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Robotic Process Automation: Systematic Literature Review


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Robotic process automation (RPA) emerges as a new technology which is focused on automation of repetitive, routine, rule-based human tasks, aiming to bring benefits to the organizations that decide to implement such software solution. Since RPA is a relatively new technology available on the market, the scientific literature on the topic is still scarce. Therefore, this paper aims to investigate how academic community defines RPA and to which extent has it been investigated in the literature in terms of the state, trends, and application of RPA. Moreover, the difference between RPA and business process management is also addressed. In order to do so, the systematic literature review (SLR) based on Web of Science and Scopus databases has been conducted. The paper provides the results of the conducted SLR on RPA providing an overview of the RPA definitions and practical usage as well as benefits of its implementation in different industries.
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Robotic Process Automation: Systematic Literature
Lucija Ivančić1 () [0000-0003-0491-7230], Dalia Suša Vugec1[0000-0002-4702-6000] and Vesna
Bosilj Vukšić1[0000-0002-0841-7754]
1 Faculty of Economics and Business, University of Zagreb, Croatia
Abstract. Robotic process automation (RPA) emerges as a new technology
which is focused on automation of repetitive, routine, rule-based human tasks,
aiming to bring benefits to the organizations that decide to implement such soft-
ware solution. Since RPA is a relatively new technology available on the market,
the scientific literature on the topic is still scarce. Therefore, this paper aims to
investigate how academic community defines RPA and to which extent has it
been investigated in the literature in terms of the state, trends, and application of
RPA. Moreover, the difference between RPA and business process management
is also addressed. In order to do so, the systematic literature review (SLR) based
on Web of Science and Scopus databases has been conducted. The paper provides
the results of the conducted SLR on RPA providing an overview of the RPA
definitions and practical usage as well as benefits of its implementation in differ-
ent industries.
Keywords: Robotic Process Automation, Literature Review, Business Process
1 Introduction
Changes in the global economy driven by the development of new technologies require
businesses to become more agile and to quickly respond to the needs, wishes, and de-
mands from their customers. Moreover, competitive and financial pressures force or-
ganizations to be more efficient, thus constantly seeking for new technologies and
methodologies that would help them become more productive, save costs and add value
to their business.
One of the solutions which is emerging as a new technology is robotic process auto-
mation (RPA) which can replace employees on repetitive tasks and automate them, and
therefore, enable employees to be involved in more complicated tasks which can bring
organization more value. According to the reports of consulting companies RPA is rec-
ognized as an emerging and disruptive technology that is already delivering value (e.g.
[10, 15]).
Although there is a number of authors reporting various benefits of implementing
RPA within an organization (e.g. [7, 8, 16, 29, 39]), according to authors’ best
knowledge, RPA is, at the moment, more often implemented in practice than it is in-
vestigated by the researches. Thus, it very important to discuss differences, similarities,
and complementarities between RPA and similar technologies and approaches, one of
which is business process management (BPM). For example, there is a recommendation
for investigating the integration of BPMS and RPA [33]. Moreover, investigating the
state of the BPM market, Harmon [20] indicated that 30% of the surveyed practitioners
would like to add some kind of RPA capabilities to their process modeling suite.
Therefore, aiming to properly understand RPA, to assess its relevance within the
research community and to investigate its link to BPM, a systematic literature review
(SLR) has been conducted. In that sense, this paper reports on three research questions
related to the state and progress of the RPA research, its definition and practical usage,
which are addressed in more detail later in this paper. Moreover, the paper aims to
provide an understanding of the differences between RPA and BPMS.
With the purpose of meeting the paper’s goal and to answer the research questions,
the paper is structured as follows. After this introduction, a brief background on RPA
is given in the second part of the paper, explaining RPA in theory and practice and its
relation to BPM. The third part of the paper refers to the employed research methodol-
ogy, in terms of identification of research questions as well as the SLR protocol. Next,
research results regarding three research questions are presented in the fourth part of
the paper, while in fifth, they are discussed. Last, the sixth part of the paper brings the
2 Background on Robotic Process Automation
2.1 Robotic Process Automation in Theory and Practice
According to the findings of preliminary literature overview, RPA is defined as the
application of specific technology and methodologies which is based on software and
algorithms aiming to automate repetitive human tasks [16, 21, 33, 39]. It is mostly
driven by simple rules and business logic while interacts with multiple information sys-
tems through existing graphic user interfaces [17]. Its functionalities comprise the au-
tomation of repeatable and rule-based activities by the use of non-invasive software
robot, called "bot" [27, 29, 38].
Recently, RPA definition is extended towards its conjunction with artificial intelli-
gence (AI), cognitive computing, process mining, and data analytics. The introduction
of advanced digital technologies allows RPA to be reallocated from performing repeti-
tive and error-prone routines in business processes towards more complex knowledge-
intensive and value-adding tasks [3, 17, 45].
To assess the state of the RPA market Forrester [15] identified 12 RPA vendors of-
fering enterprise-level, full-corporate solutions that can support the requirements of a
"shared service" or enterprise-wide RPA utility. Though some RPA vendors offer in-
dustry-specific solutions, Schmitz et al. [42] see "the general concept of RPA as indus-
try agnostic". On the other hand, the RPA vendors' partnership with the leading artifi-
cial intelligence providers enabled the extension of traditional RPA functionalities with
the new, emerging technologies such as self-learning from the process discovery, train-
ing robots, AI-screen recognition, natural language generation and automated processes
documentation generation [3].
A majority of 400 companies surveyed by Deloitte [10] have started on their RPA
journey and almost a quarter more plan to do so in the next two years. They also report
that payback periods are averaging around a year and their expectations of cost reduc-
tion, accuracy, timeliness, flexibility, and improved compliance are met or exceeded
[10]. Forrester [15] estimates that by 2021, there will be over 4 million robots automat-
ing repeatable tasks, but the focus will be moved toward integrations with AI and im-
provements of RPA analytics. Similarly, Everest Group [12] points out that though a
majority of buyers are highly satisfied with RPA solutions, they require the enhance-
ment of analytics and cognitive capabilities.
Despite the high benefits from RPA, only 5% of companies involved in Deloitte
research [10] have implemented more than 50 robots in their operations. Organizational
capability and the understanding of business goals of RPA implementation are crucial
for the success of RPA projects. A lack of understanding of what RPA means and where
it can be applied, a lack of management support and a fear of job loss by employees are
identified key challenges for automating processes [43]. A change management strat-
egy, a change of organizational culture and a shift in mindset could help to bridge the
gap between RPA being an IT tool and the business side of it [10, 28, 43]. On the other
side, Everest Group study [13] participants rated good customer support, training and
educational materials, RPA maintenance services and good RPA vendor ecosystem for
complementary technologies as very important drivers of RPA adoption. Besides, the
introduction of new technologies brings up questions about the management of robots,
its' central control, and governance [15].
2.2 Robotic Process Automation and Business Process Management
As already indicated, it is important to investigate similarities and differences, as
well as complementarities between RPA and like technologies. In that sense, since RPA
and BPM are neighboring disciplines having complementary goals, Mendling et al. [33]
call for the BPM research community to investigate business process management sys-
tems (BPMSs) and RPA integration.
BPM is a multidimensional approach aiming to achieve better business performance
through continuous process improvement, optimization and digital transformation.
BPMS as a holistic software platform that encompasses a wide range of functionalities
such as process design, analytics, and monitoring is very often one of the BPM initiative
inevitable perspectives [6]. On the other side, RPA deals with discreet, repetitive tasks
and execute processes as a human would. According to Cewe at al. [8] "BPMS is used
to orchestrate end-to-end process, and to manage human, robots and system interac-
tions, RPA is responsible for repetitive sequences of tasks that can be fully delegated
to software robots".
Though these technologies are very often used separately, the authors from business
practice [14, 36] strongly suggest combining both to gain even more business value. In
a case of the lack of resources and/or time to completely implement BPMS, RPA can
be a valuable and relatively inexpensive tool to solve or complement some of the un-
fulfilled goals.
3 Research Methodology
3.1 Identification of Research Questions
The results of the brief literature overview (as presented in Section 2) revealed the sig-
nificance of RPA for business practitioners and researchers, and the lack of SLR in the
RPA domain. The preliminary findings showed the gaps in research contexts, the lack
of theoretical frameworks and discrepancies in the definition of RPA and its content.
Besides, the ad-hoc portrait of recent RPA literature showed that RPA is recognized in
business practice as a leverage for performance improvement. Though many benefits
and challenges of RPA implementation were addressed, the need to systematize expe-
riences from business practice referring to the usage of RPA was noticed. Finally, the
discussion regarding RPA as a newly emerged area of BPM was evidenced in both
professional and academic literature.
Following the previous annotations about scientific and professional papers that fo-
cus their attention on RPA, the research questions are determined. They are defined
from more general to more specific, as follows:
RQ1 What is the state and progress of research on RPA?
RQ2 How is RPA defined (RQ2-1) and what is a difference between RPA and
BPMSs according to the researchers (RQ2-2)?
RQ3 How is RPA used in business practice, as mentioned in the scientific litera-
While RQ1 is related to the results of bibliometric analysis, the answers on RQ2 and
RQ3 are grounded on the qualitative outcomes from the detailed content analysis of the
sampled articles.
3.2 Systematic Literature Research Protocol
In order to fulfill the objectives of this paper and to answer the research questions, a
SLR approach was adopted. SLR methodology has been originated in medicine re-
searches, but during the last two decades, this approach became popular in management
and information systems field researches because it systematizes knowledge from a
prior body of research and ensures the fidelity, completeness, and quality of findings
[32, 35, 44, 48]. According to a typical SLR guideline [5, 24], our literature retrieval
was conducted through a three-step approach: (1) SLR protocol definition and literature
search and selection; (2) quality appraisal and extraction of relevant articles; and (3)
qualitative analysis and synthesis of the accepted articles.
For the first step of SLR, a research protocol was designed and presented (Table 1).
Next, the articles were browsed in two collections: Scopus and Web of Science Core
Collection (WoS). These digital databases were chosen in order to comprise articles
from two fields related to RPA: social sciences and information systems. According to
our inclusion criteria, the search string was composed of the keywords "robotic process
automation" while the search was not restricted, neither to a specific time limit nor to a
specific field or index. This search strategy was employed to comprise all useful find-
ings from various fields giving an insight into the evolution of RPA researches until the
end of March 2019, which is when our research was conducted.
As a result of our search 46 articles were found (12 in WoS and 34 in Scopus). After
excluding the duplicate articles, 36 articles remained (8 in both WoS and Scopus, 2
only in WoS, 18 only in Scopus).
Table 1. RPA research protocol
SLR Protocol ele-
Translation in RPA research
Digital sources
Scopus and Web of Science Core Collection (WoS).
Searched term
Robotic process automation.
Search strategy
No publication date limit; no topic limit; search term contained an-
ywhere in the articles; articles and conference papers only (no edi-
torial, review, conference review).
Inclusion criteria
Search string “robotic process automation”
Exclusion criteria
Articles without full access; extended abstracts (without full text);
book chapters; professional papers; articles citing the term “robotic
process automation” with a different meaning.
For step 2 several exclusion criteria were applied. As we sought to analyze peer-
reviewed journal articles and scientific conference papers, the articles without full ac-
cess (2), extended abstracts only (2) and the articles mistakenly classified as peer-re-
view articles (1 book chapter and 1 professional paper) were excluded. Consequently,
a total of 30 potentially appropriate articles remained for further analysis. Besides, the
abstracts of all the 30 articles were analyzed to determine its' relevance to the goals of
this research. Our research followed the definition of RPA provided in preliminary lit-
erature overview (presented in Section 2.2), where the RPA is comprehended as a soft-
ware robot, which automates repeatable and rule-based activities [27, 29, 38]. As a re-
sult of abstract analysis, 3 articles with a different meaning of "robotic process automa-
tion" than the one understood in the context of our research were found. Finally, 27
articles were extracted as revealing significance for the objective of this SLR. Appendix
outlines the articles resulting from the SLR.
Step 3 of our SLR protocol is where the selected research articles were further ana-
lyzed based on the full text reading and codded by using the programs MS Excel and
NVivo. The quantitative results from MS Excel were used to answer RQ1, while the
results of the qualitative analysis conducted in NVivo gave the answers to RQ2-RQ3.
4 Research Results
4.1 SLR Results: the State and Progress of Research on RPA
This section responds to RQ1 presenting the basic bibliographic results obtained from
the analysis of the coded fields: ‘Year of publication’, ‘Publication outlet (a journal or
a conference proceeding), ‘Study strategy (a theoretically applied approach, an empir-
ical research or a review) and ‘Journal title’.
Figure 1 presents a publishing frequency (2016-2018) regarding publication outlet.
A total of 20 out of 27 articles were published in 2018, among which 14 conference
papers and 6 journal articles. Only 4 journal articles and 3 conference papers were pub-
lished in 2016 and 2017.
Fig. 1. Appearance of RPA articles by publication year (2016-2018) and the publication outlet
From the methodological point of view, the articles are grouped into 3 study strate-
gies: empirical researches (a qualitative or a quantitative), a theoretical applied ap-
proach and literature review articles.
The majority of articles (18) used the empirical research strategy among which 16
qualitative (12 case studies and 4 reviews of a specific type of RPA technology) and 2
quantitative researches (questionnaire surveys) were found. A half (6) of the case study
articles were published in peer-reviewed journals. A theoretical applied approach was
employed in 4 articles (1 journal article and 3 conference proceeding articles) while the
results of a literature review were presented in 5 articles (2 journal articles and 3 con-
ference proceeding papers). Within the last category, only 1 was an SLR article. Figure
2 presents the distribution of articles regarding the methodological approach.
Two journals containing the highest number of RPA papers were Journal of Infor-
mation Technology Teaching Cases (4) and MIS Quarterly Executive (2) while most
of the conference proceedings papers came from ACM International Conference Pro-
ceeding Series (3) and Lecture Notes in Business Information Processing series (3).
Fig. 2. RPA articles regarding the methodological approach
Appendix outlines the articles resulting from the SLR and the bibliographic results
used to respond RQ1.
4.2 SLR Results about RPA Definition and Understanding the Difference
between RPA and BPM
For RQ2-1, the results of the brief literature overview (as presented in Section 2.2)
show that the definitions of RPA vary in the extant professional and academic literature.
While some of the available articles incorporate a narrow view of using specific soft-
ware and algorithms aiming to automate repetitive manual tasks, the others have built
their definitions on the extension of the traditional RPA functions with the advanced
digital technologies such as: AI (e.g. machine learning, image recognition), drones and
remote sensing technologies. The content of the articles is analyzed in order to identify
the definition of RPA, its characteristics and functionalities as addressed by the re-
Most of the definitions provided within the observed articles define traditional RPA
as an emerging technology which automates repetitive human tasks, both digital and
physical (e.g. [1, 7, 16, 18, 19, 30, 39]). Moreover, Geyer-Klingeberg et al. [17], as well
as Leno et al. [29], stress out that those tasks are usually error prone and therefore are
suitable for automation. Furthermore, Aguirre and Rodriguez [1], Anagnoste [3], Gupta
et al. [18] as well as Tsaih and Hsu [45] view RPA as the usage of cognitive technology
and refer to it as cognitive automation. Gejke [16], Mendling et al. [33] and Penttinen
et al. [37] emphasize that RPA is a software solution configured to interact with existing
applications and systems the way like a human would do.
According to Issac et al. [22], functionalities of the traditional RPA are:
front office (attended) automation and back office (unattended) automation,
script based designer and visual process designer,
the openness of the platform,
macro recorders for process mapping,
control through coding,
execution of automated test cases on remote machines,
bot development and core functions,
the control room, system management, reporting and resilience, and
RPA analytical potential.
The results of detailed content analysis of the sampled articles show that the integra-
tion of RPA with the emerging technologies is elaborated in Anagnoste [3], Kobayashi
et al. [25], Kulbacki et al. [26], Lin et al. [31], Schmider et al. [41], Tsaih and Hsu [45];
and Van Belkum et al. [47]. All of these 7 articles were published in 2018. Table 2
summarizes the findings and contributes to the understanding of what impact these
technologies will have on RPA future development and implementation (RQ2-1).
Table 2. Traditional RPA and advanced digital technologies integration
Field of deployment
Machine learning
Healthcare (product development and life-cycle
management of healthcare products)
Healthcare (processing of adverse event reports)
Tourism (tourist behavior prediction)
Machine vision / im-
age, screen, voice,
pattern recognition
Sales (vendors’ documentation processing)
Semiconductor manufacturing (controlling the
equipment and using screen image recognition)
Natural language
Consulting (chatbots applied in the HR department)
Tourism (chatbots used to provide one-stop-shop
for travel information)
Drones and associated
Agriculture (usage of drones, sophisticated, cam-
eras, and RPA for agriculture automation)
Internet of Things (IoT)
Distribution, delivery (parcel delivery service using
IoT, QR code recognition and RPA)
To address the RQ2-2 of what is a difference between RPA and BPMSs the content
of the sampled articles is retrieved and analyzed. BPM is mentioned in a total of 10 out
of 27 articles. However, only 6 articles [1, 8, 27, 37, 43, 50] discuss the characteristics
that distinguish RPA from BPMS, specify the steps of RPA deployment and explain
how RPA complements BPMS.
While BPMS interacts with business applications through APIs, RPA connects the
process with the applications by interacting with the user interface [9, 46]. According
to Cewe et al. [8] "RPA can be taken for a special kind of BPMS that relies on the
graphic user interface (GUI) automation adaptors instead of regular interfaces (i.e. ap-
plication programming interfaces APIs) for intersystem communication". In a case of
BPMS development advanced programming skills are usually necessary for hard cod-
ing and integration with the existing systems via APIs [1, 8]. On the other side, the
development of RPA is considerably less time and cost consuming, the knowledge of
programming is mostly not needed. The most important conclusions of these articles
are in line with the RPA/BPMS preliminary overview presented in Section 2.3.
4.3 SLR Results: RPA in Business Practice
To respond to RQ3 about the usage of RPA in business practice content of 12 case
studies is further investigated looking at the organization's industry type, a type or name
of process chosen for automation and a country the organization comes from (Table 3).
The results show that two-thirds of RPA implementation projects as mentioned by
the researchers come from two industries - services (7) and telecommunications (3)
while the other implementations are related to finance and insurance (2), healthcare
management (1), sales (1) and oil & gas (1) industry. Though human resource manage-
ment, finance and accounting, and administrative back-office processes are detected as
the best candidates for automation, the organizations conducted RPA initiatives in out-
sourcing services, sales and purchasing processes. As presented in Table 3 RPA initia-
tives are mostly conducted by organizations having its headquarters in the developed
countries, such as Finland, UK, and the USA and by global companies.
Table 3. Implementation of RPA by industry type, process type and country
Industry type
Process type
Recruitment (HRM services)
Payroll process (outsourcing services)
Financial process automation
Payment receipt (outsourcing services)
Process of promotion in HRM (outsourcing
HRM, IT management, Public relations,
Knowledge management (consulting ser-
n/a, global company
HRM (audit, tax, and consulting services)
n/a, global company
n/a, global company
Sales (capacity check for bid processing)
Subscription-based online service
Back-office processes
Financial and
Healthcare claims adjudication process
Administrative back-office process; Premi-
ums processing; E-policies offshore process
n/a, global company
Administrative, back-office processes
Vendor information processing
n/a, global company
Oil and Gas
Finance and accounting: the process of rec-
onciliation the bank with the cash from the
stations in the previous day
These results can lead towards the assumption that digital competitiveness of a coun-
try and the high level of organization's ICT maturity positively influence RPA imple-
mentation. Moreover, the usage of RPA in business practice has been investigated from
a benefits point of view, analyzing the content of 12 case studies. The results reveal the
following benefits of the RPA implementation in business practice:
increased efficiency [1, 39],
reducing human labor, i.e. reducing workforce [39],
employees can concentrate on value creation [39],
costs savings [1, 17, 19, 37, 39],
ease of use [2, 19, 37],
increased volume of performed tasks [17, 39], and
increased quality of work, i.e. tasks are performed accurately, correctly and consist-
ently [1, 17, 39].
5 Discussion
The aim of this section is to analyze and discuss the previously raised research ques-
tions. To address the RQ1 the bibliometric analysis of a sample of articles was con-
ducted showing that the research on RPA was almost tripled in 2018 in comparison to
period 2016-2017. This can lead to the conclusion that the number of RPA researches
will continue the growth in the future. Having in mind that RPA is a rather new and
emerging field, the results identifying the appearance of 17 conference papers against
10 journal articles imply that the full research potential on RPA topic hasn’t been
achieved yet. Hence, it can be concluded that the studies on RPA have only begun to
emerge and it is expected they will achieve its proliferation in the next few years, in-
cluding appearance in peer-reviewed journals.
A total of 18 out of 27 articles fell into the "empirical research" category indicating
the scarcity of RPA theoretical researches and conceptual frameworks. Only 1 struc-
tured literature study (e.g. SLR article) investigating RPA case studies proved our as-
sumption about the lack of SLR approach in the field. The top 2 conferences publishing
RPA studies are information-systems related (Lecture Notes in Business Information
Processing Series), and IT and computing-related (ACM International Conference Pro-
ceeding Series). Similarly, half of the journal articles about RPA were published in
journals covering the management of information systems issues (MIS Quarterly Ex-
ecutive) and case studies on contemporary information and communications technol-
ogy themes (Journal of Information Technology Teaching Cases). Only 3 authors (Lac-
ity, Willcocks, and Anagnoste) contributed with more than one paper.
The goal of RQ2-1 is two-fold, first to define the aim and scope of RPA form a
traditional point of view; and second, to examine how RPA extends towards the emerg-
ing technologies. Responding the first goal of RQ2-1, the analysis on the definitions
of RPA indicates that a common agreement is achieved among the researchers defining
RPA as a "relatively new technology for process automation based on software and
algorithms aiming to emulate a human work and to perform manual activities by inter-
acting with information systems through existing user interfaces" [16, 33, 39]. From a
business perspective, RPA is mainly used to "capture and interpret existing applications
for processing a transaction, manipulating data, triggering responses and communi-
cating with other digital systems" [47]. Thus, it is considered "suitable for high volume,
repetitive, monotonous, well-structured and standardized tasks, where there is no need
for subjective judgment, creativity or interpretation skills" [1]. RPA solutions are min-
imally invasive, easy to use, inexpensive and quite simple to implement since RPA sits
on the top of existing information systems, does not store any transactional data and
does not require a database [1, 19, 33, 50].
The results of the analysis about the RPA and advanced technologies integration
indicate what is coming next to RPA, so giving the answer on the second goal of RQ2-
1. According to Anagnoste [3], RPA solutions are moving toward AI technologies, such
as: "IOCR, chat-bots, machine learning, cognitive platforms, anomaly detection, pat-
tern analysis, voice recognition, data classification and many more". Besides, the im-
plementation of the "advanced RPA" within different fields is evidenced (e.g.
healthcare, tourism, agriculture, distribution, and sales), thus proving the wide range of
integrated RPA and advanced technologies applicability.
A discussion point we want to explore in relation to RQ2-2 is whether the RPA
research field is in conjunction with the concept of BPM and how it can be integrated
with BPMSs. The researchers agree that despite the differences BPMS and RPA com-
plement each other [1, 8, 46]. Thus, deployed together BPMS and RPA can help the
digital transformation and business performance improvement.
For RQ3, the findings refer to the benefits of RPA implementation in different in-
dustries (e.g. banking and insurance services, healthcare and pharmaceuticals, telecom-
munications) and business processes [4, 27]. Several business functions are recognized
by business practitioners as good candidates for RPA implementation, among which
the most often mentioned are sales, finance and accounting, and human resources man-
agement [43]. A majority of early RPA adopters automated their back-office tasks and
internal support processes, like accounting, billing, travel expenses, master data man-
agement, keeping employee records and claims processing [1, 43, 49], but recently sev-
eral researchers documented a number of RPA applications aiming to automate core
business processes and shared service operations [40, 42]. According to Willcocks et
al. [50], the significant expansion of RPA initiatives not only in back office processes
automation but also amongst business process outsourcing (BPO) service providers
started in 2016.
The results of the comprehensive analysis reveal that the perceived value of RPA is
mainly related to organizational performance enhancement and costs reduction by re-
ducing human labor in routine business processes, and also by increasing the quality of
the work [23]. However, the outcomes that cannot be directly measured financially are
also comprised, such as competence, market position, innovation, knowledge discov-
ery, research and development [34, 39]. Since the costs of RPA development and
maintenance can exceed the obtained savings, business processes must be carefully an-
alyzed in order to evaluate their suitability for RPA [7, 17].
6 Conclusion
This paper presented the results of SLR on RPA based on the search results from
WoS and Scopus databases. According to the authors’ best knowledge, this paper rep-
resents the first SLR paper focused on all RPA related publications from the named two
databases, which is one of its contributions. The results of the SLR conducted for the
purpose of this paper revealed the existence of another RPA related SLR; however, it
dealt only with case studies and not all available publications [51]. Moreover, named
SLR has been focused on publications available on the public Web and Google Scholar.
Besides the named contribution, this paper focused on opinions and writings of the
academics regarding the RPA, elaborated through three research questions presented in
the methodology section of the paper. In that sense, the paper gives an overview of
definitions, usage, and benefits of RPA in practice, as well as the explanation of the
difference between RPA and BPMS. Moreover, the results of the conducted SLR re-
vealed lack of theoretical studies on RPA, indicating that the area is still relatively new
and that no theoretical frameworks have been formed.
The limitations of this paper include lack of access to two papers which have been
found through the search process and therefore their exclusion from the presented anal-
ysis. Based on the results of the conducted SLR, research gap in terms of the lack of
both theoretical as well as empirical research has been noticed. Therefore, future re-
search of this topic suggests researches towards filling this gap. One of the possible
directions for future research is the investigation of both direct and indirect effects of
RPA on organizational performance.
Acknowledgments. This paper has been fully supported by the University of Zagreb
under the project Information technology and business models in the digital environ-
Appendix Articles resulting from the SLR
Title of the paper
Towards a Process Analysis Approach to Adopt Robotic Pro-
cess Automation
Survey of Drones for Agriculture Automation from Planting
to Harvest
Automation in recruitment: a new frontier
Apply RPA (Robotic Process Automation) in Semiconductor
Smart Manufacturing
Robotic process automation - Creating value by digitalizing
work in the private healthcare?
Artificial intelligence in clinical development and regulatory
affairs Preparing for the future
How do machine learning, robotic process automation, and
blockchains affect the human factor in business process man-
A new season in the risk landscape: Connecting the advance-
ment in technology with changes in customer behaviour to
enhance the way risk is measured and managed
Process mining and Robotic process automation: A perfect
How to choose between robotic process automation and
back-end system automation?
Multi-Perspective process model discovery for robotic pro-
cess automation
Identifying candidate tasks for robotic process automation in
textual process descriptions
Innovation in Pharmacovigilance: Use of Artificial Intelli-
gence in Adverse Event Case Processing
Artificial intelligence in smart tourism: A conceptual frame-
SNS Door Phone as Robotic Process Automation
Delineated Analysis of Robotic Process Automation Tools
The key factors affecting RPA-business alignment
Minimal effort requirements engineering for robotic process
automation with test driven development and screen record-
How OpusCapita used internal RPA capabilities to offer ser-
vices to clients
Robotic Automation Process - The operating system for the
digital enterprise
Robotic process automation: Strategic transformation lever
for global business services?
Resolving tussles in service automation deployments: Service
automation at Blue Cross Blue Shield North Carolina
Automation of a business process using robotic process auto-
mation (RPA): A case study
Software bots -The next frontier for shared services and func-
tional excellence
Robotic Automation Process - The next major revolution in
terms of back office operations improvement
Turning robotic process automation into commercial success
- Case OpusCapita
Robotic process automation at telefónica O2
Note: Col. Collection; W WoS; S Scopus; SS Study strategy; EA Empirical
approach; TA Theoretical approach; LR Literature review
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... Furthermore, we plan to research intra-and inter-dependencies between ASL constructs and related languages [61,62], considering the minimisation of their combinatorial effects [63]. Finally, we intend to explore additional concepts and transformations to increase the overall quality and productivity of the proposed approach, for instance, considering emerging areas of blockchain and smart contracts [49,64], robotic process automation [62,65,66], and hyperautomation applications [67]. ...
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Low-code development platforms have gained popularity as an effective solution to address urgent market demands for software applications. These platforms have often overcome challenges faced by traditional software development processes, including requirements engineering processes, as they tend to incorporate the requirements in their prototyping phase. However, low-code platforms have followed different approaches with proprietary languages, which is a problem when customers need to move to other technologies or intend to define the specification of their applications in a readable and platform-independent way. To mitigate these challenges, this article discusses a model-driven approach that semi-automatically produces software business applications by combining rigorous requirement specifications (defined with the ITLingo ASL language) with a concrete low-code platform (Quidgest Genio). First, we analyse the common concepts in both ITLingo ASL and Genio languages. Then, we discuss model-to-model transformations that allow converting ASL specifications into Genio low-code projects. Finally, the code generation capabilities of the Genio low-code platform are employed to generate the source code of the target software applications. To evaluate the consistency of the proposed approach, we use and discuss a simple and representative case study based on a fictitious system, the Invoice Management System (IMS), whose requirements are similar to those found in many business applications.
... Recent systematic literature reviews show that there is a growing interest in the area (Ivančić et al., 2019) as RPA is being massively applied to industry. A literature review by Syed et al. (2020) has pointed to several relevant research challenges. ...
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This paper reports a study of User Experience (UX) with Robotic Process Automation (RPA), in the perspective of workers of EdP Brazil, a large electric utility company that operates in Brazil. RPA are software solutions for automating business processes that find increased interest of companies because they are inserted in workgroups as a co-worker, emulating human workers operating on GUI interfaces. Although the technology promises to drive a new wave of productivity in service companies, its impact on co-workers' experience is still unexplored. Based on projective interviews using the AXE (Anticipated eXperience Evaluation) protocol, after the first 18 months of RPA operation, the analysis of workers' collaboration with the robots has evidenced multiple facets of UX, technology acceptance and innovation adoption. For this case, RPA has provided an overall positive user experience mainly due to the perceived utility of the spared time, the upgrade in career opportunities and the pride for actively participating in the innovation adoption. Negative experience comes mainly from the lack of visibility that hinders robot management for efficiency and improvement. The methodology used in the study was successful in capturing the multifaceted workers' experience and is potentially useful to support user research in new expansion RPA projects.
... Robotic process automation (RPA) has emerged as an important technology for reducing repetitive and manual labor in administrative and standardized tasks [1,2]. In recent years, the public sector has increased its use of robotic process automation (RPA) in administration, decision making and citizen services [3]. Available studies mostly focused on the specific cases of using RPA in public organizations [4]. ...
The public sector has increased its use of robotic process automation (RPA) in administration, decision making and citizen services. Available studies mostly focused on the specific cases of using RPA in public organizations. Thus, we lack the helicopter view of the adoption of RPA in a country. In this paper, we present the results of a national survey of RPA adoption in the public sector in Sweden. The results show that the awareness of RPA is high in the Swedish public sector although the level of adoption is still modest. Also, there are notable differences in the level of adoption between central and local government. The study goes beyond the limitations of case studies, and contribute new knowledge of RRA adoption, benefits, routine capability and governance on a national level. The knowledge and insights can serve as a reference for other countries and public administrative models.KeywordsRobotic process automationPublic sectorInformation technology adoptionSurveyRoutine capabilityBenefit
... Process Mining und Data Analytics diskutiert(Ivančić et al. 2019). Im Vergleich mit anderen Tools ist RPA mit einem geringen Umsetzungsaufwand verbunden, da keine Anpassungen an bestehenden Systemen notwendig sind(Arnautovic et al. 2017). ...
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Zusammenfassung Der stetige Wandel und die damit verbundenen Anforderungen sind Treiber der Weiterentwicklung von Unternehmen. Um am Markt bestehen zu können, wird eine kontinuierliche Verbesserung der Geschäftsprozesse benötigt. Um Geschäftsprozesse verbessern zu können, setzen Finanzinstitute vielfach auf den Einsatz von Lean Six Sigma (LSS) und Robotic Process Automation (RPA). Diese beiden Methoden kommen dabei allerdings selten kombiniert zur Anwendung. Auch die Forschung konzentriert sich vorwiegend auf die separate Anwendung dieser beiden Methoden. Die vorliegende Studie untersucht die Mehrwerte und Herausforderungen einer kombinierten Nutzung von LSS und RPA. Die Analysen basieren auf ExpertInnen-Interviews, einer LinkedIn-NutzerInnen Umfrage sowie einer Fallstudie, welche in einer Schweizer Grossbank durchgeführt wurde. Die Ergebnisse zeigen, dass die Kombination von LSS mittels RPA einen Mehrwert in Bezug auf die Verbesserung der Geschäftsprozesse liefern kann. Mehrwerte können in den Bereichen „Prozessverbesserungen“, „strukturierte Vorgehensweise“, „Optimierung RPA“ und „Ressourceneinsparungen“ ausgemacht werden. Die zentralen Herausforderungen beim kombinierten Einsatz von LSS und RPA liegen in den Bereichen „Führung“, „Vorgehen“, „Mitarbeitende“ und „Vorgaben“. Es werden fünf zentrale Handlungsempfehlungen ausgesprochen: Organisatorisch klar geregelte zentrale Leitung, proaktive und umfassende Wahrnehmung der Führungsverantwortung, systematische Kompetenzentwicklung in den Bereichen LSS und RPA, klar strukturierte Vorgehensweise für die Prozess- bzw. Problemanalyse sowie Fokussierung auf die Sicherstellung nachhaltiger Massnahmen.
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When a company decides to automate its business processes by means of RPA (Robotic Process Automation), there are two fundamental questions that need to be answered. Firstly, what activities should the company automate and what characteristics make them suitable for RPA. The aim of the presented research is to design and demonstrate a data-driven performance framework assessing the impact of RPA implementation using process mining (PPAFR). Firstly, we comment on and summarise existing trends in process mining and RPA. Secondly, we describe research objectives and methods following the Design Science Research Methodology. Then, we identify critical factors for RPA implementation and design process stages of PPAFR. We demonstrate the design on real data from a loan application process. The demonstration consists of a process discovery using process mining methods, process analysis, and process simulation with assessment of RPA candidates. Based on the research results, a redesign of the process is proposed with emphasis on RPA implementation. Finally, we discuss the usefulness of PPAFR by helping companies to identify potentially suitable activities for RPA implementation and not overestimating potential gains. Obtained results show that within the loan application process, waiting times are the main causes of extended cases. If the waiting times are generated internally, it will be much easier for the company to address them. If the automation is focused mainly on processing times, the impact of automation on the overall performance of the process is insignificant or very low. Moreover, the research identified several characteristics which have to be considered when implementing RPA due to the impact on the overall performance of the process.
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Robotic process automation (RPA) as a lightweight automation technology has witnessed an increasing uptake in the industry in recent years. Despite considerable changes in employees’ tasks and processes brought about by the introduction of RPA, there is a lack of research that explores how employees react to an RPA implementation. Hence, the goal of this research is to understand employees’ perceptions of and reactions to RPA as these affect their interaction with the technology and, ultimately, their adoption and use. To address this research gap, we conducted a case study at a financial institution in New Zealand and interviewed 18 employees of the business units and members of the RPA team. Building on a configurational approach, we developed a mid-range theory and identified four distinct configurations that show how employees’ perceived consequences of software robots on their jobs influenced their collaboration with the automation team, their attitude towards the change in work tasks and processes and ultimately their interactions with software robots and attribution of software robots’ roles and performance. Our findings may inform implementation and change management strategies and accommodation initiatives to support employees’ needs to facilitate adoption, which is crucial for organisations to realise the benefits of RPA.
Since half a decade, there has been an increasing interest in Robotic Process Automation (RPA) by business firms. However, academic literature has been lacking attention to RPA, before adopting the topic to a larger extent. The aim of this study is to review and structure the latest state of scholarly research on RPA. This chapter is based on a systematic literature review that is used as a basis to develop a conceptual framework to structure the field. Our study shows that some areas of RPA have been extensively examined by many authors, e.g. potential benefits of RPA. Other categories, such as empirical studies on adoption of RPA or organisational readiness models, have remained research gaps.
Conference Paper
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In Spanish: La adopción de herramientas tecnológicas que incorporan algoritmos, especialmente aquellos que facilitan decisiones automatizadas, puede contribuir significativamente con los objetivos de los Estados. Por ejemplo, la implementación de sistemas asistidos por inteligencia artificial (IA) por parte de entidades públicas puede aumentar la velocidad y precisión del procesamiento de grandes volúmenes de datos; reducir los tiempos de respuesta de solicitudes y casos; y, eximir al talento humano de tareas rutinarias para reasignarlo a actividades más complejas, entre otros. Sin embargo, el uso de algoritmos en la gestión pública también puede generar riesgos y potenciales efectos negativos para los ciudadanos. La implementación de IA por los gobiernos puede implicar la pérdida de predictibilidad de los procesos de la administración pública en la medida en que los sistemas arrojen resultados o decisiones que no sean comprensibles o cuyas justificaciones no sean verificables (el efecto “caja negra”); reducir o eliminar el control de los funcionarios sobre las herramientas que utilizan; y, generar riesgos en relación con el tratamiento de datos personales, particularmente aquellos sensibles, y pérdida o afectación de la privacidad, entre otros. La literatura sobre el uso de IA en el sector público de Colombia incluye casos de estudio sobre herramientas puntuales, pero no cuenta con trabajos que mapeen y caractericen el uso de sistemas de decisión automatizada (SDA) por el Estado colombiano. Los problemas de investigación abordados por este trabajo buscan contribuir a cerrar esa brecha de la literatura: ¿Con qué finalidades son utilizados los sistemas de IA y los SDA en la administración pública de Colombia? ¿Qué beneficios ofrecen y qué riesgos generan? Para responder a las preguntas se recolectó y procesó información disponible públicamente, información solicitada directamente a entidades estatales, y entrevistas semiestructuradas a funcionarios públicos encargados de diseñar, pilotear y/o implementar los SDA. Con dicha información se creó un catastro de sistemas de IA y de SDA implementados en Colombia. A partir de los resultados del estudio se presentan implicaciones de política pública en materia de ética en el uso de los datos, transparencia algorítmica y, en general, sobre la gobernanza del uso de SDA e IA (y de los datos que los alimentan) en el sector público. In English: The adoption of technological tools that incorporate algorithms, especially those that facilitate automated decisions, can contribute significantly to states' objectives. For example, the implementation of artificial intelligence (AI)-assisted systems by public entities can increase the speed and accuracy of processing large volumes of data; reduce response times for requests and cases; and relieve human talent from routine tasks to reassign them to more complex activities, among others. However, the use of algorithms in public management can also generate risks and potential negative effects for citizens. The implementation of AI by governments may imply the loss of predictability of public administration processes to the extent that the systems produce results or decisions that are not understandable or whose justifications are not verifiable (the "black box" effect); reduce or eliminate the control of civil servants over the tools they use; and generate risks in relation to the processing of personal data, particularly sensitive data, and loss of privacy, among others. The literature on the use of AI in the Colombian public sector includes case studies on specific tools, but there are no studies that map and characterise the use of automated decision systems (ADM) by the Colombian state. The research questions addressed by this paper seek to contribute to closing this gap in the literature: For what purposes are AI systems and ADMs used in the Colombian public administration? What benefits do they offer and what risks do they generate? To answer these questions, we collected and processed publicly available information, information requested directly from state entities, and semi-structured interviews with public officials in charge of designing, piloting and/or implementing the systems. This information was used to create a registry of AI systems and ADMs implemented in Colombia. Based on the results of the study, public policy implications are presented in terms of ethics in the use of data, algorithmic transparency and, in general, on the governance of the use of ADMs and AI (and the data that feed them) in the public sector.
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Robotic Process Automation (RPA) performs high-volume tasks such as checking invoices. However, the governance and maintenance of large-scale software robot environments can be challenging when robot servers perform automatized tasks simultaneously for customer organizations with complex programming rules, dedicated parameters, and dependencies on timetables. A multivocal literature review (MLR) was conducted to explore whether there are 1) mechanisms to improve software robot maintenance in large-scale robot environments, 2) or software robot maintenance practices for scalable RPA in organizations providing shared services, 3) or governance models for optimizing the performance of software robot maintenance, and 4) is the Center of Excellence (CoE) one of the success factors concerning large-scale robot environments. By doing this, 5) we found eleven functional requirements for the monitoring tool to support maintenance in a large-scale environment. In addition, we adapted them to the RPA monitoring tool abilities for the Finnish Government Shared Services Centre for Finance and HR (Palkeet). As a result, the eleven functional requirements and the monitoring tool abilities are adaptable for other large-scale environments to improve software robot maintenance. However, commercial monitoring tools for RPA maintenance do not fulfil functional requirements, and organizations in large-scale environments must develop their monitoring tools. Based on MLR, either in-house or outsourced CoE seems to be one of the success factors in RPA maintenance in large-scale environments.
Purpose This study intends to find the industries that have leveraged Robotic Process Automation (RPA) technology and elucidate the extent of the adoption of RPA in various industry domains with benefits. The identification of tasks eligible for RPA itself is a challenge. Therefore, the study further brings out the challenges faced in various industry verticals and postulates the future direction of research and applications in RPA. Design/methodology/approach The study focuses on articles from popular databases such as SCOPUS, Web of Science and Google scholar. PRISMA methodology is used for systematic literature review and 113 papers are shortlisted for study. Three questions are framed to carry out the review and set the research direction. Findings It is evident from this study that RPA has been widely used in banking and related areas with moderate use in healthcare and manufacturing leading to operational efficiency and productivity. However, there are a lot more opportunities in other domains that need to be taped by leveraging technology advancements and a research agenda has been devised by postulating future directions. Originality/value The study brings out a new comprehensive perspective as regards RPA implementation across domains. There is no promising study found that gathers three-dimensional aspects of the meta-themes applications, benefits and challenges. The study summarizes the research agenda and projects the industry domains that have not yet explored, the benefits of RPA. This will be a good reference article for those who develop RPA techniques and organizations that have plans to go for RPA.
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Automation of pharmaceutical safety case processing represents a significant opportunity to impact the strongest cost driver for a company's overall pharmacovigilance budget. A pilot was undertaken to test the feasibility of employing artificial intelligence and robotic process automation to automate processing of adverse event reports. The pilot paradigm was used to simultaneously test proposed solutions of 3 commercial vendors. The result confirmed feasibility of using artificial intelligence‐based technology to support extraction from adverse event source documents and evaluation of case validity. In addition, the pilot demonstrated viability of the use of safety database data fields as a surrogate for otherwise time‐consuming and costly direct annotation of source documents. Finally, the evaluation and scoring method employed in the pilot was able to differentiate vendor capabilities, and identify the best candidate to move into the discovery phase. This article is protected by copyright. All rights reserved.
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Artificial Intelligence (AI) is set to transform healthcare product development with enormous potential to benefit patients, but also to other stakeholders including regulators and industry. This progress will present new challenges to the systems in place which regulate these products. Stakeholders must now work together to ensure the current regulatory systems evolve in time to embrace the future benefits of AI. This article reviews several areas where AI is being applied in healthcare product development which test current regulatory frameworks, or are topics that will need further consultation between industry and regulators to determine the optimal way to regulate these products in the future.
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This paper summarizes a panel discussion at the 15th International Conference on Business Process Management. The panel discussed to what extent the emergence of recent technologies including machine learning, robotic process automation, and blockchain will reduce the human factor in business process management. The panel discussion took place on 14 September, 2017, at the Universitat Politècnica de Catalunya in Barcelona, Spain. Jan Mendling served as a chair; Gero Decker, Richard Hull, Hajo Reijers, and Ingo Weber participated as panelists. The discussions emphasized the impact of emerging technologies at the task level and the coordination level. The major challenges that the panel identified relate to employment, technology acceptance, ethics, customer experience, job design, social integration, and regulation.
The risk management puzzle is becoming more multifaceted with increased focus on geopolitical risks, regulatory changes and new participants entering the financial markets, including Fintech and non-regulated bank-like entities. Customers are also changing their behaviour with the evolving market environment and launch of new financial products and applications. In parallel, the technology scene and IT capabilities have advanced significantly, providing opportunities to create tools that can enhance the way risk is measured and managed. In this new and highly dynamic environment, how can banks best manage risk? A complex challenge is present with numerous paths and buzzwords such as Blockchain, machine learning and robotic process automation (RPA) to navigate. The industry, including the risk management function, needs to embrace the technical environment and recognise both its potential and its limitations. Technology enhancements benefit from a holistic view, combining subject matter expertise across multiple areas. Even the smartest cognitive system requires oversight to ensure relevance of data and the patterns observed to make business decisions. Market movements and concentrations may be ascribed to artificial intelligence and machine learning models going forward, and risk managers need to be able to navigate this space and manage the underlying risk factors. Connecting the dots and recognising that risk comes in multiple shapes and form, it can still be identified along with preventative actions.
Conference Paper
We developed SNS Door Phone by making an interphone system an IoT device. We integrated SNS and QR-code recognition function with an interphone system. Thanks to connection with SNS, we can know the visit of the parcel delivery service anytime through SNS even if during going out. Thanks to introduction of QR-code recognition function, if a parcel deliveryman only showed the QR-code of the parcel in front of SNS Door Phone, the re-delivery operation information would be sent to a user automatically through SNS. Then, the user can call or ask re-delivery arrangement using smart phone without inputting any additional data. We can consider this kind of seamless re-delivery operation to be a good example of Robotic Process Automation.
Conference Paper
Since 2015, Robotic Process Automation (RPA), the software robot, imitate human behaviors to take complicated tasks is more and more popular in various industry. The current references are mainly concepts the case studiess that focused on the dedicated enterprise, however, less of generalization. For the goal of stepping out and going further of find the genera key factors about RPA-Business alignment, researchers will use multi-valued qualitative comparative (mvQCA) method and IT-Business alignment theory. The general factors of IT-Business alignment can also affect RPA-Business. Second, there are two ways to accelerate the RPA-business alignment and six ways to slow down RPA-business alignment from the calculation results. The positive and negative have different configurations. With this research result, other mvQCA requirements could take the most of the positive factors of RPA-Business alignment. Meanwhile, the negative factors can avoid in advance. The essence of RPA is information technology.
Conference Paper
Organizations are applying digitalization to the constantly increasing amounts of different organizational processes [2]. The healthcare sector is also changing and actively seeking better ways to enhance performance, especially in the private healthcare sector [7]. Automation of workflow processes, e.g., Robotic Process Automation (RPA), in organizations has been emerging as a solution to this demand [3, 4]. To meet this clear demand, automation of workflow processes in organizations has been a rising trend during the past few years [3]. We analyze the value creating functions of the RPA potential in the private healthcare industry sector, using modified Walter et al.'s function-oriented value analysis as our theoretical lens for identifying the potential of RPA.
(a) Situation faced: Due to the high number of customer contacts, fault clearances, installations, and product provisioning per year, the automation level of operational processes has a significant impact on financial results, quality, and customer experience. Therefore, the telecommunications operator Deutsche Telekom (DT) has defined a digital strategy with the objectives of zero complexity and zero complaint, one touch, agility in service, and disruptive thinking. In this context, Robotic Process Automation (RPA) was identified as an enabling technology to formulate and realize DT’s digital strategy through automation of rule-based, routine, and predictable tasks in combination with structured and stable data. (b) Action taken: Starting point of the project was the aim to implement DT’s digital strategy. In an early stage of the project, it was decided to utilize RPA as enabler, in particular to drive digitization and automation of transactional activities. From a methodical perspective, the set-up and conduction of the RPA project was structured into (1) organization and governance, (2) processes, and (3) technology and operations. From the content perspective, the RPA project defined and implemented a multitude of detailed RPA use cases, whereof two concrete use cases are described. (c) Results achieved: Within less than 6 months from the project start, the first transactions were performed automatically through RPA. In March 2016, approx. 229 thousand automatic transactions were successfully realized. Since then, the number of automatic transactions through RPA per month has been increasing significantly. The increase of automatic transactions per month was realized through a growing amount of usage of RPA in different process areas of DT. Within 1 year, the number of automatic transactions per month has been increased to more than 1 million. (d) Lessons learned: The case provides an example for a concrete technology-induced change as part of a digital transformation. The concept of RPA provides an opportunity to automate human activities through software robots. The lessons learned utilizable for future RPA projects are: (1) Agile design and implementation are important for a successful digital transformation. (2) Understand technical innovations as enabler of the digital transformation. (3) Investigate technical and organizational interrelations from the beginning. (4) RPA is more than a pure cost cutting instrument. (5) The impact of RPA on the people dimension should be managed carefully from the beginning.