=Paper=
{{Paper
|id=Vol-2673/paperDA8
|storemode=property
|title=Products and Processes in the Age of the Internet of Things (Extended Abstract)
|pdfUrl=https://ceur-ws.org/Vol-2673/paperDA8.pdf
|volume=Vol-2673
|authors=Louis Christian Püschel
|dblpUrl=https://dblp.org/rec/conf/bpm/Puschel20
}}
==Products and Processes in the Age of the Internet of Things (Extended Abstract)==
https://ceur-ws.org/Vol-2673/paperDA8.pdf
Products and Processes in the Age of the
Internet of Things (Extended Abstract)
Louis Christian Püschel
Research Center FIM, University of Bayreuth,
Project Group Business & Information Systems Engineering of the Fraunhofer FIT,
Bayreuth, 95444, Germany
louis.pueschel@fim-rc.de, louis.pueschel@gmail.com
1 Introduction
Digital technologies, also known as SMAC technologies (i.e., Social, Mobile, Ana-
lytics, and Cloud), have led to profound changes in our private and professional lives
(Bharadwaj et al. 2013; Borgia 2014; Legner et al. 2017). One digital technology that
has received considerable attention in recent years is the Internet of Things (IoT). The
IoT involves physical objects equipped with sensors, actuators, computing logic, which
are able to communicate via the Internet (Oberländer et al. 2018; Porter and Hep-
pelmann 2014; Rosemann 2013; Yoo et al. 2012). These physical objects, usually re-
ferred to as smart things, are the nucleus of the IoT and connect the physical with the
digital world (Borgia 2014).
As a fast-moving, global megatrend, digitalization in general and the IoT in particu-
lar transforms value networks across all industries and presents organizations with
many challenges (Collin 2015). When it comes to digital technologies such as the IoT,
many organizations are uncertain as to which technologies have the potential to enhance
their processes, products, services, and business models (Legner et al. 2017). Despite
the prevailing uncertainty, the IoT holds enormous potential for organizations. Digital
technologies such as the IoT make it possible for internal processes to be handled more
efficiently (i.e., they have a positive impact on the typical dimensions of Business Pro-
cess Management: quality, flexibility, throughput times, and costs) and allow the de-
velopment of entirely new business models, products, and services (Gimpel et al. 2018;
Legner et al. 2017). By 2015, IoT market spending amounted to USD 690 billion and
could reach USD 11.3 trillion by 2025 (IDC 2019; Johansson et al. 2019). Due to its
high potential in different applications fields, an in-depth understanding of the IoT is a
necessary prerequisite. In particular, products and processes are essential elements for
organizations to survive in competitive markets and for putting digital technologies into
context (Gimpel and Röglinger 2017). Thereby, not only essential elements of organi-
zations are influenced by digital technologies such as the IoT, but also the related aca-
demic disciplines such as Business Process Management (BPM) and the product devel-
opment. How products and processes are influenced by the IoT will be shown in more
detail below.
Innovative technologies such as the IoT have led to the integration of information
technologies in many products (e.g., to enable new service offerings). New products
Note: The full reference list can be found in the PhD thesis
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons
License Attribution 4.0 International (CC BY 4.0).
and digital services emerge and existing products and related services are comple-
mented and/or enriched by digital technologies such as the IoT (Legner et al. 2017). As
a result, offering digital services in addition to a physical product is increasingly be-
coming a prerequisite for market entry in many industries (Fleisch et al. 2015; Porter
and Heppelmann 2014; Yoo et al. 2012). In a 2019 study by the Harvey Nash Group
and KPMG, over 3,600 participating organizations estimate that, within the next three
years, “44% of organizations are undergoing some kind of major digital change that
will fundamentally impact their organization. This is either through introducing new
products and services that will be equal to or more dominant than existing ones (38%)
or – more radically – fundamentally changing their business model, for instance moving
from selling products to selling services (6%). A further 41% of organizations will be
introducing new products and services to supplement existing ones” (Harvey Nash
Group and KPMG 2019). Based on the potential of the IoT, organizations have now to
decide how the IoT should be used to enrich already existing products or to develop
entirely new products (Porter and Heppelmann 2014).
Process orientation as an important paradigm with the goal of designing and rede-
signing organizations’ internal operations (Recker and Mendling 2016) is also affected
by digital technologies such as the IoT (Legner et al. 2017). Business Process Manage-
ment (BPM), which is the related management discipline of process orientation, focuses
on two overarching topics: business processes improvement and BPM capability devel-
opment (vom Brocke and Rosemann 2015). Process improvement (i.e., the improve-
ment of organizations’ business, support, and management processes), in particular, has
long been recognized as an important topic and continues to be a top priority topic for
process managers (Harmon and Wolf 2016). The 2019 study by the Harvey Nash Group
and KPMG confirms that improving businesses processes is still ranked as number two
of the top five priorities by company boards (Harvey Nash Group and KPMG 2019).
Digitalization has an ever-increasing influence on the processes of established organi-
zations, leading to significant changes in their existing work routines (Lasi et al. 2014;
Legner et al. 2017). Companies in many industries are still trying to increase the auto-
mation and digitalization of their business processes (Legner et al. 2017; Matt et al.
2015). Nevertheless, due to the current lack of in-depth knowledge, organizations are
still struggling to identify which digital technologies they should adopt in order improve
their business processes (HBRAS 2015; Legner et al. 2017).
In addition to the individual design and redesign of products and processes, products
and processes can be influenced simultaneously by the IoT. The fundamental charac-
teristics of smart things, such as sensors, actuators, computing logic, and the ability to
communicate via the Internet (Fleisch et al. 2015), enable the (remote) integration of
different actors, such as customers and organizations, with the goal of creating value
for both sides in an innovative way (Beverungen et al. 2017). For example, in a busi-
ness-to-customer (B2C) context, a smart thing can integrate a customer, who uses the
device, and an organization, which can use the device in order to provide its knowledge
and skills. Thereby, the integration changes the customer’s behavior (i.e., its processes)
and the organization’s processes. In addition, smart things not only integrate customers
and organizations. In a business-to-business (B2B) context, for example, they can also
integrate organizations with the aim of building so-called product systems, consisting
Note: The entire reference list can be found in the PhD thesis.
of interacting smart things, and IoT ecosystems, consisting of interconnected product
systems. Similar to the B2C context, the integration of organizations leads to changes
in operations (i.e., processes) within and among participating organizations (Legner et
al. 2017; Porter and Heppelmann 2015; Beverungen et al. 2017).
2 Structure of the Thesis
In order to tackle the impact of the IoT on products and processes, this cumulative
doctoral thesis consists of five research articles structured along the overarching topics
of products and processes, as well as the integrated perspective of both products and
processes. Figure 1 shows how the individual research articles are assigned to the over-
arching topics.
Internet of Things
Products Processes
Products & Processes
RA #1 RA #2 RA #3
RA #4 RA #5
RA = Research Article
Fig. 1. Assignment of the Research Articles to the Structure of the Doctoral Thesis
Firstly, as in the age of the IoT a shift has seen in the nature of products towards
smart products, namely smart things, an in-depth understanding of smart things as the
nucleus of the IoT is a prerequisite to tap the full potential of the IoT (i.e., in research
or practice). Despite the need for detail insights into smart things in supporting organi-
zations with profound knowledge (e.g., for product development), the academic litera-
ture has failed to provide appropriate works until now. The literature has discussed the
IoT from multiple perspectives (e.g., technical fundamentals and needs as well as B2B
and B2C perspectives). While the individual contribution of the literature is undisputa-
ble, smart things are nevertheless treated as a black box in most of the works. In order
to provide a better understanding of smart things, research article #2 as extension of
research article #1 examine the individual smart thing as the nucleus of the IoT. The
results of research article #2 are twofold: (1) In order to capture the nature of an indi-
vidual smart thing, a taxonomy based on the method by Nickerson et al. (2013) has
been developed. The development and validation of the taxonomy were based on the
latest insights from the IoT literature and on a sample of 200 smart things chosen from
Note: The entire reference list can be found in the PhD thesis.
all important IoT application fields across the B2C domain. (2) Based on the classified
sample of 200 smart things, a hierarchical cluster analysis was conducted in order to
identify which combinations of smart thing characteristics typically occur together
(Everitt et al. 2010; Ferreira and Hitchcock 2009; Fraley and Raftery 2002; Kaufman
and Rousseeuw 2009). To confirm robustness, clarity, and meaningfulness, the identi-
fied clusters were evaluated using the Q-Sort. Both the taxonomy of individual smart
things and the smart thing clusters emphasize that smart things should not be treated as
a black box. This new understanding of smart things facilitates the adoption and af-
fordance of smart things in further settings and provides a basis for the use of smart
things in broader contexts such as IoT ecosystems. In addition, practitioners might lev-
erage the results in, for example, product development processes. In this case, the clus-
ters would provide an initial understanding of common types of smart products. The
taxonomy could then be used to discuss in more detail the fundamental characteristics
a smart product should address.
Secondly, with research article #3 this thesis enables a process-oriented view by ad-
dressing a method providing guidance how organizations can optimally exploit the dig-
italization potential of their business processes. The existing literature provides a huge
variety of approaches aiming to improve business processes (e.g., process enhancement
or process redesign patterns) (Dumas et al. 2018b; van der Aalst 2013; Vanwersch et
al. 2016). For example, some works consolidate the diverse ideas of process improve-
ment in so-called process enhancement or process redesign patterns (Dumas et al.
2018c; Limam Mansar and Reijers 2007; Recker and Mendling 2016). Other works
focus on approaches which prioritize process improvement projects which are evalu-
ated in terms of their influence on process performance (Darmani and Hanafizadeh
2013; Limam Mansar et al. 2009; Linhart et al. 2015; Ohlsson et al. 2014). In addition,
there are holistic approaches, such as frameworks, which provide organizations with
methods for generating improvement ideas along different decision dimensions (Van-
wersch et al. 2016). Although these works represent a significant contribution to the
knowledge of business process improvement, they fail to link the fields of business
process improvement and digitalization. To connect these fields, research article #3 of
this doctoral thesis proposes a method which guides organizations in evaluating which
digital technologies they should consider in order to exploit the digitalization potential
of their business processes. Thereby, research article #3 goes beyond the evaluation of
IoT technologies (e.g., smart things), and enables organizations to identify and select
digital technologies independently of a particular type of digital technology. To support
the selection of digital technologies for process improvement, a method based on the
action design research (ADR) (Gregor and Hevner 2013; Rijsdijk and Hultink 2009;
Sein et al. 2011) and the situational method engineering (SME) approach has been de-
veloped (Braun et al. 2005; Vanwersch et al. 2016). In line with ADR, the method has
been co-developed with, and continually evaluated by, five organizations along two
design cycles (i.e., first cycle with five and second cycle with three organizations). The
method comprises four activities, each including techniques, tools, roles and a distinct
output. The detailed description of activities and further related elements guides organ-
izations through an evaluation of digital technologies in order to reveal those best suited
to improving specific business processes. The proposed method aims to reduce
Note: The entire reference list can be found in the PhD thesis.
organizations’ uncertainty when it comes to the evaluation of digital technologies.
Thirdly, in the age of the IoT, it is increasingly important for organizations to take an
integrated view of products and processes. In order to address this topic, research arti-
cles #4 and #5 suggest ways in which organizations can be supported in the introduction
of smart things and the possible (re-) alignment of the underlying processes.
Thanks to their ability to integrate various actors (e.g., customers, organizations, and
smart things), smart things are a prerequisite for building complex interaction relation-
ships, such as IoT ecosystems, which are enabled by interconnected product systems or
so-called smart service systems (SSS) (Beverungen et al. 2017; Lim and Maglio 2018;
Medina-Borja 2015; Wuenderlich et al. 2015). However, smart things in broader con-
texts such as IoT ecosystems respectively SSS have so far received little academic at-
tention. Research article #4 therefore responds to this absence, proposing a domain-
specific modeling language (DSML) that involves all relevant actors for analyzing and
designing SSS respectively IoT scenarios (e.g., in B2C and B2B contexts) from a pro-
cess-oriented and structural view. The DSML draws on the literature on service science
and the IoT as justificatory knowledge. To develop the DSML, the design science re-
search approach (Gregor and Hevner 2013; Peffers et al. 2007) was combined with the
domain-specific modeling language engineering method (Frank 2013). The result of
this development process is an abstract – i.e., semi-formal – metamodel for describing
how to build a conceptual model (Eriksson et al. 2013) and a concrete syntax – i.e.,
textual and graphical notational elements for representing diagrams (Mannadiar 2010).
The DSML has been evaluated by modeling fictitious and real-world examples, inter-
viewing domain experts, conducting a competing artefact analysis and its discussion
along different design objectives.
Organizations may be interested in assessments of the economic feasibility of IoT
scenarios developed using the DSML from research article #4. Research article #5 picks
up this topic by supporting organizations in this decision process. Thereby, most of the
prevailing IoT literature focuses on describing the impact of IoT on products, processes,
and business models (Boos et al. 2013; Bucherer and Uckelmann 2011; Fleisch et al.
2015; Porter and Heppelmann 2014). Very few works focus on an economic perspec-
tive regarding the IoT (Lee and Lee 2015). Hence, research article #5 provides an eco-
nomic decision model to assess which IoT investments (i.e., IoT projects) lead to the
largest increase in the long-term firm value of an organization. Thereby, research article
#5 focuses on manufacturing companies. By determining an optimal sequence of IoT
projects, the decision model indicates whether it is a product, process, and/or an infra-
structure project that an organization should execute next. The decision model builds
on value-based management (VBM) (i.e., value contributions to a company’s long-term
firm value are used for control purposes) (Buhl et al. 2011; Rappaport 1986; vom
Brocke and Sonnenberg 2015) and project portfolio selection (PPS) (i.e., determining
an optimal project portfolio) (Archer and Ghasemzadeh 1999) as justificatory
knowledge. In order to develop the decision model, the design science research ap-
proach was applied (Gregor and Hevner 2013). The evaluation was conducted in line
with the evaluation framework by Sonnenberg and vom Brocke (2012) (i.e., deriving
design objectives, feature comparisons and expert interviews, demonstrations using a
prototype).
Note: The entire reference list can be found in the PhD thesis.