A Framework to Speed Manufacturing's Digital Business Transformation

A Framework to Speed
Manufacturing’s Digital
Business Transformation
Manufacturers must fully embrace social, mobile, analytics
and cloud technologies to achieve the operational
excellence, agility, innovation and customer centricity
required to remain relevant with customers, business
partners and the entire manufacturing ecosystem.

2 KEEP CHALLENGING November 2015
Executive Summary
Businesses across the globe are changing fast, driven by emerging
digital technologies. Some are leading this revolution and defining
trends, while others are taking a wait-and-watch approach. In either
case, the undoubted winner is the customer. With unprecedented
information availability, product choices and channel options, customers
can call the shots. The race to identify and deliver on ever-changing
customer needs is gaining momentum as new players with novel
business models challenge the establishment.
This white paper highlights the challenges and opportunities that
manufacturers face as a result of this changing business landscape. We
cite several industry examples to illustrate how digital leaders in the
manufacturing space, such as Mercedes-AMG and Dow Chemical, are
defining new boundaries for performance and efficiency.
The paper also elaborates on four interconnected mandates that
manufacturers must embrace through emerging digital technologies:
• Operational excellence: Productivity and efficiency across processes
and functions.
• Agility: Response to internal and external changes.
• Innovation: Initiatives leading to cost reductions and new revenue
opportunities.
• Customer centricity: Meeting customer expectations.

A FRAMEWORK TO SPEED MANUFACTURING’S DIGITAL BUSINESS TRANSFORMATION 3A FRAMEWORK TO SPEED MANUFACTURING’S DIGITAL BUSINESS TRANSFORMATION 3
Manufacturers can determine their level of maturity for each area by
assessing three critical organizational attributes: leadership support,
execution mechanisms and performance management through
KPI tracking and management accountability. This paper can help
organizations rate their digital capabilities and benchmark themselves
against competitors, using our recommended reference framework and
scoring mechanism.
Finally, we present an approach for developing a transformation
roadmap and implementation approach built on our digital maturity
framework. Throughout the paper, we draw on insights from some of
our large transformational engagements across various manufacturing
organizations and geographies, as well as primary research, such
as our informed manufacturing CxO study (see our white paper
“Informed Manufacturing: Reaching for New Horizons”).

Understanding Global Manufacturing
Trends and Digital Imperatives
Manufacturers today face a changing business paradigm, in which emerging technologies
are forever changing how products are made, service is delivered and business is conducted.
Embedded technologies are enabling manufactured products to be more “informed;”1
new
stakeholders with innovative products and services are entering the ecosystem; traditional
supply chains are being disrupted through new channel options; and, above all, customers
are demanding an ever-increasing level of customization, not just in products and services,
but also across the entire procurement and product usage experience.
These trends have not changed traditional business fundamentals of profitably delivering
products and services that meet customer needs. Manufacturers continue to be laser-
focused on customer centricity, and are committed to achieving operational excellence
to attain cost and quality leadership. They are also pursuing agility and flexibility to adapt
to changes in the external and internal environments, as well as delivering innovative
products, processes and business models to meet sustainability objectives.
What is new, however, are the technological developments of the last decade. Advance-
ments across the so-called SMAC Stack (aka, social, mobile, analytics and cloud) and the
Internet of Things (IoT) have enabled a wide range of applications that were previously
unimaginable. Today, the objective is to use modern technology to do the same things in a
dramatically more efficient and effective way.
Our experience working with multiple manufacturers, as well as insights gleaned from
primary interviews with numerous industry stakeholders, points to four key mandates that
manufacturing companies must master through technology-led innovation (see Figure 1).
Manufacturing’s New Mandate
■ Omnichannel customer behaviors
demand a uniform experience
across channels.
■ Customers are more informed
because of proliferation of the Internet
(blogs, social media, user reviews, etc.).
■ Demand has increased for better product
usage and service experience.
■ Reduced product lifecycle/shelf life
necessitates faster new product
development and go-to-market
strategies.
■ Product commoditization and rise in
supplier power increases margin
pressure.
■ Green innovation efforts and
sustainability KPIs are required
as a result of penalty clauses.
■ Rising competition calls for higher
quality at lower cost.
■ Rising labor costs increase the
need for automation.
■ Demand has increased for product
customization and personalization.
■ Supply and demand volatility requires
higher supply chain resilience.
■ Changing business environment
requires reinvention across
the value chain.
■ Supply chain visibility is more
important due to large and complex
global supply chains.
Social Media
Telematics
Mobility IoT
AnalyticsTRENDS
Cloud
AGILITYCUSTOMER CENTRICITY
OPERATIONAL
EXCELLENCE
INNOVATION
Figure 1

• Operational excellence: Modern shop floors are highly automated and leverage the
industrial Internet (aka, the Internet of Things) to manage day-to-day operations, as well
as prevent disruption. Flexibility and efficiency — the traditional manufacturing goals —
are becoming increasingly business-critical, partly due to spiraling customer demand for
additional product customization and personalization with the least possible price impact.
In light of these trends, operational excellence is acquiring new meaning. It is no longer
only about incremental improvements in quality, productivity and waste reduction, but
also optimizing plant operations, leveraging technologies such as intelligent products,
enabling machine-to-machine collaboration and utilizing prescriptive analytics. A typical
example would be an automotive shop floor, in which embedded devices in the chassis
(informed products) communicate seamlessly with machines in the assembly line, and
direct specific processes and part types to be fitted to build the car according to the bill
of materials (BOM).
According to our 2014 global informed manufacturing study, 60% of respondents
believe that leveraging data from informed products is vital for product engineering
and development; 65% felt this data is critical to improving manufacturing operations.
Digital leaders, such as Mercedes-AMG, are beginning to leverage the huge volumes of
data generated from informed products to reduce waste and increase efficiency, especially
for high-investment equipment such as dynamometers. The car maker recently piloted a
quality assurance platform based on predictive analytics2
to optimize its engine-testing
capacity and speed resolution of engine issues. Rather than the traditional process of
analyzing results after all tests are conducted, Mercedes now compares historical engine
test data with real-time sensor data during test runs to identify quality issues and take
immediate action. The result: Significant time savings and less resource waste.
• Agility: Present-day supply chains are diverse, dispersed and complex to manage, as
the result of a global supply base with multiple manufacturing plants that address
the needs of multiple markets. Boeing, for example, has a supply base of more than
5,000 production facilities for its global operations3
and employs a half-million people
worldwide. To ensure smooth and responsive operations of these large and complex
supply chains, many manufacturers integrate their supply chain partners through
a common platform, facilitating communication and joint risk management. Supply
and demand volatility, on the other hand, remains the rule rather than the exception
following the 2008-2009 global recession, and it shows no sign of stability in the near
term. These trends have forced manufacturers to adopt technologies such as mobility
and cloud to enable greater visibility and control.
We estimate that close to 80% of all manufacturers and service providers are using
technology such as barcoding and RFID to generate more data from products, and
about half use this data for supply chain track-and-trace operations.
Companies such as Dow Chemical are leveraging cloud technology to generate
tremendous visibility and flexibility across the value chain. The chemical manufacturer
makes more than 6,000 products and operates in more than 36 countries, which results
A FRAMEWORK TO SPEED MANUFACTURING’S DIGITAL BUSINESS TRANSFORMATION 5
By introducing a platform that enables sample
requests, shipping and customer follow-up,
Dow has achieved campaign response rates of
40% to 50%, in addition to gaining tremendous
insights into sample performance.

in an exceptionally high volume of customer requests. By introducing a platform that
enables sample requests, shipping and customer follow-up, Dow has achieved campaign
response rates of 40% to 50%, in addition to gaining tremendous insights into sample
performance through automation of follow-up processes.4
• Innovation: The traditional integrated value chain from the supplier’s supplier to
the customer’s customer is now broken into distinct chunks, as new players leverage
emerging technologies to provide innovative products and services through newer
business models. Companies such as Flipkart5
(the India-based e-commerce giant also
known as the Amazon of India) and Paytm6
(the India-based online wallet and payment
solutions provider, similar to SQUARE in the U.S.) have become giants in a very short
span of time, snatching business from existing players. These companies are succeeding
by developing completely new business models that address
consumer pain points, such as stock-outs in physical stores,
and providing convenience, such as secure online transac-
tions and home delivery.
The challenge for manufacturers is to figure out where and
how to innovate, in order to reduce risk and ensure sustained
growth. While product engineering and technology remain
key targets for innovation, an area of growing importance is
the development of holistic strategies that connect the entire
product, service and delivery channel. Environmental sustain-
ability — ecosystem preservation, waste disposal and carbon
emission regulation — is another hotbed of innovation with
vast potential for manufacturers. With warnings of global
warming and increased customer awareness, manufacturers
must find innovative ways to implement green practices.
Another key challenge is nurturing a culture of innovation
within the organization. Investments in technology, such as
collaboration platforms for knowledge-sharing, can help with innovation, but they will
only yield results when accompanied by change management initiatives that bring about
a mindset shift to a new philosophy of working. In our experience, roughly a quarter of
all manufacturing organizations have a crowdsourcing/co-innovation platform to fuel
managed innovation, which has become a key differentiator for leading players.
Over the years, 3M has cultivated a culture of innovation7
through new processes and
platforms, enabling it to consistently maintain an enviable average gross margin of
around 50%. Employees are encouraged to use 15% of their time to work on projects
outside of their core responsibilities, and failures are gracefully tolerated. The company
has broken down silos within the company and between the company and its customers,
and makes available various forms of seed-funding to foster innovation.
• Customer centricity: Customers can now access information and conduct transactions
anytime/anywhere, whether on the Web, their smartphone or in a traditional store. The
number of users accessing the Web from a mobile device is quickly escalating, and is
expected to reach 7.6 billion by 2020, exceeding the current world population.8
The
adage “the customer is king” is perhaps more true today than ever, as a bad customer
experience can spread like wildfire over the Internet if not detected and corrected in
near real-time. An increase in competition, coupled with the explosion in Internet con-
nectivity and availability of mobile devices, has presented customers with a cornucopia
of choices and increased their expectations for product availability and a strong digital
experience. As a result, manufacturers today have little choice but to make their
products and services available across multiple channels and devices while providing
consistency of experience, service and information access.
On the plus side, intelligent data mining and analysis of social media information, among
other technologies, now make it possible for manufacturers to obtain an unprecedented
360-degree view of their customers’ behavior and needs. According to our informed
In our experience, roughly a
quarter of all manufacturing
organizations have a
crowdsourcing/co-innovation
platform to fuel managed
innovation, which has
become a key differentiator
for leading players.

Strategy
■ Top-down approach
■ Defined objectives
■ Budgeting
Execution
■ Effective processes
■ Enabling technologies
Performance Management
■ Target setting
■ Progress monitoring and
accountability
manufacturing study, roughly 70% of respondents had integrated social media and
internal planning system data to inform customer sentiment analysis and enhance
product research, development and planning.
Lenovo, for example, leverages advanced analytics9
for enhancing customer satisfac-
tion and loyalty. It aggregates customer data from all sources, including social media, to
provide a very high level of personalization via one-to-one customer relationships. This
also enables the company to run extremely effective targeted marketing campaigns to
maintain customer interest, from product announcement to release.
Understanding Manufacturing’s Imperatives
Many manufacturers have taken an ad hoc approach to addressing these requirements.
Many have implemented point solutions, while others are still grappling with where to
start and what is relevant to them and their customers and partners. To assess and build
effective digital capabilities, manufacturers need a comprehensive framework that spans
these four mandates, as well as a structured method that helps formulate a strategy,
lay out an execution process and develop comprehensive performance management for
tracking progress (see Figure 2). This framework includes the following:
• Strategy and vision statements. A formal strategy statement is indicative of leader-
ship buy-in and involvement and displays the requisite accountability and responsibility
to drive success. A top-down approach to digital transformation ensures that funding
is allocated for various initiatives, as well as successful adoption. For instance, in order
Pillars of Digital Excellence
Figure 2
Senior managers not only need to fund advanced
analytics to generate insights from the vast volumes
of operational data available on a modern shop
floor, but they also need to guide and motivate
the workforce to use these insights to improve
productivity and efficiency.

to achieve operational excellence, senior managers not only need to fund advanced
analytics to generate insights from the vast volumes of operational data available on a
modern shop floor, but they also need to guide and motivate the workforce to use these
insights to improve productivity and efficiency.
• Strategy execution. Systems and mechanisms must be in place to enable employees to
work more effectively toward the goal. Technology needs to be leveraged for collabora-
tion, visibility and efficiency. Take innovation, for example; co-innovation platforms must
be utilized by innovation groups to organize activities for idea generation, shortlisting
Assessing Current Maturity
Figure 3
Operational Excellence
Strategy
Alignment
How well does your operational strategy and
budget align with your ability to leverage emerging
technologies?
Execution
How do you rate the digital maturity of your current
operational processes from suppliers to customers in
terms of implementation and adoption?
Performance
Management
How comprehensively does your organization leverage
operational performance measurement technologies,
such as RFID, etc.? How do you provide the resulting
information to stakeholders?
Agility
Strategy
Alignment
Does your organization focus on increasing agility
through technologies that make employees more
informed and/or reduce the time required to perform
standard activities?
Execution
How well does technology enable your organization to
respond to internal and external change?
Performance
Management
Does your organization use clearly defined KPIs and
accountability to measure and improve agility across
the value chain?
Innovation
Strategy
Alignment
Does your organizational strategy include technology
investments that help enable idea generation,
evaluation and validation for achieving innovation
goals?
Execution
How well is innovation managed in your organization?
Do you use co-innovation platforms and
infrastructures, such as labs and testing facilities?
Performance
Management
How well does your organization measure innovation
performance and accountability in terms of idea
generation, bottom-line improvements and future
top-line contribution potential?
Customer Centricity
Strategy
Alignment
How inclined are leaders to implement new
technologies for better customer experience and
intelligence generation?
Execution
How effectively does your organization use actionable
customer insights across the value chain to produce
more customer-centric products and offer better
customer experience?
Performance
Management
Does your organization have technology support and
mechanisms in place for measuring customer centricity
and managing accountability?
and building proofs of concept in order to meet chal-
lenges in product design, business models, etc.
• Performance measurement. This third lever helps
quantify the current state and the future envisioned
state, while tracking progress along the way. Ac-
countability cannot be achieved unless the impact
is measured. For example, in order to meet agility
goals, corresponding KPIs need to be correctly de-
fined to prioritize initiatives and set targets for prog-
ress tracking.
The Maturity Framework
Manufacturers can assess their current state by
answering a set of questions across manufactur-
ing’s four primary imperatives (see Figure 3). These
questions are kept intentionally open-ended and at a
very high level to encourage discussion and debate. We
suggest that manufacturers interpret them in a way
that best represents their organization.
Scoring Mechanism
These mandates apply to all manufacturers – be it a
tractor company or a chemical company. However,
we have observed a varied degree of adoption from
different types of manufacturers as a result of the
nature of their business. A method for making these
questions more objective and capable of measuring
overall maturity across the themes is depicted in Figure
4 (next page). The weights are determined by our past
experience and roughly represent the sum total of
management efforts required, implementation costs
and perceived benefits.
While our approach offers a sound starting point, we
recommend that manufacturers tweak the framework
to match their business, based on industry sector,
target customer segment, geographic location, etc.
Scoring for each mandate is performed by rating the
three parameters, based on the guidelines provided,
and then applying the corresponding parameter
percentage to calculate the weighted rating.
For example:
Agility Score = 0.4 * Strategic Alignment + 0.3
* Execution + 0.3 * Performance Management

Assessing Digital Maturity
Scores are based on a scale from 1 to 3, where 1 represents least maturity,
and 3 represents highest maturity.
Figure 4 continued on page 10
Weight Basic (1) Advanced (2) Transformational (3)
Strategy
Alignment
30%
A digital operations strategy and
vision is defined.
The digital operations strategy
includes a department-specific
list of digital initiatives.
For all digital initiatives, owners
are identified, and implementa-
tion timelines are defined.
Leaders communicate the
operational strategy and review
progress to motivate the
workforce.
Leaders monitor improvements in
process efficiencies, productiv-
ity, etc. that result from any
initiative.
Leaders assign responsibility
to process owners for meeting
targets and achieving ROI.
Execution 40%
Data is captured and stored in a
central repository for root-cause
analysis.
Operational data from the central
repository is analyzed to define
standard operating procedures,
improve quality and reduce main-
tenance costs.
Harmonized data from the
central repository is analyzed
in real-time to predict failures
before they occur.
Engineering platforms assist
managers in scheduling and
performing operations based on
orders and capacities.
Engineering platforms automati-
cally schedule operations using
predefined decision models.
Engineering platforms auto-
matically schedule and perform
activities, such as sequenced
delivery of raw materials.
Performance
Management
30%
Cost, quality and productivity
data is manually collected and
displayed.
Informed products automatically
monitor performance data during
manufacturing.
Performance data is collected
and analyzed in real-time to
generate deviation warnings and
course-corrections.
Performance reports are
generated for monthly reviews.
Dashboard-based performance
data displays real-time updates
and drill-downs.
Mobility and cloud solutions
enable anytime/anywhere
reporting and alerts.
Agility
Strategy
Alignment
40%
Leadership is flexible to the
changing business environment,
but responses are mostly
reactive.
Proactive measures are taken
by leadership to handle changes
based on internal and external
information.
Leadership leverages advanced
analytics and scenario analysis
models to remain future-ready.
Customer-facing functions such
as sales and service continuously
evaluate new technologies for
agility.
Upstream functions such as
supply chain management have
technology budgets to improve
agility.
All functions, from product
development to sales and service,
invest in technologies to boost
efficiency and improve response.
Execution 30%
Digital platforms enable periodic
communication between
downstream functions
(such as sales) with upstream
ones (such as manufacturing).
Digital platforms integrate all
functions for demand and supply
visibility within the organization.
A common platform includes
upstream and downstream value
chain partners, such as suppliers
and retailers, for real-time
information on sales, inventory,
supplier excess capacity, etc.
Senior managers and key people
in the organization leverage data
to improve decision-making.
Almost everyone in the organiza-
tion uses data and basic descrip-
tive analytics.
A dedicated analytics team
supports the organization
with data analysis and insights
generation.
Performance
Management
30%
Business-level KPIs are used as
an indicator for agility improve-
ment as a result of technology
implementation.
Specific agility KPIs, such
as supply chain velocity and
turnaround time, are used to
prioritize investments and
develop a digital roadmap.
Specific agility KPIs are used to
prioritize investments and track
progress.
Accountability exists only for
implementation targets.
Accountability for improving
specific agility KPIs exists at a
function/department level.
Individual KPI ownership and
accountability exists for achieving
agility targets.

Innovation
Weight Basic(1) Advanced (2) Transformational (3)
Strategy
Alignment
50% Innovation goals and targets are
set mostly for product develop-
ment and marketing teams.
Innovation targets for additional
functions are set, such as sales,
service and operations.
Companywide and cross-
functional innovation targets and
goals are set.
Technology budget is mostly
in line with product design and
testing.
Technology budget addtion-
ally supports improvements to
cross-function, cross-geography
collaboration.
Technology budget additionally
supports the building of labs
that support innovation across
functions.
Execution 30% Incremental innovation is enabled
through the use of existing
facilities and resources.
Managed innovation is enabled
through events and fairs, with
dedicated resources leveraging
collaborative platforms.
Innovation additionally includes
work conducted with supply
chain partners for solving
industry-wide challenges, using
tools such as PLM-centric team
collaboration.
Basic tools such as CAD/CAM are
used to help with faster and more
efficient product innovation.
Simulation and virtual validation
tools are used to reduce design
and testing times.
Rapid prototyping, testing,
analytics and industrial 3-D
printing technology are used to
augment product development
capabilities.
Performance
Management
20% Innovation KPIs measure annual
cost savings and product perfor-
mance improvement.
Innovation KPIs addtionally
measure the number of viable
new product ideas, profitability
increases, etc.
Innovation KPIs additionally
measure future revenue possible
from new products and business
models.
Accountability and target-
setting are conducted for some
functions, such as R&D and
marketing.
Accountability and target-setting
are used across all functions,
from procurement to customer
service.
Individual, functional and cross-
functional targets are set, as well
as accountability for innovation.
Customer Centricity
Strategy
Alignment
40% Basic customer segmentation
is performed, based on account
value or demography.
Complex, multi-attribute
techniques for segmentation are
used, supported by CRM tools.
Advanced analytics drive
segmentation, leveraging next-
generation CRM tools.
A limited customization and per-
sonalization strategy exists.
Basic personalization is possible
through a multi-channel strategy.
Superior personalization is
enabled at the strategy level, for
one-to-one customer interac-
tions.
Execution 40% Key customer data is harmonized
and maintained in a central
repository for reference.
All customer data is maintained
and basic analytics are used
to support decision-making,
spanning product and service
delivery.
Comprehensive profiles are
developed for each customer,
including personal details,
spending patterns and preferred
touchpoints, with advanced
analytics for faster decision-
making.
Manual recording of customer
data is performed during inquiry,
purchase and service.
Feedback is generated through
online surveys and secondary
sources, such as social media.
Products and services are
co-created with customers, as
well as support across buying and
usage cycles.
Performance
Management
20% Customer satisfaction KPIs, such
as NPS and customer complaints,
are captured and monitored.
Operational KPIs, such as service-
ability and repeat service, are
monitored to measure customer
centricity.
Advanced customer metrics,
such as lifetime value and
sentiment scores, are periodically
measured.
Assessing Digital Maturity continued
Figure 4

Assess
Plan
Recommend & Transform
Current-State Assessment and
Competition Benchmarking
Recommendation
Workshop
Roadmap
Execution
Future State
Prioritization and Preparation
of the Business Case
Roadmap
Preparation
Operational
Excellence
Customer
Centricity
Agility
Innovation
Future State
Deﬁnition
Competitive
Lean
Green
Reliable
Connected
Roadmap execution
Lowest Priority Moderate Priority
Moderate Priority Highest Priority
B C
(Bubble size represents implementation risk)
BENEFIT
COST
Gap Analysis
Identify limitations
Review system
Conceptualize solution
Validate
1
3 4
6 7
5
2
Using the Framework
Manufacturers can use this framework to either devise a transformation strategy
themselves or hire a third-party to do so. Both approaches are covered in Figure 5.
Digital Transformation Approach
Figure 5

Phase 1: Assess
The first step entails thoroughly understanding both the as-is and to-be states of the orga-
nization. This stage typically involves conducting several workshops and interviews with
company stakeholders and external subject matter experts. Further, competitive analysis
should be carried out with local and global players.
Competitive Benchmarking
(Illustrative)
Envisioning the Future State (Illustrative)
Figure 6
Figure 7
2
1
1
1
1
2
2
3
1.5
1.5
1.5
1.5
2.5
2.5
2.5
2.5 0
0.5
1
1.5
2
2.5
3
Agility
Innovation Client
Benchmark
Business
Excellence
Transformational
Customer
Centricity
Supply chain visibility and flexibility
What-if scenarios and predictive analytics
Easy access to reliable and consolidated data for all
Crowdsourcing and co-innovation platforms
Collaborative operations planning and execution
Machine learning and
prescriptive analytics
Omnichannel platform
Collaborative tools for faster NPD
and process improvement
Tools for capturing VoC
Vendors &
Supplier
Plant Operations
& R&D Supply Chain &
Logistics
Sales &
Marketing
Dealer &
Customer
Experience
Management
Senior
Management
Corporate
Functions
Operational
Excellence
Customer
Centricity
Agility
Innovation
• Current-state assessment and competition benchmarking:
To get started, manufacturers must understand their current
strengths and limitations, as well as how their digital capabilities
compare with those of their competitors and best-in-class compa-
nies. Figure 6 offers a high-level representation of the result of a
typical competitor benchmarking and scoring exercise.
>> Conduct due diligence: Understand and document current sys-
tems and processes across the aforementioned industry man-
dates through observation and user interviews; play it back to
stakeholders for confirmation and approval.
>> Identify comparable organizations: Select one or more direct
competitors/best-in-class companies from across the globe to
serve as a comparison.
>> Complete benchmarking: Rate capabilities against
benchmark/s across each theme depicted in the framework in
order to gauge maturity levels.
• Future-state definition: This step involves defining digital capa-
bilities across the themes as the end-state vision. The future-state
vision is derived from the company vision, capability benchmark-
ing, technological developments and industry best practices across
the globe. Figure 7 provides a representation of an end-state vision
at the conclusion of the assessment phase, with broad improve-
ment areas highlighted with vision statements.

Phase 2: Plan
In this phase, further analysis of collected information is conducted to derive a list of ini-
tiatives that are eventually prioritized to prepare the digital transformation roadmap. This
phase entails the following:
• Gap analysis: Analyze differences in the current state and future vision for each
parameter and prepare a list of initiatives.
>> Identify limitations: Identify broad capability limitations and document them, using
the digital framework.
>> Review existing systems: Develop a detailed understanding of
as-is capabilities, along with additional requirements to address
documented limitations.
>> Conceptualize and validate the solution: Create a list of iden-
tified initiatives that meet all requirements, comprehensively.
• Prioritization and business case preparation: Determine the
relative importance of each initiative based on criticality and
return on investment.
>> Rate each initiative on a cost, benefit and risk scale. Plot them
in the risk benefit matrix, as shown in Figure 8.
>> Conduct estimated ROI calculations, starting from low-cost,
high-benefit quadrants, and prepare a broad-level business
case.
>> Present the business case to senior leaders for approval.
• Roadmap preparation: Create a detailed roadmap for a phased
implementation across each theme (see Figure 9).
© 2014 Cognizant
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Shop floor Manpower and Machine
Productivity KPIs
• C*$:A*1):"?$+'1,1>#'7B#'
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© 2014 Cognizant
9
Q1 Q2 Q3 W[& WX& WY& WZ& W[& WX& WY& WZ& W[&
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data visualization
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management
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#configurable products
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Product evaluation
System integration
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• NPD cycle time
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Cost-Benefit Matrix (Illustrative)
Roadmap Across the Four Mandates
Figure 8
Figure 9
Lowest Priority Moderate Priority
Moderate Priority Highest Priority
B
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F
E
D
C
(Bubble size represents implementation risk)
Benefit
Cost

Phase 3: Recommend & Implement
The final step includes:
• A recommendation workshop: Prepare a detailed business case (as depicted in Figure
10) for final budgetary approval. The business case should identify all revenue- and
cost-related metrics that would be impacted by the digital transformation, calculating
total implementation cost, agreeing upon improvement targets and arriving at the net
business value gain. The detailed business case is presented to the key stakeholders
(decision-makers), and concerns are cited and addressed. The workshop helps in final
validation and user buy-in before implementation. Stakeholders also agree on imple-
mentation timelines and risk mitigation measures for the transition.
Preparing a Business Case
Figure 10
SALES KPIs
PROCUREMENT
MAN-HOURS
Net business
value
Total business
value
Total cost of
ownership
OPERATIONAL KPIs
Metrics impacting
top line
Metrics impacting
bottom line
Implementation
expenses
• Execution: Finally, initiatives are implemented according to the roadmap, and progress
is monitored until completion. Respective performance for the initiatives is continu-
ously measured to assess impact.
Moving Forward
Digital technology has evolved at a rapid pace, and businesses are beginning to leverage
the SMAC Stack by building new systems of engagement that act as a front end to legacy
systems of record. Digital leaders already have a head start and are enjoying a significant
competitive advantage.
As other manufacturers embark on a digital business transformation journey, or refine
existing strategies, it is important for them to understand how they can maximize the
impact of the new approach. SMAC Stack technologies are only a means to an end:
enablement of a business process innovation or renovation. Fully adopting implemented
technologies is critical to producing the business performance impact desired and, in turn,
market relevance with partners and customers.
Our experience with digital transformation initiatives suggests that organizations should
hold workshops for generating end-user buy-in, identify innovation leaders within various
departments (and model their behaviors throughout the organization), and embrace
change management techniques. Only then can manufacturers fully embrace digital
business adoption and realize the resulting performance boost. A phased implementation
roadmap, coupled with an adequate change management strategy, is critical to ensuring
a successful transformation.

Footnotes
1 For additional insights, please read our white paper “Informed Manufacturing: The Next
Industrial Revolution,” April 2014, http://www.cognizant.com/InsightsWhitepapers/
Informed-Manufacturing-The-Next-Industrial-Revolution.pdf.
2 Stephanie Overby, “Mercedes-AMG: A Showcase for Real-Time Business Decisions,”
Forbes Insights, August 2014,
http://www.forbes.com/forbesinsights/sap_mercedes/index.html.
3 Eric Fetters-Walp, “Chain Reaction: Boeing’s Supplier Management Works To Be More
Effective, More Efficient — and Reduce Risks,” Boeing Frontiers, February 2011,
http://www.boeing.com/news/frontiers/archive/2011/february/i_eot02.pdf.
4 “Dow Chemical Automates the Sample Process,” Oracle Corp., 2014, https://www.oracle.
com/marketingcloud/content/documents/casestudies/dow-chemical-customer-success-
oracle.pdf.
5 Amit Tiwari, “India’s Best Known Startup Story: The Journey of Flipkart,” Techstory,
March 19, 2014, http://techstory.in/flipkart-story/.
6 “Paytm: Journey from Mobile Recharge to E-Commerce Market,” Delhi School of Internet
Marketing, May 8, 2015, http://dsim.in/blog/case-study-paytm-journey-from-mobile-
recharge-to-e-commerce-market/.
7 “3M: A Culture of Innovation,“ 3M, 2012, https://solutions.3m.com/3MContentRetrievalAPI/
BlobServlet?lmd=1349327166000&locale=en_WW&assetType=MMM_Image&assetId=13192
09959040&blobAttribute=ImageFile.
8 Anthony Hill, “Global Internet Users to Reach 7.6 Billion within the Next Five Years,”
Broadband Choices, Sept. 23, 2014, http://www.broadbandchoices.co.uk/news/2014/09/
global-internet-users-230914.
9 “Lenovo Orchestrates Messages across Channels to Drive Engagement,” Oracle Corp.,
https://www.oracle.com/marketingcloud/content/documents/casestudies/lenovo-custom-
er-success-oracle.pdf.

Acknowledgments
The authors would like to thank Badrinath Setlur, Associate Vice-President, Cognizant Business
Consulting, and Ganesh Dhulipati, Director, Manufacturing and Logistics Practice, for their
guidance and support.
About the Authors
Arun Krishnan is a Director in Cognizant Business Consulting’s Discrete Manufacturing Practice.
He has over 21 years of consulting experience throughout the manufacturing industry. He has led
various projects in strategy consulting, process re-engineering, business analysis, problem struc-
turing and solution development, program management and change management across diver-
sified manufacturing and logistics companies. He earned his M.B.A. (PGDM) from IIM, Bangalore,
and has a B-Tech in mechanical engineering from University of Calicut. He can be reached at
Arun.Krishnan2@Cognizant.com | https://www.linkedin.com/profile/view?id=22686378.
Gajanan Pujari is a Senior Consulting Manager within Cognizant Business Consulting’s Manufac-
turing and Logistics Practice. He has 12-plus years of experience and has led multiple business
consulting engagements in the areas of export sales distribution, supply chain analytics and
IT portfolio rationalization for top automotive and industrial manufacturing companies. His
areas of interest include the impact of IoT, digital and big data analytics technologies on the
manufacturing industry. He holds an M.B.A. in analytical finance and operations management
from the Indian School of Business (ISB), Hyderabad, and has a bachelor’s degree in production
engineering from National Institute of Technology, Trichy, India. He can be reached at
Gajanan.Pujari@cognizant.com | https://www.linkedin.com/profile/view?id=29549276.
Nirman Sarkar is a Consultant within Cognizant Business Consulting’s Manufacturing and
Logistics Practice. He has five years of industry and consulting experience in value chain
analysis and roadmapping, supply chain management, operations management and product
development across the automotive and industrial products manufacturing industries. He
holds an M.B.A. in finance and operations management from the Indian School of Business
(ISB), Hyderabad, and has a bachelor’s degree in mechanical engineering from the National
Institute of Technology, Durgapur, India. He can be reached at Nirman.Sarkar@Cognizant.com |
https://www.linkedin.com/profile/view?id=66782826.

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