013). The final phase of our research
will explore the co-creation of value more comprehensively by collecting data from all participating actors
of a specific service system.
We first present a brief literature review of value co-creation and data-driven services. Next, we explain the
study methodology and analysis to date. We illustrate our current thinking by conceptualizing the
influencing factors of the joint sphere and real value creation—supported by examples from our application
domain. The paper closes with a discussion of preliminary results and a description of our next steps.
Related Work
Value Co-Creation
The goods-dominant logic views products and services as outputs of a production process that are valuable
as objects in existence. This value is consumed and destroyed by the user or customer. By contrast, service-
dominant logic (S-D logic) considers the value of an offering as co-created through the application of the
operand and operant resources of both provider and customer (Vargo and Lusch 2004). Ultimately, this
means that value is not determined by the features of an offering but by the value perceived by the user
(Vargo and Lusch 2004). The service-dominant view and the co-creation lens have found broad adoption,
and authors have focused on a wide range of aspects of this view. This has included modifying the initial
conceptualization (e.g., Chandler and Vargo 2011), adding new perspectives (e.g., Payne et al. 2008),
looking into applications (e.g., Yan et al. 2010), and clarifying issues around the perception of co-creation

Value Co-Creation in Data-Driven Services
Fortieth International Conference on Information Systems, Munich 2019 3
as such (e.g., Vargo and Lusch 2016). Moreover, S-D logic serves as the foundation for service science
(Spohrer and Maglio 2008; Vargo and Lusch 2016).
Many scholars agree that the initial S-D logic view on co-creation was too vague to sufficiently understand
value creation between a service provider and a customer (e.g., Ballantyne et al. 2011; Grönroos and Voima
2013). Thus, Grönroos and Voima (2013) proposed that co-creation results from the interaction between
providers and customers, and introduced the concept of provider, customer, and joint spheres (cf. Figure
1). This view specifies co-creation to be a joint process in which firms (or other actors) and customers
together create value in interaction (Grönroos and Voima 2013). Before this joint creation of value, the
provider acts independently and without customer involvement in the provider sphere. In the provider
sphere, the provider facilitates value creation, that is, the provider creates potential value for a customer.
The customer then (in the customer sphere) independently transforms potential value from the provider
into value-in-use or real value (Gummesson 2007). Therefore, the only way the provider can directly
influence real value is by interacting with the customer and co-creating value in the joint sphere. The joint
sphere is defined as the locus where value co-creation in interaction takes place (Grönroos and Voima
2013).
Figure 1. Value creation spheres, adapted from Grönroos and Voima (2013)
The concept of value creation spheres was criticized by Vargo and Lusch (2016) as being incomprehensible
and without valuable contribution for scholars and practitioners (Vargo and Lusch 2016). Specifically, they
criticized the poor distinction between “facilitate” and “co-create“ (Vargo and Lusch 2016). Both
perspectives contribute intriguing and useful insights to the conversation and help us to understand how
value is co-created between actors. While Vargo and Lusch (Lusch and Vargo 2014; Vargo and Lusch 2016)
see the beneficiary of a service always as a co-creator of value, Grönroos and Voima (2013) add a more
differentiated view by determining that co-creation only occurs if provider and beneficiary interact in the
joint sphere.
Data-Driven Services
Information systems that gather, store, access, and analyze data to help business users make better
decisions, commonly referred to as decision support systems, have been widely discussed in the IS literature
(Chen et al. 2012; McAfee and Brynjolfsson 2012; Watson 2009). When building decision support systems
to generate efficiencies, the literature usually distinguishes among three steps: data, insight, and action—
sometimes referred to as the data value chain (Watson 2009; Wixom et al. 2013).
Beyond using data to achieve operational efficiencies for themselves, companies can also use their data to
innovate service offerings and, thus, create meaningful value for customers. Practitioners and scholars alike
have turned to integrating this notion into their frameworks, beliefs, and systems (Beverungen et al. 2019;
Davenport 2013; Gottlieb and Rifai 2017). Because this research is still developing, many conceptualizations
and terms are being proposed. Some academics (Allmendinger and Lombreglia 2005; Beverungen et al.
2019; Spohrer et al. 2018) use the term “smart services” to describe service offerings based on smart

Value Co-Creation in Data-Driven Services
Fortieth International Conference on Information Systems, Munich 2019 4
products; smart products have connections, sensors, actuators, and interfaces that enable the products to
communicate and act. Schüritz et al. (2017) and Hunke et al. (2019) see the opportunity to utilize data and
analytics in services as part of the approach to create a new value proposition for the customer. Regardless
of different conceptualizations or terms, current research in this space consistently describes the use of data
and analytics to support the decision-making process of the customer via data and analytics-based features
and experiences in form of a stand-alone offering or bundled with an existing product or service; we refer
to this phenomenon as data-driven services.
Methodology
To explore how companies use data and analytics to co-create value with customers, we adopted an
exploratory qualitative approach that would help us learn about a new phenomenon, develop constructs
and possible relationships, and generate explanations for our observations (Myers 1997).
First, we assembled a database of diverse data-driven services examples. We involved 86 executives who
were responsible for the analytics strategy in large, multinational companies (e.g., Chief Data Officers, Chief
Analytics Officers). Within the context of a closed online community—moderated by two members of the
research team—we asked the executives to provide their “best example in which [their] organization
provides customers with some form of data and/or analytics to increase the value of a product or service”.
The community provided us with 36 examples of which 27 were data-driven services. The others
represented traditional decision support systems applications that did not provide direct value to the
customer. For the data-driven services examples, we identified differences in maturity and in the level of
integration between provider and customer. We therefore choose to conduct interviews for select examples
to better understand meaningful distinctions.
In order to purposefully select a subset of the 27 service examples, we established a set of selection criteria
that would generate diverse perspectives (Patton 2002): we identified a set of data-driven services that were
launched and in use by customers, represented a variety of industries, and represented both B2B- and B2C-
relationships. Based on these criteria we selected eight examples, and conducted 16 semi-structured
interviews of 30 to 60 minutes with the product manager of each service as well as their analytics
counterpart—both interviewed about the same data-driven services example (cf. Table 1). The paired
interviews provide complementary information as to the nature of the service, the service design and
development, the evolution of the service, and the value creation for the customer. In two examples, the
product manager was analytics-savvy enough to answer our questions independently, and in two examples,
both a data and an analytics manager answered our set of technical questions.
All interviews were conducted via an online video conferencing tool, recorded (with consent), and
transcribed. Researchers analyzed the data independently in several rounds of coding, using memoing and
an open coding approach. We later applied axial coding to group the codes into categories (e.g., type of
Table 1. Overview of interviews
Service
Industry
Revenue
Product
manager
Analytics
counterpart
Alpha
Professional Services
>1B USD
ü
üü
Beta
Financial Services
>15B USD
ü
Gamma
Telecommunication Provider
>20B USD
ü
ü
Delta
Financial Services
>15B USD
ü
ü
Epsilon
Technology Provider
>1B USD
ü
üü
Zeta
Governmental Agency
N/A
ü
ü
Eta
Financial Services
>10B USD
ü
Theta
Information Services
>5B USD
ü
ü

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Fortieth International Conference on Information Systems, Munich 2019 5
interaction between provider and customer, resulting customer benefits, etc.), which we then further
developed into common themes and concepts. Through continuous abstraction in small workshops among
the researchers, we identified different manifestations of the joint spheres and extracted factors that we
found to impact the joint sphere during value co-creation.
Observations
In our analysis of data-driven services examples, the joint sphere (Grönroos and Voima 2013) helped to
distinguish the provider alone creating potential value and the provider creating real value with the
customer. By distinguishing the creation of potential value from the creation of real value, we could identify
varying proportions of joint spheres in the data-driven services examples. We termed three primary varying
proportions as no or limited joint sphere, developed joint sphere, and extensive joint sphere. We also
identified properties of services that seemed associated with different proportions.
Co-Creation in Data-Driven Services
Data-driven services without any or with only a limited joint sphere provide data in raw or aggregated
form to customers. The provider facilitates value creation by collecting as well as preprocessing data and by
"delivering” the data via reports, dashboards, or APIs; the provider does not have direct understanding of
how clients use the data, what insights they derive, or how the provided data influences their actions.
Customers derive insights and take actions themselves—as our example from Beta illustrates: A bank
provides its institutional customers with an API to allow them to access their financial transactions and to
download the transactions into internal processes if and how the customers choose. A limited join sphere
may exist if customers give the provider adoption requirements, such as technical file requirements or fields
to include; this happened in the Beta example as an API was customized for top customers.
We identified another category of data-driven services through which providers deliver insights to
customers. The insights manifest as the provision of alerts, identification of aberrational activities,
comparisons against benchmarks, or proposals of next steps. In these cases, the joint sphere includes more
provider-customer activity; for example, the customer supplies the provider with data and information to
incorporate into services; customers also provide the provider with requirements regarding their intended
independent value creation. The services, however, still depend on the customer action to turn insights into
real value: for instance, in our data-driven services examples, the professional service firm Alpha offers
financial auditing for its business customers and uses investigative and trend analytics to make the process
more efficient, and customers provide access to data as part of the audit process. Using the engagement
data and engagement insights, Alpha developed data-driven services in the form of scores that reflect
fraudulent or corrupt practices and transactions. Although the scores could impact real value creation if
acted upon; the customer creates real value independently only if corrective actions are put in place post-
engagement.
Finally, we observed an extensive joint sphere in some of our examples. In these cases, providers directly
acted with or on behalf of the customer in ways that generated real value, e.g., in performing predictive
maintenance to avoid unplanned machine downtime. The action manifested as manual interventions or
automated processes. For example, in our example at Epsilon, hearing aid users grant access to behavioral
data and give the provider permission to control device settings. The provider then automatically adjusts
the hearing aid settings using algorithms that optimize hearing based on a noise context while the customer
is wearing the device. In these cases, the provider and customer processes and practices are deeply
interwoven, and there is a large joint sphere in which the provider participates substantially and regularly
in real value creation and can ensure that real value is created.
Table 2 illustrates a continuous spectrum (rather than distinct categories) of possible joint sphere
constellations. The table provides actions in the provider sphere for value facilitation, actions in the joint
sphere for real value creation, and actions in the customer sphere for independent real value creation. We
include supporting quotes regarding joint sphere activities for each spectrum.

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Fortieth International Conference on Information Systems, Munich 2019 6
Towards Re-Conceptualizing the Joint Sphere for Value Co-Creation
Our analysis of data-driven services leads us to a re-conceptualization of the joint sphere. We consider the
joint sphere to include the range in which the provider directly affects real value creation by integrating
resources with the customer. Our analysis identified three factors that may impact the proportion of the
joint sphere: interaction, access to customer processes and behaviors, and decision power (cf. Figure 2):
1. Interaction is defined by “physical, virtual, or mental contact, such that the provider creates
opportunities to engage with its customers’ experiences and practices and thereby influences their flow
and outcomes” (Grönroos and Voima 2013, p. 140). In data-driven services, interaction includes
contacts like data exchange, requirements elicitation, automated actions, etc. More interactions – and
two-way interactions - provide opportunities for more and deeper understanding of customer needs
and meaningful services.
2. Access to customer processes or behaviors represents how and when a provider can integrate into the
daily activities of the customer. Increased access to customer processes and/or behaviors increases a
provider’s context knowledge of customer motivations, problems and latent needs. In addition, access
can better position a provider to influence or perform customer processes and behaviors in a beneficial
way, thus ensuring real value creation.
3. In this services context, we define decision power as the extent to which one actor can make decisions
regarding the decision-making process of another actor. Traditionally, the customer controls real value
creation and retains full decision power regarding services. Our analysis revealed examples in which
the provider has some decision power and thus can directly affect real value creation through action-
based data-driven services.
Table 2. Exemplary activity in spheres
Joint Sphere
Spectrum
Provider Sphere
Joint Sphere
Customer
Sphere
Quote
No or
Limited
Joint
Sphere
§ Collecting and
preprocessing
data
§ Optional: customer
communicates
requirements
§ Deriving
insights and
acting
“[…] [W]e don’t know what is
the intended user of that
information once it’s delivered
to the customer.”
Beta, product manager
Developed
Joint
Sphere
§ Collecting and
preprocessing
data
§ Applying
resources to
derive insights
from data
§ Customer shares
information and gives
access
§ Provider gains
knowledge about the
customer to derive
insights from data
§ Acting based
on provided
insight
“[The data-driven service]
allows them to see insights on
their business, and also
anonymized insights on their
peers, and maybe the area
they’re in […].”
Delta, product manager
Extensive
Joint
Sphere
§ Applying
resources to
derive insights
from data
§ Customer opens
processes and grants
decision rights
§ Provider empowered
to make decisions and
changes in customer
processes and
practices
§ No
independent
action
“[…] [I]t’s really the processor
itself […] monitoring or
classifying the environment on
an ongoing basis. […] [T]he
software automatically adjusts
its setting to the appropriate
settings for that environment.”
Epsilon, product manager

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Fortieth International Conference on Information Systems, Munich 2019 7
We believe the joint sphere can be enlarged through some combination of interaction, access and/or
decision power. To maximize the joint sphere, we believe that all three factors need to be fully developed.
Figure 2 gives an overview of the relationship between the joint sphere, the factors influencing its
proportion, and potential and real value creation (via resource integration).
Discussion
Using data and analytics to inform decision making has long been an area of interest for academia and
industry alike. Enriching product and service portfolios by helping customers make decisions has recently
become an interesting strategy by companies and is now being actively explored by academics. When actors
co-create value using data-driven services, the data value chain is shared between a provider and a
beneficiary. The design of the service defines what activities are conducted by which actor, such as collection
of data, preprocessing of data, the application of analytics on this data to derive insights, and even decision
making and resultant action. Depending on the nature of the interaction, the access to customer processes
or behaviors, and the decision power, the data value chain may be shared in a way that creates a larger joint
sphere. Ultimately, the way the data value chain is shared has a tremendous impact on value creation. If the
nature of sharing increases the joint sphere, then the provider can participate in more real value creation.
For some time, there has been a call for a refinement of how actors contribute resources to create value
(Lusch and Nambisan 2015; Nenonen and Storbacka 2018). We see value in a more nuanced view of co-
creation of value by taking the perspective that the provider facilitates value in the provider sphere and only
creates real value in the joint sphere. In our data, this distinction was important, and we argue that the joint
sphere determines whether resources that are integrated by the provider are used purposefully to ensure
that potential value is realized and transformed into real value. Interaction initially defined the size of the
joint sphere (Grönroos and Voima 2013). This conceptualization, however, does not include the impact of
access to customer process and behaviors and the impact of decision power. We believe a deeper
understanding of the joint sphere includes three factors that influence the joint sphere proportion.
Future Research
Our research at this point has a strong dyadic customer and service provider perspective because it does
not consider other actors. Further, our research to date only included data collected from providers.
To further advance this research on value co-creation using data-driven services, we want to shift to a more
comprehensive perspective and collect data from all participating actors in data-driven services setting,
including customers. We intend to perform a series of case studies of companies that have data-driven
services with varying proportions of joint spheres. We intend to collect data from 2-3 different companies
in two different industries, and we would like one industry to reflect a B2B business types and the other to
reflect B2C.
Figure 2. Re-conceptualized value creation spheres

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Fortieth International Conference on Information Systems, Munich 2019 8
Within each case study we will review artifacts that that help us understand the service design and value
creation process (e.g. websites and presentation material). We will interview representatives of the provider
including product managers, service managers and executives, and technical experts. In addition, we will
interview multiple representatives of the customer. In a B2B context this will include the department that
is benefiting from the service as well as departments that are concerned with service integration. In a B2C
context this will include end users. For a comprehensive treatment of the context, we also plan to include
other actors that participate in the value creation process, such as IT service providers, partners and
platforms (Yin 2013). Data will be analyzed using qualitative methods.
The case study phase results will help us refine the concepts presented earlier in Table 2. Prior to ICIS 2019,
we will identify case sites and set up researcher visits, draft the case study interview questions, and collect
and review publicly-available artifacts in preparation for the visits. We intend to begin interview visits after
we receive and incorporate feedback during the ICIS conference.
Conclusion
Through the analysis of examples and interviews in the domain of data-driven services, we identified three
factors influencing the provider and customer joint sphere of value co-creation: interaction, access to
customer processes or behaviors, and decision power. We suggest that the proportion of the joint sphere
determines the purposeful integration of resources, which enables the provider to influence real value
creation with the customer using data-driven services. While our data collection limits our findings to the
domain of data-driven services, we believe that they are applicable for value co-creation in general.
For academics, we believe that this more nuanced conceptualization of value creation and the joint sphere
sheds new light on our understanding of value co-creation and the service logic. Adopting and manifesting
this more nuanced conceptualization of value co-creation enables academics to investigate value co-
creation in a digital era in which interaction take place via digital interfaces or devices and decisions are
enacted using algorithms.
For practitioners, our findings inform service design by proposing factors beyond interaction that can
directly affect real value creation in data-driven services. By further developing our findings, we hope to
equip managers with a better understanding of how to influence real value creation for customers in more
and different ways.
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