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1 23
The International Journal of
Advanced Manufacturing Technology
ISSN 0268-3768
Volume 88
Combined 1-4
Int J Adv Manuf Technol (2017)
88:369-380
DOI 10.1007/s00170-016-8770-6
Application of emerging technologies
in ERP implementation in Indian
manufacturing enterprises: an exploratory
analysis of strategic benefits
Shree Ranjan, Vijay K.Jha & Pralay Pal
1 23
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ORIGINAL ARTICLE
Application of emerging technologies in ERP implementation
in Indian manufacturing enterprises: an exploratory analysis
of strategic benefits
Shree Ranjan
1
&Vijay K. Jha
2
&Pralay Pal
1
Received: 23 August 2015 / Accepted: 11 April 2016 / Published online: 23 April 2016
#Springer-Verlag London 2016
Abstract Manufacturing “smart connected products”and
building “factories of future”are need of the hour in global
manufacturing arena, which is forcing enterprise decision
makers to develop deeper insight in relevance of emerging
technologies in enterprise resource planning (ERP) such as mo-
bility, cloud computing, analytics, social network computing
and Internet of Things (IoT) to leverage them for strategic ben-
efit and competitive advantage. In this paper, we explore stra-
tegic engagement of these technologies in manufacturing enter-
prises. We conducted exploratory factor analysis (EFA) of the
benefits and studied their impact on four objective indicator
areas such as employee, process, customer, and finance. We
used IBM SPSS to perform EFA on the response data from
questionnaire survey to identify critical benefit factors and ben-
eficiary objective indicators. We compared our work with other
research findings. This work will help practitioners develop
better insight and decisiveness for investing in advanced tech-
nologies in pursuit of manufacturing excellence. For academia,
the work will open new research directions.
Keywords Enterprise .ERP .Advanced manufacturing .
Mobility .Cloud computing .BSC .SPSS .Decisiveness .
Transformation driver
1 Introduction
Enterprise resource planning (ERP) facilitates seamless flow
of the information through the organization that integrates,
optimizes, and controls all the manufacturing processes and
transactions in order to enhance efficiency and maintain a
competitive position [2]. ERP systems have become vital stra-
tegic tools for advanced manufacturing enterprises to improve
the performance of the supply chain and reduce the cycle
times of new products and product variants launch, fostering
innovative culture in the organization, creating customer loy-
alties and shareholder values [6].
Investment in ERP emerging technologies in manufactur-
ing enterprises particularly, in original equipment manufac-
turers (OEMs) is strategic due to complexity involved, high
cost of implementation, change management issues, and pos-
sibility of business disruption. Therefore, it is crucial for de-
cision makers to understand the relevance of ERP technolo-
gies with the enterprise objectives that deliver performance to
fulfill implementation objectives [2,21,24]. The objective of
the study is to find out relevance of such technologies
connecting ERP and manufacturing and their individual po-
tential to contribute in strategic benefits earning. We choose a
set of manufacturing enterprise functions based on enterprise
balanced scorecards (BSCs), addressing various strategic
areas as in Fig. 1. State-of-the-art technology components
such as social virtual networking, mobility, big data analytics,
cloud computing, and Internet of Things (IoT) have been con-
sidered, and their interface with the strategic objective indica-
tors are explained. We deliberated on role of transformation
drivers in an ecosystem between enterprise computing and
emerging technologies and their impact on advanced
manufacturing facilities. To conduct analysis of benefits, we
listed applications of these technologies and carefully formu-
lated survey questionnaire along with their possible benefits.
*Pralay Pal
Pralay.Pal@tatatechnologies.com
1
Tata Technologies, Jamshedpur, Jharkhand, India
2
BIT Mesra, Ranchi, Jharkhand, India
Int J Adv Manuf Technol (2017) 88:369–380
DOI 10.1007/s00170-016-8770-6
Author's personal copy
Exploratory factor analysis (EFA) was performed on the col-
lected responses using IBM SPSS Statistics V23 to identify
critical benefit factors adopting the principal component anal-
ysis (PCA) approach. Eight most important benefit factors and
their corresponding technology enablers were identified and
ranked. The results are compared with outcome of research
conducted by other authors and implementability of the work
in modern age manufacturing has been discussed.
The organization of this paper is as follows. Review of re-
search on ERP emerging technologies is presented in Sect. 2.
Significance of BSCs and how ERP offerings address BSCs are
discussed in Sect. 3.Section 4 deals with an ecosystem of
enterprise computing and emerging technologies to illustrate
importance of adoption of these technologies. Research design,
methodology, and data analysis are presented in Sect. 5.
Summary results and comparison of findings with other works
are presented in Sect. 6. How practitioners will implement these
research findings in manufacturing has been expounded in
Sect. 7. Limitations of research and future directions are delib-
erated in Sect. 8.Section 9 presents a conclusion of the work.
2 Review of research on ERP emerging technologies
We identified emerging trends and technologies in ERP hav-
ing direct relevance with strategic benefits such as cloud com-
puting, mobility, big data analytics, insurgence of social
media, and IoT and those having indirect relevance such as
open-source ERP, enterprise application integration (EAI),
sustainability, and special IT adoption such as data
warehousing. Our work aimed at establishing a decision sup-
port methodology for corporations for investing in technolo-
gies and help academia in finding new avenues of research.
Exploring strategic benefits of ERP emerging technologies is
an important prerequisite of our study. To realize value from IT
investment, strategic alignment between the business and IT of an
organization is essential [8]. Strategic value of IT can be derived
by “digitization”of business models of organizations for compet-
itive edge [3,4]. To achieve this, the balanced scorecard (BSC)
concept was introduced as a strategic planning and performance
management system for “vision to action”across four balanced
perspectives in manufacturing organizations: financial, customer,
internal business processes, learning, and growth [11–13]which
eventually became the fundamental building block for evaluating
strategic benefits of ERP [4,18] satisfying business objectives.
Lately, the objective of investing in emerging technologies in
manufacturing is to achieve futuristic factories with facilities such
as “smart machine supervisory system framework”[1] and man-
ufacture “smart, connected products”[20].
Few authors advocate leveraging emerging technology
stack called “social-mobile-analytics-cloud”and IoT for en-
terprise efficiency and effectiveness enhancements. These
technologies converged to enterprise application platforms
with consumerism of IT and mobility [9]. Enhancing mobile
Strategic Iniave @ ERP Implementaon
MISSION
Why the OEM exists?
In what the OEM believes?
VALU ES
What the OEM wants to be?
VISION
What is OEM’s game plan?
STRATEGIC PLANNING
OBJECTIVE INDICATORS
Employee
Learning and Growth
to Innovate
Process
Developing Strategic
Capabilies, Efficiency
Customer
Delivering specific
Value to Market
Finance
Increasing
Shareholder Values
Employee Process Customer Financial
Quality Mgt.
Producon
Planning
Sales Distribn.
Prodn. Book,
Sourcing
MES & SRM
Personnel
Mgmt.
Org.
Managemt.
Travel Mgmt.
Payroll, Emp.
Engagement
Tal en t
Management
CRM, Pipeline
Management
Account Sales
Proposal Mgt.
Marketng Mgt.
Dealer, Client
Collaboraon
Sales Territory
Management
General Ledger
A/C payable,
receivable
Bank/Excise
/MRP
Cost, Profit
Centre A/C
Mat. Purchase
to Prod, Spare
Strategic
Iniaves
Training Hours
Succession
Plan
Perform ance
Measure
IPRs, Employee
Engagement
Arion Rate
Deviaons/
Incidents
NPI & TTM
Inventory Turns
Vendor Capact.
Expansion
Capacity Ulize
Customer Sat
Service
Touch-point
Market Share
Customer,
Dealer Loyalty
Sales
Touch-point
Cash Flow
Profitability
EBIDTA
Revenue
growth
Return On
Capital Expense
BSCs
BSCs
ERP FUNCTION
ERP FUNCTION
Fig. 1 BSCs derived from MVV
and strategic function integration
using ERP
370 Int J Adv Manuf Technol (2017) 88:369–380
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applications by cloud computing will lead to maturity of cloud
ERP [23]. Cloud computing, multi-tenancy, and Software-as-
a-Service have transformed traditional legacy ERP to cloud
ERP [4]. The five futuristic emerging trends are IoT, wearable
technology, big data analytics, the age of context (context
aware mobile apps), and finally, opening business to innova-
tion, results of which can be seen in the bottom line of enter-
prises [17]. Part explosion process in MRP using hierarchical
structure and query processing are important for real-time
production scheduling, purchase, and inventory recording in
mass and batch manufacturing [16]. In all cases, assessing the
performance of an ERP system is essential with appropriate
performance indicators, indicator structure, and consistent
evaluation standards [24]. These contributions helped us iden-
tify emerging technologies for our work.
EAI, open-source ERP, sustainable ERP, and ERP value
system influence strategic alignment for manufacturing excel-
lence. In integration of ERP with supply chain and other ap-
plications, EAI offers exchange of data, objects, and processes
through application layers resulting in better globalized com-
petitive advantage for virtual organizations [22].Theneedof
creation and sustenance of competitive advantage and custom-
er focus has compelled companies to deliver value-added
products and services faster through rapid flow of information
using data warehousing [26]. Small and mid-sized enterprises
(SMEs) prefer adopting open-source ERP than proprietary
ERP [10] irrespective of cost. Semantically described business
remote function call (BRFC) and concept of heterogeneous
data translator are useful for seamless integration of ERP
and PDM systems [25]. Similarly, agent-based framework in-
tegrates PDM and ERP fostering manufacturing collaboration
such as replacement parts requirement analysis [19].
In the globalization era, automotive industry increases com-
petitiveness by quality program, strategic planning, monitoring
performance, encouraging communication, customer and pro-
cess focus, innovation, and learning to mitigate challenges of
high quality and trade regulations [6]. Antecedent factors such
as system quality attributes, organizational capabilities, and de-
sired strategic benefits play crucial roles in successful adoption
of ERP and emerging technologies [21]. Future trends such as
web-based procurement and ERP outsourcing pose challenges
such as global compatibility and flexibility in ERP value sys-
tem [5]. Sustainable ERP promotes collection, integration, au-
tomation, and monitoring of information to support sustainabil-
ity and integration issues [3]. Tangible ERP benefits are largely
industry independent while intangible benefits vary across in-
dustry and their analyses can help a firm while investing in ERP
[18]. Though ERP migration to cloud platform IaaS involves
low infrastructure cost and reduced support calls, it lacks in data
security, legality, and privacy [14].
Study of critical failure factors (CFFs) of ERP implementa-
tion in SMEs [2] has rendered a guideline for statistical multi-
variate data analysis [7,15]. Our study was quite in-depth from
strategic point of view. No literature was found on strategic
benefits of emerging technologies substantiating ERP in
manufacturing enterprises which we address in our work.
3 Supporting BSCs through ERP functions—a
strategic approach
Enterprises invest in technology initiatives in order to achieve
strategic competitive advantages. Strategic planning translates
mission, values, and vision into BSCs [13] to measure perfor-
mances across four balanced, mutually interacting and interde-
pendent perspectives or objective indicators such as finance, cus-
tomer, internal processes, and employee related such as learning,
innovation, and growth. BSC tells the knowledge, skills, and
systems that employees will need (learning and growth perspec-
tive) to innovate and build the right strategic capabilities and
efficiencies (internal processes perspective) that deliver specific
value to the market (customer perspective) which will eventually
lead to higher shareholder value (financial perspective) as in
Fig. 1. An overall process measure and few critical success factors
are indicated through BSCs. We show manufacturing enterprise
BSCs for each objective indicator in Fig. 1. ERP functions ad-
dress these BSCs based on their relevance and appropriateness in
order to integrate these functions as part of strategic alignment [8].
An enterprise bridges BSCs with strategic initiative like
ERP using various functions. Decision makers and technolo-
gy selectors need to identify advanced technology enablers
and platforms to connect ERP and operations in meeting stra-
tegic goals and earning competitive advantages.
4 Supplementing ERP framework using emerging
technologies
Emerging digital technologies supplement various ERP func-
tions which address company BSCs under objective indicators
as shown in Fig. 1. Social, mobile, analytics, cloud and IoTare
individual technologies and platforms which came in lime-
light in recent years and have shown their immense potential
while leveraged for augmenting productivity of various busi-
ness processes [4,9,17,23]. Enterprises treat these disruptive
components as an integrated new master IT architecture and a
new game-changer global consumer technology platform
transforming traditional business models. These technologies
will reinforce ERP interface pillars such ascustomer interface,
machine and process interface, partner and shareholder inter-
face, and the employee interface through smart mobile devices
and mobile apps, high speed communication loops (social
groups of connected people), predictive insights in data ocean,
cloud service models, and network connectivity for automatic
data sharing using embedded electronics, software, and sen-
sors in “smart connected products”as in Fig. 2,whichwill
Int J Adv Manuf Technol (2017) 88:369–380 371
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eliminate large spending on IT such as communication, col-
laboration, and private hosting of computing infrastructures.
This new architecture will transform manufacturing enterprise
with low total cost of ownership (TCO) of technologies, de-
ployment of innovative applications supporting decision mak-
ing, and roll out new business models with increased reach to
customers and deliver specific value to market.
Figure 2represents an ecosystem spurred from fusion of
emerging technologies with ERP interface pillars and resultant
“transformation drivers”which impact advanced manufactur-
ing setup in enterprises. The ecosystem will foster transforma-
tion to futuristic organization with greater ability of market
penetration and disruptive innovations. Hence, need of the
hour is to understand the strategic benefits of the ecosystem
and prioritize technologies with deeper insight. In this figure,
we plotted eight transformation drivers based on the results of
the study as specified in Table 3, i.e., critical benefit factors.
5 Research design and methodology
The primary objective of our exploratory study is to analyze
benefits of emerging technologies in enterprise ecosystem in
terms of their relative impacts on strategic objectives. This re-
search attempts to identify perceived critical benefit factors
such that if such knowledge are considered carefully, and are
made use of, it would lead a deeper insight of corporate deci-
sion makers, help in realizing the value creation to enterprise
manufacturing processes, and supplement new technology
selection decisions. This paradigm was established by rigorous
discussions with specialists and subject matter experts. A set of
25 unique benefit factors was shortlisted in the context of ad-
vanced manufacturing for higher reliability in analysis. No pre-
vious literatures were found in this area of research. Our meth-
odology includes identifying all unique benefit factors, opinion
survey using online questionnaire, response collection, and data
analysis.
5.1 Identifying benef it factors
Among several contexts of the research study, important are
domains of the industry aimed for the study, geography influenc-
ing cultural diversity of the people, and the maturity of the orga-
nization indicated by successful implementations. To identify
appropriate benefit factors, we conducted literature review and
brain-storming, a standard industry practice. Twenty-five benefit
factors are detailed in Table 1such as “easy talent acquisition and
retention,”“productive, effective connected employees,”“higher
technical maturity of employees,”“higher project centricity of
employees,”“decisive insights in data-ocean,”“enhanced em-
ployee availability,”“intellectual property (IP) protection and
knowledge management,”and so on.
5.2 Survey questionnaire design, hosting, and response
collection
The survey questionnaire was carefully framed with 25 ques-
tions, one for each benefit factor for rating their relevance in
Employee
Interface
Machine,
Process
Interface
Customer
Interface
Partner &
Shareholder
Interface
E
R
P
Analycs
Cloud
Mobile
Social
High speed Communicaon
Loop for, Adverse, Feedback
Smart devices, Apps, High
processing power
Decisive, predicve, informed
insight in data ocean
SaaS, HaaS, PaaS, IaaS cloud
service models
EMERGING
TECHNOLOGIES
FINANCIAL
DECISIVENESS
PROMOTION OF
CONSUMERISM
PRODUCT
PERSONALIZATION,
CONFIGURABILITY
MANUFACTURING
EXCELLENCE
EMPLOYEE
INNOVATIVENESS
DATA &
INFORMATION
SECURENESS
LEARNING
MATURITY, CULTURE
EMPLOYEE PROJECT
CENTRICITY
Beer insights and higher decisiveness of futurisc, transformed organisaon with greater ability
of penetraon, posive disrupon
Transformaon Drivers
Transform aon D rivers
IoT
Electronics, H/w, soware,
sensors embedded, connected
A D V A N C E D M A N U F A C T U R I N G F A C I L I T I E S
Fig. 2 Ecosystem of ERP and
emerging technologies and their
benefits
372 Int J Adv Manuf Technol (2017) 88:369–380
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view of the central idea, i.e., benefits of application of
ERP emerging technologies. These questions were segre-
gated into four subsets (response categories) addressing
all objective indicator areas such as seven questions for
“employee,”seven for “process,”six for “customer,”and
five questions for “finance.”Each of these subsets ad-
dressed emerging technology areas such as social net-
working, mobile computing, big data analytics, cloud
computing, and IoT. For example, in question subset un-
der employee, effectiveness of the talent acquisition and
retention process is measured by asking “Does social net-
working help HR practice in talent acquisition and reten-
tion in your organization?”in a five-point scale. Similarly,
employee project centricity due to adoption of smart de-
vices can be measured by asking “Can smart devices help
you pay more attention to project activities?”in a 5-point
scale. In framing the questions, few important basic
criteria were followed such as in each question, its rela-
tion to the objective of the study was clearly stated, and
ambiguities were avoided. A 5-point standard Likert scale
was used for responding each question with response
options ranging “Strongly disagree,”“Disagree,”
“Neither,”“Agree,”and “Strongly agree.”The question-
naire was reviewed and refined iteratively by experts.
Questionnaire was hosted in Google docs with caption
“Benefits of application of emerging technologies in en-
terprise resource planning.”Initially, the web link of the
questionnaire was circulated to 200 participants and
around 150 responses were collected in the first lot.
There were follow-up mails and fresh 200 circulations
out of which, around 100 responses were collected.
Overall response was 63 %. Verification of the effective-
ness of questionnaire was done through measurement of
reliability and internal consistency of the data, outlined in
Sect. 5.5. An additional measurement of survey effective-
ness has also been presented through interrater reliability.
5.3 Organizational context
The survey was conducted in multinational OEMs of
Indian origin with perspective of ERP emerging technol-
ogy adoption in advanced manufacturing enterprises. The
criteria for selection of an OEM were market share, em-
ployee strength, and turnover and OEM was expected to
rank within the top three positions as per the selection
criteria in their respective domain such as aerospace and
automobile manufacturing. Another important selection
criterion was that an OEM should have futuristic ad-
vanced manufacturing facilities to produce smart connect-
ed products. Both the companies selected for study qual-
ified in their respective domains satisfying designated
criteria. We browsed many website databases to find out
ranking of the OEMs and almost all websites were unan-
imous about the ranking of OEMs based on our specified
criteria; for example, http://top10companiesinindia.co.in/
and http://business.mapsofindia.com/. We selected two
large OEMs, one automobile making and the other
aerospace, both Indian multinational in nature with their
business units spread across the Asia-Pacific (APAC) re-
gion. These companies continue to adopt ERP and emerg-
ing and advanced manufacturing technologies from time
to time and do not have scientific statistical model to
support decisiveness for their adoption. These companies
mostly resort to TCO-net present value (NPV)-return on
investment (ROI) type of financial calculations, guess-
work, and rule of thumb in the absence of a statistical
model to strengthen manufacturing operations and im-
prove efficiencies and effectiveness of internal processes.
The targeted survey participants were employees in the
middle, senior, and top management levels spread across
all functional areas, strategic management areas, IT infra-
structure, and systems department. In all, 252 responses
were collected. The ratio of respondents from automotive
and aerospace was 60:40.
Tabl e 1 Communalities of factors
Factors Initial Extraction
Easy talent acquisition and retention 1.000 0.686
Productive, effective connected employees 1.000 0.830
Higher technical maturity of employees 1.000 0.718
Higher project centricity of employees 1.000 0.768
Decisive insights in data ocean 1.000 0.728
Enhance employee availability 1.000 0.582
IP protection and knowledge management 1.000 0.860
Sensing the pulse of stakeholders 1.000 0.788
Low security threat to vital business data 1.000 0.748
More scope of innovative thinking 1.000 0.781
Business processes refinement and dashboard 1.000 0.600
Faster NPI and improved product quality 1.000 0.719
Supply chain alignment, low inventory 1.000 0.636
Reliable, scalable, agile computing 1.000 0.662
Capturing individual user experiences 1.000 0.742
Scalable way to co-create, collaborate 1.000 0.754
Brand loyalty of customers and dealers 1.000 0.779
Promotion of consumerism through IoT 1.000 0.716
Easier life-cycle support and disposal 1.000 0.602
Voice of customers and pulse of market 1.000 0.564
Long term value of investing in ETs 1.000 0.767
Impact on organizational value chain 1.000 0.769
Strategic financial decision making ability 1.000 0.749
Low carbon footprint due to cloud ERP 1.000 0.690
Resource management in global operations 1.000 0.622
Extraction method: principal component analysis
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5.4 Data analysis and results
Our exploratory research worked on identified 25 significant
factors in support of objective of study. Using analysis pack-
age IBM SPSS Statistics V23, we found that the correlation
among these 25 factors were quite high, and Barlett’stestof
sphericity was found to be significant (p<0.05). We further
conducted Shapiro-Wilk test to check absence of unwanted
normal distribution of data to authenticate it for factor analy-
sis. Since our motto was to conduct EFA, we used PCA factor
extraction method on different measures and validated various
dimensions of the problem in hand.
Basic objective of application of FA on exploratory variables
is to extract minimum number of factors that account for max-
imum variance in data [7,15]. Table 1exhibits communality
measures of the exploratory variables adopting PCA extraction
technique and “varimax”rotation method. In PCA dimension
reduction, we use the Kaiser-Mayer-Olkin (KMO) index for
measure of sampling adequacy and Barlett’s test of sphericity
to check redundancy between the variables and whether we can
summarize the information by initial variables in a few number
of factors. Factors whose eigenvalues are greater than 1 consti-
tute 71.44 % cumulative variance confirmed by the “total var-
iance explained”table (not shown) in SPSS indicating appre-
ciable factor analysis has been conducted with 25 items as per
KMO criteria resulting into extraction of 8 components.
PCA is a widely used first phase of EFA for factor extraction
in which factor weights are computed in order to extract the
maximum possible variance, with successive factoring continu-
ing until there is no further meaningful variance left. The factor
model must then be rotated for analysis. Rotation serves to
make the output more understandable by allowing the factors
to correlate, since a pattern of loadings where items load most
strongly on one factor and much more weakly on the other
factors. Varimax rotation is the most common rotation option,
which is an orthogonal rotation of the factor axes to maximize
the variance of the squared loadings of a factor (column) on all
the variables (rows) in a factor matrix (such as rotated compo-
nent matrix in SPSS), which has the effect of differentiating the
original variables by the extracted factor. Each factor will tend
to have either large or small loadings of any particular variable.
A varimax solution yields results which make it easy to identify
each variable with a single factor. Table 2represents rotated
component matrix, which summarizes the results of factors
identified by varimax orthogonal rotation.
The idea of applying varimax orthogonal rotation is to
achieve uncorrelated factors in the form of rotated component
matrix in which the variables having higher factor loading
values (in Table 2) are considered as most important and rel-
evant [7,15], i.e., identification of most influential and rele-
vant factors contributing to the objective. The most influential
factors identified based on entries in Table 2are (sequentially,
with priority): higher project centricity of employees
(5), IP protection and knowledge management (1), low secu-
rity threat to vital business data (6), more scope of innovative
thinking (8), faster new product introduction (NPI) and im-
proved product quality (3), capturing individual user experi-
ences (2), promotion of consumerism through IoT (7), and
strategic and financial decision making ability (4).
5.5 Validity of data and computing
In SPSS, reliability analysis and internal consistency of input
data are conducted in categorical principal component analy-
sis (CATPCA) dimension reduction technique of factor anal-
ysis, which was found good (0.7 ≤α≤0.9) by computing
Cronbach’s alpha using menu options and subjecting all 25
questions, i.e., factor equivalents for the test. Our Cronbach’s
alpha consistency value was computed as 0.744, which is
within acceptable range [7]. KMO measure of sampling ade-
quacy is 0.610 (>0.50) which indicates that data is useful for
factor analysis. Bartlett’
s test of sphericity tests the hypothesis
that the correlation matrix is an identity matrix, which would
indicate that the variables are unrelated and therefore unsuit-
able for structure detection. Small values (less than 0.05) of
the significance level indicate that a factor analysis may be
useful with data. In our case, the value is well below this limit
indicating factor analysis is useful. The Shapiro-Wilk’s statis-
tic is calculated for no weights or integer weight scenario, to
detect whether the variables are normally distributed using
normality plots of individual variables when the weighted
sample size lies between 3 and 5000. None of our variables
was found normally distributed from the Shapiro-Wilk’snor-
mality plots. Interrater reliability is the degree of agreement,
concordance, or consistency between raters, i.e., survey par-
ticipants. It gives a score of homogeneity, or consensus in the
ratings given by survey participants. If various raters (survey
participants) do not agree, either the scale is defective or the
raters need to be retrained. For measuring interrater reliability,
we adopted ANOVA Interclass correlation coefficient in SPSS
for 95 % confidence interval, for lower and upper bounds at
0.695 and 0.789, respectively, for the 25 item-variables and
252 respondents with smaller diversity (automotive, aero-
space), validated both adequate awareness level of respon-
dents and the accepted interrater reliability of data for analysis.
6 Summary of results
According to our analysis of factor loading, the most influenc-
ing strategic benefit factors are listed with computed priority
in Table 3for the engagement of emerging technologies in
ERP. The table displays the corresponding objective indicator
of each benefit factor, their corresponding enabler technolo-
gies and transformation drivers. The Scree plot presents eigen-
value plot for 25 component factors in Fig. 3.
374 Int J Adv Manuf Technol (2017) 88:369–380
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Tabl e 2 SPSS result of rotated component matrix
Factors Component
12345678
Easy talent acquisition and retention 0.111 0.382 −0.113 0.599 0.263 −0.247 −0.152
Productive, effective Connected employees 0.210 0.792 0.173 0.117 −0.321
Higher technical maturity of employees 0.578 0.188 −0.118 0.140 0.500 −0.160 −0.187
Higher project centricity of employees 0.831 0.121 0.244
Decisive insights in data ocean −0.220 −0.118 0.158 0.783 −0.149
Enhance employee availability 0.274 0.691 0.100
IP protection and knowledge management 0.169 0.127 −0.122 0.882
Sensing the pulse of stakeholders 0.536 0.416 −0.470 0.310
Low security threat to vital business data −0.189 −0.222 0.800 0.102
More scope of innovative thinking 0.126 0.775 0.380
Business processes refinement, dashboard −0.373 0.256 0.532 0.272 −0.132 0.148
Faster NPI and improved product quality 0.150 0.832
Supply chain alignment, low inventory 0.130 0.125 0.528 −0.189 0.271 0.394 0.244
Reliable, scalable, agile, computing 0.542 0.516 0.140 0.260
Capturing individual user experiences 0.841 0.115 0.129
Scalable way to co-create, collaborate −0.170 −0.102 0.277 0.785 0.105
Brand loyalty of customers, dealers 0.466 0.602 0.152 −0.267 −0.162 0.273
Promotion of consumerism IoT based 0.793 −0.269
Easier lifecycle support and disposal 0.684 0.257 0.135 −0.201
Voice of customers and pulse of market −0.146 −0.192 0.489 −0.236 0.411 0.178
Long term value of investing in ETs 0.541 0.476 −0.155 0.374 −0.203 −0.183
Impact on organizational value chain 0.430 0.283 0.538 −0.462
Strategic financial decision making ability −0.164 0.831 −0.146
Low carbon footprint due to cloud ERP −0.198 0.311 −0.137 0.703 0.185
Resource management of global operations 0.120 0.759 0.103 −0.115
Extraction method: principal component analysis; rotation method: varimax with Kaiser Normalization; rotation converged in 10 iterations
Tabl e 3 Critical benefit factors
Benefit factor/strategic gain Rank/influence Objective indicator Emerging Technology/
platform enabler
Transformation driver in ecosystem
Higher project centricity of employees 5 Employee Mobility, cloud hosting Employee project centricity
IP protection and knowledge management 1 Employee Cloud hosting Learning maturity and learning culture
Low security threat to
vital business data
6 Process Cloud hosting Data secureness
More scope of innovative thinking 8 Process Mobility, cloud
hosting, IoT
Innovativeness of employee
Faster NPI and improved
product quality
3 Process Big data analytics Manufacturing excellence through quality
and process innovation
Capturing individual user experiences 2 Customer Virtual social N/w,
mobile apps, IoT
Product personalization and
configurability, collaboration,
co-creation, smart connected products
Promotion of consumerism
through IoT
7 Customer Virtual social N/w,
mobile apps
Promotion of consumerism
Strategic financial
decision making ability
4 Finance Big data analytics Financial decisiveness for
low TCO and high ROI
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Eight key benefit factors emanating from the analysis ad-
dresses all four objective indicators. The prioritized benefits
belonging to specific objective indicator are as follows:
&Two factors belonging to “employee”with overall highest
priority (1) attributed to “IP protection and knowledge
management,”with transformation driver “learning
maturity.”
&Two factors belonging to objective indicator “customer”
with highest priority (2) attributed to “capturing individual
user experiences”; transformation driver is “product per-
sonalization and configurability.”
&Three factors belonging to objective indicator “process”
with highest priority (3) attributed to “faster NPI and im-
proved product quality”; transformation driver is
“manufacturing excellence.”
&One factor in objective indicator “finance”with priority
(4) attributed to “strategic financial decision making abil-
ity”;transformationdriveris“financial decisiveness.”
Strategic objective indicators, in order of relevance to the
objective of study are (1) employee, (2) customer, (3) process,
and (4) finance. Employees will be benefitted in terms of IP
protection, IP management, and knowledge management and
being highly project centric leading to creating long-term val-
ue and competitive advantages of the enterprise, which is
learning maturity. The most important drivers for transforming
the organization were found out to be (1) learning maturity, (2)
product personalization and configurability, (3) manufactur-
ing excellence, and (4) financial decisiveness. All emerging
technologies are indispensable such as mobility and cloud
hosting, virtual social networking and mobile applications
and IoT, and big data analytics.
The survey study and analysis of results will help
advanced manufacturing and OEM enterprises in myriad
ways. Investment for imbibing new technology in the
organization can be supplemented by perceived deci-
siveness and statistically guaranteed alignment with the
strategic objectives. Corporations can have deeper in-
sight into the relevance of the benefit factors besides
NPV, ROI, and TCO calculations leading to sustainable
and profitable decisions. With the insight of benefits,
decision makers can focus on fewer emerging technolo-
gies leading to maximum competitive advantage gain
for the company and long-term value creation for the
customer. The approach focuses more on technology
relevance rather than on mere technology adoption and
aligns with the mission, vision, and values and strategic
planning of the enterprises.
The results are supported and validated by the global trends
of large OEMs increasingly considering IP protection as man-
date rather than as choice in terms of patents and copyright
filing, publication of innovative works in scholarly interna-
tional journals, reaching out more and more to individual cus-
tomers and valuing individual feedbacks resulting in co-crea-
tion, enhancing personalization, configurability, and
customizability of the product, i.e., creating personalized
products and solutions, inculcating habit of faster high-
quality new product introduction, and so on. All these are
direct evidences of validity of the research findings.
Extracon Method: Principal Component Analysis
Fig. 3 Scree plot from SPSS
376 Int J Adv Manuf Technol (2017) 88:369–380
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6.1 Comparing results with other research f indings
We have compared our findings with the results presented by
contemporary researchers. While most researchers presented
benefits of ERP and emerging technologies, some of them
listed risk factors also since, Gartner, the world’sleadingIT
research firm, has estimated that 55 to 75 % of all ERP pro-
jects fail to meet their objectives [4]. While listing the benefit
factors, it is essential that objective indicators from the orga-
nizational perspective [11–13] and the strategic alignment of
IT for organizational transformation [8] be emphasized. While
very few researchers distinctly consider BSCs [6] for ERP
implementation, others overlook the relevance of BSCs and
strategic objectives such as employee, process, customer, and
finance. But interestingly, the stated benefits address these
four indicators automatically in almost all cases. To compare
the results, we rationalize and segregate the benefits presented
in various literature explicitly advocating benefits of ERP and
emerging technologies based on their relevance with four stra-
tegic objective indicators and presented them in Table 4.
The comparison demonstrates good correlation between
our findings and the findings reported by other researchers.
The critical benefit factors are italicised in Table 4and it has
been investigated whether other research outcomes are corrob-
orating them. It has been found that at least four key benefits
have been confirmed by Hurbean et al [9], O’Leary [18], and
Ularu et al. [23]. All other listed authors in Table 4mentioned
at least two common benefits [4,14,22,24–26]. While the
same benefits have been mentioned in different forms in dif-
ferent literature, all of them advocate benefits of ERP and
emerging technologies.
7 Implementation of research f indings
in manufacturing
ERP emerging technologies and analysis of their strategic
benefits touch virtually every aspect of the strategy pillars in
a manufacturing enterprise irrespective of the type of industry.
The research findings can be used mainly in three distinct
ways: first, building early decisiveness for new advanced
manufacturing technology adoption through confirmatory
analysis; second, preempt manufacturing strategies to stay
ahead in competition, i.e., applying a panoramic view to fur-
ther the limit beyond technical benchmark; and third, foster
seamless integration between business and engineering and
also within advanced technologies for organizational benefit
and competitive advantage.
7.1 Acquire decisiveness for technology adoption
Acquisition and adoption of new advanced technologies re-
quires assessment in a holistic perspective for achieving better
competitive advantages beyond mere benchmark exercises
particularly in an era of smart factories and smart connected
products. For example, while selecting a metal cutting ma-
chine, instead of only assessing its productivity, some more
factors such as its ability to network with other product sys-
tems and management systems [20], smart features, data se-
curity, lower operator engagement time for allowing innova-
tive thinking, scope of artificial intelligence (AI), etc. should
also be considered. To achieve such decisiveness, we propose
multivariate analysis with variables such as employee project
centricity, learning maturity, data and information secureness,
manufacturing excellence, employee innovativeness, product
personalization and configurability, and consumerism and fi-
nancial decisiveness using structural equation modeling in a
confirmatory analysis approach. Final decisiveness will be the
resultant effect of all such variables in an appropriate structur-
al relationship model.
7.2 Preempt manufacturing strategies
Obsolescence, upgrade, or outsource decisions are part of a
manufacturing strategy which necessitates evaluation of align-
ment of existing manufacturing setup with corporate strate-
gies. With the help of both exploratory and confirmatory ap-
proach, it is possible to develop decisiveness to preempt
“make-or-buy,”phasing out or upgrade a technology to stay
ahead in competition.
7.3 Foster seamless integration
Information technology is revolutionizing the products and
production facilities which mandate seamless integrations in
the context of manufacturing smart connected products [20]
and promoting futuristic manufacturing concepts [1]. Besides
mechanical and electrical parts, these products also combine
hardware, sensors, data storage, microprocessors, software,
and connectivity in myriad ways to become complex systems.
Such products are made possible by improvements in process-
ing power, device miniaturization, and availability of ubiqui-
tous network connectivity to promote new functionality, great-
er reliability, higher product utilization, and capabilities [20].
Our research will pave the way for manufacturers to seamless-
ly integrate manufacturing facilities with ERP emerging tech-
nologies to foster design, development, and manufacture of
smart connected products.
8 Limitations and further scope of work
We identified the following limitations of our work, each of
which warrants a future scope of work:
Int J Adv Manuf Technol (2017) 88:369–380 377
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Tab l e 4 Strategic benefits advocated by various authors
Author ERP emerging technology area Strategic objective indicators
Employee Process Customer Finance
Engebrethson [4] Cloud computing,
SaaS, multi-tenancy
Data reliability, redundancy
avoidance, cloud benefits—
accessibility, mobility, usability
Multi-tenancy
benefits—scalability,
upgradability, low
implementation time
Global outreach Multi-tenancy benefits—
business cost reduction
Hurbean et al.
(Yankee group data)
[9]
Mobile, social, cloud,
enterprise app platform
Mobile devices to employees,
worker collaboration,
life work balance
Better operational efficiency
by B-process transformation,
Worker productivity
Customer collaboration,
Responsiveness
–
Khajeh-Hosseini, [14] Cloud migration—
enterprise IT to IaaS
Less tedious work, improve
work satisfaction, skill
development, growth
–Offer new products,
services, improved status
Manage income and outgoing
O’Leary [18] ERP technologies in general Information/visibility,
redundancy avoid, less
training, transfer, analysis,
decisiveness, growth
Low inventory, maintenance,
improve process, speed,
productivity, integration,
standardization, flexibility
On-time delivery, sales
automation, customer
responsiveness, globalization
Low fin close cycle, transport/
logistics, IT cost, better cash
mgmt, B-performance,
revenue/profit, fin control,
acquisition
Themistocleous et al. [22] EAI, ERP and supply chain Manageable, maintainable
system, more understanding
and control of B-processes
Reduce data, application
redundancy, B-cycle shortened,
enhance data reliability
–Reduce operational cost,
employees population
Ularu et al. [23] Machine learning for
ERP configure
Flexibility with mobile app,
faster employee connectivity
Automated ERP configuration,
data portability
Faster connectivity
to customer
Cost-effective connectivity to
employee, customer
Wei, Chun-chin [24] Using implement objectives
for ERP perf. Eval.
–Customized, tailored,
reengineered B-processes,
performance enhancement
Responsiveness Quality-cost flexibility,
turnover, ROI
Wei, Zhe et al. [25] Using BFRC integrate
ERP-PDM
–Integrating heterogeneous
data systems, stability,
reliability, reusability,
security, privacy
––
Zeng, Yun et al. [26]ERPanddata
warehousing integration
Support organizational
information need
Support organizational
information need
Responsiveness, closeness,
faster value-added
product, services
–
Ranjan, Jha, Pal
(Our work)
Social, mobile,
analytics, cloud, IoT
Productive, effective, connected,
aware, Innovative employees,
higher project centricity,
Decisive insights
Easy talent acquisition,
retention, IP protection,
KM, data security, reliable,
scalable, agile processes,
Faster NPI, better
product quality
Individual user experience,
co-create, collaborate,
brand loyalty, customer’s
voice, consumerism
Long term value of
investment, Strategic and
financial decision making,
low carbon footprint,
global operations
378 Int J Adv Manuf Technol (2017) 88:369–380
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a. Proposed exploratory analysis of strategic benefits of ERP
technologies deals with building decisive and predictive in-
sights of decision makers based on opinion survey of experts
and statistical analysis of survey data. The model, however,
cannot serve as an expert system since it is not empirically
supported by large number of project data from applications in
industries.
b. Our opinion survey participants are distributed in the APAC
region. Survey in other important geographies such as Europe,
USA, and South America has not been considered. Opinion
data collection from across all geographies could be a relevant
task and geography-based results can be compared to under-
stand variation in perceived decisiveness about imbibing
emerging technologies across geographies due to geospatial
behavioral diversities of people.
c. TCO and NPV calculation of emerging technologies could
be an intriguing area of research dealing with both tangible
and intangible benefits and values and so is ROI. These cal-
culations will help corporate decision makers in budget pro-
visioning for imbibing emerging technologies besides explor-
atory analysis of benefits. These two approaches can be
integrated.
d. We anticipate a strong possibility of confirmatory analysis
based on hypothesized causal covariant structures as a part of
multivariate data analysis and thereby finding interrelation-
ships between the factor variables. For example, “IP protec-
tion and knowledge management”(learning maturity) could
be an antecedent and cause for “more scope of innovative
thinking”(innovativeness). Similarly, “higher project centric-
ity of employees”could be antecedent for “faster NPI and
improved product quality”(manufacturing excellence). Such
confirmatory analysis could be of immense help to corporate
policy makers and senior leadership for strategic alignment
with the help of statistically supported perceived decisiveness
to achieve business objectives.
e. SMEs could be benefitted besides OEMs. For this, explor-
atory analysis should be extended to technologies having in-
direct impacts on strategic objectives and benefits; for exam-
ple, open-source ERP [10], sustainable ERP [3], and EAI [22].
Survey and analyses of these technologies could be relevant
for small and medium manufacturing industry sectors.
9 Conclusion
The purpose of the study was to conduct an exploratory anal-
ysis on strategic benefits of application of ERP-based emerg-
ing technologies in large manufacturing enterprises and
OEMs for strategic alignment and develop insight for better
decisiveness. An ecosystem model of social computing, mo-
bility, analytics, cloud computing, IoT, and ERP was con-
ceived with few resultant drivers to transform the organization
for better ability to meet strategic objectives and create higher
competitive advantages. We conducted opinion survey on
benefit factors in four strategic objective indicator areas, i.e.,
employee, process, customer, and finance and analyzed the
data in IBM SPSS adopting the PCA approach to find out
the most significant benefits. We found “IP protection and
knowledge management”of highest priority followed by
“capturing individual user experience,”“faster NPI and im-
proved product quality,”and “strategic financial decision
making ability.”These four top benefits hailed from all objec-
tive indicator domains. The addressing emerging technologies
were also identified and prioritized.
In today’s dynamic and changing environment, manufactur-
ing companies have strong need to create and sustain compet-
itive advantages. This is possible by embracing right emerging
technologies rapidly in which, our research will play an advisor
role. By understanding the potential of individual technologies
to contribute to strategic objectives, it will be easier for indus-
tries to make important investment and obsolescence decisions.
For academia, our research will open new research avenues. We
listed limitations in our work, each of which can potentially
further the research. The work detailed in this paper is explor-
atory, analytical, and versatile and it aligns with the technology
trends in vogue in global advanced manufacturing and OEM
enterprises and promises a deeper sustenance of corporate de-
cisions culminating in higher ROI, competitive advantage gain
for the enterprise, and higher value creation for the customer to
stay ahead in competition.
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