Factors Affecting Cloud Adoption and Their Interrelations
Radhika Garg and Bu
rkhard Stiller
Communication Systems Group CSG, University of Zürich UZH, Binzmühlstrasse 14, CH-8050, Zürich, Switzerland
Keywords: Cloud Computing, Cloud-based Services, Cloud Adoption, Technical Factors, Economical Factors,
Organizational Factors.
Abstract: Cloud Computing has emerged as a paradigm that relies on sharing resources over the network and,
therefore, potentially has cost advantages in terms of lower variable and capital cost. However, the adoption
of cloud-based technology for a given IT (Information Technology) setting is a complex decision as it is
influenced by multiple interdependent factors. To successfully adopt cloud-based services and evaluate their
consequential impact, relevant factors, which denote the performance of such services, have to be identified.
This paper, therefore, analyzes and identifies relevant technical, economical, and organizational factors.
This is performed as exploratory research consisting of performing (a) a literature review and (b) multiple
case-studies with 17 organizations, who have adopted or plan to adopt cloud-based services. Also, as these
factors are not mutually exclusive, this paper discusses interrelations of these factors and its complexity.
1 MOTIVATION AND
INTRODUCTION
Ever since the advent of Cloud Computing (CC)
numerous definitions have been proposed. The
definition provided by NIST (Badger, 2012) states,
“Cloud computing is a model for enabling
ubiquitous, convenient, on-demand network access
to a shared pool of configurable computing
resources (e.g., networks, servers, storage,
applications, and services) that can be rapidly
provisioned and released with minimal management
effort or service provider interaction.” In addition to
the explicit listing of major technical characteristics
of CC, this definition also hints at an economical
and organizational impact of CC.
CC is based on computing technologies such as
of virtualization, Service-oriented Architecture, Web
2.0, Web 3.0, and Distributed Computing. The major
benefits being pay-as-you-go model, on-demand
scalability, business agility, increase in economies of
scale. Depending on the provisioning location, CC
has four deployment models (1) Private Cloud, (2)
Public Cloud, (3) Hybrid Cloud, and (4) Community
Model. Initially, CC delivered three fundamental
service models: Software-as-a-Service (SaaS),
Platform-as-a-Service (PaaS), and Infrastructure-as-
a-Service (IaaS). But, today it is extended to XaaS
(Anything-as-Service), which can include anything
such as Network–as-Service, Database-as-a-Service,
or Communication-as-a-Service.
As numerous cloud-based alternative solutions
are available, in order to successfully adopt one in
an organization it is important to evaluate value and
impact of incorporating the cloud into business for
fulfilling IT (Information Technology) requirements.
Currently, many organizations tend to fail to retrieve
the best return from the cloud-based solution. This is
due to the lack of complete understanding of factors
(both by cloud providers and customers) that impact
organizations, which adopt cloud-based services to
fulfill their IT requirements. Factors that affect CC
depend on (a) requirements of the cloud-customer,
(a) type of service model, and (c) deployment
model. Therefore, in order to formalize the impact of
cloud-based services, and to take a decision whether
to adopt cloud or not, identifying factors from
technical, economic, and organizational perspective
is necessary (Garg, 2014b).
The identification of factors in this paper here is
done based on exploratory research. In exploratory
research, conclusions are based on the review of
available literature/data, or qualitative approaches
such as discussions, focus group, or case-studies.
Therefore, for identfying major factors from the
technical, economical, and organizational
perspective, this paper uses (a) review of available
literature and (b) case-studies with 17 organizations,
87
Garg R. and Stiller B..
Factors Affecting Cloud Adoption and Their Interrelations.
DOI: 10.5220/0005412300870094
In Proceedings of the 5th International Conference on Cloud Computing and Services Science (CLOSER-2015), pages 87-94
ISBN: 978-989-758-104-5
Copyright
c
2015 SCITEPRESS (Science and Technology Publications, Lda.)
who have adopted cloud-based services, or plan to
do so. Once relevant factors are identified, the
method to identify interelations between these
factors is discussed. This leads to assisting
organizations in successfully adopting cloud-based
services and predicting impact with a possibility of
preparing counter-measures in advance in case a
failure occurs in future.
The remainder of this paper is structured as
follows. Section 2 discusses related work done in the
field of the identication of relevant factors from all
perspectives influencing the adoption of clouds in an
organization. It also highlights existing gaps in this
field and how this paper bridges them. Section 3
determines the research metholodolgy followed in
terms of research questions addressed, the design,
and the study. Section 4 summarizes and analyzes
key findings and explains how interrelations
between identified factors can be identified. Section
5 summarizes and concludes the paper.
2 RELATED WORK
According to a recent report of 2014 by the
International Data Corporation (IDC), spending on
public IT cloud services would increase to a
compound annual growth rate of 22.8 percent over
the next five years, hence making it a $127 billion
value (IDC, 2014). In order to completely utilize
benefits of CC, industry and research have tried to
understand and solve challenges affecting the cloud
adoption, such as that of security and privacy.
However, these efforts have been concentrated
mainly toward addressing technical issues, such as
multi-tenancy, scalability, monitoring of cloud-
architecture, or performance (Tang, 2014), (Kaur,
2013), (Kuyoro, 2011). There are some efforts
toward optimizing cost or Return-of-Investment
(ROI) of adopting cloud-based services (Chaisiri,
2012), (Misra, 2011). In addition, there are studies to
understand and calculate how cloud-based services
conserve capital and reduce ongoing cost.
Comparing Total Cost of Ownership (TCO) of
cloud-based service and on premise solution leads to
an assessment of total costs involved in deploying
these two models (Walterbusch, 2013), (Martens,
2012). However, efforts in both of these directions
follow a narrow approach and do not identify and
analyze the impact of adopting cloud-based services
from all perspectives (Garg, 2014a).
There was effort invested in the direction of
addressing how the decision of adopting cloud-based
services can be taken (Geczy, 2012), (Hoesseini,
2011), (Saripalli, 2011). They do identify that this
decision is influenced by multiple factors that can be
interrelated. However, neither do these approaches
list factors that should be considered to take such a
decision nor do they identify that these factors
belong to all technical, economical, and
organizational fields. Also, the identification of
interrelations is only restricted to the analysis of
their relative importance and it does not include their
interdependence in terms of their performance
requirements and evaluation.
Table 1: Comparison of Related Work with Respect to
Main Characteristics of Current Work.
Features Methods for
Decision of
Adoption of
Cloud
Methods for
Optimizing
Technical
Factors
Methods for
Optimizing
Cost
Technical
Analysis
✕ ✓ ✕
Economical
Analysis
✕ ✕ ✓
Organizational
Analysis
✕ ✕ ✕
Inter-relations
Between Factors
✓
(partially)
(only between
technical
factors)
✕
As shown in Table 1, gap still exists in research
efforts in terms of identifying factors, which
influences the decision of cloud adoption. The
comparison of related work to the work done in this
paper is based on four key features; “
✓” describing
the presence and “
✕” denoting the lack of that
feature. This paper, therefore, fills this gap by (a)
identifying factors from all perspectives-technical,
economical, and organizational, and (b) identifying
interrelations between these factors.
3 RESEARCH METHODOLOGY
Given the lack of empirical data for these factors
that should be considered, while evaluating impact
of cloud-based services or decision to adopt cloud,
this paper follows an exploratory method. This is a
qualitative approach, to understand information in
depth and analyze diverse and complex data. In
order to identify relevant factors, two methods were
used. First is that of a case study, wherein semi-
structured interviews were conducted with
organizations. Second is that of analyzing available
literature, both from industrial and academic
surveys.
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3.1 Case Study Design
Case studies are useful for collecting data, where
little or no information exists. It helps to understand
a “case” from holistic and real-world perspective
(Yin, 2013). This paper here lists and analyzes data
collected from case studies conducted with 17
organizations, who have adopted or plan to adopt
cloud-based services for fulfilling their IT
requirements. These interviews were conducted
between June 2013 and October 2014, and their
duration varied between 45 and 60 minutes. These
interviews were either conducted on landline phone
or as face-to-face meetings.
3.1.1 Selection of Participants for Case
Studies
The selection of organizations interviewed was
based on random and convenience sampling.
Random sampling is considered as a fair way of
selecting a sample from a given population since
every member is given equal opportunities of being
selected (Gravetter, 2010). This was combined with
Table 2: Details of Organizations involved in Case
Studies.
Org Domain of Expertise Organiza-
tion’s Size
a
Geographic
Scope Served
C1 ICT Provider 60000 Europe, USA,
Singapore
C2 Health Insurance 450 Switzerland
C3 Communications 20000 Switzerland
C4 IT Infrastructure
Provider
5000 Europe, USA,
Australia,
China
C5 Financial Services 2600 Worldwide
C6 Property and
Life Insurance
4000 Switzerland
C7 Professional
Services
180000 Worldwide
C8 Networking Solutions 67000 Worldwide
C9 ICT Association - Switzerland
C10 Financial Services 140000 Worldwide
C11 Banking Services 255000 Worldwide
C12 Technology and
Consulting
431000 Worldwide
C13 Technology and
Consulting
305000 Worldwide
C14 IT services 318000 Worldwide
C15 IT Infrastructure
Provider
107000 Worldwide
C16 Life Insurance 3000 Switzerland
C17 Digital Media
Solutions
12000 Worldwide
a
Number of employees as per October 2014.
convenience sampling, due to the availability and
proximity of participants. Convenience sampling
helps to collect information in more depth as
participants are in proximity (Gravetter, 2010).
Bias, which can often result from convenience
sampling, was avoided with two countermeasures:
(a) Participants were selected with varied
geographical scope and domain of expertise. This
helped in collecting data, which can be
representative of the complete population. (b)
Questions were based on interviewees’ experience
of adoption of cloud-based services (varied as per
their domain of expertise) and with general benefits
or challenges associated with the adoption of cloud-
based services, therefore, making generalizations
possible. Details of organizations are listed in Table
2. Interviewees from these organizations were senior
decision-makers with experience of assessing
various cloud alternatives. Participation was
voluntary and their identity is kept anonymous,
while reporting and analyzing the data collected.
This was mainly due to the confidentiality and
sensitivity of data and opinions shared by the
decision makers of various organizations.
3.1.2 Research Questions
These case studies were conducted as semi-
structured interviews. Owing to the semi-structured
format of the interview, the interviewer was able to
adapt the interview based on individual
circumstances. All topics discussed (major ones
listed below) within this interview supported two
research questions that served as trigger point for
discussion.
• What are the factors (technical, economical, and
organizational) that should be considered while
making a decision to adopt cloud-based services
for fulfilling IT requirements?
o Key reasons for adopting a cloud-based
solution.
o Factors that decide the eligibility of candidate
to be migrated to cloud-based solution
o Limiting factors and risks for selecting a
cloud-based service.
o Factors that decided which deployment
model will be selected.
• Are these factors interdependent? If yes, then
how?
o Impact of migration to cloud-based service on
organization.
o Evaluation of success or failure of adoption
FactorsAffectingCloudAdoptionandTheirInterrelations
89
3.2 Literature Study
The literature review is used as the second method to
collect data in terms of factors affecting the adoption
of clouds in an organization. This covered reviewing
various technical and economic papers, white
papers, and surveys provided by industry and
academic research. Even though these efforts do not
list factors from all relevant perspectives, they
collectively give a valuable insight into challenges
and benefits of the cloud adoption decision.
The topics covered in literature available can be
broadly categorized into the following categories:
• Security and privacy issues related to the
adoption of cloud computing
• Technical issues in migrating and integrating
cloud-based services with existing systems to
fulfill IT requirements
• Generalized benefits and challenges of adopting
cloud-based services
• Structural changes in ROI and TCO models,
including cost benefits
4 KEY FINDINGS AND
ANALYSIS
The data analysis in this paper was based on the
targeted result of identifying factors and their
interrelations. In order to avoid any
misinterpretations all case studies were fully
transcribed. The data (both of case studies and
literature review) was aggregated, converged, and
aligned in a database, thereby helping in identifying
multiple occurrences of factors and cross case-study
synthesis. This enabled the identification of
regularities and differences across and within
various data sources and provided for plausible
explanations on importance of a particular factor.
Also, due to the presence of multiple data sources,
result credibility was ensured. The qualitative data
was categorized in three categories (technical,
economic, and organizational). Factors, found in the
exploratory research, can have a different priority or
relevance for different organizations. This depends
on overall requirements and expectations from the
cloud-based service. Thus, key findings of this
exploratory research in terms of technical,
economic, and organizational factors and their
interdependencies are derived as follows.
4.1 Technical Factors
CC has major benefits in terms of its technical
Table 3: Relevant Technical Factor.
Scalability
Availability
Elastic Resourcing
Network Quality
• Bandwidth
• Connectivity
Interoperability
Speed/Latency
Quality of Service
Portability
Compliance and Standards
Usability
• Application Launch Time
• Graphics Agility
• Simplicity
Data Loss
Reliability
• Elasticity
• Disaster Recovery
Privacy
Compatibility with Existing Systems
Software Assurance
Customization
Integration
Management and
Maintenance of Identity Platform
Management of Authentication Platform
Security Configuration and Maintenance
• Confidentiality
• Integrity
• Availability
• Auditability
• Multi-tenant Trust
Functionality
Triability
Delay in Migration and Data Transfer
Vendor Lock-in
Process Redesign
Accessibility
Standards for API
Backup
• Data
• Application
Workload Management
• Classification
• Capacity Planning
• Performance Management
Configuration Management
• Mission Criticality
Multi-tenancy
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characteristics. Table 3 lists the key factors, which
must be evaluated before adopting a cloud-based
service. An IDC report reported 75% of the
respondents mentioned security as one of most
important factor to be evaluated, while adopting
cloud-based services (Sultan, 2011). This is of
utmost importance for the public cloud. Another
important factor is that of sensitivity of data. As the
provider has full access to the data, responsibility of
data theft, loss, and adherence to legal and regulative
guidelines for storage of data has to be carefully
evaluated. This factor has higher priority in cases,
when public or hybrid deployment models are
selected (as compared to private deployment model).
For Small and Medium Enterprises (SME), it is
important to take measures to increase the network
quality in terms of bandwidth and connectivity
(Yeboah-Boateng, 2014). Network quality is
important, because in many cloud architectures (e.g.,
Amazon Elastic Block Store (EBS) architecture) the
data storage layer is abstracted in the compute layer
of the application. These compute and data storage
nodes are connected via a network. If the network is
not of good quality, the application can fail to
respond (Joyent, 2014).
As pointed out by every organization, which
participated in these case studies, vendor lock-in is
an obstacle for a successful adoption of cloud-based
services. It also has high negative impact in terms of
cost and interoperability in case when the service
provider has to be switched. It highlights the need of
common standards for APIs across cloud-service
providers, so that interoperability is possible. Public
cloud tends to get significant advantage over private
cloud for all organizations, which participated in the
case study, because of its capability to handle
unexpected hike in workloads. Therefore, a flexible
infrastructure capacity and a provisioning time
determine a critical factor for the adoption of a
cloud. Organizations participating in this case study
also mentioned usability and functionality as
deciding factors. Not only the technological know
how is important for a successful adoption of cloud
based services, but also the ease-of use is crucial for
these organization
4.2 Economic Factors
As found in these case studies (specifically pointed
out by SMEs) and within the literature review,
cloud-based services reduce upfront costs and
operational complexities of converting small
businesses into larger ones (Chaisiri, 2012), (Misra,
2011). These costs are shifted to data centers, which
benefit from economics of scale and scalability. CC
follows the Operating Expenditure (OPEX) model
and offer elasticity in terms of scaling resources as
per demand. This transfers the risk of over- or
under-provisioning to the service provider.
However, customers should evaluate, if scaling-up
of resources (e.g., increasing the power of server) or
scaling-out of resources (e.g., increasing the number
of servers) is more appropriate for their specific use-
case. This is specifically required as clouds operate
at the large scale (Hasan, 2012). For example, in
some cases, where the number of customers pre-
decides the number of software licenses, increasing
them later for an unexpected increase in demand will
be very expensive or even impossible. Table 4 lists
the key factors from the economic perspective.
All organizations, irrespective of its size and
geographical scope, considered the reduction of their
carbon footprint as one of the major goals. This
leads to evaluation of alternatives of cloud-based
services so that a best trade-off is achieved between
performance, Quality-of-Service (QoS), and energy
consumption of storing, processing, and
transportation (Mouftah, 2012). Service Level
Agreements (SLA) indicate the description of an
agreed upon service, service level parameters,
guarantees, actions, and penalties in case of failure
or violations (Wu, 2012). SLAs help the
organization to monitor the performance and billing
of the service provider. If any of the guaranteed
metric is not fulfilled, the provider incurs penalties.
Table 4: Relevant Economical Factors.
Cost
• License
• Maintenance
• Back-up
• Energy
• Hardware
• Migration
• Future Requirements
• Performance
• Data Loss
• Switching Providers
• Integration
Operating Cost (OPEX)
Marginal Cost and Profit
Energy Use and Carbon Emission (Carbon Foot Print)
Contracts and Service Level Agreements (SLA)
Billing and Metering of Resource Usage
Traceability and Audibility
• Data
• Application
Return-of-Investment (ROI)
Total Cost of Ownership (TCO)
Migration Time
FactorsAffectingCloudAdoptionandTheirInterrelations
91
However, the major consequence of this is on the
business continuity of the customer. Consequent
economical losses due to failure of any cloud-based
services can be very high. Another important factor
is the calculation of the Return-of-Investment (ROI).
For calculating ROI of a traditional IT infrastructure,
the initial cost of project, the investment made, and
the cost savings done owing to the new
investment has to be identified (Chang, 2012).
However, for calculating the ROI associated with
cloud-based services, increase in profit, reductions
in cost, license cost, and any implicit cloud costs
have to be identified also. Based on the calculated
ROI, the suitability of an adoption of a specific
cloud-based service can be recognized (Misra,
2011).
4.3 Organizational Factors
As determined from both, literature review and case
studies, currently organizational factors are the least
evaluated factors for the decision on a cloud
adoption. This is because understanding the
significance and extent of impact of an adoption of
cloud-based services in an organization on the
management and operation of IT infrastructure is a
challenge. However, the evaluation of a cloud-based
service from this perspective is equally important.
To name a few required changes in an organization
due to CC are a change in the accounting model, the
security model, compliance requirements, and the
project management (Hoesseini, 2011). Table 5 lists
other key factors from the organizational
perspective, which must be evaluated before
adopting a cloud-based service.
CC has a distinct disadvantage in terms of loss of
control of both data and resources. This leads to
issues of privacy and security. Also, as cloud-based
services lack transparency in terms of location where
data is stored and performance levels of the
application as compared to the terms in the SLA, it
raises problems related to legal and regulative issues
(Battey, 2012). Legal risks also include the liability
of the service provider to protect the data from
security threats and privacy breaches. Security
threats include the deletion of data, multi-level risks,
physical attacks, and isolation failure (Kuyoro,
2011). On one hand, CC has advantage in terms of
improved process efficiency and increased employee
productivity by better internal collaboration. On
other hand, CC can have a major disadvantage in the
overall efficiency and productivity of the
organization, if employees are unable to adapt
themselves to changes brought by CC. A successful
adoption of cloud-based services is dependent on
how easily can the new technology be learnt by
employees of the organization (Saini, 2012). As
identified by organizations, which participated in
case studies, CC has the capability of transforming
business, as the employees need to concentrate only
on the innovation of application, the cloud-service
provider handles everything else. However, to
achieve this, technical support from service-
providers and the competence of employees of the
organization are two crucial factors.
Table 5: Relevant Organizational Factors.
Size of Organization
Degree of Centralization
Managerial Structure
Competence of Employees
Control
Transparency
Business Flexibility and Agility
User and Technical Support from the Provider
Legal and Regulative Compliance
Skills and Expertise of the Cloud Providers
4.4 Relation between Factors
The factors outlined above can have numerous and
complex interrelations based on use case-specific
requirements of the organization. Therefore,
understanding and identifying these interrelations is
equally important to completely evaluate any cloud-
based service. Figure 1 illustrates an example of how
factors can be interrelated. Scalability leads to cost
savings, which can be used in acquiring end user
systems and training. To manage failures, such as
that of an uptime time failure or a data loss, many
cloud-service providers recommend customers to
maintain multiple levels or redundancy. This,
however, leads to higher capital and operational cost
for establishing and maintaining such a system. The
lack of standards causes major difficulties, when a
decision is made to move applications or data
between clouds. These problems include (a) security
levels, (b) handling data movement and encryption
of data, and (c) setting up of network with the same
configuration as that of the source cloud. These
issues consequently have an economic impact in
terms of cost and ROI. Security and privacy issues
associated with cloud computing include multiple
issues as that of (a) regulatory compliance in terms
of liability of data, location of data storage, (b)
proper means of data segregation so that availability,
reliability, and confidentiality of data is ensured
(Kaur, 2013), and (c) a cloud-based solution that has
be able to replicate data across multiple sites to
ensure proper recovery in case of any disaster
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(Kuyoro, 2011). These issues affect the cost,
performance, and control an organization has on a
cloud-based service. The costs of cloud-based
services are lower, mainly owing to the sharing of
resources. This, however, means less guarantees of
performance. Therefore, it is important to have strict
SLAs, where each relevant performance metric is
identified with an expected level of performance.
Scalability
Availability
Interoperability
Quality of Service
Standards
Privacy
Migration Time
Security
Data Loss
Elasticity
Cost
OPEX
SLA
Billing and
Metering
ROI
TCO
Control
Legal and
Regulative
Compliance
Competence of
Employees and
Service Provider
Business
Flexibility and
Agility
Migration Time
Transparency
Managerial
Structure
Factor A
effects
B
Figure 1: Interrelations between Factors.
As cloud-based services allow scalability and
variable levels of resource usage, billing and
metering as per the usage is essential. Cloud-based
services contribute primarily to business agility and
flexibility, but it also restricts an organization in
terms of control it has on its own data and
applications. Cases of data loss or the need to move
data between cloud providers can lead to huge
losses. A successful adoption of a cloud-based
service is also dependent on the adaptability of the
organization in terms of its managerial roles,
structure, and competence. Identification of
interrelations leads to a systematic evaluation for all
tradeoffs and risks involved in considering specific
clouds (Garg, 2014b).
5 SUMMARY AND
CONCLUSIONS
This paper has bridged the existing gap between
identifying relevant technical, economic, and
organizational factors and their interrelations. To
achieve this, exploratory research was used in terms
of a literature review and 17 case studies with
organizations that have either adopted or plan to
adopt cloud-based service in the future. In turn, the
work showed that interrelations exist between
factors of multiple domains and how these relations
can be identified.
In conclusion, these factors and their
interrelations have a clear influence on (a) the
decision of the adoption of cloud-based services and
(b) on the impact analysis of a cloud-based service.
These lists of factors developed classify available
cloud-based services. This classification can be done
on the basis of a capability of cloud service
providers to fulfill the expected level of performance
for each of these factors, thereby aiding
organizations to select the best alternative as per IT
requirements and business objectives. Furthermore,
organizations can ensure that all relevant and critical
factors are specified in the SLA with a guaranteed
level of expected performance. Lastly, it has also
been identified that areas of standardization,
interoperability, security, and privacy need to evolve
(e.g., ease in encryption of data while in transit
between cloud service provider). This is because of
their wide impact in terms of technical, economic,
and business value.
ACKNOWLEDGEMENTS
This work was partly funded by FLAMINGO, the
Network of Excellence Project ICT-318488,
supported by the European Commission under its
Seventh Framework Program.
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