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Impact of Digital Transformation Strategies on Performance of Manufacturing Companies in India
February, 17th 2021

Impact of Digital Transformation
Strategies on Performance of

Manufacturing Companies in India

Research Committee

The Institute of Chartered Accountants of India

(Set up by an Act of Parliament)
New Delhi
© THE INSTITUTE OF CHARTERED ACCOUNTANTS OF INDIA

All rights reserved. No part of this publication may be reproduced, stored in a
retrieval system, or transmitted, in any form, or by any means, electronic,
mechanical, photocopying, recording, or otherwise without prior permission, in
writing, from the publisher.

Basic draft of this publication was prepared by CA. (Dr.) Nisha Kohli

Disclaimer:
The views and opinions expressed in this document are those of the author
and based on his experience and not necessarily those of the Institute or
any other regulatory body. Examples of analysis performed, methodologies
and approaches described within document are only examples which have
been truncated with a lot of specifics omitted for brevity of these articles.
They should and must not be utilized ‘as-is’ in the real-world without having
sufficient guidance or experience or otherwise consulting a professional.

Edition : February, 2021

Committee/Department : Research Committee

E-mail : research@icai.in

Website : www.icai.org

Price : ` 140/-

ISBN : 978-93-90668-16-8

Published by : The Publication Department on behalf of
the Institute of Chartered Accountants of
Typeset by : India, ICAI Bhawan, Post Box No. 7100,
Indraprastha Marg, New Delhi - 110 002.
Printed by :
Elite-Art, New Delhi

Sahitya Bhawan Publications, Hospital
Road, Agra - 282 003.
February/2021/500 copies
Foreword

The incorporating of digitalisation in the production process has become
imperative with the advent of the 4th Industrial Revolution. The manufacturing
industry worldwide has gradually started adopting advanced manufacturing
technologies. Therefore, it is crucial for the manufacturing companies in India
as well to pace up with technology adoption and meet the competition by
exploring technologies such as Artificial Intelligence (AI), Cloud computing,
Internet of Things (IoT), and Robotics.

This research study utilises Technology - Organisation - Environment
(TOE) Framework to assess the level of technological readiness for adopting
digital transformational change adopted by manufacturing concerns in India. It
also explores the link between digital transformation and financial performance
of manufacturing firms and utilises Theory of Transformation and Theory of
Organizational Readiness for Change.

I am pleased to note that the Research Committee of the Institute under the
‘ICAI Research Project Scheme 2020’ undertook the Research Project on the
topic of “Impact of Digital Transformation Strategies on Financial
Performance in the Indian Manufacturing Sector”.

I would like to take this opportunity to express my thanks to CA. Anuj Goyal,
Chairman, Research Committee and CA. Kemisha Soni, Vice-Chairperson,
Research Committee, who took the initiative to introduce ‘ICAI Research
Project Scheme 2020’ to encourage research-based activities. I would also like
to take this opportunity to express my gratitude to members of the Research
Committee who have made invaluable contribution through their expert
guidance in the finalisation of the Research Report.

I am confident that this Research Report will be extremely useful for the
members, Indian Manufacturing Industry and other stakeholders as well.

New Delhi CA. Atul Kumar Gupta
January 29, 2021 President, ICAI
Preface

The findings of the Research Report on “Impact of Digital Transformation
Strategies on Financial Performance in the Indian Manufacturing Sector”
have an important implication for manufacturing firms in India, policymakers,
regulators, financiers and other key stakeholders in the market. The findings
of this research will form an important input into creating an effective
environment and motivation for implementing digital transformation and
Industry 4.0 strategies in India, thereby resulting in an increase in overall
profitability and better firm value, positively impacting the country’s
manufacturing sector and the overall economy.

I am thankful to CA. Atul Kumar Gupta, President, ICAI and CA. Nihar
N. Jambusaria, Vice President, ICAI who inspired me and Research
Committee to introduce ‘ICAI Research Project Scheme’ and undertake
research projects on contemporary and relevant topics.

I would also like to extend my thanks to CA. Kemisha Soni, Vice-Chairperson,
Research Committee and all the members of the Research Committee.

Further, I would like to take this opportunity to congratulate CA. (Dr.) Nisha
Kohli for writing Research Report on the topic of “Impact of Digital
Transformation Strategies on Financial Performance in the Indian
Manufacturing Sector” and to express my thanks to CA. Saurabh Goenka,
Expert for providing his valuable comments and suggestions for improvement
of technical and presentation aspect of the Research Report. I also
acknowledge the assistance and co-operation rendered by Dr. Amit Kumar
Agrawal, Secretary, Research Committee and CA Rahul Paul, Project
Associate who gave their valuable inputs during finalisation of this Research
Report.

I believe and trust that this Research Report will be immensely useful to the
members and to others interested.

New Delhi CA. Anuj Goyal
January 29, 2021 Chairman, Research Committee
Table of Content

EXECUTIVE SUMMARY.......................................................................... 1
TARGET STAKEHOLDERS..................................................................... 6
CHAPTER 1: THE INDIAN MANUFACTURING SECTOR AND DIGITAL

TRANSFORMATION ....................................................... 9
CHAPTER 2: DIGITAL TRANSFORMATION AND INDUSTRY 4.0 IN

MANUFACTURING ....................................................... 17
KEY TECHNOLOGIES ASSOCIATED WITH INDUSTRY 4.0 AND THEIR REAL
WORLD APPLICATIONS ....................................................................... 19
KEY PERFORMANCE DRIVERS OF INDUSTRY 4.0 AND DIGITAL
MANUFACTURING ..................................................................................
CHAPTER 3: DIGITAL TRANSFORMATION ECOSYSTEM IN INDIA .... 30
CHAPTER 4: STRATEGY FRAMEWORK FOR DIGITAL

TRANSFORMATION ........................................................ 35
PROCESS FOR DEVELOPMENT OF DIGITAL STRATEGIES ........................ 41
DIGITAL TECHNOLOGY ADOPTION AND FIRM PERFORMANCE ................. 43
IMPACT OF INFORMATION TECHNOLOGY INVESTMENTS – FINANCIAL
VARIABLES....................................................................................... 46
CHAPTER 5: METHODOLOGY AND RESEARCH FINDINGS ................... 48
SECTION 1: STAKEHOLDER PANEL DISCUSSIONS ................................. 48
Discussions and Conclusions .......................................................... 55
SECTION 2: FINDINGS FROM PRIMARY SURVEY ..................................... 56
Research findings ........................................................................... 59
Discussions and Conclusions .......................................................... 68
SECTION 3: FINDINGS FROM SECONDARY DATA ANALYSIS ..................... 70
Regression Analysis........................................................................ 81
Findings and Conclusions ............................................................... 82
CHAPTER 6 : DIGITAL TRANSFORMATION AND IMPLEMENTATION
CASE STUDIES ............................................................... 84

DIGITAL TRANSFORMATION IMPLEMENTATION AT HERO MOTORS ........... 85
DIGITAL TRANSFORMATION IMPLEMENTATION AT TATA MOTORS ............ 91
CHAPTER 7: CONCLUSIONS AND RECOMMENDATIONS .................. 98
RESEARCH LIMITATIONS..................................................................... 101
BIBLIOGRAPHY .................................................................................... 102
APPENDIX ...................................................................................... 107
Executive Summary

Technology has permeated in our lives leading to a paradigm shift in ways of
doing business. The process of incorporating digitalisation in the production
process has become imperative with the advent of the 4th Industrial Revolution.
The manufacturing industry worldwide, primarily comprising non-tech firms,
has gradually started adopting advanced manufacturing technologies and
relying on intelligent machines generating intelligent data. It is crucial for
manufacturing companies in India as well to pace up with technology adoption
and meet the competition. Fortunately, the Indian manufacturing value chain
is gradually transforming itself as reflected by some large corporates who are
already exploring technologies such as Artificial Intelligence (AI), Cloud
computing, Internet of Things (IoT), Robotics, and so on. Embedding
traditional manufacturing with digital systems and transitioning to newer
technologies has become inevitable for MSMEs as well. The focus of this study
is on all sizes of manufacturing firms- large, mid, small and micro-cap in India.

Prior literature has emphasised that digital initiatives create high value for
many firms indeed, yet some others destroy this value in the execution process
due to lack of digital understanding and inability to cope with the disruptive
economic realities of digital competition (Westermann et al., 2011). Firms often
invest in digital transformation technologies without the relevant knowledge at
both the technology and strategic levels. This study utilises Technology -
Organisation and Environment (TOE) Framework to assess the level of digital
ecosystem/external environment, impact of strategic focus, organisational
readiness and technological readiness for adopting digital transformational
change by manufacturing firms in India. Other theories utilised in this research
are Theory of Transformation and Theory of Organizational Readiness for
Change. The study also explores the link between digital transformation and
financial performance of manufacturing firms.

We used both primary and secondary research methods for this study. Our
research team,

(a) Undertook a literature review of the theories mentioned above and
identified key parameters for the survey questionnaire;

(b) Employed interpretive research methods for conducting expert panel
and individual interviews and incorporated the insights gathered into the
survey questionnaire;
Impact of Digital Transformation Strategies on Performance of Manufacturing …

(c) Conducted a comprehensive survey of 90 leaders and managers from
the manufacturing sector in India through telephone, face to face
meetings, and online survey (survey monkey), followed by subsequent
data analysis;

(d) Conducted an in-depth case analysis of two manufacturing companies
in the automotive sector - analysed digitalisation strategies at Hero
MotoCorp and Tata Motors and evaluated their achievements in
financial as well as non-financial terms; and

(e) Analysed the annual reports, press releases and media reports of 100
manufacturing companies - 25 companies from each sector (large, mid,
small, and micro firms) - using stratified sampling to assess the impact
of Digital Activities on their financial performance. The team conducted
textual frequency analytics and used that frequency as a proxy for digital
activities. The proxy was correlated and regressed with parameters of
financial performance to study the impact of digitalisation on firm
performance.

Key findings of the research from stakeholder and panel discussions, primary
survey and secondary data analysis are:

Findings at the eco-system level:

• India has several eco-system characteristics required for digital
transformation and adopting Industry 4.0 in terms of Information and
Communication Technology (ICT) infrastructure, trainable human
capital, competitive pressure, collaboration and knowledge sharing
within the industry, a perceived ability of suppliers to adapt to changes
resulting from adoption of Industry 4.0 technologies and consumer
demand. However, this is not translating to digital transformation on
ground.

• India is far behind countries around the world in terms of digital
transformation and adoption of Industry 4.0 in the manufacturing sector,
especially amongst MSMEs. Industry 4.0 adopted by large
organizations such as Tata Motors and Hero Motor Corp can at best be
considered as only one of cases of digital transformation in the country.

• Key bottlenecks are:

2
Executive Summary

─ There is a significant lack of awareness, understanding and
technical knowhow about Industry 4.0 technologies, their
advantages and application to manufacturing in India. Simple
digitisation such as facial recognition in attendance are
considered to be great advancements in technology adoption.
Although more acute in MSMEs, the knowledge gap is widely
prevalent in large manufacturing sector organizations as well.

─ While the government has launched a number of initiatives to
create a conducive eco-system for adoption of Industry 4.0 in the
country, the effort has been fairly recent with limited results on
ground so far. This is particularly an issue for the MSME sector
that needs significant handholding and financial support from the
government to undertake digital transformation.

─ The country has a weak cybersecurity infrastructure, considered
inadequate and risky for extensive digital transformation.

Findings at the firm level:

• Manufacturing firms in India demonstrate organizational readiness for
digital transformation in terms of leadership, commitment and resources
and communication across the organisation (based on perception
survey of manufacturing sector executives).

(Note: This is likely to be an overestimation based on executives’
assessment of basic digitization initiatives implemented in the
organization, misunderstood as significant technological
advancements.)

• However, the perceived organizational readiness is not translating into
digital transformation and adoption of Industry 4.0 on the ground level
due to the following key bottlenecks:

─ There is limited awareness and understanding about Industry 4.0
at the senior level, directly impacting ability of manufacturing
sector firms in India to value the benefits and invest in digital
transformation. Further, firms are unknowingly setting much lower
goals and aspirations in terms of digital transformation due to
limited knowledge.

3
Impact of Digital Transformation Strategies on Performance of Manufacturing …

─ Lack of multi-level readiness – i.e. different levels of awareness
and understanding about digital transformation at the lower,
middle and senior management level - is impeding success of
digital transformation at the strategy as well as implementation
phase.

─ There is piecemeal adoption of digital transformation in
manufacturing organizations in India, thereby limiting cross-
functional synergies and subsequently value creation.

─ There is a significant skill gap in the manufacturing sector
workforce impeding digital transformation.

─ Prevalence of legacy infrastructure, for instance having old
machinery that cannot be digitally connected, is a key bottleneck
for adopting Industry 4.0. in India as it leads to multiplication in
costs and effort for the firm

• Theoretical findings (based on the primary survey):

─ There is a strong positive correlation between organisational
context-leadership and change management 0.89 and
Governance 0.73 with technology context.

─ There is a strong positive correlation (0.71) between
environmental context with technological context. This implies
that favourable ecosystem and external environment with strong
leadership commitment, governance and overall positive change
management climate can lead an organisation to be ready for
adoption of digital manufacturing technologies.

• Digital transformation and financial performance (based on secondary
data analysis on 100 Indian manufacturing firms – large, mid, small and
micro capitalization):

─ Profile of firms that adopt digital activity are relatively larger, more
profitable and have better sales revenues. We report positive,
though not so statistically significant, associations between digital
activity and total revenues, which is consistent with prior studies
that attributed the results to the performance pressure channel.
Studies have shown that when market pressures force the firms
to go digital, digitalisation does not necessarily result in improved
sales. This is because in case of high market competition it is
very difficult for the firms to increase their market shares through

4
Executive Summary

digital activities as price is the main consideration. This is also
consistent with our panel interview results and surveys conducted
that firms which adopt digitalisation due to competitive pressures
and on piecemeal basis without giving due regard to customer
value proposition or understanding the ripple effects on different
areas of the value chain may find it difficult to generate more
sales due to digitalisation.

─ Firms which have higher market capitalisation are more likely to
adopt digitalisation. This suggests that firms show early signs of
going digital when they receive higher valuations in the market.
According to value creation theories, firms command better
valuations in the market if they provide value proposition to
customers and provide better quality products for their
customers. Therefore, considering this theoretical concept we
can presume that firms will command higher valuations indirectly
if they focus their digitalisation strategies on value proposition
and serve their customers well by using technologies. For
manufacturing firms this is possible through digitalising the
products, innovating and re-designing the product with tech
capabilities and solutions for the customers.

─ Digitalisation can be associated with profitability only in the long
run due to challenges of integration between various
complementary technologies both inside and outside the firm.
Further, besides digital investments in new technologies,
providing resources for operationalising the same also prove to
be costly in the short term.

─ Short term positive impacts can be seen in non-financial KPIs
such as improvements in productivity, efficiency, and reduction in
run time, defects and so on.

Our findings have important implications for manufacturing firms in
India, policymakers, regulators, financiers and other key stakeholders
in the market. The findings of this research will form an important input
into creating an effective environment and motivation for implementing
digital transformation and Industry 4.0 strategies in India, thereby
resulting in an increase in overall profitability and better firm value,
positively impacting the country’s manufacturing sector and the overall
economy.

5
Target Stakeholders

The findings of this study will be extremely useful for the Government, the
manufacturing industry and researchers and academia (see Table 1 below).

Table 1: Target stakeholders

Target Potential use
stakeholders
Government Gain insights on:
• Issues in the manufacturing growth story in India
Industry
despite several government initiatives.
• Overall level of adoption of digitization and Industry

4.0 in India, and also in comparison to worldwide
adoption.
• Importance of Industry 4.0 for India to remain
relevant in the global manufacturing scenario and
increase contribution of manufacturing to India’s
Gross Domestic Product (GDP) and exports.
• Drivers of Industry 4.0 and digital manufacturing.
• Bottlenecks and shortcomings in adopting Industry
4.0 and challenges in the current eco-system.
• Gap areas in government policy support.
Potential application:
• Strengthen government policy support based on
gap areas identified.
• Plan the incorporation of Industry 4.0 technologies
on enterprises and institutions run by the
Government.

Gain insights on:
• Issues in the manufacturing growth story in India.
• Meaning of Industry 4.0, the various technologies

and their application in manufacturing.
• Drivers of Industry 4.0 and digital manufacturing.
Target Stakeholders

Researchers • Overall level of adoption of digitization and Industry
and academia 4.0 in India, and also in comparison to worldwide
adoption.

• Benefits of digital transformation in manufacturing
in terms of the manufacturing process, overall
competitiveness especially in the international
market and the firm’s financial performance.

• Performance of firms in terms of governance,
motivation, multi-level readiness, quality of
infrastructure and leadership, and time and
resource commitment to undertake digital
transformation.

• Developing and implementing a robust digital
transformation strategy.

Potential application:

• Use findings to generate value from successful
digital transformation.

Gain insights on:
• Overview of India’s manufacturing sector.

• Issues in the manufacturing growth story in India
despite several government initiatives.

• Importance of Industry 4.0 for India to remain
relevant in the global manufacturing scenario and
increase contribution of manufacturing to India’s
Gross Domestic Product (GDP) and exports

• Meaning of Industry 4.0, the various technologies
and their application in manufacturing.

• Drivers of Industry 4.0 and digital manufacturing.

• Overall level of adoption of digitization and Industry
4.0 in India, and also in comparison to worldwide
adoption.

• Bottlenecks and shortcomings in adopting Industry
4.0 and challenges in the current eco-system.

• Benefits of digital transformation in manufacturing
in terms of the manufacturing process, overall

7
Impact of Digital Transformation Strategies on Performance of Manufacturing …

competitiveness especially in the international
market and the firm’s financial performance.
• Performance of firms in terms of governance,
motivation, multi-level readiness, quality of
infrastructure and leadership, time and resource
commitment to undertake digital transformation.
• Developing and implementing a robust digital
transformation strategy.
Potential application:
• Use findings as a base for further research

8
Chapter 1

The Indian Manufacturing Sector and
Digital Transformation

The Indian manufacturing sector is valued at INR 29,128 Billion (2019) and
currently accounts for 14% of the country’s Gross Domestic Product (GDP).1
The sector includes a number of industries such as automobile,
pharmaceuticals, textiles and garment, electronics, chemicals, food
processing, defence manufacturing, electrical machinery, and leather. It
employs around 12% (2014)2 of India’s workforce. Studies show that every job
created in the manufacturing sector in India has a multiplier effect in creating
2–3 jobs in the services sector.3

In 2011, with the roll out of the National Manufacturing Policy, the Government
of India set an ambitious target to increase the share of the manufacturing
sector to 25% of the GDP and create 100 million new jobs in manufacturing by
2022.4 This was followed by the launch of the Make in India initiative by Prime
Minister Narendra Modi in 2014 with the aim to make India a global design and
manufacturing hub.5 Ever since there has been no looking back. The

1 Manufacturing, value added (current US$), World Bank Data. Retrieved from
https://data.worldbank.org/indicator/NV.IND.MANF.CD?locations=IN (last accessed
January 09, 2021); Manufacturing, value added (% of GDP) – India, World Bank Data.
Retrieved from https://data.worldbank.org/indicator/NV.IND.MANF.ZS?locations=IN (last
accessed 2021, January 09)

2 Confederation of Indian Industry (CII). Manufacturing. Retrieved from
https://www.cii.in/sectors.aspx?enc=prvePUj2bdMtgTmvPwvisYH+5EnGjyGXO9hLECvT
uNsfVm32+poFSr33jmZ/rN+5#:~:text=The%20Indian%20Manufacturing%20sector%20c
urrently,jobs%20in%20the%20services%20sector (last accessed 2021, January 09)

3 Confederation of Indian Industry (CII). Manufacturing. Retrieved from
https://www.cii.in/sectors.aspx?enc=prvePUj2bdMtgTmvPwvisYH+5EnGjyGXO9hLECvT
uNsfVm32+poFSr33jmZ/rN+5#:~:text=The%20Indian%20Manufacturing%20sector%20c
urrently,jobs%20in%20the%20services%20sector (last accessed 2021, January 09)

4 Department of Industrial Policy & Promotion, Ministry of Commerce & Industry,

Government of India (2011). Press Note NO. 2 (2011 Series). National Manufacturing

Policy. Retrieved from

https://www.meity.gov.in/writereaddata/files/National%20Manufacturing%20Policy%20%

282011%29%20%28167%20KB%29.pdf (last accessed 2021, January 09)

5 Make in India Website. About Us Section, Retrieved from
https://www.makeinindia.com/about (last accessed 2021, January 09)
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Government has rolled out a number of schemes and initiatives to boost the
manufacturing sector of the country (see Table 2 below).

Table 2: Key government initiatives to boost the manufacturing sector in
India

National Policy on Reduction of Defense Procurement

Electronics (2019) 6 corporate tax rates: 7 Procedure (DPP) 2020

● Promote domestic ● Corporate tax (Draft) 8

manufacturing and reduced to 22% for ● Aims to encourage

export in the entire existing indigenous design

value-chain of companies, and to capacity and

Electronics System 15% for new higher localization

Design and manufacturing in defence

Manufacturing companies. equipment

(ESDM)

● Achieve a turnover

of INR 26,00,000

crore by 2025.

6 Government of India (2019). Cabinet approves the proposal of National Policy on

Electronics 2019. Retrieved from

https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1565285 (last accessed 2021,

January 09)

7 (2020, January 16). Nirmala Sitharaman slashes corporate tax to fire up economy, market
responds with a massive surge. Economic Times. Retrieved from
https://economictimes.indiatimes.com/news/economy/policy/corporate -tax-slashed-for-
domestic-companies-and-new-domestic-manufacturing-
companies/articleshow/71213356.cms?from=mdr (last accessed 2021, January 09)

8 Das, P (2020, April 15). India’s defence procurement policy 2020: Old wine in a new

bottle. Observer Research Foundation. Retrieved from

https://www.orfonline.org/expert-speak/indias-defence-procurement-policy-2020-

old-wine-in-a-new-bottle-64673/ (last accessed 2021, January 09)

10
The Indian Manufacturing Sector and Digital Transformation

Ease of doing Atma Nirbhar SAMARTH Udyog

business rankings Bharat10,11 Bharat 4.012

(EoDB) 9 ● INR 20 lakh crore ● Aims to facilitate

● The government package to enable and create an

has made India to compete in ecosystem for

significant efforts to global supply adoption of Industry

improve India’s chains and support 4.0 by all Indian

ease of doing vulnerable sections manufacturing firms

business rankings of society deeply by 2025 through

from 130 in 2016 to impacted by the experiential and

63 in 2020 pandemic demonstration

● The government ● Increase in Foreign centres

focused on Direct Investment ● Five Common

improving its EoDB Limit under Engineering Facility

rankings to make automatic route Center Projects are:

India attractive for from 49% to 74% in ─ Center for

foreign investors, defence Industry 4.0

encourage the manufacturing. (C4i4) Lab Pune

private sector ─ IITD-AIA

(especially Foundation for

manufacturing) and Smart

boost overall Manufacturing

competitiveness as ─ I4.0 India at IISc

part of the Make in Factory R & D

India campaign. Platform

9 The World Bank (2020). Doing Business 2020. Comparing Business Regulation in 190
Economies. Page 10

10 (2020, May 14). PM Modi announces Rs 20 lakh crore special economic package.
Economic Times. Retrieved from https://economictimes.indiatimes.com/news/politics-
and-nation/pm-narendra-modi-address-live-centre-announces-an-economic-package-of-
rs-20-lakh-crore/articleshow/75699154.cms (last accessed 2021, January 09)

11 Singh, Rahul (2020, 16 May). Govt plans higher FDI, local weapons for self-reliant
defence sector. Hindustan Times. Retrieved from https://www.hindustantimes.com/india-
news/govt-plans-higher-fdi-local-weapons-for-self-reliant-defence-sector/story-
TkWwgfAwZuTnm70ek7xamL.html (last accessed 2021, January 09)

12 SAMARTH Udyog Bharat 4.0. Retrieved from https://www.samarthudyog-i40.in/ (last
accessed 2021, January 09)

11
Impact of Digital Transformation Strategies on Performance of Manufacturing …

─ Smart

Manufacturing

Demo &

Development

Cell at CMTI

─ Industry 4.0

projects at DHI

CoE in

Advanced

Manufacturing

Technology, IIT

Kharagpur

The manufacturing growth story is missing

Despite the impetus provided by the government, the manufacturing sector
growth story continues to be a miss. Although India’s manufacturing sector
value added grew at a compounded annual growth rate (CAGR) of
approximately 7% from 2005 to 2019 (see Figure 1 below), the growth
trajectory is far behind in achieving the goals set by the government. In fact,
the contribution of the manufacturing sector to India’s GDP has declined from
17.3% in 2006 to 13.7% in 2019 (see Figure 2 below). These figures are much
lower than countries such as Indonesia whose manufacturing sector
contributes 20% to GDP, Malaysia (22%), Thailand (27%) and China (29%).13

13 Bangera, S. (2018, September 14). Economic slowdown: Manufacturing growth sluggish
at 7%, share in GDP stagnant at 16%; urgent need of more than just a policy overhaul.
Firstpost. Retrieved from https://www.firstpost.com/business/economic-slowdown-
manufacturing-growth-sluggish-at-7-share-in-gdp-stagnant-at-16-urgent-need-of-more-
than-just-a-policy-overhaul-7338301.html (last accessed 2021, January 09)

12
The Indian Manufacturing Sector and Digital Transformation

Figure 1: India’s manufacturing sector value added (INR Billion)

INR Billion 35000
30000
25000 2007 2009 2011 2013 2015 2017 2019
20000 Year
15000
10000

5000
0
2005

Percentage of GDP (%)Source: The World Bank

Figure 2: Contribution of India’s manufacturing value added to GDP
(percentage)

20
18
16
14
12
10

8
6
4
2
0

Year

Source: The World Bank

The reasons for the downfall of India’s manufacturing sector are many - lack
of financing and credit facilities further worsened by a crisis in the banking
sector due to non-performing assets, contraction in government spending,
challenges in transportation and logistics, shortage of power and infrastructure
bottlenecks, burdensome government compliances and regulations, impact of

13
Impact of Digital Transformation Strategies on Performance of Manufacturing …

demonetization on small and medium businesses, and shrinking demand from
consumers and business due to a general slowdown in the Indian economy.14

However, one of the most important factors impeding growth of India’s
manufacturing sector is the lack of competitiveness of the domestic industry to
compete in the global market as well as its increasing inability to cater to
domestic demand due to competition from imports. The manufacturing sector
has been lobbying with the government for protection from imports through
tariffs and duties. While the government has set up import controls on and off
in sectors such as electronics, cashew kernels, PVC, auto parts, and synthetic
rubbers,15 with the aim to protect and encourage the domestic value chain, it
is important to recognize that this is only a temporary bandage.

Competing in the global market and from imports at home requires
manufacturing firms in India to enhance their competitiveness and products by
embracing digital transformation and Industry 4.0.

There are also other complexities and diverse factors which affect India’s
manufacturing sector. The investment that goes behind setting up captive
power supply for stable and uninterrupted power becomes a huge cost burden
for all relevant financial investors in energy-intensive manufacturing units.
Further, with additional tax burdens being levied on heavy manufacturing
industries like coal cess, etc. there is an increase in the overall energy cost for
manufacturing firms. Also, in terms of international energy quality standards,
India ranks 80 out of 137 countries as per World Economic Forum data. Recent
data released by the World Bank brought forth that access to electricity is the
second-most significant impediment for manufacturing firms and has played a
major role in holding back corporate investments in the manufacturing sector.16

14 Dhar, B (2019, July 08). Manufacturing sector: Struggling to take off. Business Line.
Retrieved from https://www.thehindubusinessline.com/opinion/manufacturing-sector-
struggling-to-take-off/article28322705.ece (last accessed 2021, January 09)

15 (2019, July 05), Budget 2019: Government hikes customs duty on CCTV camera, split

AC. ET Retail. Retrieved from

https://retail.economictimes.indiatimes.com/news/consumer -durables-and-information-

technology/consumer-electronics/budget-2019-government-hikes-customs-duty-on-cctv-

camera-split-ac/70090707 (last accessed 2021, January 09)

16 EIA International Energy Outlook 2019 - Issue in Focus - U.S. Energy Information
Administration (EIA). (2021). Retrieved 9 January 2021, from
https://www.eia.gov/outlooks/ieo/section_issue_aiso.php

14
The Indian Manufacturing Sector and Digital Transformation

Further, it also important to consider the cost behind Indian Logistics,
estimated to be around 14%-15% of GDP, almost double of 7%-8% of GDP in
developed countries. Nearly 60% of the cargo in India travels by road. Over-
saturated railway networks, high rail freights, long transit times, inadequate
port depths, high turnaround time at ports, and poor warehousing facilities
have been attributed to these excess incurred costs.17 Let's take the
comparative base between China and India as anecdotal evidence, the
distance from Guangzhou in China to Mumbai is five times greater than that
between Delhi to Mumbai, but the cargo cost is almost comparable.

Further, from a bird’s eye view, India’s demographic and low labour cost may
look like an advantage but a closer analysis reveals that this advantage is
haunted and limited by growing skill mismatch and low productivity. While 62%
of India’s population is in the working age group and more than 54% of the
total population is below 25 years of age, only 4.7% of India’s workforce is
skilled formally, significantly lower than the demographics in countries such as
United States (52%), United Kingdom (68%), Germany (75%), Japan (80%),
South Korea (96%) and China (24%). Estimates bring forward that India needs
to train 126 million people across 34 sectors.18 According to Aspiring Minds,
an Indian employability assessment enterprise, 80% of engineers in India are
“unemployable”. All of this has resulted in much lower productivity for India in
the manufacturing sector. For instance, as compared to India, China and
Brazil’s manufacturing productivity in terms of value added per hour worked
are 1.6 and 2.9 times higher respectively. 19

Expenditure on Innovations and R&D is critical if India is to realise its goal of
increasing the manufacturing share in its GDP to 25%. The Economic Survey
recently released India’s R&D expenditure as a percentage of GDP to be
stagnant at 0.6%-0.7% since the last two decades. This is much lower than

17 Anon(2021). Retrieved 9 January 2021, from

http://niti.gov.in/writereaddata/files/document_publication/Freight_report.pdf

18 Priya, P. and Ghosh.A. (2018, September 06). Why India’s manufacturing sector needs a

big push. Financial Express. Retrieved from

https://www.financialexpress.com/opinion/why-indias-manufacturing-sector-needs-a-big-

push/1303968/ (last accessed 2021, January 09)

19 Priya, P. and Ghosh.A. (2018, September 06). Why India’s manufacturing sector needs a

big push. Financial Express. Retrieved from

https://www.financialexpress.com/opinion/why-indias-manufacturing-sector-needs-a-big-

push/1303968/ (last accessed 2021, January 09)

15
Impact of Digital Transformation Strategies on Performance of Manufacturing …

the United States (2.8%), China (2.1%), South Korea (4.2%) and Israel
(4.3%).20 Along with greater state and central government spending there is
also a need for industrial application oriented R&D and greater collaboration
with the private sector. An exchange of researchers between public research
organisations and industry has become very important for facilitating transfer
of knowledge and understanding each other’s perspectives.
If we want to see India’s manufacturing sector grow, it becomes really
important for us to push the frontier for MSMEs which contribute to nearly 29%
of the GDP.21 We have to see that necessary steps are taken to reduce the
cost of capital for these firms so that they stay competitive and innovative.
The Indian manufacturing sector needs to upgrade to compete globally,
however, without effective and targeted policy support it would not be possible
for the sector to progress. It will stagnate and not be able to compete with its
emerging market peers. Only through effective collaboration between the
government and the private sector will India’s manufacturing sector be able to
see any progress.

20 EAC-PM (2019). R&D Expenditure Ecosystem. Current Status and Way Forward.
Retrieved from https://www.indiascienceandtechnology.gov.in/sites/default/files/file-
uploads/roadmaps/1571900991_R%26D%20book%20expenditure%20ecosystem.pdf
(last accessed 2021, January 09)

21 (2019, July 05). MSMEs to contribute 50% to India's GDP, provide 15 cr jobs in 5 years:
Gadkari. Economic Times. Retireved from https://economictimes.indiatimes.com/small-
biz/sme-sector/msmes-to-contribute-50-to-indias-gdp-provide-15-cr-jobs-in-5-years-
gadkari/articleshow/70092226.cms?from=mdr (last accessed 2021, January 09)

16
Chapter 2

Digital transformation and Industry 4.0
in Manufacturing

From Britannica to Wikipedia, from Encyclopaedia to Google, and from hand
assembly to robots and automation, the journey of industrial transformation
and the use of technology is constantly evolving. Industrial revolutions were
historically marked by the use of power. The 1st Industrial Revolution
mechanised the production process through the power generated by water and
steam. The 2nd Industrial Revolution made mass production possible by the
use of electricity. The 3rd Industrial Revolution was marked by information
technology leading us to the 4th Industrial Revolution (Industry 4.0) which uses
integrated technologies and has touched all spheres of our life making it a truly
distinct revolution. The impact, scope and exponential pace of revolution is
phenomenally marked by breakthroughs. The disruption created by Industrial
Revolution 4.0 heralds the transformation of covering entire organisational
systems, management and production.
Figure 3: Industrial revolutions

Source: Momentum, L. (2019). The Industrial Revolution: From Industry 1.0 to Industry 4.0.
Retrieved 15 January 2021, from https://www.seekmomentum.com/blog/manufacturing/the-
evolution-of-industry-from-1-to-4
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Industrial revolution 4.0 is marked by the power of Data. As stated by some
experts “data is the new oil”. Digital-born businesses like Google and
Amazon are power producers and other digital savvy companies are the
companies of next industrial age. Traditional manufacturing companies have
to advance and digitally transform themselves to become new age companies.
Therefore, digital transformation entails changes in job and income creation
strategies, changes in business models, facing the competition and meeting
customer expectations. It requires reinventing of business models, digitisation
of supply chains and use of technology in all the operational and functional
departments of the company”.22

Digital transformation should not be construed as merely a technological leap.
It is more than just implementing new software and platforms in an
organisation. Leaders and managers should not just focus on the technical
capabilities or hardware and software updates, rather they should focus on
adapting their business models, their institutional and operational ecosystems
in line with digitalisation initiatives. Digital transformation is essentially an
application of a flexible business model which is focused on digitalisation.

Furr et al in their Harvard Study, ‘Digital Doesn’t Have to Be Disruptive’, have
stated that digital transformation is not only a rearrangement of technology,
business models, and processes but also transformation of the core using
digital tools and discovering new opportunities. They stated that the key to
success is the focus on customer needs and organisational flexibility .23 The
adoption of digital transformation is actually determined by customer pull.
Digitalised organisations are able to reduce the product design and
manufacturing time to meet the demands of customers. This is only possible
when data is used for optimal and faster decision processes at every level of
manufacturing. This results in increase in productivity and, growth, and lowers
costs.

In a nut shell, “[I]ndustry 4.0 is the information-intensive transformation of
manufacturing (and related industries) in a connected environment of big data,
people, processes, services, systems and IoT-enabled industrial assets with

22 Schallmo Daniel, Willams Christopher A.; Boardman Luke (2018)”Digital Transformation
of Business Models-Best Practice, Enabler, and Roadmap”, International Journal of
Innovation Management, 21(8): 1740014-(17 pages)

23 Digital Doesn’t Have to Be Disruptive. (2019). Retrieved 9 October 2020, from
https://hbr.org/2019/07/digital-doesnt-have-to-be-disruptive

18
Digital transformation and Industry 4.0 in Manufacturing

the generation, leverage and utilization of actionable data and information as
a way and means to realize smart industry and ecosystems of industrial
innovation and collaboration”24 It integrates Information Technology (IT) and
Operational Technology (OT) to evolve into a cyber-physical system in which
it brings together physical industrial assets and digital technologies.25

Key technologies associated with Industry 4.0 and
their real world applications

In the Table 3 below we have described the key technologies in manufacturing:

Table 3: Key technologies associated with Industry 4.0 and digital
transformation in the manufacturing sector

Industry 4.0 – Device layer Technologies

Industrial Internet of Things (IOT) - Device Layer
IOT connects physical devices digitally and facilitates information exchange
through the Internet.
In the manufacturing sector, IOT facilitates collection of real-time data about
parameters such as machine condition and performance by integrating
sensors, Radio Frequency Identification (RFID) tags, software and
electronics with industrial machines and systems.
In the manufacturing sector, tracking is one of the major applications of IOT
and it is highly used for asset management. BJC Healthcare in the United
States used RFID tags to track and manage its medical supplies across 15
hospitals.26

Open Process Automation (OPA) - Device Layer
OPA provides an open architecture of automation which is flexible and can
be easily adapted for industrial application. Open Process Automation

24 I-SCOOP. Industry 4.0: the fourth industrial revolution – guide to Industrie 4.0. Retireved
from https://www.i-scoop.eu/industry-4-0/ (last accessed 2021, January 09)

25 I-SCOOP. Industry 4.0: the fourth industrial revolution – guide to Industrie 4.0. Retireved
from https://www.i-scoop.eu/industry-4-0/ (last accessed 2021, January 09)

26 (2019, March 28). Industry 4.0: 7 Real-World Examples of Digital Manufacturing in Action.
AMFG. Retrieved from https://amfg.ai/2019/03/28/industry-4-0-7-real-world-examples-of-
digital-manufacturing-in-
action/#:~:text=Industry%204.0%20in%20a%20nutshell,connectivity%2C%20intelligence
%20and%20flexible%20automation (last accessed 2021, January 09)

19
Impact of Digital Transformation Strategies on Performance of Manufacturing …

results in easy updating and low maintenance, therefore, manufacturers can
put focus more on improving their manufacturing process than on
supporting automation. It allows integration of best in class components as
well as significantly reduces the costs of future replacements.
An example of ExxonMobil Corporation can be cited here which used OPA
to replace their old and obsolete DCS installations. 27

Advanced Robotics - Device Layer
Robotics have always been part an integral of the manufacturing sector,
however Industry 4.0 has given it a new dimension. Powered by state of the
art software and sensors, robots today are able to recognise, analyse and
act upon information received from the environment. They can also
collaborate and learn from humans.
A new concept of “Cobots” has also emerged where robots work in a
collaborative setting with humans, taking over repetitive and dangerous
tasks performed by humans.
Fetch Robotics in the United States is manufacturing Autonomous Mobile
Robots (AMRs) for performing tasks such as locating, tracking and moving
inventory in their warehouse and logistics facilities. DHL in the Netherlands
is using Fetch AMRs to perform pick and place operations in their facility
alongside humans.

Augmented and virtual reality (AR/VR) - Device Layer
AR superimposes virtual images or data onto physical objects and stitches
the gap between the digital and physical world. This technology involves
use of AR capable devices such as smartphones, tablets and smart glasses.
In the manufacturing, AR glasses can project data, such as layouts and
sites of possible malfunction on a real machine part, thereby making work
procedures more efficient and relatively easier.
General Electric is piloting AR glasses at its jet manufacturing facility in the
United States. AR glasses are not only eliminating the need for supervision
by engineers but also ensuring that tasks are undertaken correctly. 28

27 Forbes, H. (2018, January 19). What is Open Process Automation? ARC Advisory Group.
Retrieved from https://www.arcweb.com/blog/what-open-process-automation (last
accessed 2021, January 09)

28 (2019, March 28). Industry 4.0: 7 Real-World Examples of Digital Manufacturing in Action.
AMFG. Retrieved from https://amfg.ai/2019/03/28/industry-4-0-7-real-world-examples-of-
digital-manufacturing-in-

20
Digital transformation and Industry 4.0 in Manufacturing

Factory workers are also increasingly being trained with AR based learning
systems where they can simulate their operating the machines in a learning
environment without actually operating them.

Industry 4.0 – Data Layer Technologies

Big Data and Data Engineering Analytics - Data Layer
Big data refers to large and complex data sets collected through IOT
devices such as sensors and cameras and from databases such as ERP
and CRM. The data collected from various sources can be stored in data
lakes in a structured or unstructured form at any scale.29 It is then analysed
to provide actionable insights or tangible/lucrative business benefits.
Machine learning models and data visualisation are important tools that
support the analysis of big data.
In the manufacturing sector, insights obtained from analysis of these initially
isolated sets of data helps optimize processes.
Bosch has combined the use of IOT and big data in its automotive diesel
system factory China. The company uses sensors fit in its machines to
predict failures and plan maintenance well in time. Data analysis has helped
Bosch increase output by more than 10% output in certain areas, along with
an improvement in delivery and customer satisfaction. 30

Cloud Computing - Data Layer
Cloud Computing is the revolutionizing concept where a platform which can
be accessed remotely becomes the storage point of all data collected by
manufacturers. While cloud computing is not a solution by itself, it saves the
manufacturer from investing in computing infrastructure and enables
implementation of solutions that require heavy computer power.

action/#:~:text=Industry%204.0%20in%20a%20nutshell,connectivity%2C%20intelligence
%20and%20flexible%20automation (last accessed 2021, January 09)
29 AWS. What is a data lake? Retrieved from https://aws.amazon.com/big-data/datalakes-
and-analytics/what-is-a-data-lake/ (last accessed 2020, January 09)
30 (2019, March 28). Industry 4.0: 7 Real-World Examples of Digital Manufacturing in Action.
AMFG. Retrieved from https://amfg.ai/2019/03/28/industry-4-0-7-real-world-examples-of-
digital-manufacturing-in-
action/#:~:text=Industry%204.0%20in%20a%20nutshell,connectivity%2C%20intelligence
%20and%20flexible%20automation (last accessed 2021, January 09)

21
Impact of Digital Transformation Strategies on Performance of Manufacturing …

One of the pertinent roles of cloud computing is that it allows organizations
to have centralized operations and the information stored on cloud can be
accessed by all members of the organisation.

Edge Computing ( Data Layer- Distributed Computing)
Edge Computing enhances the power for processing and allows more
activities to be performed by user end devices. This decreases inefficiency
by reducing the stacks associated with the IOT and cloud computing,
increasing information security , and reducing conveyance costs. Edge
allows increased handling capacity and opens up numerous conceivable
outcomes inside the scope of the IOT such as dodging deterrents, dialect
handling, protest location, face recognition and other machine learning
applications.
We can see several applications of the Edge Computing in Autonomous
vehicles where they were first used to track obstacles and relay real time
data on the road ahead to the vehicles adaptive system.
Fog computing provides a network connecting cloud servers and machines
with data entry points and storage locations. Fog Computing forms a link
between edge and cloud machines.

Artificial Intelligence (AI) - Data Layer
AI is an extension of computer science that enables smart machines to
perform like humans having similar intelligence as they learn from
experience, continuously incorporate inputs into their response , make
decisions and judgments which “normally require human level of expertise
and help people anticipate problems or deal with issues as they come up”.31

Advanced Analytics and Machine Learning – Data Layer
Analytics helps executives understand – (a) What is happening in their
business? - descriptive analytics, (b) Why is it happening? – Diagnostic
Analytics, (c) What is likely to happen? – Predictive Analytics, and (d) What
do I need to do? – Prescriptive Analytics.32

31 Shubhendu and Vijay (2013) In West, D. M. (2018, October 04). What is artificial
intelligence? Brookings. Retrieved from https://www.brookings.edu/research/what-is-
artificial-intelligence/ (last accessed 2021, January 09)

32 (2017, January 19). The 4 Types of Data Analytics. Principa. Retrieved from
https://insights.principa.co.za/4-types-of-data-analytics-descriptive-diagnostic-predictive-
prescriptive (last accessed 2021, January 09)

22
Digital transformation and Industry 4.0 in Manufacturing

Analytics have become the backbone of industry's several digital
applications. Real time updates received from sensors and other data
collection points can be analysed easily. Machine learning is a very
powerful means of using data to understand the behaviour and performance
of machines in setting up manufacturing as algorithms.
There are several uses of ML in manufacturing - ML based predictive
maintenance of digitalised instruments and predicting demand for inventory
management and mapping with production schedules.

Blockchain: Data layer- Distributed Technology
Blockchain is defined as a decentralized technology which uses distributed
network systems. Blockchain enables improved tracking and traceability
and superior data security due to encryption. It can be used for supply chain
auditing, streamlining warranty lifecycles by closing information
asymmetries between manufacturers, warranty providers, other supply
chain participants and the consumers, and creating smart contracts to
minimize transaction costs for instance, a smart contract can automatically
assess if the pre-set conditions to successful delivery have been met. 33
Cybersecurity: Data layer
This has to deal with the aspect of data integrity and is done through the
protection of internet-connected systems such as hardware, software and
data from cyber-threats. We have mostly seen its utility in protecting against
unauthorized access to data centres and other computerized systems.
The goal of implementing cybersecurity is to make a good secure system
accessible to stakeholder’s computers, servers, networks, mobile devices
and the data stored on these devices from attackers with malicious
intent. We have seen incidents in the past where cyber-attacks have been
designed to access, delete, or extort an organization’s or user’s sensitive
data, making cybersecurity vital. 34

33 Birlasoft. Three blockchain use cases that will accelerate Industry 4.0 journey for
manufacturers. Retrieved from https://www.birlasoft.com/articles/three-blockchain-use-
cases-that-will-accelerate-industry-4-journey-for-manufacturers (last accessed 2021,
January 09)

34 (2019, March 28). Industry 4.0: 7 Real-World Examples of Digital Manufacturing in Action.
AMFG. Retrieved from https://amfg.ai/2019/03/28/industry-4-0-7-real-world-examples-of-
digital-manufacturing-in-
action/#:~:text=Industry%204.0%20in%20a%20nutshell,connectivity%2C%20intelligence
%20and%20flexible%20automation (last accessed 2021, January 09)

23
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Industry 4.0- Process Layer Technologies

Robotics Process Automation (RPA)- Process
RPA enables organizations minimize manual time spent on tasks such as
data entry, generating financial reports, or culling out insights from a
customer management system. RPA automates automates administrative
and mundane tasks that do not require deep cognitive abilities and unlike
machine learning the software does not learn from inputs or results over
time.35

Additive Manufacturing (AM)- Process Layer
AM works by using digital 3D models and manufacturing parts through 3D
printing layer by layer.
AM is proving to be a valuable digital manufacturing technology. AM offers
the possibility of manufacturing from tooling to mass customizations across
all industries. The primary function of AM is distributed manufacturing which
is storing of parts as design files in virtual inventories and producing them
on demand or customising them. This leads to saving in travel, inventory
and storage spaces.
AM is being used by Fast Radius offers supply chain optimization through
its virtual inventory. The company has created a warehouse of 3000 virtual
parts for a heavy equipment manufacturer instead of storing all parts -
including those that are rarely used - physically. It is able to print and supply
the parts on demand. 36

Industry 4.0 – Enablers

35 Sremack, J. (2018, September). An Introduction to Robotic Process Automation for

Manufacturers. BDO United States. Retireived from

https://www.bdo.com/insights/industries/manufacturing-distribution/an-introduction-to-

robotic-process-automation-

for#:~:text=Robotic%20Process%20Automation%20(RPA)%20is,to%20deliver%20missi

on%20critical%20work (last accessed 2021, January 09)

36 (2019, March 28). Industry 4.0: 7 Real-World Examples of Digital Manufacturing in Action.
AMFG. Retrieved from https://amfg.ai/2019/03/28/industry-4-0-7-real-world-examples-of-
digital-manufacturing-in-
action/#:~:text=Industry%204.0%20in%20a%20nutshell,connectivity%2C%20intelligence
%20and%20flexible%20automation (last accessed 2021, January 09)

24
Digital transformation and Industry 4.0 in Manufacturing

Digital Twins. (Simulation) - Enabler
Digital twin technology uses digital representation of a real-world product,
machine, process or system in order to provide better understanding,
analysis and optimisation of processes for companies through real-time
simulation. The simulation helps predict potential issues and improves
machine up-time. It also helps in improving the design and performance of
a product.
American pro-racing squad Team Penske is using a digital twin application
to create a virtual test bed for testing innovations in new parts and
optimising car performance before incorporating the changes into a physical
car. 37

Asset Performance Management (APM) – Enabler
APM enables data analytics. This technology can integrate data from
multiple plants and sites and can get equipment from OEM. APM enables
predictive forecasting, reliability asset maintenance and condition
monitoring. Commonly it is used for web applications. APM leverages data
analytics and digital twin models to detect very subtle indicators of potential
failure.
Companies like GE Digital, Bruce Power and Xcel Energy use APM to
reduce costs and increase efficiency.

Sources: See the Footnotes38

37 (2019, March 28). Industry 4.0: 7 Real-World Examples of Digital Manufacturing in Action.
AMFG. Retrieved from https://amfg.ai/2019/03/28/industry-4-0-7-real-world-examples-of-
digital-manufacturing-in-
action/#:~:text=Industry%204.0%20in%20a%20nutshell,connectivity%2C%20intelligence
%20and%20flexible%20automation (last accessed 2021, January 09)

38 (2019, March 28). Industry 4.0: 7 Real-World Examples of Digital Manufacturing in Action.
AMFG. Retrieved from https://amfg.ai/2019/03/28/industry-4-0-7-real-world-examples-of-
digital-manufacturing-in-
action/#:~:text=Industry%204.0%20in%20a%20nutshell,connectivity%2C%20intelligence
%20and%20flexible%20automation (last accessed 2021, January 09); Forbes, H. (2018,
January 19). What is Open Process Automation? ARC Advisory Group. Retrieved from
https://www.arcweb.com/blog/what-open-process-automation (last accessed 2021,
January 09); AWS. What is a data lake? Retrieved from https://aws.amazon.com/big-
data/datalakes-and-analytics/what-is-a-data-lake/ (last accessed 2020, January 09);
Shubhendu and Vijay (2013) In West, D. M. (2018, October 04). What is artificial
intelligence? Brookings. Retrieved from https://www.brookings.edu/research/what-is-
artificial-intelligence/ (last accessed 2021, January 09); 2017, January 19). The 4 Types
of Data Analytics. Principa. Retrieved from https://insights.principa.co.za/4-types-of-data-

25
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Figure 4: Industry 4.0 Technologies

Source: Industry 4.0: fourth industrial revolution guide to Industrie 4.0 Industry 4.0:
fourth industrial revolution guide to Industrie 4.0. (2021). Retrieved 15 January 2021,
from https://www.i-scoop.eu/industry-4-0/

analytics-descriptive-diagnostic-predictive-prescriptive (last accessed 2021, January 09);
Birlasoft. Three blockchain use cases that will accelerate Industry 4.0 journey for
manufacturers. Retrieved from https://www.birlasoft.com/articles/three-blockchain-use-
cases-that-will-accelerate-industry-4-journey-for-manufacturers (last accessed 2021,
January 09); Sremack, J. (2018, September). An Introduction to Robotic Process
Automation for Manufacturers. BDO United States. Retrieved from
https://www.bdo.com/insights/industries/manufacturing-distribution/an-introduction-to-
robotic-process-automation-
for#:~:text=Robotic%20Process%20Automation%20(RPA)%20is,to%20deliver%20missi
on%20critical%20work (last accessed 2021, January 09);

26
Digital transformation and Industry 4.0 in Manufacturing

Key Performance Drivers of Industry 4.0 and digital
manufacturing

Digital manufacturing creates a number of benefits and efficiencies for firms
including:

Higher productivity: A 2019 study undertaken by Deloitte and the
Manufacturer’s Alliance for Productivity and Innovation (MAPI)39,40 in the
United States shows that companies reported up to 12% improvement in
output, factory utilization and labour productivity through smart factory
initiatives. Lower unplanned asset downtime and higher asset utilization are
key benefits of Industry 4.0 technologies that enhance productivity of
manufacturing firms and lead to cost savings. For instance, unplanned
machine downtimes are one of the biggest challenges for manufacturers as
they immediately stall the production process. As a result, manufacturers
engage in costly periodic maintenance irrespective of need, wasting financial
and time resources and reducing return on assets on the shop floor. IOT and
data analytics – important Industry 4.0 technologies – can help minimize such
losses. According to a study, a German automotive manufacturer was able to
reduce downtime losses by more than 40,000 Euros per minute through
predictive and real-time IOT. 41 Deloitte (2017) estimates that predictive
maintenance using Industry 4.0 technologies can lower plant maintenance
time by 20% - 50%, increase equipment uptime and availability by 10%-20%
and decrease overall costs of maintenance by 5%-10%.42

Improved asset turnover: Productivity gains have been seen to improve
asset turnover for firms. Tracking non-tech US firms over a 3-year period that
adopted digitization, Chen & Srinivasan (2019) show their asset turnover

39 Deloitte and MAPI interviewed 600 executives at manufacturing firms with their
headquarters in the United States and with a global factory footprint

40 Deloitte and Manufacturer’s Alliance for Productivity and Innovation (MAPI) (September

2019). https://www2.deloitte.com/us/en/pages/about-deloitte/articles/press-

releases/2019-deloitte-and-mapi-smart-factory-study-capturing-value-along-the-digital-

journey.html (Last accessed on 2020, November 11)

41 PTC (2019). Quantifying the Value of Digital Transformation in Manufacturing, Page 1

42 Coleman, C., Damodaran, S., Chandramouli, M., & Deuel, E. (2017). Making maintenance
smarter. Deloitte Insights. https://www2.deloitte.com/us/en/insights/focus/industry-4-
0/using-predictive-technologies-for-asset-maintenance.html (Last accessed on 2020,
November 11)

27
Impact of Digital Transformation Strategies on Performance of Manufacturing …

increased throughout the time period, with a 2%-7% increase seen in the third
year compared to industry peers. 43

Operational efficiency: Manufacturing firms often suffer from operational
inefficiencies due to lack of synchronization between their information
technology (IT) systems and operational technology (OT) systems. Industry
4.0 technologies enable integration between the IT and OT systems of
manufacturing firms, providing a single-screen real-time view of all aspects of
the production process to managers. Woodward Inc. – a manufacturer of
designer, manufacturer, and service provider of energy control and
optimization solutions for aerospace and industrial markets, headquartered in
United States44 - is able to save USD 1.7 million per plant by implementing the
IOT enabled single view application. 45

Higher firm value: A 2019 study46 of US listed non-tech firms from 2010 to
2017 shows that the market-to-book ratio of non-tech US firms adopting digital
technologies is 7%-23% higher than their industry peers. The study also finds
that firms that engage in digital activities are “larger, younger, less CapEx
intensive, hold more cash and are in industries with higher digital activity”.
Further, the research shows that digitization leads to higher valuation for firms
that have a relatively higher CapEx, stronger sales growth and operate in
industries with significant digital activity and/or cater to business customers.
Given that firms that adopt digitization are more valued, they also exhibit a
43% - 127% higher Earnings Response Coefficient (ERC) annually based on
digital engagement as compared to peers. Digital disclosure also has a
positive impact on the stock market.

Improved decision-making and operational efficiency: Embracing Industry
4.0 technologies also helps in strengthening strategic and operational decision
making by leveraging the power of data. This plays a key role in improving
efficiency and cost effectiveness of firms.47

43 Chen, W. & Srinivasan, S. (2019). Going Digital: Implications for Firm Value and
Performance. Harvard Business School, Working Paper 19-117, Pages 2-5

44 Woodward. About Woodward. Retrieved from https://www.woodward.com/en/about (Last
accessed on 2020, January 09)

45 PTC (2019). Quantifying the Value of Digital Transformation in Manufacturing, Page 6

46 Chen, W. & Srinivasan, S. (2019). Going Digital: Implications for Firm Value and
Performance. Harvard Business School, Working Paper 19-117, Pages 2-5

47 Vassallo, D. and Jacobs, M. Don’t Lose Sight of the “Human Factor” in Industry 4.0.
DuPont Sustainable Solutions. Retrieved from https://www.consultdss.com/don_t-lose-

28
Digital transformation and Industry 4.0 in Manufacturing

Reduction of Defects and Wastages: High resolution measuring of
production processes and monitoring the production parameters throughout
the entire process with the use of new Machine Learning technologies and
IOTs can help firms reduce their defects and wastages during the production
processes.
Reduction of Costs: Capturing and analysing the data throughout the digital
value chains- production line, transportation, and logistics can help in cost
reductions. Companies can predict their lead times and manage their inventory
well without any stock outs. By using Robotics Process Automation back office
costs be reduced to half in some cases.
Product Customisation: Digital transformation can help in increasing the
value for the customers by enabling customisation. Data analysis can help in
offering customised products with manufacturing lines with digitalization can
offer varying options to the customers without affecting mass production at
competitive pricing. 48
Safety of Workers: The most important benefit of digital technologies is the
improved supervision and safety of workers particularly in manufacturing
sectors where greater supervision and safety is required of workers performing
hazardous tasks. Some of these difficult tasks can be performed by robots.
Use of sensors can greatly help in reducing hazards by alarming the workers
of safety issues.
Other benefits of Industry 4.0 in manufacturing are greater agility, flexibility
and operational performance, reduction in inventory, improved quality, a
shorter time to market, and an expansion and customization in the range of
products supplied.49

sight-of-the-human-factor-in-industry-4-
0/#:~:text=The%20large%2Dscale%20digitization%20of,
efficient%20and%20cost%2Deffective%20operations (Last accessed on 2021, January
09)
48 PTC (2019). Quantifying the Value of Digital Transformation in Manufacturing,
49 PTC (2019). Quantifying the Value of Digital Transformation in Manufacturing,

29
Chapter 3

Digital Transformation Ecosystem in
India

Industry 4.0 originated in Germany in 2006 when the German government
presented its “High-Tech Strategy” at Hannover Messe with a proposal to drive
innovation in the form of technical and social innovation in the country. ‘Digital
economy and society’ was a key task identified by the German government as
a means to create value and enhance quality of life going forward. The key
characteristics of the future of production revolved around individualization of
products, involving customers and business partners in value creation and
connecting production with high-quality services to create hybrid products. The
government promised clear support to the business and science sectors
towards developing Industry 4.0. and even set up a Working Advisory Group
for innovation policy. Five years later the work of the advisory group was
presented, and Germany embraced Industry 4.0 thereon.50

Following Germany, Industry 4.0 has spread to various parts of the world
across various industries. At an industry level, the automotive sector leads the
way.

Figure 5: Industry-wise penetration of Industry 4.0 (worldwide)

40%

35%

30%

25%

20% 36% 29% 29% 29%
15%
26% 25% 24% 24%
10%

5%

0%

50 I-Scoop. Industry 4.0: the fourth industrial revolution – guide to Industrie 4.0.
https://www.i-scoop.eu/industry-4-0/ (Last accessed on 11 November 2020)
Digital Transformation Ecosystem in India

Note: The results are based on a survey of 150 OT and IT decision makers in
manufacturing firms worldwide51

At a regional-level, North America has an Industry 4.0 adoption of 36%,
followed by 27% in Europe and 20% in Asia (focus on China). The leading
adopters are GE, Tesla and Boeing in North America, Siemens, ABB and BMW
in Europe and Toyota, Huawei and Foxconn in Asia.

Figure 6: Region-wise penetration of Industry 4.0 (worldwide)

40% 27% 20%
35% Europe Asia (focus on China)
30%
25%
20%

36%
15%
10%
5%
0%

North America

Note: The results are based on a survey of 150 OT and IT decision makers in
manufacturing firms worldwide52

Despite the benefits, firms in India are far behind in embracing digital
transformation and Industry 4.0. For instance, India has a robot density of only
3 Robots per 10,000 employees, much below the global average of 74 and far
below that of geo-politically competing countries such as China.

51 IOT Analytics (2020). Industry 4.0 & Smart Manufacturing Adoption. Retrieved from
https://iot-analytics.com/product/industry-4-0-smart-manufacturing-adoption-report-2020/
(Last accessed on 2020, November 11)

52 IOT Analytics (2020). Industry 4.0 & Smart Manufacturing Adoption. Retrieved from
https://iot-analytics.com/product/industry-4-0-smart-manufacturing-adoption-report-2020/
(Last accessed on 2020, November 11)

31
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Table 4: Robot Density in Manufacturing Companies in 2016 (Robots per
10,000 Employees)

Countries Number Countries Number

R Korea 631 Singapore 488

Germany 309 Japan 303

US 189 UK 71

China 68 Brazil 10

Russia 3 India 3

Global average 74

Source: International Federation of Robotics, (2018, February 07). Executive

Summary, Robot density rises globally, World Robotics 2017, Industrial Robots53

Further, India ranked only 88 out of 134 on the World Economic Forum’s (WEF)
Network Readiness Index (NRI) 2020, much lower than Korea (14), China (40),
Brazil (59), Vietnam (62), Mexico (63) and Indonesia (73). The NRI ranks
countries on digital transformation based on their performance across 60
variables grounded in mainly four fundamental dimensions - Technology,
People, Governance and Impact.54

Adoption of Industry 4.0 in India is particularly grave for the small industries.
A 2019 survey conducted by SME India Forum showed that out of over
1,29,537 MSME respondents, only 7% adopt digital technologies. Over 70%
of the MSMEs interviewed stated reasons such as lack of knowledge, high
costs and lack of skilled manpower as key challenges impeding adoption of
digital technologies.55

53 Bhat, T. P. (2020, January). India and Industry 4.0. Institute for Studies in Industrial
Development

54 World Economic Forum in collaboration with A.T. Kearney. (2018)

55 (2019, November 20) Indian MSMEs struggle for technology adoption continues; poor
digital understanding restricting growth. Financial Express. Retrieved from
https://www.financialexpress.com/industry/sme/msme-tech-small-business-technology-
msme-cloud-adoption-digital-technology-india-sme-forum-intel-india/1770091/ (last
accesses 2021, January 09)

32
Digital Transformation Ecosystem in India

Immediate need for Indian manufacturing firms to
adopt Industry 4.0 and digital transformation

According to the literature, as more companies adopt digital technologies and
a critical mass is reached, ripple effects change the prevalent competitive
dynamics in the market and also alters the existing commercial landscape.
Further, digitization also disrupts business models and operations of traditional
firms, creates changes in consumer behaviour and offers opportunities for
smaller firms with smaller legacies, which can easily adapt to changes.56 These
ignored and unexploited opportunities lead to a loss of market share. For
instance, Google Maps completely took over the market for stand-alone GPS
makers within two year.57 In the manufacturing sector, firms adopting additive
manufacturing are completely re-inventing supply chain management through
virtual inventories, eliminating the need for long transportation overhauls and
physical inventory storage. Firms that do not embrace Industry 4.0 going
forward face the risk of being left behind by not just immediate competitors but
the entire industry.58 86% of the 600 manufacturing sector executives
interviewed in the United States in 2019 said that smart factory initiatives will
drive competitiveness in the sector over the next 5 years. 59

On superimposing this theory to the global manufacturing scenario, it is
important to note that if Indian manufacturing firms fail to embrace Industry 4.0
and digital manufacturing technologies, they will get left behind in being able
to cater to domestic or international demand. This is especially relevant in
today's era where customers are well informed and quick to embrace new
technologies that create not only efficiencies and savings but are also
environment friendly. Moreover, if India’s manufacturing sector fails to digitize
quickly and catch up with the global Industry 4.0 trends and consumer
demands, it will not be able to reach its potential in attracting foreign

56 Nadkarni, S., Prügl, R. Digital transformation: a review, synthesis and opportunities for
future research. Manag Rev Q (2020). https://doi.org/10.1007/s11301-020-00185-7

57 Bughin, J. and Zeebroeck, N. V. (2017, May 09). The best response to digital disruption.
McKinsey Global Institute. Retrieved from mckinsey.com/mgi/overview/in-the-news/the-
right-response-to-digital-disruption (last accesses 2021, January 09)

58 PTC (2019). Quantifying the Value of Digital Transformation in Manufacturing, Page 1

59 Deloitte and Manufacturer’s Alliance for Productivity and Innovation (MAPI) (September

2019). https://www2.deloitte.com/us/en/pages/about-deloitte/articles/press-

releases/2019-deloitte-and-mapi-smart-factory-study-capturing-value-along-the-digital-

journey.html (Last accessed on 2020, November 11)

33
Impact of Digital Transformation Strategies on Performance of Manufacturing …

investment from companies who are looking to relocate their facilities from
China amidst the ongoing geo-political tensions.

Further, digitization is the key to unlocking the potential of India’s
manufacturing sector60 and moving towards achieving the government’s
ambitious target of manufacturing sector contributing to 25% of the GDP.
Digitization in the manufacturing sector can lead to accelerated and distributed
production, efficiency gains and harnessing of India’s natural advantage in the
IT sector (see Table 5 below).

Table 5: Digitization - key to unlock the potential of India’s
manufacturing sector

Accelerate Manufacturing can be made economically efficient at

and smaller scales with the help of digital manufacturing where

distribution technologies connect the factory floor with supply chains

production and the distribution network. India can greatly benefit from

this and distribute manufacturing opportunities across

states catering to different conditions.

Efficiency Digitization can help India make traditional industries more

gains efficient and also develop new cutting-edge technologies.

The Government aims to create an IoT industry in India

worth USD 15 billion by 2020. According to FICCI-EY

report, the manufacturing sector will account for 18% of

Internet of Things (IOT) revenue in India.

Harnessing Given its well-established IT sector and government

India’s natural initiatives such as Digital India and Start-Up India, India

advantage will be able to multiply the benefit of its inherent

advantages by embracing Industry 4.0 and digital

manufacturing successfully.

Source: Annunziata, M. (2016, October 06). Why digitizing industry will create more

and better jobs in India. Medium. Retrieved from

https://medium.com/@marcoannunziata/why-digitizing-industry-will-create-more-

and-better-jobs-in-india-70ca3d6a4a9 (last accessed 2021, January 09); IOT Policy

Document, https://www.meity.gov.in/sites/upload_files/dit/files/Draft -IoT-

Policy%20%281%29.pdf; Rishi, R. and Saluja, R. Future of IOT, FICCI and EY,

http://ficci.in/spdocument/23092/Future-of-IoT.pdf

60 Molly R (January 2020). Industry 4.0: A great future. Manufacturing Today.
https://www.manufacturingtodayindia.com/sectors/6089-industry-40-a-great-future (Last
accessed on 2020, November 11)

34
Chapter 4

Strategy Framework for Digital
Transformation

Studies suggest that over time in the coming decade with the increasing digital
maturity companies and the onset of Industry 4.0, there will be no separation
of a digital strategy from a business strategy any longer.61
However, when firms get started with digital transformation, they fail to
strategize effectively and follow a step-by-step guide with the following steps–
─ First, analyse every aspect of the business;
─ Second, reimagine the business model and aspirations;
─ Third, understand how new technologies affect working processes;
─ Fourth, understand where the business currently stands; and,
─ Fifth, build the transformation roadmap.62
According to a study by Wipro Digital (2017), 35% of the 400 senior executives
surveyed in the United States on digital transformation in their organizations
found lack of a clear transformation strategy to be a key bottleneck preventing
the firm from achieving its maximum potential.63 In an earlier study undertaken
by MIT Sloan and Deloitte University(2015), lack of a clear strategy was
identified a key hindrance by 50% of the respondents for digital maturity

61 Lipsmeier, A., Kühn, A., Joppen, R., & Dumitrescu, R. (2020). Process for the
development of a digital strategy. Procedia CIRP, 88, 173-178. doi:
10.1016/j.procir.2020.05.031

62 Atluri, V., Eaton, J., Kamat, M., & Rao, S. (2018). Tech-enabled disruption of products
and services: The new battleground for industrial companies. https://www.mckinsey.com/.
Retrieved 1 October 2020, from https://www.mckinsey.com/business-functions/mckinsey-
digital/our-insights/tech-enabled-disruption-of-products-and-services..

63 Wipro Digital (2017). New Survey Highlights Leadership Crisis in Digital Transformation.
Retrieved from https://wiprodigital.com/news/new-survey-highlights-leadership-crisis-
digital-transformation/ (Last accessed on 16 November 2020)
Impact of Digital Transformation Strategies on Performance of Manufacturing …

amongst firms that were at a very early stage of digitization.64,65

Digital Transformation is a strategic change for any company resulting into
profound changes in structure that creates something new. Transformation
occurs through a system of continual questioning, challenging, exploration,
discovery, evaluation, testing, and creation of an organization’s management
theory and application; beginning with the realization or revelation that the
organization’s current thinking (i.e., management theory) is incomplete,
limiting, flawed, or even worse – destructive (Daszko & Sheinburg, 2005)66

An examination of the extensive literature on Transformational Change shows
implementing and designing changes in an organisation requires consideration
of a variety of contextual factors. Those contextual factors could be internal as
well as external. The contextual factors relevant for adoption of technology in
manufacturing organizations can be assessed using Technology, Organization
and Environment (TOE) framework. The framework identifies three aspects of
an enterprise's context which influence the process of adoption and
implementation of a technological innovation: technological context,
organizational context, and environmental context (Tornatzky & Fleischer,
1990).67

The TOE framework provides a useful analytical framework that can be used
for studying the adoption and assimilation of different types of IT innovation.

Technological context describes both the internal and external technologies
relevant to the firm. A firm’s existing technologies are important in the adoption
process because they set a broad limitation on the scope and pace of

64 Study results were based on a survey of 4,800 business executives, managers and
analysts from organizations around the world – across 129 countries, 27 industries and
various organization sizes.

65 G. C. Kane, D. Palmer, A. N. Phillips, D. Kiron and N. Buckley (2015), Strategy, Not
Technology, Drives Digital Transformation, MIT Sloan Management Review and Deloitte
University Press..

66 Daszko, M., & Sheinberg, S. (2005). SURVIVAL IS OPTIONAL: Only Leaders With New
Knowledge Can Lead the Transformation. Retrieved 2 October 2020, from
https://www.researchgate.net/publication/228484177

67 Tornatzky, L.G. and Fleischer, M. (1990). The Process of Technology Innovation.
Lexington: Lexington Books.

36
Strategy Framework for Digital Transformation

technological change that a firm can undertake (Collins et al. 1988)68. The
ability of businesses to adopt new Industry 4.0 technologies will depend upon
its easy access and related support infrastructure. To be technology ready
firms have to train and educate their existing workforce and recruit new talent
and also address issues related to data governance and cybersecurity. There
should be compliance to standards and the technology should be
comprehensive, interoperable, inter-connectable, analytics-enabled, and
scalable.

Organizational context refers to descriptive measures about the organization
such as scope, size, and managerial structure. The Organizational Context
represents “characteristics and resources of the firm, including linking
structures between employees, intra firm communication processes, firm size
and amount of slack resources”. Organic and decentralized organizational
structures are associated with adoption (Burns and Stalker 196269; Daft and
Becker 197870).

Also, Organisational context can also be referred to organisational readiness.
A practical definition of organizational digital readiness/ preparedness is “level
at which an organization has optimized key attributes required to successfully
implement internet-enabled business strategies and initiatives” (Hartman,
Sifonis, & Kador, 2000).71 In general, Organizational readiness for change is a
multi-level construct based on the individual, group, unit, department and
organizational levels where the construct’s meaning, measurement and
interactivity with other variables differ (Weiner, 2009)72

Further, Organizational readiness for change is not only a multi-level construct,
but a multi-faceted one. Specifically, organizational readiness refers to
organizational members' change commitment and change efficacy to

68 Collins, P. D., Hage, J., & Hull, F. M. (1988). Organizational and technological predictors
of 417 change in automaticity. Academy of Management Journal, 31(3), 512–543.

69 Burns, T., & Stalker, G. M. (1962). The management of innovation. Chicago: Quadrangle
Books

70 Daft, R. L., & Becker, S. W. (1978). The innovative organization: Innovation adoption in
school 423 organizations. New York: Elsevier.

71 Hartman, A. & Sifonis, J. & Kador, J.. (2000). Net ready-Strategies for Success in the
Economy.

72 Weiner, B.J. A theory of organizational readiness for change. Implementation Sci 4, 67
(2009). https://doi.org/10.1186/1748-5908-4-67

37
Impact of Digital Transformation Strategies on Performance of Manufacturing …

implement organizational change (Weiner, 2009). Commitment to change
refers to organizational members' shared resolve to pursue the courses of
action involved in change implementation, and change efficacy refers to
organizational members' shared beliefs in their collective capabilities to
organize and execute the courses of action involved in change implementation
(Bandura, 2012)73.

Studies have suggested that organisational readiness for transformation is
dependent on five factors- Awakening, Vision, Method, Learning, and
Integration. The aim of awakening is to impress the importance of the need to
change, and it creates a deeply motivated vision for change. The method for
transformation is the system of profound knowledge which includes specific
thinking and the learning process involving the system of profound knowledge
as a lens through which beliefs and paradigms, systems and processes,
language and tools are developed and evaluated as the core of creating a
transformation. Lastly, the feedback and reflection loop suggests an iterative
and progressive transformation process. The challenge with each of these
components is communication with others in the system. One person’s
dissatisfaction has to be effectively communicated to others. Leaders need to
acknowledge the fears of employees. They should recognise that transforming
an organization requires create an environment of openness and participation
and preparing people for the journey.

There are four pillars of organizational readiness: Leadership, Governance,
Competencies and Technology (Lalic & Marjanovic, 2010)74 Dedicated and
strong leadership is the prerequisite of effective implementation of the other
pillars. The most successful organizations are those who have leaders who set
the vision to grow the organization using ICT solutions strategically.
Executives understand how web-based processes can create opportunities for
innovation, productivity, and efficiency, hence they empower the organization
to view information technology as a tool and a strategic asset.

The second pillar, Governance, describes the operational structure of the
organization, including assignment of authorities, roles, and responsibilities.

73 Bandura, A. (2012). Social cognitive theory. In P. A. M. Van Lange, A. W. Kruglanski, &
E. T. Higgins (Eds.), Handbook of theories of social psychology (p. 349–373). Sage
Publications Ltd. https://doi.org/10.4135/9781446249215.n18

74 B. Lalic and U. Marjanovic, Success of Social Networking Sites: Evidence from the
University of Novi Sad, in: F. Jakab (Ed.), 15th IEEE Int. Conf. Emerg. eLearning Technol.
Appl., IEEE, The High Tatras, 2017, pp. 233–238.

38
Strategy Framework for Digital Transformation

Governance establishes an effective model to organize, fund, and execute IT
initiatives. A flexible and effective governance model of successful Internet-
ready organisations establishes cross-functional teams to promote
collaboration, focuses near-term results and tangible returns on IT investment,
encourages accountability for e-business success, actively promotes web-
based applications, considers IT department as strategic consultants in
decision-making process, and dictates strong partnership between IT and
business.

The third pillar, Competencies, include strategic components to address an
organisation’s ability to plan, operational, managerial, and technical
competencies. Competencies determine how an organization addresses
customers’ demand or achieves its purpose. Technology as the last pillar
contains three essential elements: skills in technological domain, IT
applications and infrastructure. It determines the organisation’s ability to
develop or acquire a technology platform capable of supporting current and
future growth.

Further, researchers have also suggested that organisations should define
three sets of pre-requisites for prioritising digital initiatives and allocating
resources. (Atluri, Rao & Sahni, 2018)75. At the foundation or functional level
they should focus on data strategy, cybersecurity, cloud infrastructure, and
analytics and at the organizational level focus should be on agile operating
model and change fostering culture. Finally there should be emphasis on
design thinking and development of digital ecosystem. Azhari et al. defined the
model for the digital transformation focusing on eight dimensions of
digitisation, namely strategy, leadership, products, operations, culture, people,
governance and technology.76

The last element of TOE framework, the Environmental context is the arena in
which a firm conducts its business—its industry, competitors, the presence or
absence of technology service providers and dealings with the government.
The level of competition is intense and is expected to stimulate the adoption

75 https://www.mckinsey.com/~/media/McKinsey/Industries/Advanced%20Electronics/Our%
20Insights/Accelerating%20the%20impact%20from%20a%20tech%20enab led%20transf
ormation/Accelerating-the-impact-from%20a%20tech-enabled-transformation.pdf

76 Azhari, P., Faraby, N., Rossmann, A., Steimel, B., & Wichmann, K. S. (2014). Digital

Transformation Report. Retrieved from

http://www.wiwo.de/downloads/10773004/1/dta_report _neu. pdf

39
Impact of Digital Transformation Strategies on Performance of Manufacturing …

of new technologies and innovation. (Mansfield et al. 1977)77. Not only
competitive pressures but also consumer pull and influence of dominant firms
within the value chain can lead to adoption of new technologies by other firms.
(Kamath and Liker 1994)78. There is an unclear evidence about innovation and
technology adoption in the mature or declining industries (Tornatzky and
Fleischer 1990)79. Other factors in the environment that lead to technological
adoption are the availability of talent, skilled work-force, consultants, or
suppliers of technology and services. (Rees et al. 1984). Finally, regulatory
support can have a positive impact on the level of adoption. Regulatory
pressures, on the other hand can have both positive as well as negative effects
on technology. Investment in innovation and technology is inevitable if there
are constraints placed on the industry, such as reduction in industrial
emissions requiring pollution-control devices. Those firms, which do not
comply would have to face penalties or reputation loss.
Figure 7: TOE Framework

77 Mansfield, Edwin, et al. 1977. "Social and Private Rates of Return from Industrial
Innovations." Juarterly Journal of Economics May

78 A Second Look at Japanese Product Development , "A Second Look At Japanese Product
Development". Harvard Business Review, 1994, https://hbr.org/1994/11/a-second-look-
at-japanese-product-development.

79 Tornatzky, L.G. and Fleischer, M. (1990). The Process of Technology Innovation.
Lexington: Lexington Books.

40
Strategy Framework for Digital Transformation

Process for Development of Digital Strategies

While the need for digital transformation in manufacturing is apparent, the
strategy and process itself are not very straightforward. There are no standard
strategy templates available. Digital transformation of each firm needs to be
customized based on its level of digital maturity and goals.

According to the management literature, there are three levels of strategies –
(i) Corporate strategies (first level) which comprises the firm’s mission
statement, core competencies, and strategic business areas and programs; (ii)
Business strategies (second level) which comprises of the business model,
strategic success positions, products and services offered, measures for
implementing strategy and so on in the different functional areas, along with
the strategy compliant organisation work culture; and (iii) Sub-strategies (third
level) where specific goals are decided for each functional area.80 There is a
lot of ambiguity around choosing the ideal level for positioning a digital strategy
and whether the digital strategy should have a positioning integrated with
business strategy or as an independent strategy. As a result, most often digital
transformation gets implemented in silos which leads to loss of value from
potential synergies across the organization. 81

According to Andre Lipsmeier et al. / Procedia CIRP 88 (2020), digital strategy
should be positioned at the second level i.e. business strategy level. Although
initially a separate document, the digital strategy should eventually merge with
business strategy as the firm matures digitally. Further, the firm should adopt
a down-up approach82 in terms of the process for development of a digital
strategy as summarized in the paragraphs below (Figure 8).

Step 1: Form a strategic direction – digital guiding principles at the
corporate and business level. The digital guiding principles comprise of:

• Digital Assessment: Assessing the current level of digital adoption and
analysing the digital readiness of the firm.

• Digital vision, a concrete and feasible vision for the company with a

80 Lipsmeier, A., Kühn, A., Joppen, R. & Dumitrescu, R. (2020). Process for the development
of a digital strategy. Procedia CIRP. 88. 173-178. 10.1016/j.procir.2020.05.031

81 Lipsmeier, A., Kühn, A., Joppen, R. & Dumitrescu, R. (2020). Process for the development
of a digital strategy. Procedia CIRP. 88. 173-178. 10.1016/j.procir.2020.05.031

82 Contains elements of bottom up and top-down approaches to strategy development

41
Impact of Digital Transformation Strategies on Performance of Manufacturing …

time horizon of 5 – 8 years, and including digital transformation of
product and services and/or value creation (this section focuses on
value creation);

• Digital mission, comprising the rationale for digital transformation in
the firm;

• Digital policies, comprising central values around digitization in the
firm, for instance, principles governing digital leadership, data usage, IT
security, change management, people policies and so on;

• Digital targets and KPIs, providing concrete shape to the digital
transformation strategy and usually qualitative in nature; KPI’s provide
an effective tool for monitoring and,

• Digital terms, defining and unifying concepts related to digitisation
across the firm.

Step 2: Define detailed digitisation initiatives using a bottom-up approach. For
each digital vision, define Digital-Use Cases i.e. specific digitization initiatives
(e.g. predictive maintenance). Thereafter, group similar digital-use cases into
digital focus topics at the functional area level.

Step 3: Define concrete strategic objectives and identify digital focus topics at
the cross-functional level. Based on digital guiding principles and digital-use
cases identified, define specific strategic objectives for the functional
areas. Also, based on the function area digital focus topics, identify digital
focus topics at the business level, which will form the basis for cross-
functional synchronization.

Step 4: Assign quantitative values to digital targets set up in step 1, keeping
in mind the cross-functional topics

Step 5: Given the digital guiding principles and cross-functional topics, create
a digital strategy for each business unit.

The digital strategy comprises of primary strategic elements – digital guiding
principles , strategic direction (i.e. digital transformation of products or services
or value creation), and measures and organization, and secondary strategic
elements – digital culture, digital competencies, IT/OT architecture and value
creation network. These elements are specific for each business unit.

Step 6: Considering the strategic objectives identified, set-up concrete
digital programs and projects to implement the digital strategy at the
business level.

42
Strategy Framework for Digital Transformation

Step 7: Create umbrella digital programs at the corporate level that bring
together business level programs and create synergies across the
organisation.

Figure 8: Process for Development of Digital Strategies

Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7 Step 8

Corporat Form a Create

e strategic umbrella

strategy direction digital

(first - digital program

level) guiding s for

principle synergie

s s across

the firm

Business -Digital Create Assign Considerin Set up a
strategy vision cross- quantitati g the business level
(second -Digital function ve values implementati
al digital to digital strategic on roadmap
level) mission focus objectives for the digital
-Digital topics targets identified,
policies programs
set up identified
-Digital concrete

targets digital
-Digital programs

terms and

Function Identif Define Create projects to
al y specific
strategic a implement
strategy digital objective
(third use digital at the
level) s
cases, strateg digital
group
into y for strategy at
digital
each the

busines business

s unit level

focus

topics

at

functio

n level

Source: Lipsmeier, A., Kühn, A., Joppen, R. & Dumitrescu, R. (2020). Process for the

development of a digital strategy. Procedia CIRP. 88. 173-178. 10.1016/j.procir.2020.05.031

Digital Technology Adoption and Firm
Performance

Digital technology can improve the firm performance in two ways - by
increasing productivity through better workflow efficiencies and by improving

43
Impact of Digital Transformation Strategies on Performance of Manufacturing …

the financial performance. Technology adoption has been linked to productivity
and performance since the time of industrial digital revolution in 1990s.
Researchers such as (Barua et al. 199583) and (Brynjolfsson and Hitt
1998)84have attributed this relationship to a variety of factors. According to
Melville et al (2004), the main driver of an organisation’s performance is its
ability to collect and process information for decision making.85 Other
researchers also argue that it is the actual usage and not the investment in
technology that leads to improved performance (Devaraj and Kohli 2003) .86

Emerging literature on ERP systems and Supply Chain Management also
purport to similar views (Hitt et al. 2003)87. For instance, Baxter a
pharmaceutical company implemented an Analytical Systems Automated
Purchasing (ASAP) system which allowed hospitals to electronically generate
50k purchase orders annually directly from wholesalers reducing costs of data
entry (Vitale and Konsynski, 1986).88 Along with the automation of ordering
system the entire supply chain was automated including inventory systems
and stockroom space. The supply chain management system created several
efficiencies in the processes. In 1988, Johnston and Vitale,89 concluded that
organisations can reduce costs, time and resources deployed for managing
inventory and interacting with suppliers by implementing technologies such as

83 Barua, A., Kriebel, C. H. and Mukhopadhyay, T. (1995). "Information Technologies and
Business Value: An Analytic and Empirical Investigation". Information Systems Research,
6(1), pp. 3-23.

84 Brynjolfsson, E. and Hitt, L. M. (1998). "Beyond the Productivi ty Paradox".
Communications of the ACM, 41(8), pp. 49-55.

85 Melville, N., Kraemer, K. and Gurbaxani, V. (2004). "Review: Information Technology and
Organizational Performance: An Integrative Model of IT Business Value". MIS Quarterly,
28(2), pp. 283-322

86 Kohli, R. and Devaraj, S. (2003). Measuring Information Technology Payoff: A Meta -
Analysis of Structural Variables in Firm-Level Empirical Research, Information Systems
Research, 14(2), pp. 127-145.

87 Greve, Henrich & Hitt, Michael & Ireland, R. & Camp, Michael & Sexton, Donald. (2003).
Strategic Entrepreneurship: Creating a New Mindset. Administrative Science Quarterly.
48. 348. 10.2307/3556674.

88 Vitale, M. R. (1986a) American Hospital Supply Corp. (A): the ASAP Systems,Harvard
Business School Case Services, No. 9–186–304, Boston, MA 02163, March.Google
Scholar

89 Johnston, H. and M. Vitale. “Creating Competitive Advantage with Interorganizational
Information Systems.” MIS Q. 12 (1988): 153-165.

44
Strategy Framework for Digital Transformation

electronic data interchange, internet-based procurement systems, and other
interorganizational information systems.

Dell Computer showed improvements in sales and market share by enhanced
customer interactions through a customer relationship management software
and online technical support capabilities (Rangan and Bell, 1999).90 Another
example of technology based customer relationship is of UPS which handles
700,000 package tracking requests via the Internet every day. The company
benefitted customers by reducing costs from USD 2 spent on telephonic
enquiry versus 10¢ per piece for the information provided through the Internet
(Seybold and Marshak, 1998).91

Several researchers have also examined the relationship between productivity
of employees working on technology and a firm’s productivity. Their estimates
are consistent with prior estimates of technology’s output (Black and Lynch,
1996).92

Therefore, many studies reveal clear positive relationships between firm’s
success in terms of productivity, cost reduction, and improvements in sales
with implementation of information technology (Bynjolfsson and Hitt (1995)).93
However, some studies have found that success varies with the size of firms
and size of investments. There are questions about the success of these
variations. Some companies spend disproportionately on their digital
strategies. These expenditures or investments are mostly on intangible assets
such as implementation of new processes, acquiring and developing human
capital, and major transformational change management, which may not be
recorded in the financial statements.

Newer studies explore the impact of technologies such as artificial intelligence
and machine learning on firm performance (Cockburn et al. 2017).94 They

90 Rangan, V. Kasturi, and Marie Bell. "Dell Online." Harvard Business School Case 598-
116, March 1998. (Revised March 1999.)

91 Seybold, P. B., & Marshak, R. T. (1998). Customers.com: how to create a profitable
business strategy for the Internet and beyond. New York: Times Business.

92 Black, Sandra & Lynch, Lisa. (1996). Human-Capital Investments and Productivity.
American Economic Review. 86. 263-67.

93 Brynjolfsson, E. and Hitt, L. M. (1998). "Beyond the Productivity Paradox".
Communications of the ACM, 41(8), pp. 49-55.

94 John P. O'Doherty, Jeffrey Cockburn, Wolfgang M. Pauli, Annual Review of
Psychology 2017 68:1, 73-100

45
Impact of Digital Transformation Strategies on Performance of Manufacturing …

conclude that such technologies increase the value of existing assets and
resources by complementing them. Therefore, we can expect that there are
invisible and intangible benefits of digital technologies.

Impact of Information Technology Investments –
Financial Variables

Productivity

For measuring productivity - sales or value added can be used as the output
and labour, information technology and materials can be used as inputs. This
is modelled using the Cobb-Douglas Production Function (Brynjolfsson
1998).95 In this study, we captured the input variable of technology adoption
by conducting text analytics on firm’s published media and annual reports.

Profitability

Another important alternative method of measuring performance is the
measure of profitability, derived from financial statements. Prior studies such
as research conducted by the MPI group have stated that artificial intelligence
helps manufacturing companies identify defects early in the production
process and with reduced human errors, which in turn helps in lowering costs
and improving the profitability of the firms.96 Accounting profits such as
Earnings Before Interest and Taxes (EBIT) or Net Profit (PAT) allow diversity
of interpretations of performance and variables that go into the calculations of
these figures help in interpreting the performance from various perspectives
such as performance of resources, marketing strategies, costs, and so on.

Ratio (Measure ) Numerator Denominator

Gross Profit Margin Gross Profit Sales

Return of Assets Pre-tax Income Assets

However, there are certain limitations of these variables in capturing firm
performance. These ratios are not forward looking as they are derived from

95 Brynjolfsson, E. and Hitt, L. M. (1998). "Beyond the Productivity Paradox".
Communications of the ACM, 41(8), pp. 49-55.

96 Howells, Richard. "SAP Brandvoice: How Industry 4.0 Boosts Productivity And Profitability

In Intelligent Factories". Forbes, 2020,

https://www.forbes.com/sites/sap/2020/07/01/how-industry-40-boosts-productivity-and-

profitability-in-intelligent-factories/?sh=4bfabbfa48ec. Accessed 28 Dec 2020.

46
Strategy Framework for Digital Transformation

past financial information and are distorted by accounting conventions. These
ratios do not reflect risk and do not capture the value of intangible assets. They
also do not reflect time lags necessary for realizing the potential of
organizational change.

Market Value

Another important financial performance metric is the total market value of the
firm which serves as an alternative to accounting measures. Various studies
have used different constructs of market value such as Tobin’s q ratio which
is defined as stock market valuation of a firm divided by calculated book value,
intangible assets and technological assets (Hall 199397; Hirschey 198298).
Therefore, market value can be used as a reasonable measure to estimate the
value of tangible as well as large intangible assets such as value added by
human capital or organisational capital or value of improved information
systems. Even though it is difficult to measure these intangible assets, market
value is able to capture some insights into the impact of information
technology-related intangible assets. These intangible assets have greater
impact in the long run than the short term. Berndt, Morrison and Rosenblum,
199299 suggested that multiple years of adaptation and investment is required
to realise the benefits of such assets.

97 Hall, B. H. (1993). The stock market's valuation of R&D investment during the 1980's. The
American Economic Review, 83(2), 259-264.

98 Hirschey, Mark, 1982. "Intangible Capital Aspects of Advertising and R&D
Expenditures," Journal of Industrial Economics, Wiley Blackwell, vol. 30(4), pages 375-
390, June.

99 Ernst R. Berndt, Catherine J. Morrison & Larry S. Rosenblum, Journal of Econometrics,
vol. 65, no. 1, pp. 9-43, (1994) Annals of Econometrics

47
Chapter 5

Methodology and Research Findings

Section 1: Stakeholder Panel Discussions

Identification of Speakers

We conducted expert interviews with stakeholders who are directly or indirectly
involved in formulation and implementation of digital transformation in
manufacturing firms in India. The choice of experts was made on the basis of
the definition given by Bogner, Littig, and Menz, 2009100-“An expert possesses
technical, process and interpretative knowledge in their areas of expertise. ”
We used purposive sampling and made deliberate choices for deciding our
expert panels and interviewees. Our sample selection was done on the virtue
of the expert’s proximity to the research question and those who were able to
provide the richest and relevant information.
Glaser and Strauss (1967)101 suggested that the number of interviews
conducted impacts the quality of research. According to him, at least ten
interviews should be conducted to adequately analyse. We made a list of
approximately 100 stakeholders from different stakeholders groups like
Government, Academia, Industry Experts, Consultants and Business Leaders.
Then we contacted them by personally visiting, emailing and making phone
calls. We conducted one panel discussion and two roundtables. Those
speakers who could not join the roundtables were interviewed personally.
Overall, we interviewed 40 experts. The table below provides the number of
stakeholders and the method of their interviews or discussions.

100 Bogner, A., Littig, B., Menz, W. (Eds.), Interviewing Experts, 2009, Palgrave Macmillan
UK

101 Glaser, B., & Strauss, A. (1967). The Discovery of Grounded Theory: Strategies for
Qualitative Research. Mill Valley, CA: Sociology Press.
Methodology and Research Findings

Table 6: Number of Stakeholders and Methods of Interviews

Stakeholder Type Panel Discussion/ Individual/ One –to-

Government Roundtables one interview
Academia
Consultants 3 3
Industry Leaders
2 2

4 6

3 17

Total: 40 interviews

Research Methodology

We designed research questions on the basis of literature reviewed to
investigate the digital transformation phenomenon in India and the existing
ecosystem. Our research questions were directed to analyse the three pillars
of the TOE research framework. We conducted our discussions and interviews
in an open minded way to understand how different stakeholders describe
Digital Transformation/ Industry 4.0 approaches and how they understand the
terms and implementation in their real life context (Saldaña, 2014) 102.

Therefore, with an aim to understand the stakeholders’ perceptions, activities,
views/ opinions and their approaches, we adopted an interpretative research
method. In interpretive research, the aim is to view social reality as being
embedded within, and the reality is interpreted through a “sense-making”
process rather than a hypothesis testing process (Saldaña, 2014). 103 A list of
sample questions is provided in Appendix A.

Expert Interview/ Panel Research findings:

Our discussions with industry experts and senior executives in the
manufacturing sector in India yielded the following key insights -

India is far behind in the adoption of Industry 4.0 in manufacturing,
particularly amongst MSMEs. While large firms such as Tata Motors, Hero
Motor Corp, and Mahindra have embraced Industry 4.0 in India, at best these

102 Matthew B. Miles, A. Michael Huberman, and Johnny Saldaña. Thousand Oaks, CA:
SAGE, 2014. 381 pp. Johnny Saldaña. Thousand Oaks, CA: SAGE, 2013. 303 pp.

103 Matthew B. Miles, A. Michael Huberman, and Johnny Saldaña. Thousand Oaks, CA:
SAGE, 2014. 381 pp. Johnny Saldaña. Thousand Oaks, CA: SAGE, 2013. 303 pp.

49
Impact of Digital Transformation Strategies on Performance of Manufacturing …

can only be considered as one of cases of digital transformation. Several large
industries and manufacturing organizations in the country are still trying to
comprehend the meaning and adoption of Industry 4.0.

Furthermore, the level of modernization and technology adoption is highly
graded in India. For instance, while Siemens has adopted modern and smart
factory initiatives, has set up demo factories and is taking its solutions to
multiple industries, automotive plants located at the outskirts of Delhi NCR
have no form of automation on their shop floor.

In the MSME sector, most Indian MSMEs are still operating in industry 2.0.

“More than 80% MSMEs in India are still in industry 2.0 – there is hardly any
automation, and automation is not even Industry 4.0.” – Mr. Anupam Kaul (CII),
Principal & Head (Quality, Metrology & Standards)

This is a huge bottleneck for India as a country in terms of achieving an
industrial revolution as typically large industry cannot work in isolation of small
industry.

“You can’t unplug – large companies cannot be in industry 4.0 while others are
still in industry 2.0. In fact, MSMEs have to drive the industrial revolution in
India” – Mr. Anil Jauhri – CEO, NABCB

Therefore, there is an urgent need to handhold the MSME sector in India and
motivate them through a push from Original Equipment Manufacturers
(OEMs), regulatory pressure, demonstrating benefits to sales and profit, and
so on.

Awareness and accurate understanding about Industry 4.0 is a critical
issue amongst manufacturing firms in India: Manufacturing companies in
India are operating with a serious lack of understanding about Industry 4.0
technologies – their existence, application and benefits. While the problem is
more widespread amongst MSMEs, it is rampant in large manufacturing
organizations in India as well.

“Even in multi-billion-dollar companies in India, the expected awareness of the
senior management team in terms of Industry 4.0 policies is missing. They do
not have the minimum knowledge in terms of Industry 4.0 technologies such
as Internet of Things, Augmented Reality or Artificial Intelligence. Management
also tends to take a cautious approach with little investment to see benefits of
Industry 4.0 technologies before deployment to factories.” – Mr. Giri G,
Academic and Consultant.

50
Methodology and Research Findings

MSMEs consider basic digitalisation such as facial recognition for employee
attendance to be great advancements in technology adoption - almost
analogous with adopting Industry 4.0 technology. This reflects their complete
lack of understanding of Industry 4.0 and the anomaly comes out very clearly
in our primary survey results (discussed more in the sections below). In
MSMEs, areas such as office accounting and human resource management
may be found to be digitalised to an extent, however there is negligible
digitalisation on the production line.

Industry 4.0 is being adopted on a piece meal basis: Another key
characteristic of adoption of Industry 4.0 in the manufacturing sector in India
is that companies implement technology on a piece meal basis, for instance
from department to department.

“From last 2-3 years of interactions with Indian companies, only two companies
opted for a 5-year strategic plan for digital transformation and Industry 4.0.
The rest of the companies are adopting Industry 4.0 technologies on a piece
meal basis.” – Mr. Giri. G, Academic and Consultant

The government has started building an eco-system for Industry 4.0 in
India: A number of government agencies are working on the Industry 4.0 eco-
system in India since the last two years and are proactively organizing
webinars and trainings. For instance, NITI Aayog is working with McKinsey to
set up India’s first Digital Capability Centre (DCC) which will offer technologies
and a test bed to manufacturing firms in the country. The Department of Heavy
Industries launched the Samarth Udyog Bharat 4.0 initiative as part of its
scheme on Enhancement of Competitiveness in Indian Capital Goods Sector.
It aims to set up experiential and demonstration centers for Industry 4.0 to
increase awareness amongst manufacturing firms. Ongoing Common
Engineering Facility Center (CEFC) projects include Center for Industry 4.0
(C4i4) Lab Pune, IITD-AIA Foundation for Smart Manufacturing, I4.0 India at
IISc Factory R & D Platform, Smart Manufacturing Demo & Development Cell
at CMTI, and Industry 4.0 projects at DHI CoE in Advanced Manufacturing
Technology, IIT Kharagpur.104 However, the various government initiatives are
yet to show progress at the ground level.

Industry bodies have also set up initiatives to build an Industry 4.0 eco-system

104 SAMARTH Udyog Bharat 4.0. Retrieved from https://www.samarthudyog-i40.in/ (Last
accessed 2021, Jaunary 09)

51
Impact of Digital Transformation Strategies on Performance of Manufacturing …

in the country. For instance, the Confederation of Indian Industry (CII) has set
up a Smart Manufacturing Platform which will offer various services related to
Industry 4.0 including trainings, case studies, state level intervention centre &
demonstration facilities, policy research, standardization, and so on.105 As part
of the Smart Manufacturing Platform initiative, CII will work with key
stakeholders in the eco-system including government agencies, technology
providers, user industries, consulting and audit agencies, education &
research institutions, and international organizations. 106

Government support for MSMEs is inadequate: There is an urgent need for
the government to reach out to the MSME sector to understand their
requirements for adoption of Industry 4.0. While schemes have been rolled out
for the MSME sector, their implementation and performance are questionable,
a key indicator being large amounts of unspent money sanctioned for these
schemes, implying that the MSME sector is not interested in the offerings being
proposed under existing government schemes. MSMEs are struggling to stay
in the market and most concerned about bottom line issues.

Financial support schemes for MSMEs will be key in their transition from
Industry 2.0 to Industry 4.0.

India must build Industry 4.0 across the value chain to be able to grow
its manufacturing sector and capture the opportunity presented by the
current geo-political developments around China: India is well-placed to
adopt Industry 4.0 given favourable government intent, a large and growing
information technology sector and a young human resource with potential to
be trained in Industry 4.0.

Further, on the geo-political front, as the international market is trying to move
out of China, India presents a promising destination for relocation of global
manufacturing facilities. However, to capture this opportunity, it is imperative
for the country to build in and offer an Industry 4.0 enabled manufacturing
value chain. Fundamentally, Industry 4.0 requires India to be able to integrate
the new technologies to achieve a level of digital readiness of manufacturing
firms and also across other sectors.

105 CII Smart Manufacturing Platform. About CII Smart Manufacturing Platform. Retrieved
from https://smartmanufacturingindia.com/ (Last accessed 2021, January 09)

106 CII Smart Manufacturing Platform. About CII Smart Manufacturing Platform. Retrieved
from https://smartmanufacturingindia.com/ (Last accessed 2021, January 09)

52
Methodology and Research Findings

So far, the share of manufacturing in GDP is constantly shrinking and
manufacturing firms in India have not been able to make much head way
despite campaigns such as Make in India and Atma Nirbhar Bharat. Although
the Government has announced and is trying to implement Industry 4.0
schemes, the said schemes are not translating into tangible progress on the
ground and therefore adoption of Industry 4.0 is extremely poor. In comparison
to China, United States and the developed world, India is nowhere close in
terms of adoption of Industry 4.0 technologies.

“India’s strategy going forward needs to focus on spreading Industry 4.0 from
a few islands of excellence to all across the country.” – Mr. Sanjeeva Shivesh,
Founder and CEO of The Entrepreneurship School

In order to increase adoption of Industry 4.0 in India’s manufacturing sector, it
will be key to work on the following three dimensions:

• Build talent: Universities in India should collaborate with innovators and
leaders and offer Industry 4.0 programs.

• Focus on proximity to customers: This drives innovation and presents a
business case for it. For instance, MSMEs primarily engage in industrial
selling and B2B sales and are a feeder to larger businesses, who in turn
have the responsibility to act as a mother board to create an eco-system
that lifts MSMEs in the surrounding network and help them climb the
Industry 4.0 ladder. An example is automotive industries in Pune who
have modernized primarily because OEMs drove that innovation.

• Make government support well targeted and effective: The government
must focus on Industry 4.0 to make manufacturing more competitive in
India which will increase the sectors contribution to GDP as well as
exports.

The manufacturing sector in India needs to have an export focus to
develop Industry 4.0: The Indian market has grown tremendously over the
last 15 years with the manufacturing sector largely content by selling to the
domestic market. For selling to Indian consumers, the priority of manufacturing
firms is to make their products cheap. In order to achieve this, their focus is
primarily on ramping up capacity, with relatively less attention to quality. While
the focus is on meeting demands, the companies may not want to deviate their
resources towards innovation and implementation of digital technologies. They
do not like to have disruption in their normal business. This has been an
important factor leading to manufacturing firms in India being left behind in the
Industry 4.0 revolution as there is limited motivation.

53
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Large manufacturing firms in India which have focused on export have
improved their manufacturing process through implementation of Industry 4.0
technologies. An example of the same is Bajaj Auto, especially their 2-wheeler
segment, which earns over 40% of its revenue from exports. The
manufacturing set up of Bajaj Auto integrates Industry 4.0 technologies
significantly more than other automotive companies.

“The question for manufacturing firms adopting Industry 4.0 is to a great extent
dependent on priority and choice of market where the manufacturer wants to
sell. If the manufacturing firm intends to sell in the international market with
higher quality standards based on Industry 4.0 and competitors such as China
and South Korea, adoption of Industry 4.0 technologies is key. This criterion
comes from the vision of the company as to whether it wants to be an Indian
company or expand to be a global company, in which investment in Industry
4.0 technologies is imperative.” – Mr. Sandeep Ruhela, Head Group Strategy,
Escorts Ltd.

Further, it is noteworthy that manufacturing firms in the United States,
Germany, Japan and so on have an average standard profitability in the range
of 8%-10%.107 In India, manufacturing firms are chasing profitability in the
range of 15%-18%,108 implying that they are not reinvesting the money to
improve innovation or product standards. This is a key reason for the Indian
manufacturing sector lagging behind its counter parts across the world.
Therefore, the vision of the company is of great importance.

A dedicated digital transformation project is key for embracing Industry
4.0 at the firm level: Traditionally, manufacturing firms in India underwent
transformation only to increase revenue and decrease costs. However, given
increased competition, traditional manufacturing businesses in India cannot
afford to run in this way anymore. Current focus on implementing an effective
digital transformation strategy instead of focusing on financial performance will
be the key to their sustenance in the long run.

Further, it is important for manufacturing firms in India to set up dedicated

107 (January 2021) Margins by sector US. Retrieved from
http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/margin.html (Last
accessed 2021, January 09)

108 IBEF. Indian Manufacturing: Profit Potential and Opportunities Across The Value Chain .
Retrieved from https://www.ibef.org/download/Indian-manufacturing-profit-potential-and-
opportunities-across-the-value-chain.pdf (Last accessed 2021, January 09)

54
Methodology and Research Findings

Digital Transformation Projects with clear Key Performance Indicators (KPIs)
across departments and levels. This will help manufacturing organizations
prioritize digital transformation amidst their highly complicated manufacturing
operations coupled with tight schedules. Business owners need to take
specific decisions for implementation of digital transformation and incorporate
the same in their business vision.

“Key steps for planning digital transformation include (a) assess the current
ecosystem – current company performance, market share, competitors and
how to adapt to new technology, (b) undertake a SWOT Analysis, (c) define
goals, KPIs and a clear Digital Transformation Road Map, (d) identify roles and
responsibilities within and outside the organization, (e) prioritize what has to
go first, (f) monetize the digital transformation plan, (g) follow a milestone and
have monthly targets, and (h) have a strategy for financial and non-financial
factors, assigning adequate weightage to the non-financial factors as well.” –
Mr. Sooraj Jayaraman, Co-Founder and Country Head, Perfomatix

Further, given that manufacturing firms in India are cash sensitive, supporting
grants or funding from governmental or private organizations is a necessary
booster.

Companies should consider both quantitative and qualitative advantages
of digital transformation in their business case:

• Quantitative benefits – Gains in productivity, being able to deliver the
right products at the right time and at the right cost.

• Qualitative benefits – Being able to reduce the complexity in the
manufacturing system which automatically improves quality or lowers
down time.

Skill gap is a key bottleneck: Currently, there is a huge skill set gap for
embracing digital transformation and Industry 4.0 in terms of leaders and
availability of human resources who are capable of implementing the same.
These difficulties are key bottlenecks in formulating and implementing the right
digital transformation strategies. The skill gap bottleneck needs to be
addressed at the country level as well as at the firm level.

Discussions and Conclusions

The insights presented in this section based on expert interviews and panel
discussions highlight that India’s manufacturing sector is lagging behind in
undertaking digital transformation and adopting Industry 4.0 technologies.

55
Impact of Digital Transformation Strategies on Performance of Manufacturing …

There is a significant lack of awareness and understanding about Industry 4.0
and basic digitalisation initiatives, for instance, in human resource and
accounting, are considered to be great advancements. It is also noteworthy
that while the awareness issue is more acute amongst smaller organization, it
is apparently evident in large organizations as well. Successful digitalisation
cases amongst large organizations are more like exceptions rather than the
norm.

Further, while the government is undertaking a number of initiatives to create
a conducive eco-system for adoption of Industry 4.0 in the country, the
initiatives are too new and yet to show results on the ground level. Going
forward, the MSME sector will specifically need significant handholding and
financial support from the government to undertake digital transformation.

Therefore, India’s manufacturing sector has a long way to go and the
stakeholders must act quickly to speed up the sector’s adoption of Industry 4.0
technologies in order to (a) stay relevant and competitive in the worldwide
manufacturing landscape, (b) realize externalities from the ongoing geo-
political developments around China, and (c) increase the share of
manufacturing in India’s GDP (as envisioned by the Government).

At the firm level, key barriers to digital transformation include piecemeal
adoption that limits value creation for the manufacturing organisation.
Therefore, it is imperative for firms to undertake digital transformation as a
dedicated project with a focused strategy (including a vision, goals, KPIs, roles
and responsibilities and so on), assessing both quantitative and qualitative
benefits.

Furthermore, there is a significant skill gap amongst the workforce to embrace
Industry 4.0 in manufacturing firms. This is an issue that needs to be
addressed at a national as well as firm level by building an adequate
knowledge and training ecosystem.

Section 2: Findings from primary survey

Methodology:

We undertook a survey of 90 manufacturing firms in India to assess their (a)
perception on the state of the Indian eco-system to facilitate adoption of
Industry 4.0 in the manufacturing sector, and (b) firm’s organizational
readiness for digital transformation in terms of leadership, commitment and

56
Methodology and Research Findings

resources; organizational governance; motivations for digitisation; barriers to
digitisation; quality of physical infrastructure; and communication. The survey
was undertaken through telephonic interviews, face to face meetings, and
zoom calls. Questions were designed to obtain the scores on a Likert’s scale
from 1-5.

Figure 9: Methodology for primary survey

Undertook literature Identified (a) eco- Designed the
review to identify key system and (b) questionnaire
organizational
factors that affect readiness to be the
adoption of Industry two broad critical

4.0 categories

Undertook pilot Downloaded Converted
survey. Found that database of questionnaire to
manufacturing digital form on
there was an companies from survey monkey
awareness and Capital IQ and
understanding issue contacted
about Industry 4.0 executives through
amongst several LinkedIn and
executives. As a industry contacts
result, used personal
interaction for filling

the surveys.

Got survey filled by Cleaned survey data Undertook data
sharing link, face to analysis
face interviews or
Synthesized key
zoom/telephonic findings and
interviews
conclusions from
data analysis

57
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Demographic profile of the respondents:

Maturity of the organisation

11% 0-5 years
11%
5-10 years
52%
26% 10-15 years

More than 15
years

Turnover of the organisation

10% Upto INR 5 crore
19%
Upto INR 50
47% crores
Upto INR 250
24% crores
More than INR
250 crores

Ownership structure

28% Indian ( listed in
46% India)
Indian MNC (listed
16% outside India)
10% Foreign MNC

Incorporated in
India - Unlisted

58
Methodology and Research Findings

Research findings

An analysis of data collected through the primary survey yielded the following
insights:

ECO-SYSTEM

Our respondents agreed that India has several eco-system
characteristics required for digital transformation and adopting Industry
4.0, as agreed by 48% of the manufacturing sector executives surveyed
(Figure 10), and ‘neither agreed nor disagreed’ by another 48% of the
executives. The eco-system includes ICT infrastructure, adequate competitive
pressure, collaboration and knowledge sharing within the industry and a
perceived ability of suppliers to adapt to changes resulting from adoption of
Industry 4.0 technologies.
Most importantly, there is also a strong perception around relevant demand
with 89% of the executives surveyed ‘agreeing’ or ‘strongly agreeing’ that there
is a demand for products with new capabilities and features manufactured
using Industry 4.0 technologies in India. This is likely a result of the young
demographic profile of the country where the large youth population demands
and is quick to embrace new technology.
Figure 10: Perception on state of eco-system for adoption of Industry 4.0
in India

59
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Average eco-system 48% 48% 4%

There is significant collaboration and knowledge sharing within 48% 24% 24% 4%
the industry to develop and adopt industry 4.0 technologies in 62%
24% 14%
India

Suppliers will be able to adapt to changes emerging from
adoption of industry 4.0 by my organisation

My firm urgently needs to adopt industry 4.0 due to competitive 62% 24% 10% 4%
pressure

There is a demand for the products with new capabilities and 17% 72% 3%8%
features manufactured using industry 4.0 technology in India

Current government regulations are effective in enabling 7% 38% 31% 21% 3%
adoption of industry 4.0

There are adequate schemes by the government to facilitate 41% 31% 24% 4%
adoption of industry 4.0

India's ICT infrastructure is conducive enought to enable your 14% 41% 28% 17%
company to adopt industry 4.0 technologies

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%100%
Percentage of respondents

Strongly agree Agree Neither agree nor disagree Disagree Strongly disagree

However, the presence of a fairly conducive eco-system is not translating
into Industry 4.0 adoption on the ground. As discussed above, India is far
behind countries such as the United States, China, South Korea, Japan and
Brazil. Key reasons for this include:

• Relatively weak government support to enable adoption of Industry
4.0: Only 41% of the manufacturing executives surveyed agreed that
there are adequate schemes by the government to facilitate adoption of
Industry 4.0 (Figure 10). Further, only 45% of the executives found the
existing government schemes to be really effective on ground. This is
likely a result of Industry 4.0 focussed government initiatives being fairly
recent in India.

• Lack of technological know-how and tech-savy talent: Inadequate
technological capabilities and tech-savy talent emerged as top barriers
hindering adoption of Industry 4.0 in the manufacturing sector in India
(Figure 11).

• Concerns around cyber security: 62% of the manufacturing sector
executives surveyed cited lack of adequate cybersecurity infrastructure
as one of the top 3 bottlenecks for digital transformation (Figure 11).

60
Methodology and Research Findings

Figure 11: Percentage of respondents identifying a barrier as one of the
top 3 bottlenecks in adopting Industry 4.0 technologies and undertaking
digital transformation in their firm

High costs of adoption and 29%
implementation 40%
37%
Difficult to justify business case 70%
62%
Lack of commitment/ direction from 73%
senior management
Percentage of respondents
The firms faces lack of skilled tech-savvy
talent and specialists

Cybersecurity and data privacy concerns
with digital transformation

Inadequate technological capabilities/
Technical know-how

ORGANIZATIONAL READINESS

At the organization level, the most critical learning from the primary survey is
that there is a significant lack of awareness and understanding about
Industry 4.0 amongst manufacturing firms in India. While the problem is
much more acute in case of MSMEs, as also highlighted in the stakeholder
discussion section above, it is prevalent amongst large and listed firms as well.

While conducting the primary survey, our research team came across several
executives in both small and large firms who had very limited understanding
about Industry 4.0 technologies and their application in manufacturing. As a
result, we eventually had to alter our survey methodology from only sharing
the link to our survey form to conducting personal interactions for filling the
survey for several executives.

According to the primary survey undertaken, only around 35%, 39% and 47%
employees have a good level of awareness and understanding about digital
transformation and Industry 4.0 at the lower, middle and senior management
level respectively. As is expected, the proportion of employees with a good
understanding of Industry 4.0 is higher at the senior levels. This result leads

61
Impact of Digital Transformation Strategies on Performance of Manufacturing …

to two key implications for adoption of Industry 4.0 in India’s manufacturing
sector:

i. Limited awareness and understanding about Industry 4.0 at the senior
level, (a) directly impacts a firm’s ability to value its benefits and invest
in digital transformation, and (b) will lead to the firm unknowingly setting
much lower goals and aspirations in terms of digital transformation.

ii. Even in firms which attempt digital transformation, the lack of multi-level
readiness is likely to impede its success at the strategy as well as
implementation phase. As discussed above, formation of a digital
transformation strategy should be a down-up process (Andre Lipsmeier
et al. / Procedia CIRP 88 (2020)).

Figure 12: Level of awareness and understanding about digital
transformation and Industry 4.0

9% 13%

20% 17%

Percentage of respondents 44%

45% 43% 48%

30%

35% 39%
35%

Lower/operational 5% 17% Average
management Senior management
Middle
management

Extremely aware Very aware Somewhat aware

Not so aware Not at all aware

Further, interactions with company executives during the primary survey
revealed that many executives consider basic digitalisation of human resource
and accounting systems as significant advancements towards digital

62
Methodology and Research Findings
transformation and Industry 4.0. As a result, we expect the relatively
favourable results from the primary survey towards organizational readiness
to be overestimates.

Leadership commitment and resources

67% of the manufacturing sector executives surveyed agreed that their firms
have the leadership commitment and resources required to undertake digital
transformation and adopt Industry 4.0 technologies (Figure 13). The response
was favourable towards embracing Industry 4.0 across a number of factors
such as having a clear long term vision and strategic roadmap, top-down
direction, motivation and inspiration, resources in terms of money and time,
and evaluating the external environment (e.g. customers, competition, the
economy, technology, political and social conditions).
Executives also rated their firms highly in terms of change management
parameters of provision of adequate training to learn new technologies and the
management’s focus on deriving a key value proposition from digital
transformation.
Figure 13: Perception on level of leadership commitment and resources
for adoption of Industry 4.0 in their firms

63
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Average 67% 33%

Senior management is focused on key value 65% 13% 13%

proposition to be achieved from industry 4.0 9%
technologies and digital transformation.

My organisation provides adequate training to 65% 9% 26%
learn industry 4.0 technology and digital
processes effectively.

The management of my firm assesses the

external environment before planning digital 13% 79% 8%

transformation

The management of my firm understands the 75% 21% 4%
time required to implement digital
transformation across the firm.

My firm has enough resources or can acquire 63% 29% 8%
and deploy resources as needed to adopt
industry 4.0 technologies

The management of my firm directs, motivates 75% 21% 4%
and inspires others to participate in the
digitalisation initiatives

The management of my firm has a clear long 50% 17% 20%

term vision and strategic roadmap of adopting 13%
digitisation and industry 4.0

Percentage of respondents

Strongly agree Agree

Neither agree nor disagree Disagree

Strongly disagree

Governance

70% of the manufacturing sector executives surveyed agreed that their firms
have good governance to undertake digital transformation. Specifically, their
firms

• Develop business outcome based metrics to track digital transformation,

• There are formalised rules and procedures in place to undertake digital
transformation, and,

• Organisational control is not concentrated in the hands of a few people.

Further, 92% of the executives agreed that their firm has successfully
implemented change initiatives in the past.

64
Methodology and Research Findings

Figure 14: Perception on organizational governance for adoption of
Industry 4.0 in their firms

Average 70% 22% 8%

My organisation has a track record of

successfully implementing change 41% 51% 4%4%

initiatives in the past.

Controls in my organisation are not

concentrated in the hands of relatively 4% 70% 9% 17%

few individuals

My organisation emphasises on following

formalised rules and procedures and has 8% 70% 9% 13%

in place sound policies related to data…

My organisation has a governance model

that develops business outcome based 8% 70% 13% 9%

metrics for undertaking digital…

Percentage of respondents

Strongly agree Agree

Neither agree nor disagree Disagree

Strongly disagree

Further, along with governance, communication regarding digital
transformation initiatives across different levels in the organisation – in terms
of strategy and implementation - is also perceived to be fairly good by the
manufacturing sector executives interviewed.

65
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Figure 15: Perception on communication across the organisation for
adoption of Industry 4.0 in their firms

The progress, updates and changes related to

digital transformation in my firm gets 9% 74% 13% 4%
conveyed to all levels of the organisation in a

timely manner

The sequential steps for implementing digital

strategies are clearly communicated to all 4% 74% 13% 9%

stakeholders of the firm

Communication is simple, clear, candid, and

heartfelt and the stakeholders of digital 13% 74% 4%9%
transformation in my firm feel valued and

engaged.

Percentage of respondents

Strongly agree Agree Neither agree nor disagree Disagree Strongly disagree

However, it is interesting to note here that despite the favourable
leadership commitment, resources, governance and level of
communication perceived above, the level of digital transformation and
adoption of Industry 4.0 is quite low in the Indian manufacturing sector.
In the paragraphs below we present some key reasons for this.

Legacy infrastructure at the firm level

Manufacturing firms in India are grappling with legacy infrastructure which is a
key bottleneck in adopting Industry 4.0. For instance, a firm may have old
machinery that cannot be digitally connected and will necessarily have to be
replaced if the firm wants to undertake digital transformation. This will lead to
multiplication in costs and effort for the firm. 70% of the manufacturing
executives surveyed agreed that there is a high level of legacy infrastructure
in their manufacturing firms. Another challenge in terms of physical
infrastructure in manufacturing firms in India is the lack of comprehensive and
scalable technology infrastructure.

Further, as discussed above, employee skill is a significant challenge with only
48% of executives agreeing that employees in their organisation are

66
Methodology and Research Findings

competent enough for digital transformation and adoption of Industry 4.0
technologies.
Figure 16: Perception on quality of infrastructure for adoption of Industry
4.0 in their firms

Level of employee competence at your firm 9% 39% 35% 17%
to adopt industry 4.0 technologies

Level of firm having comprehensive and 9% 43% 26% 22%
scalable technology infrastructure 57% 22% 8%

Level of legacy infrastructure at your firm
which hinders adoption of industry 4.0 13%
technologies

0

Percentgae of respondents

Very high High Neither high nor low Low Very low

Piecemeal digital transformation

Digital transformation is being implemented in silos in manufacturing firms in
India. Only about 40% of the manufacturing sector executives surveyed agreed
that the level of understanding and commitment towards digital transformation
and Industry 4.0 is same across all departments in their an organisation. As
discussed previously, this is a critical barrier in realizing cross-functional
synergies (Andre Lipsmeier et al. / Procedia CIRP 88 (2020)), and is a key
reason for value destruction while investing in digital transformation initiatives.

67
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Figure 17: Piecemeal digital transformation

All departments of my organisation show 39% 26% 30%
the same level of commitment to digital 5%
35% 26% 35%
transformation

All departments of my organisation show
the same level of understanding of digital 4%

transformation and industry 4.0

Percentage of respondents

Strongly agree Agree

Neither agree nor disagree Disagree

Strongly disagree

Discussions and Conclusions

The perception survey of senior executives in India’s manufacturing sector
reveals that the prevalent eco-system is conducive to adoption of Industry 4.0
by manufacturing organisations in terms of ICT infrastructure, demand,
competitive pressure and industry collaboration. However, certain key
bottlenecks have limited digital transformation in the sector – (a) Government
initiatives are fairly new and are still to show results on ground, (b) There is a
significant gap in terms of technical knowhow and skill, and (c) Cyber security
is a major concern at the national as well as firm level.

In terms of organizational readiness, senior executives in small as well as large
firms in India’s manufacturing sector lack awareness, understanding, and
technical depth about Industry 4.0 technologies and their application in
manufacturing. This likely results in lesser value assigned to Industry 4.0 by
the senior management and/or setting of lower goals at the top. There is also
lack of multi-level readiness which impedes strategy formulation and
implementation for digital transformation.

Further, executives have a highly favourable perception of leadership,
commitment and resources, governance and communication in their
manufacturing firms in the context of organizational readiness for digital
transformation. This is likely to be an overestimation based on executives’
perception of basic digitalisation initiatives implemented in the organization,
misunderstood to be significant technological advancements. Nevertheless,
the perceived organizational readiness has not translated into greater digital

68
Methodology and Research Findings

transformation of manufacturing firms on ground due to issues around (a)
prevalence of legacy infrastructure on the manufacturing floor, and (b)
implementation of digital transformation in departmental silos, eroding cross-
functional synergies and limiting value creation.

TOE Framework Analysis

Using our perception survey scores we performed TOE framework analysis. A
correlation analysis of Organisational readiness score measured by adding
the leadership commitment scores, governance scores and change
management scores (O) was conducted with Technology readiness scores
(T) measured as quality of infrastructure for adoption of Industry 4.0 in their
firms. We also performed a correlation between Environmental context ( E)
measured by adding up ecosystem variable scores and technological context
scores.
Figure 18: TOE Framework Analysis

Correlations Analysis of TOE Factors

As expected we found a strong positive correlation between Organisational
context- leadership and change management 0.89 and Governance 0.73 with
Technology context. In our second pair – Environmental context with
technological context we found a significant positive relationship with a value
of 0.71. This implies that favourable external ecosystem with strong leadership
commitment, governance and overall positive change management climate
can lead an organisation to be ready for adoption of digital manufacturing
technologies (DMT) as shown in the charts below ( Figure 19). We note that
organisational readiness and ecosystem does exist in the context of Indian

69
Impact of Digital Transformation Strategies on Performance of Manufacturing …

manufacturing firms, however, there are other major impediments (as
discussed in the above sections) which have impaired the successful
implementation of digital transformation of manufacturing firms in India.
Figure 19: Correlations Analysis of TOE Factors

Section 3: Findings from Secondary Data Analysis

Data Collection

We took a sample of 25 manufacturing firms from each capital size - large,
medium, small and micro scale from the Capital IQ Database using stratified
sampling methodology. The manufacturing firms were identified using the list
of industry codes.
We accessed key financial data related to the financial year 2019-2020 to do
our cross-sectional productivity, profitability and valuation analysis. Our
analysis focused on finding the financial impact of digitalisation on
performance of firms.
We report sample statistics for the key variables used in our study in the charts
below which describe several key characteristics of the sample of
manufacturing firms classified into large, mid, small and micro-cap firms and
by their primary activities.

70
Methodology and Research Findings

Figure 20: Average Market Capitalisation, Revenue and Enterprise Value
of Sample Firms - Size Wise

30000 USD Mn

25000 Average of Market
20000 Capitalization] ($USDmm,
15000
10000 Average of Total Revenue )
($USDmm,

Average of Total Enterprise
Value ($USDmm,

5000

0
Large Cap Micro Cap Mid Cap Small Cap

Figure 21: Average of Profitability Margins and Operating Expenses of
Sample Firms- Size Wise

-30% Micro Cap 105%

30%

Small Cap 30% 93%
42%

Mid Cap 11% 49% 94%
90%
Large Cap 12%
46%

-40% -20% 0% 20% 40% 60% 80% 100% 120%
Gross Margins
OP Expenses % Net profit Margin

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Impact of Digital Transformation Strategies on Performance of Manufacturing …

Figure 22: Average EBIT growth % in last 3 years Size wise and sector
wise

Avg. EBIT Growth in last 3 years

45% 38%
40%

35%

30%

25% 16%

20%

15%

10% 5% 4%
0%
5%

0%

-5% 0%
-10%
-6%

7% 6% 6%
6% Mid Cap

6%

5%

4% 4%
Small Cap
3%

2%

1%

0%
Large Cap Micro Cap

72
Methodology and Research Findings

Figure 23: Average Market Capitalisation, Revenue and Enterprise Value
of Sample Firms-Sector Wise

30000
25000
20000
15000
10000

5000
0

Average of Market Capitalization ($USDmm)
Average of Total Revenue ($USDmm)
Average of Total Enterprise Value ($USDmm)

Total revenue of the sample companies has increased by 3% from 2017-2019
and EBIT has increased by 6%.

Figure 24: Average of Profitability Margins and Operating Expenses of
Sample Firms- Sector Wise

120% 95% 76% 96% 83% 93% 84% 87%
100% 45% 74% 47%
40% 69% 40% 44%
80% 13% 15% 39% 57% 16% 11% 26%
60%
40%
20%

0% Energy Health Care Industrials Materials Grand Total
Consumer Consumer

Discretionary Staples

Average of Net Income Margin Average of Operating Expenses %

Our study revolves around two variables- Digital Investments and Digital
Activities for measuring the extent of digitalisation. Average digital investment
in computer software and intangibles assets has been approximately USD 8
million in 2016 to 2018 in our sample companies.

73
Impact of Digital Transformation Strategies on Performance of Manufacturing …

For digital activities, we used a proxy for digital activities by counting the digital
terms in the firm’s disclosures, analyst presentations and conference calls. We
reviewed prior literature, numerous articles and glossaries to build a list of
digital terms related to digital transformation and Industry 4.0. For doing the
word analytics we used R and Python programming and confirmed our results
with the Lexos online software.109 An example of textual analysis is provided
in the Figure 25 below.

Figure 25: Example of Digital Words Cloud

Table 7: Digital Words for Text Analytics Cyber
Data analytics Security
Automation Platforms
Digital
Artificial intelligence Robots
Big data Internet of Things
Technology
Cloud Computing
Digitalisation

Machine learning

109 http://lexos.wheatoncollege.edu/word-cloud

74
Methodology and Research Findings

Figure 26: Average Digital Words frequency of Sample Firms Size wise
and Sector Wise

160.0 141.8
140.0

120.0 Sector Wise
100.0

80.0 67.0

60.0
37.5

40.0

20.0 11.8

0.0
Large Cap Mid Cap Small Cap Micro Cap

160

140

120

100 Size Wise

80

60

40

20

0

From the chart above, we can see that in large cap companies there is higher
digital activity as compared to other groups of firms. The median word
frequency of large cap companies is 83 while the mid cap firms have a median
score of just 50, small cap have a median score of 33 and micro-cap have a
median score of only 9. This means that in India MSME companies do not
yet talk about their digitisation or digital transformation in company
strategy statements published in media reports and annual documents.
This implies that digitalisation is not yet their main focus.

We have used digital investments and digital activity to study the impact of
various factors of financial performance. The objective of our research is to
evaluate the impact of digital transformation on the economic and financial
aspects of the manufacturing firms. We conducted correlation and regression
analysis by using E-Views Software, presented in the sections below:

75
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Impact of Digital Transformation (investment and activity)
on Performance

Before we examined the impact of digitalisation on financial performance and
explored a causal relationship between them, we performed correlation
analysis to understand whether a relationship exists between digitalisation and
financial variables such as productivity (sales), profitability and market value.
We chose these variables after extensive review of literature. Correlation
analysis was followed by a regression analysis to evaluate whether any causal
relationship exists between them.

Hypothesis 1: Higher adoption of technology is related with increase in
productivity (sales)

We analysed the impact of digital transformation on productivity by using sales
as a measure of productivity. This concept is borrowed from the Cobb Douglas
Production Function framework (Brynjolfsson 1996). We performed correlation
between last financial year’s revenue with proxy for digital activities (Sum of
Word Frequencies). We found a positive significant correlation between sales
revenue and the digital activities. We also performed correlation with digital
investments measured by capitalised or purchased software and found 0.38
as positive correlation, which is not highly significant.

Table 8: Correlation Scores between Digital Activities, Investments and
Revenue

Digital Activities Digital Investments

Total Revenue 0.70 0.38

Above results show that productivity (sales) and digital activities are positively
correlated. This correlation can point in either direction that digital activities
and digital investments lead to increase in revenue or it can also mean that
companies having higher revenues invest more in digitalisation as correlation
does not establish causal relationship. The causal relationship can be
analysed by performing a regression analysis. Since, there are more than one
variables that lead to increase in sales we controlled those variables and used
multiple regression technique. Data and analysis are presented in the next
section on regression analysis.

76
Methodology and Research Findings

Hypothesis 2: Higher adoption of technology is related with improved
profitability ( EBIT)

We analysed the co-movements of digital activity with the EBIT by using
correlation technique. We found a significant correlation of 0.74 between EBIT
and the digital activity and an insignificant positive correlation of 0.21 with
digital investments. Prior studies such as Hitt et al. 2002 and Aral et al. 2006
have used this measure to analyse the impact of ERP on firms.

Table 9: Correlation Scores between Digital Activities and Profitability
Ratios

Digital Digital

Activities Investments

EBIT growth -0.05 0.03

GP Margins -0.07 0.01

EBIT [CY 2019] ($USD Mn) 0.75 0.21

Return on Assets 0.02 0.02

Operating Expenses 0.68 0.03

When we performed correlation analysis of digital activities and digital
investments with EBIT growth we could not find any correlation, as shown by
close to zero numbers in the above table. This could be attributed to long
payback period required for digitalisation before the positive results can be
observed. We also performed correlations with Gross Margins and ROA but
could not find any significant correlation with digital activity and the margin.
We presume that there are various factors that contribute to gross margins
and the factors vary from industry to industry, the economic situation,
competitive pressures and demand from consumers. Prior studies have proved
that if firms adopt digitalisation due to competitive pressures, it is hard to reap
benefits in the short term.

Hypothesis 2: Higher adoption of technology is related with
improvements in Market Capitalisation.

Another important financial performance metric is the total market value of the
firm which serves as an alternative to accounting profit measures to analyse
the financial performance. Various studies have used different constructs of
market value which is defined as stock market valuation of a firm divided by

77
Impact of Digital Transformation Strategies on Performance of Manufacturing …

calculated book value, intangible assets and technological assets (Hall 1993;
Hirschey 1982). Therefore, market value can be used as a reasonable
measure to estimate the value of tangible as well as large intangible assets
such as value added by human capital or organisational capital or value of
improved information systems. Even though it is difficult to measure these
intangible assets, market value is able to capture some insights into the impact
of information technology-related intangible assets.

We performed correlation analysis of digitalisation variables with the market
capitalisation and found positive correlations. Digital Activity was found to be
more positively correlated than digital investments with market capitalisation.

Table 10: Correlation Scores between Digital Activities and Market
Capitalisation (log)

Digital
Digital Activities Investments

Market Capitalization 0.72 0.17

Figure 27: Correlation Scores between Digital Activities and Market
Capitalisation (log)

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Methodology and Research Findings

Correlation Scores between Digital Activities and Market Capitalisation (Size
Wise)

79
Impact of Digital Transformation Strategies on Performance of Manufacturing …

In addition to all firms taken together, we also performed correlation analysis
on different categories of manufacturing firms. We found that large-cap
companies have the strongest correlation with the digital activity as compared
to micro-cap having the least. This implies that large firms exhibit more digital
activity than the mid, small or micro firms. This can be explained with the fact
that large companies have more resources to invest in digital activities.

80
Methodology and Research Findings

Regression Analysis

Impact of digitalisation on Productivity (Sales)

Earlier researchers such as Brynjolfsson et al. (2017)110 and Cockburn et al.
(2017)111 have suggested that digitalisation leads to growth and productivity of
firms. When we performed regression analysis of Sales (log of sales) as a
dependent variable with digitalisation (Digital Activities) as an independent
variable while controlling for other contributing variables such as number of
labourers, material, asset growth, etc., our results were consistent with the
correlation results giving us a significant value of R2 - 67%. Our model was
tested with F values and it showed a good fit with a F value of 40.3. However,
our P values were higher than 0.05 at 95% confidence intervals and we
found that digital activities are insignificant in contributing towards
sales. Given these results we could not accept our hypothesis that digital
activities positively impact revenues of the firm.

However, on reversing the values of Y and X variables, we found that
companies which have higher sales adopt higher digitalisation activities. Even
though the R2 was low at 0.43 ( low significance) but P value was 0.002
which suggested that we could not reject the hypothesis and can
conclude that companies that have higher revenues adopt more digital
transformation activities. This could be true as higher sales revenues
generate better cash flows leading to higher digital investments.

We performed similar regression analysis for profitability and market values
also. In the first instance, when Y was a profit ratio or market value we could
not find a causal effect of digital activity on the financial profitability or market
value. However, in the next runs, when we used digital activity as the Y
variable, we found R2 value of 0.76 and P values lower than 0.05 suggesting
that companies which have higher market capitalisation and better profitability
are adopt digitalisation at a higher rate.

Our empirical regression analysis implied that firms with large revenues, better
resources and access to cash flows adopt more digitalisation. Our hypotheses

110 Brynjolfsson, Erik, Daniel Rock, and Chad Syverson. Artificial intelligence and the modern
productivity paradox: A clash of expectations and statistics. No. w24001. National Bureau
of Economic Research, 2017.

111 O'Doherty, John P., Jeffrey Cockburn, and Wolfgang M. Pauli. "Learning, reward, and
decision making." Annual review of psychology 68 (2017): 73-100.

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Impact of Digital Transformation Strategies on Performance of Manufacturing …

that digital transformation impacts financial performance could not be proved
given P values > 0.05, explaining that digital activities are an insignificant
contributor towards financial performance. But reverse analysis was true that
that better financial performance leads to better digital adoption.

Findings and Conclusions

The above analysis shows that the profile of firms that adopt digital activity are
larger, profitable and have better sales revenues. Moreover, we report
positive, though not so statistically significant, associations between digital
activity and total revenues, which is consistent with prior studies that attributed
the results to the performance pressure channel. Studies have shown that
when market pressures force the firms to go digital, digitalisation does not
necessarily result in improved sales. This is because in case of high market
competition it is very difficult for the firms to increase their market shares
through digital activities as price is the main consideration. This is also
consistent with our panel interview results and surveys we conducted that firms
which adopt digitalisation due to competitive pressures and on piecemeal
basis without being customer centric or focusing on customer value proposition
or understanding the rippling effects on different areas of the value chain may
find it difficult to generate more sales due to digitalisation.

Next, we hypothesised that digitalisation increases firm value. Our p values
made us reject this hypotheses. On the other hand, when we reversed our
regression equation, we found that firms which have higher market
capitalisation are more likely to adopt digitalisation. This suggests that firms
show early signs of going digital as they receive higher valuations in the
market. According to value creation theories, firms command better valuations
in the market if they provide value proposition to customers and provide better
quality products for their customers. Therefore, considering this theoretical
concept we can presume that firms will command higher valuations indirectly
if they focus their digitalisation strategies on value proposition and serve their
customers well by using technologies. In case of manufacturing firms, this is
possible through digitalising the products, innovating and re-designing the
product with tech capabilities and solutions for the customers.

Next, we examined the impact of digitalisation on profitability. We could not
prove our hypothesis here also. This is consistent with prior literature that firms
will realise improvements in profitability and returns only in the long term as
the payback of digitalisation could be very long and there are challenges of

82
Methodology and Research Findings
integration between various complementary technologies both inside and
outside the firm (Bresnahan and Greenstein 1996).112 Prior studies have also
found that margins of firms decline significantly in the short term after the firms
engage in digital activities. This could be due to the fact that digital investments
are costly in the short term and that benefits of digitalisation are eroded by
competitive pressures if the motivation to go digital was only technology push
or competition. Companies have to recruit and hire talent and spend a lot of
resources on their process redesigning and development of human capital
which leads to increase in operating costs, resulting in reduced profitability.

112 Bresnahan, Timothy, et al. "Technical progress and co-invention in computing and in the
uses of computers." Brookings Papers on Economic Activity. Microeconomics 1996
(1996): 1-83.

83
Chapter 6

Digital Transformation and
Implementation Case studies

To understand the digital transformation approaches and benefits in depth and
appreciate the multi-dimensional issues in natural practical environment we
also adopted case study approach. The purpose of case analysis is to
understand both the context, process and benefits of digital transformation,
and how they influence each other.

Data Collection

For case study analysis, we collected data by conducting interviews and also
through secondary data sources like annual reports and capital IQ. Financial
data for the past four years from 2016-2020 was used and conducted
interviews formally and informally. Interview conversations were documented
in the form of notes as a data collection strategy. The meetings were
conducted face to face and over zoom. We also collected data through annual
reports, press releases, media reports and strategy communications.

Case selection and description

We looked for two manufacturing companies in the same sector which have
been very successful in their digital transformation and implementation of
digitalization strategies. Hero motor Corp and Tata Motors both fitted this
requirement. We chose two companies so that we could compare their drivers,
process, and benefits achieved.

Methodology

In the section below we have provided synopsis of our case analysis for Hero
MotoCorp and Tata Motors. We also conducted textual analysis on annual
reports, press releases and media reports to understand the strategic
intentions and communications by the company about digitalization or Industry
4.0. Then we studied the co-movements of frequency digital strategy words
such as ( AI, ML, Big Data, Cloud Computing etc ) with the financials of the
company to interpret the impact of digital strategies on the company’s financial
performance.
Digital Transformation and Implementation Case studies

Digital Transformation Implementation at Hero
Motors

The Chief Information Officer of Hero MotoCorp- Mr. Vijay Sethi :

“Digital Transformation is not a one-time intervention – it is a journey”

The largest two-wheeler manufacturer embarked on its journey of digital
transformation in 2016 and took the first-mover advantage to race ahead to its
business rivals in the era of Industry 4.0. Hero Motors won an award for
"Manufacturing Innovator of the Year” for adopting digitalization. It undertook
a project to break the barriers between the physical and digital world and was
named as one of the top ten Gartners' Strategic Technology Trends 2017.113

Key objectives behind Hero Motor’s digitalization strategy were to improve
quality, boost productivity, and cost reduction so that they could offer high
quality products with better value to their customers. Their digital journey
started in April 2016 with the launch of their “Digital Twin” project at Vadodara,
Gujarat. They thrived to remodel traditional manufacturing approach to a digital
one, which is one of its kind in India. They redesigned their Vadodara
manufacturing facility using digital tools to incorporate needed changes and
enhanced capabilities before actually going in for physical implementation and
making investments. Digital Twin enabled them to examine their processes
and resources in a virtual context for enhanced productivity, cost
effectiveness, risk assessments and risk mitigation prior to actual
implementation.

Going Digital is about creating or unlocking value for the business by making
advancements in technology. Whether making new business models or
exploring new areas, delivering better customer experiences across the value
chain, re-engineering the ways of working in an organization including
collaboration and decision making, digitalization provides the new ways for
doing business. It is not just about using technology but also about changing
mindsets of the various stakeholders including employees especially about

113 Jha, S. (2017, March 14). How Vijay Sethi is driving the Digital Twin project at Hero Moto

Corp. Economic Times.. Retrieved from

https://cio.economictimes.indiatimes.com/news/strategy-and-management/how-vijay-

sethi-is-driving-the-digital-twin-project-at-hero-moto-corp/57625617 (last accessed 2021,

January 09)

85
Impact of Digital Transformation Strategies on Performance of Manufacturing …

using data to make better and faster decisions, changing the organizational
processes, policies, and ways of dealing with the customers.

Digital transformation initiatives at Hero Motors focused on SMAC (Social,
Mobile, Analytics & Cloud) and changing their processes and other systems.
The data related to temperature, humidity, vibration rates, rate of spinning,
quality parameters was captured using IoT sensors. Hero Motors also set up
digital cockpits in their factories where large TV screens and monitors display
real time data streaming from the IoT sensors installed in the machines. This
helps them to assess the health of their machines and apply predictive
maintenance. Besides IoT, the company has also adopted other technologies
like Artificial Intelligence , Machine Learning, Robotic Process Automation
(RPA) and Augmented Reality (AR)/Virtual Reality (VR).

As a part of this transformation, they also modernized their IT infrastructure
and applications and gave a huge thrust on enhancing competence levels of
their teams. While that was the basic step, they progressed by making it more
structured. Improving customer experience was the central theme of their
strategy. Focusing on this theme impacted other business processes and
capabilities - sales, operations, service, planning, etc positively and caused
rippling effects internally and externally. They looked at all the possible
technology solutions and interventions that could help them achieve those
objectives. They emphasized on using machine learning for thoughtful
maintenance, operational efficiency and forecasting demand. Hero Motors
also leveraged 3D Manufacturing in prototyping, simulations and testing on
one end. 114

The SAAS-based integrated talent management platform is a long-thought
strategy for spotting rising competencies and embedding them to this
acquisition framework. With an increase in the youthful workforce in the
organisation, they realized the easy use of social media to grasp more
employees and collaborations where they could also seek an expert opinion
on the side. The experience of buying bikes from Hero Motors is getting

114 Jha, S. (2017, March 14). How Vijay Sethi is driving the Digital Twin project at Hero Moto

Corp. Economic Times.. Retrieved from

https://cio.economictimes.indiatimes.com/news/strategy-and-management/how-vijay-

sethi-is-driving-the-digital-twin-project-at-hero-moto-corp/57625617 (last accessed 2021,

January 09)

86
Digital Transformation and Implementation Case studies

innovative through an online B2C marketplace. Hero Xperience app is offering
after-sales services that will track service coupons, due dates, maintenance
and would also monitor the bike performance over a period of time. A new
addition of a Xperience club and Hero Bikers Community would soon be
available, where one can mention associates/buddies and win exciting goods.
All of their inspiring advertisements as well as their plants – GPC, CIT , etc are
glorifying instances of them getting digital.

The management played an important role in building a digitally robust house
of MotoCorp, polishing the people to their fullest potential so that they could
connect with the technology and be able to use and communicate the
information generated by the smart machines. The leaders promoted creativity
and innovation, created space for employees to bring about new ideas to the
table for improving business and service models via many initiatives like
Innovation Cell, Idea Contest, Scenario Planning etc. Employees were
encouraged to use social platforms to build creativity, research, and
engagements. They implemented “mySuccess” - to digitize talent management
processes; engage, enable and empower the right people at the right time to
be future leaders. 115

All these technology interventions along with change management initiatives
landed the company in a splendid phase of high growth. Our corporate
disclosures and communication textual analysis showed that company used
more Industry 4.0 related words incrementally ( 70 words in 2016 to 139 words
in 2020). The sales of the company increased from INR Million 286,104.3 in
the year 2016 to 292,539 in 2020 resulting in a compounded annual growth
rate of 8.9%. The gross profit margin initially declined from 2017 to 2019 from
32.5% to 30% but then again increased in 2019-2020 to 31.50%. Earnings
before interest and tax (EBIT) margins of the company declined from 14%
approximately to 11% over the period . Hero Motocorp has been continuously
investing in both tangible and intangible assets. Huge investment was done in
BSVI infrastructure, a new plant capitalisation at Chittoor-Andhra Pradesh and
company continued to invest in innovation and technology. Changes in key
financial metrics are depicted in the following charts.

115 Key Technology Mega-Trends Transforming Our World. CMR. Retrieved from
http://cmrindia.com/key-technology-mega-trends-transforming-our-world/ (last accessed
2021 January 09)

87
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Figures 28-31 : Key Financial Data of Hero Motors over 2016-2020
Figures 28

Revenue Vs Digital Text Frequency

400000 324583.7 339708.2
350000
300000 286104.3 292539.7
250000
200000 70 73 95 139
150000 2016-2017 2017-2018 2018-2019 2019-2020
100000

50000
0

Figures 29

Total Assets in INR Millions

250000

200000 185043 196741
150000
100000 173967

153120

50000

0 2017-2018 2018-2019 2019-2020
2016-2017

88
Digital Transformation and Implementation Case studies

Figures 30

33.00% 32.76% Gross Profit Margins %
32.50%
32.00% 32.16%
31.50%
31.00% 31.73%
30.50%
30.00% 30.57%
29.50%
29.00%

2016-2017 2017-2018 2018-2019 2019-2020

Figures 31

EBIT Margins %

16.00% 14.29% 14.69%
14.00% 2016-2017
12.00% 12.97%
10.00%
8.00% 11.10%
6.00% 2019-2020
4.00%
2.00%
0.00%

2017-2018 2018-2019

Decline in EBIT margins can be accounted to increase in operating costs.
When digital transformation systems are implemented initially company has to
incur not only fixed investments but also has to increase the recurring
expenditures. Operating expenses have gone up due to transition from the
manual and traditional systems to the new automatic, cyber security and
database management systems. Employee costs also have increased due to
higher training costs and new hiring. It is usually expected that these expenses
reduce over a period of time as the systems set in and are well established.

According to a report prepared by the World Economic Forum (WEF) &
Accenture impact of digital transformation on financial performance of firms is

89
Impact of Digital Transformation Strategies on Performance of Manufacturing …

difficult to measure due to long payback period and short term and intangible
benefits. The study has suggested that companies must, therefore, understand
the limitations of the financial metrics inherited from the pre-digital era and
think about alternatives. Impact of digital transformation should be measured
by focusing on the non-financial metrics such as company’s Digital IQ,
Improvements in Productivity, Employee Engagement levels, Social Impact
created, Quality of Decision Making etc.

Thus, on non-financial metrics basis, Digital Initiatives at Hero MotoCorp have
resulted in the following benefits: 116

• Reduced human intervention in the quality testing process
• Round the clock continuous testing cycles.
• Reduced deviations in the testing plan and system controlled

automation.

• Increase in manpower productivity ( direct and indirect ) by 20% with the
use of Simplify (ECRS), Automation, Cycle time
optimisation/benchmarking.

• Reduced turn-around time.
• Higher quality assurance and proactive scheduling. Zero-tolerance on

quality

• Better monitoring of the test equipment.
• Reduced Total Productive Maintenance (TPM) enabled reduction of 16

losses.

• Higher accuracy, higher efficiency and faster decision making.
• Flexibility and agile manufacturing led to better asset utilisation on multi-

models.

• LEAP was launched for fixed cost optimisation and has focused on
material cost reduction with a target of ~50 bps of annual savings.

• Safe and enabling working environment of all manufacturing plants.

116 Hero MotoCorp Ltd Management Discussions. IIFL Securities. Retrieved from
https://www.indiainfoline.com/company/hero-motocorp-ltd-split/management-
discussions/237 (last accesses 2021, January 09)

90
Digital Transformation and Implementation Case studies

It’s evident from Hero Motors’ transformation journey that success of
transformational changes depends on involvement at all levels and
departments, commitment from the top, employee engagements and fostering
an environment of creativity and innovation. 117More than the transformational
changes, the focus should be clearly on how we create value for the customers
and the stakeholders. The digital transformation team at Hero Motors ensures
that their several IT/tech initiatives align with their business value propositions.
The IT team works with the business managers and understands their
improvement needs and challenges. Hero Motors also focuses on enhancing
the competence of their team and building their tech skills by conducting
training and workshops. They periodically review their policies every six
months to adapt to the internal and external environment changes.

With the inclusion of everyone into the process and making it as a ‘We’ instead
of ‘I’, it promotes the transparency and trust with the customers, shareholders,
investors giving so much credibility in the market.

Digital Transformation Implementation at Tata
Motors

“The Internet of Everything makes the world more efficient.” Jagdish Belwal,
CIO, TATA Motors

TATA Motors is an Indian listed automotive manufacturing company having
operations worldwide and headquartered in Mumbai, India. It is a subset of
TATA group. It’s product ‘Tata Tiago’ won ‘Compact Car of the Year’ Overdrive
Award in 2016 Tata Motors is committed to stay at the top in times of transition
and work with alternate firms within the Tata ecosystem to help create a viable
atmosphere for adoption of electrical vehicles.

Tata motors, like Hero Motocorp started their digital transformation journey in
2016. They spent 8-10% spend of their annual research and development
towards advanced and rising technologies. On an average, Tata Motors has
been hiring over five hundred cadres each year since 2016, where most of the
hiring happens through universities and institutions for the purpose of
innovation and implementation of digital technologies.

117 Jorapur, S. (2016, August 12). Digital transformation journey of Hero MotoCorp.
peoplematters. Retrieved from https://www.peoplematters.in/article/hr-technology/digital-
transformation-journey-of-hero-motocorp-13866 last accesses 2021, January 09)

91
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Research and development activities at Tata Motors are aimed at new product
development, sustainable technologies focusing on environment and safety of
vehicles. The company targets to reduce cycle time of product development
besides improving quality of their products and creating varied models through
the use of highly scalable digitalised technologies, virtual testing and
validations. The company has created global design studios for product
conceptualisation. Their business objectives, targets and KPIs are aligned with
digital transformation KPIs. The company has made significant investments in
their assets to enhance their capabilities and have implemented technologies
like computer aided and knowledge based engineering, digital mock up and
virtual build to reduce the time and improve quality. They also used in-house
based knowledge-based engineering framework, (KNexT), the information of
engineering processes is captured within the style of rules and reused. 118
These applications perform complicated operations with automation, thereby
eliminating the manual errors and providing faster results. Tata motors has
implemented vehicle electronics initiatives and driver information technologies
with IT enabled services. The company collects and analysis data for failure
prediction to the end customer.

Digital initiatives taken by Tata Motors also include mastering of product data
and processed using 3D digital designing and creative solutions in
collaboration with global partners. The company implemented a unified
Product Lifecycle Management (PLM) system for each passenger and
business vehicle across various countries and locations. 119Today, PLM is
employed 100% for all new vehicle development programs with progressive
modification management method. delivering insights into engineering
changes of car information at every unleashed milestone, facilitating project
groups to review changes visually. In this, integrated approach of 3D mental
image, issue management and alternate comparison was useful to accurate
design reviews, distinguish critical areas of focus and facilitate the cognitive
process for absolute decision making. Tata Motors has digitized multiple
business processes by changing either paper based or email-based processes
into laid out online applications using first in-house developed platform. 120

118 News and Stories | Tata group. (2020). Retrieved 9 December 2020, from
https://www.tata.com/newsroom

119 News and Stories | Tata group. (2020). Retrieved 9 December 2020, from
https://www.tata.com/newsroom

120 Digital Product Development Systems team anchors the digital transformation efforts at

Tata Motors. Express Computer. Retrieved from

92
Digital Transformation and Implementation Case studies

The company has also developed and tested the TAL BRABO – robotic
solutions in over 50 work streams which can be used by sectors like Light,
Aerospace, Automotive and other Engineering, Precision Machining, Software
Testing, Electronics, etc to simplify manufacturing, improve quality and
productivity.

They did not stop at that. To meet the customers' aspirations of driving high-
tech care and to embrace digital technology-driven innovation and disruption
company partnered with Microsoft. Through this collaboration Tata Motors got
access to artificial intelligence (AI), advanced machine learning, and the
Internet of Things (IoT) capabilities on the global hyper-scale Azure cloud, to
extend the digital to the physical world creating safe digital driving and owning
experience for the buyers. 121The company also partnered with Cisco for better
connectivity and teleconferencing products. Tata Motors recognizes the impact
of the Internet of Everything (IoE) on every segment of value chain. As a result,
TATA Motors is providing better service to its customers. 122

With the transformations moving towards Industry 4.0 ,TATA Co. and CII in
collaboration have set up a centre for digital transformation named 'Vision'.
TACNet 2.0 (Tata Motors AutoMobility Collaboration Network 2.0)123 facilitates
a centre of automobility innovation through partnerships for brand new
technologies and business models. It enables the business to interact with
start-ups and tech companies by sparking innovative solutions within
automotive technologies, quality scheme and exploring synergies.

https://www.expresscomputer.in/amp/interviews/digital-product-development-systems-
team-anchors-the-digital-transformation-efforts-at-tata-motors/31458/ (last accessed
2021, January 09)

121 (2017, February 16). Tata Motors and Microsoft India collaborate to redefine the connected
experience for automobile users. Microsoft. Retrieved from
https://news.microsoft.com/en-in/tata-motors-and-microsoft-india-collaborate-to-
redefine-the-connected-experience-for-automobile-
users/#:~:text=Tata%20Motors%20will%20leverage%20Microsoft's,a%20highly%20pers
onalized%2C%20smart%20and (last accessed 2021, January 09)

122 https://economictimes.indiatimes.com/tech/ites/tata-communications-and-cisco-partner-
on-fully-managed-contact-centre-solution/articleshow/71195068.cms?from=mdr

123 Sangani, P. (2019, September 19). Tata Communications and Cisco partner on fully
managed contact centre solution. Economic Times, Retrieved from
https://www.google.com/amp/s/www.theweek.in/news/biz -tech/2019/09/18/tata -motors-
launches-tacnet-to-startups-for-digital-auto-solutions.amp.html (last accessed 2021,
January 09)

93
Impact of Digital Transformation Strategies on Performance of Manufacturing …

The main challenge for the company was to change the legacy infrastructure
running on previous heavy investments. With multiple legacy systems across
locations, their modernization needed prioritization and therefore needed a
dedicated effort and time window for each project. Concurrent modernization
might have resulted in failure and disruption. To achieve their digital
objectives, Tata Motors focused on multi stakeholder management model,
compliances and IT security.

The company acknowledges the anxiety of employees so to unfreeze the
employee resistance it focused on employee engagement by providing them
training and coaching and encouraging their participation in innovation
challenges. They conducted digital and online skills assessment, to identify
educational priorities for every role, with intervention through customized
exercises and courses. By enhancing the talents of its staff on future
technologies, this company has been ensuring a smooth transition towards
adoption of latest technologies and development of new products.

The company followed a unified strategy and there has been a strong
commitment and support of the senior management. The Digital development
Systems team has been in place for implementing the digital development
roadmap to assist in creating a platform for Digital Transformation over many
years. Tata Motors has made its mark by bringing a culture of digital
transformation that’s agile, progressive and makes the business more
economical, productive, artistic and innovative.

Our textual analysis of corporate disclosures and communication showed that
company used more Industry 4.0 related words incrementally (192 words in
2016 to 201 words in 2020). Technology interventions at Tata Motors along
with change management led to positive improvements in their turnover levels.
The sales of the company increased from INR Million 26,98,496 in the year
2016 to 30,25,597 in 2019 but declined in the year 2020 due to COVID to INR
million 2616806. The company’s compounded annual growth rate of 5.8 % for
the period 2016-2019. The gross profit margin averaged at 43% higher than
the industry average of 35%. We noticed similar impact on EBIT margins as in
the case of Hero Motors. It declined 7% in 2016 to 1.25% in 2019. The
company has been continuously investing in both tangible and intangible
assets. Total asset turnover declined from 1.1x to 0.8x and Return on assets
also showed the same declining trend from 4.8% to 0.7% in 2019. Changes in

94
Digital Transformation and Implementation Case studies

key financial metrics are depicted in the following charts. 124
Figures 32-35 : Key Financial Data of Tata Motors over 2016-2020
Figures 32

Revenue (INR million) Vs Digital Text Frequency

3500000 2921087.5 3025597.8
3000000
2500000 2698496.6 2616806.2
2000000
1500000 192 186 173 201
1000000 2016-2017 2017-2018 2018-2019 2019-2020
500000

0

Figures 33

Total Assets ( INR Million)

3500000
3000000
2500000
2000000
1500000
1000000
500000

0

2015-2016 2016-2017 2017-2018 2018-2019 2019-2020

124 Capital IQ Database

95
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Figures 34

Gross Profit Margin %

45.00% 44.40%
44.00%
43.00% 42.40% 42.70%
42.00%
41.00% 41.20% 2019-2020
40.00%
39.00%

2016-2017 2017-2018 2018-2019

Figures 35

EBIT Margins %

7.00% 5.78% 4.04% 1.25% 0.11%
6.00% 2016-2017 2017-2018 2018-2019 2019-2020
5.00%
4.00%
3.00%
2.00%
1.00%
0.00%

Digitalisation helped the company to improve its inventory management and
production of engines on time to ensure smooth supply of engines to the
assembly line. The technologies also helped in providing early warning signals
for potential failures. It achieved mapping of energy consumption, time quality-
related data processing and analytics to monitor and improve quality at every
opportunity.

Analysis and Conclusions: Analysis of financial performance of both the
companies over a period 4 years revealed that digitalisation impacted total
revenue in absolute terms and gross profit margins positively however, return
on assets and EBIT margins declined. The positive impact on sales could be
attributed to the improved product designs, customer centric innovation and

96
Digital Transformation and Implementation Case studies
digitalisation strategies. The stable/ positive impact on gross profits is due to
improvement in productivity, reduction of costs and efficiency of production.
This is in line with the Deloitte Study (Deloitte ,2017) and (Cockburn Et Al
2017) which concluded that Industry 4.0 technologies enhance growth and
productivity of manufacturing firms and lead to cost savings.
However, we evidenced decline in EBIT margins and Return on Assets. This
is in contrast with some of the prior studies where researchers like Chen &
Srinivasan (2019) concluded that digitalisation improves return on assets over
a period of three years. Some other researchers on the other hand stated that
improvements to firm performance will only realize in the long term due to the
challenges involved in integrating new technologies (Bresnahan and
Greenstein 1996). Consistent with this expectation, we can expect that the
overall payback of digital transformation is a very long and it takes longer than
three years to achieve an overall improvement in return on investments (ROI).
Increased cost of investment (debt funding) and change management
initiatives increased the operating costs could be possible reasons for the
decline in ROA.
However, this should not be discourage companies from investing in Digital
Transformations. Digital investments are costly in the short run but will
hopefully pay off in the long run. We also noticed that that the intangible
benefits are quite encouraging for both the companies as they have benefitted
significantly in terms of their non-financial parameters and KPIs.

97
Chapter 7

Conclusions and Recommendations

From all the analysis discussed in Chapter 6, we conclude that India is far
behind in the adoption of Industry 4.0 in manufacturing, particularly amongst
MSMEs which are still operating in industry 2.0. A number of government
agencies are working on the Industry 4.0 eco-system in India since the last
two years and are proactively organizing webinars and trainings There is an
urgent need for the government to reach out to the MSME sector to understand
their requirements to help adopt Industry 4.0. There is an urgent need to
handhold the MSME sector in India and motivate them through a push from
Original Equipment Manufacturers (OEMs), regulatory pressure,
demonstrating benefits to sales and profit, and so on. Financial support
schemes for MSMEs will be key in their transition from industry 2.0 to Industry
4.0.

India must build Industry 4.0 across the value chain to be able to grow its
manufacturing sector and capture the opportunity presented by the current
geo-political developments around China. Our respondents agreed that India
has several eco-system characteristics required for digital transformation and
adopting Industry 4.0 are present and government has been taking initiatives.
However, the presence of a fairly conducive eco-system is not translating into
Industry 4.0 adoption on the ground. The manufacturing sector in India needs
to have an export focus to develop Industry 4.0.

A dedicated digital transformation project is key for embracing Industry 4.0 at
the firm level. The most critical learning from the primary survey is that there
is a significant lack of awareness and understanding about Industry 4.0
amongst manufacturing firms in India . Further, it is important for
manufacturing firms in India to set up dedicated Digital Transformation
Projects with clear Key Performance Indicators (KPIs) across departments and
levels. Companies should consider both quantitative and qualitative
advantages of digital transformation in their business case. Currently, there is
a huge skill set gap for embracing digital transformation and Industry 4.0 in
terms of leaders and availability of human resources who are capable of
implementing the same. There are also concerns around cyber security.
Manufacturing firms in India are grappling with legacy infrastructure which is a
key bottleneck in adopting Industry 4.0.Digital transformation is being
Conclusions and Recommendations

implemented in silos in manufacturing firms in India. The adoption in larger
firms also has been seen on a on a piece meal basis.

It is interesting to note here that despite the leadership commitment, resources
and governance structure and level of communication perceived above, the
level of digital transformation and adoption of Industry 4.0 is quite low in
the Indian manufacturing sector. This implies that favourable ecosystem
and external environment with strong leadership commitment, governance and
overall positive change management climate can lead an organisation to be
ready for adoption of digital manufacturing technologies (DMT). It is also
important for the manufacturing firms to have cross-functional teams, job
rotation, and collaboration among functional departments to enhance the
coordination to achieve effective implementation and create value by adoption
of technologies. Integration of such management practices and technologies
cumulatively enable successful implementation.

On study of co-movements we found that digital activities are correlated with
sales, profitability and market valuations suggesting that firms which have
higher market cap, revenues and profitability adopt digital strategies more than
those who do not have these factors. Our empirical analysis for evaluating the
causal relationship - impact of digital transformation on financial performance
did not yield desired results. We could not establish a predictive relationship
between digitalisation and financial performance. This could be due to the fact
that Industry 4.0 technologies have not yet diffused widely and is a very recent
phenomenon. Full effects of these technologies can be realised after a long
period as the payback period is very long and their implementation requires
development and implementation of complementary innovations. The
transformation also requires adjustments to costs, hiring and development of
human capital, reengineering of processes which can increase overall costs
affecting profitability negatively. Another reason could be competitive
pressures. If the firms adopt technologies as a response to cope up with tough
competition they in fact lose value. Additional costs incurred on
implementation may result in intangible benefits and capital which are not
visible in the financial statements.125 We believe that these benefits will be
reflected in market values of firms in the coming future. However, going
forward, these results should not discourage firms from adopting Industry 4.0.

125 https://www.nber.org/system/files/working_papers/w24001/w24001.pdf

99
Impact of Digital Transformation Strategies on Performance of Manufacturing …

Our analysis and evidence does provide optimism for manufacturing
companies. The breakthroughs of Digital Manufacturing Technologies are not
visible immediately but they promise larger effects as deployed across the
value chains. These technologies enable development of complementary
technologies and innovations which can create opportunities for MSMES and
other elements in the value chain.
Another important aspect will be development of non-financial KPIs and
toolkits for measuring the impact of Industry 4.0 as these technologies result
in non-financial benefits and development of intangible capital. In the long run,
financial markets will value the intangible capital created by technologies.
Overall, the reaping benefits of Industry 4.0 will not only require organisational
readiness, leadership commitment, governance, but also adaptation and
restructuring across value chain on society levels.

100
Research Limitations

The research undertaken has the following limitations:

i. The level of awareness and understanding about digital transformation
and Industry 4.0 is very low in India across all firm sizes and all levels
of management. This created several challenges for primary research.
Further, executives interviewed considered basic digitization of human
resource and accounting systems as significant advancements towards
digital transformation and Industry 4.0. As a result, favourable results
from the primary survey towards organizational readiness at the firm
level (e.g. strategy, leadership, resources, governance) are likely to be
overestimates.

ii. Given the very recent and still extremely low level of adoption of Industry
4.0 in India, it is very early for the study to be able to assess a definitive
impact of digital transformation on financial performance in the
manufacturing sector.

Another limitation of our study is that it is based on cross- sectional data.
For studying the impact of digital technology strategies longitudinal
study can be considered more suitable and can be used in future when
more companies adopt Industry 4.0 and more years’ data is available
post implementation.

iii. Further comparative research can be done for an analysis of digital
transformation strategies in Indian manufacturing Companies with
Companies in developed markets or Companies in Service sector with
companies in manufacturing sector.
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106
Appendix

Appendix A

Questions for Roundtables

A. Industry
B. Government

C. Academia/ Experts/ Think Tanks

Industry

1. Is India ready for digital transformation and Industry 4.0 in
manufacturing?

2. Where does India stand in the adoption of Industry 4.0 in
manufacturing? How does it compare to developed countries?

3. Is there enough awareness in India about Industry 4.0?
4. Is the adoption rate different amongst large manufacturing firms and

MSMEs?

5. What are the key reasons for low adoption of Industry 4.0 in India?
6. Does India have the right eco-system for embracing Industry 4.0 -

technology, skilled manpower, government policy support, funding?

7. How does low adoption of Industry 4.0 play out in terms of India’s
competitiveness in the global market?

8. What are the organization level challenges in adopting Industry 4.0,
particularly for MSMEs?

9. What are the characteristics of a successful digital transformation
strategy for a manufacturing firm in India? Are there any observations
of improvements in business performance?

10. Are CEOs of manufacturing firms in India read to lead digital
transformation? Do they have the mindset and commitment?

11. How do firms measure success of implementation of digital
transformation strategies?

12. How is the strategy different for large and small firms?
Impact of Digital Transformation Strategies on Performance of Manufacturing …

13. What are the firm-specific advantages and measures of success by
adopting Industry 4.0 in manufacturing?

Government

1. Where does India stand in the adoption of Industry 4.0 in
manufacturing? How does it compare to developed countries?

2. Is Industry 4.0 in manufacturing a top agenda for the government?
3. What initiatives is the government undertaking to encourage digital

transformation of the manufacturing sector - policy initiatives,
collaboration with the private sector, setting up labs, technology import
from developed countries, skill development, etc.?
4. How will the government ensure effective implementation of these
initiatives pan India?
5. Is there room for regulatory pressure to adopt Industry 4.0?
6. Are government sector enterprises embracing Industry 4.0?
7. How is the government measuring success in Industry 4.0 in the
manufacturing sector?

Academia/Experts/Think Tanks

1. Is India ready for digital transformation and Industry 4.0 in
manufacturing?

2. Where does India stand in the adoption of Industry 4.0 in
manufacturing? How does it compare to developed countries?

3. Is there enough awareness in India about Industry 4.0?
4. Is the adoption rate different amongst large manufacturing firms and

MSMEs?
5. What are the key reasons for low adoption of Industry 4.0 in India?
6. Does India have the right eco-system for embracing Industry 4.0 -

technology, skilled manpower, government policy support, funding?
7. How does low adoption of Industry 4.0 play out in terms of India’s

competitiveness in the global market?
8. What kind of initiatives/ projects should be undertaken by the

108
Appendix
government or through PPP to have successful adoption of digital
transformation?
9. Are government initiatives such as Make in India aligned with digital
transformation and Industry 4.0?
10. What are the characteristics of a successful digital transformation
strategy for a
manufacturing firm in India? How is the strategy different for large and small
firms?
11. What are the organization level challenges in adopting Industry 4.0?
12. What are the firm-specific advantages and measures of success by
adopting digitization and Industry 4.0 in manufacturing?

Appendix B

Primary survey link: https://www.surveymonkey.com/r/8ZG3S5T

109

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