HIGH STAKES, HIGH REWARDSimages.forbes.com/forbesinsights/ey_data_analytics_2017/Advanced... ·...
Transcript of HIGH STAKES, HIGH REWARDSimages.forbes.com/forbesinsights/ey_data_analytics_2017/Advanced... ·...
ANALYTICS
CONSUMPTION
MARKET
STRATEGY
A N A L Y T I C S L I N K A G E S
INITIATIVES
ANALYTICS
PRODUCTION
OUTCOMES
COMPETITIVEDIFFERENTIATION
OPERATINGMODEL
INITIATIVEDESIGN
MEASUREMENT& LEARNING
INTERVENTIONDESIGN
DATA & ADVANCED ANALYTICS
INDIAN ENTERPRISES OUTPERFORM GLOBAL PEERS
HIGH STAKES, HIGH REWARDS
TABLE OF CONTENTS
3
4
7
10
13
16
19
22
FOREWORD
EXECUTIVE SUMMARY
COMPETITIVE DIFFERENTIATION
OPERATING MODEL
INITIATIVE DESIGN
INTERVENTION DESIGN
MEASUREMENT AND LEARNING
CONCLUSION
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It gives me immense pleasure to share
compelling insights on how Indian enterprises
have outperformed global peers in their
commitment to use advanced analytics for
critical business decisions. According to the
study, jointly conducted by Forbes Insights and
EY, there is an increasing trend of companies,
proficiently using data and analytics for new
business initiatives, to register high growth
in revenues and profits—hitting 15% or more,
with significant improvement in their risk
profile. The study is based on a C-suite survey
of nearly 200 Indian companies, with annual
revenues ranging between $500 million and
$50 billion, approached by Forbes Insights
between August and September of 2016.
Clearly, Indian enterprises are setting an
example for the world to follow, while also
learning from global counterparts who see
competitive advantage in the use of advanced
analytics more effectively. Already, there is a
growing impetus on Analytics services and
organisations worldwide are now realising
their direct impact on business performance,
but Indian companies are proving to be the
frontrunners in this area. It is heartening to
find that more than a third of Indian executives
vouch for having a well-established analytics
strategy, which forms the core of their overall
business strategy. Therefore, as no surprise,
this puts them ahead of leaders from all parts
of the world—only 23% of enterprises overall
have reached a similar level of analytics
evolution.
I am overwhelmed to discover that executives
in India are targeting resources to better
understand the business opportunities, as
well as the risks, associated with the five
‘Synapses’ i.e. competitive differentiation,
operating model, initiative design,
intervention design and measurement and
learning, as identified in the report. The report
has also brought forth interesting insights
on Indian firms excelling at having well-
established analytics strategies that are key
to the overall business growth. However, the
management committee needs to ensure a
smooth flow of collaboration and alignment
across the enterprise and departments which
has currently been one of the biggest reasons
for the analytics projects to succeed or fail.
I encourage each one of you to read the
complete report and ask EY about what
leading organizations in India are doing to
create a competitive advantage through
analytics, and how we can help yours.
FOREWORD
Gautam Bhattacharya
Partner and National Analytics Leader, EY India
+91 806 727 5144
HIGH STAKES, HIGH REWARDS: FOREWORD | 3
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EXECUTIVE SUMMARY
A recent survey of global enterprises shows
direct linkage between proficiency in data and
advanced analytics and business performance.
Companies that are most adept at using
data for new business initiatives are more
likely to register high growth in revenues and
profits—hitting 15% or more--while also seeing
significant improvement in their risk profile.
The research conducted by Forbes Insights
and EY found significant regional trends, as
well, including analytics as one of the key
pillars of organizational maturity. For example,
Indian firms by far outperformed their global
peers in the use of advanced analytics by
senior executives.
But while Indian enterprises are leading in
some areas, as a group they also struggle
with other important elements of advanced
analytics strategies, such as fostering closer
collaboration among technical and business
stakeholders. Clearly, executives in the Indian
subcontinent have much to teach—and learn—
from counterparts throughout the world
who see a competitive advantage in using
advanced analytics most effectively.
A top priority for enterprises in India and
elsewhere is overcoming problems that arise
between the crucial steps organizations take
as they move from identifying new business
opportunities, acting on insights and then
measuring the outcomes of their data-driven
strategies. We liken them to “synapses” in the
brain, where communications pass from one
cell to another.
The difference is that, in the brain, these
communications pass naturally from cell to
cell, while in large enterprises the smooth
flow of information isn’t automatic. The EY-
Forbes Insights research shows that the way
global enterprises handle these junctures
translates into business success and defines
clear stratifications in analytics maturity.
For example, the top performers in the
overall survey who have translated analytics
strategy into well-designed initiatives are
considerably more likely to enjoy growth in
operating margins and revenues of 15% or
more, respectively, along with significant
improvement in their risk profile.
HIGH STAKES, HIGH REWARDS: EXECUTIVE SUMMARY | 5
Findings from the global survey also show sophisticated users of advanced analytics
experience additional benefits:
They can capitalize on artificial intelligence and other forms of predictive and
prescriptive modeling for insights about possible future outcomes and ways to
address them
Because leaders incorporate advanced analytics early in the business development
processes, they can deliver better outcomes by shaping initiatives based on actual
data rather than gut instinct
Leaders can accurately measure business value to demonstrate the impact—and
validity—of their investments in advanced analytics
ANALYTICS LINKAGES
OUTCOMES
MEASUREMENT AND LEARNING Quantifying and learning from
data-driven business outcomes.
OPERATING MODEL Building the underlying models that govern analytics activities, such as organizational structures that allow
collaboration, chain of command, etc. INITIATIVE DESIGN
Defining the specific activities and projects that will achieve desired
business outcomes
INTERVENTION DESIGNTranslating all the upfront goal-setting,
modeling, and methodology into action— making analytics insights an integral part of business operations.
COMPETITIVE DIFFERENTIATIONDefining the role that data and analytics plays in the company strategy and business model.
STRATEGYINITIATIVES
ANALYTICSPRODUCTION
ANALYTICSCONSUMPTION
MARKET
70%of these leaders have used advanced analytics to overhaul business strategies and update how they compete in their respective markets
75%operate a full range of enterprise, departmental, and line-of-business analytics groups that operate within a well-aligned framework
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METHODOLOGY
This report is based on a survey
of nearly 200 Indian companies
conducted in August and September
2016 by Forbes Insights. Respondents
are C-level executives, including
chief executives, presidents, and
CIOs. Industries represented include
banking, healthcare, technology, and
telecommunications. Organizations
surveyed had at least $500 million in
annual revenues, and 28% had revenues
of more than $50 billion.
However, the global study also found
stumbling blocks that inhibit a more
sophisticated use of advanced analytics. For
example, one common pain point is a lack
of collaboration among business units and
analytics specialists when defining desired
outcomes, designing operational models, and
measuring the results. Without this cross-
department cooperation, the goal of turning
analytical insights into action can break down
at any stage of the process.
To overcome these hurdles, executives in India
are targeting resources to better understand
the business opportunities, as well as the risks,
associated with each of these five synapses.
For example, an issue common to each of
the synapses is a lack of collaboration among
business units and analytics specialists.
This can derail attempts to define desired
outcomes, design operational models, and
measure the results of analytics strategies.
The survey results highlight best practices
specific to each synapse to help executives
avoid common stumbling blocks and derive
long-term value from data initiatives. In
addition, we present insights from Indian
executives who explain the unique challenges
of competing in this dynamic market and
why analytics success is vital to their ongoing
success.
HIGH STAKES, HIGH REWARDS: COMPETITIVE DIFFERENTIATION | 7
KEY FINDINGS
• Indian firms excel at having well-established analytics strategies that are central to the overall business strategy
• Many executives in India view advanced analytics as a strategic resource
• But the lack of collaboration and alignment within the management committee blocks success
Having a mature advanced analytics strategy has
a direct link to business performance, and Indian
companies as a group are distinguishing themselves
in this area. More than a third of Indian executives say
their company’s analytics strategy is well established
and central to the overall business strategy. As a group,
this puts them ahead of leaders from all parts of the
world, wherein only 23% of enterprises overall have
reached a similar level of analytics evolution.
Furthermore, 34% of Indian organizations report that
their advanced analytics strategy is starting to be
viewed as a key strategic priority, edging out the 30%
of global peers that share this viewpoint.
Analytics maturity has ripple effects. More than a
quarter (26%) of Indian executives say advanced
analytics have completely changed their business
strategy and how they compete, with another 39%
only slightly behind—they report changes to significant
elements of their strategy. Again, this put them
ahead of the global pace, with only 17% of enterprises
saying they already have completely changed business
strategies while 33% are seeing significant elements
being impacted.
“Data and analytics are like the headlights of a car, not
the taillights,” says Rajesh Mishra, vice president of
finance and supply chain for Pernod Ricard Travel Retail
Americas. “Using analytics for competitive differentiation
isn’t about analyzing past performance, its value is in
giving you a direction for the future.”
Across organizations worldwide, advanced analytics
proficiency is making the biggest changes in how
firms target and segment customers, something that is
also playing out in India. Thirty-five percent of Indian
executives have seen complete changes in this area,
which is 10% more than at organizations worldwide.
Similarly, nearly a third of Indian companies are also
using analytics to stay ahead of rapidly changing
customer taste.
But not all the news coming from India is positive.
Problems arise over how people perform their respective
roles and interact with corporate peers. Some of the
biggest challenges—which each impact more than a third
COMPETITIVE DIFFERENTIATION
STRATEGY
MARKET
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Regulatory constraints prevent us from acting 51%
Organization, culture and decision-making based more on intuition than data 48%
Lack of collaboration/alignment among members of the management committee 46%
Lack of budget and other forms of organization commitment 43%
Lack of senior leadership support 38%
No appetite for a major transformation that would result from data and analytics-driven strategies 27%
We have not had the right leader to serve as a catalyst for change 26%
Data and analytics is not changing our business strategy 7%
WHAT BEST DESCRIBES THE ROLE OF DATA AND ANALYTICS IN THE BUSINESS STRATEGY IN YOUR ORGANIZATION?
WHAT ARE YOUR TOP PAIN POINTS WHEN IT COMES TO DEVELOPING OR REFINING THE BUSINESS STRATEGY TO ACCOUNT FOR DATA AND ANALYTICS?
Analytics strategy is well established and central to the overall business strategy
Analytics strategy is establishedand starting to be viewedas a key strategic priority
Analytics strategy is established forthe enterprise, but not fully alignedacross the business
Some analytics strategy existsfor functionsor lines of business
No analytics vision orstrategy existsat this timeNote: Due to rounding, numbers presented may not total 100
37%
34%
15%
12%
1%
182 TOTAL
HIGH STAKES, HIGH REWARDS: COMPETITIVE DIFFERENTIATION | 9
RECOMMENDATIONS
1 Create a data and advanced analytics strategy that
balances enterprise goals with the needs of each
business unit, including any unique regulatory and
business requirements.
2 Create a compelling business case that demonstrates
the key role advanced analytics plays for competitive
differentiation in today’s digital marketplace.
3 Show the direct link between advanced analytics
and business value and use this to convince the C-Suite
and Board to make analytics a top priority for the
enterprise.
4 To identify new business opportunities and how they
can be supported with advanced analytics, foster closer
collaboration among stakeholders from all departments.
of Indian organizations—are lack of commitment to
data-based decision-making or organizational support
for data-driven cultures, which impair the competitive
differentiation and operating model synapses. This
problem illustrates how companies still struggle with
intuition-based decision-making, where executives
favor “gut feel” more than fact-based decisions.
OVER THE NEXT TWO YEARS, NEARLY THREE-QUARTERS OF THEM PLAN TO INVEST
$10 MILLION OR MORE FOR DATA AND ANALYTICS RESOURCES.
"WE HAVE SPONSORSHIP FROM
TOP-LEVEL EXECUTIVES, AND
THAT IS A SIGNIFICANT REASON
WHY WE’RE SUCCESSFUL."
KRISHNAKUMAR RAMASUBRAMANIANHEAD OF BUSINESS INTELLIGENCEAND ANALYTICS, MAX LIFE INSURANCE
Related to this is a widespread lack of collaboration
and alignment within the management committee,
which also impedes the smooth flow of information
during each of the synapse transition points.
To better utilize data and advanced analytics for
strategic gain, enterprises must foster a cultural
shift designed to promote collaboration and data
analytics skills. Collaboration between analytics
specialists and business people also overcomes
traditional cultures where there’s overreliance on
gut-feel decision making.
Data leaders point to one other vital element for
promoting collaboration. “We have sponsorship
from top-level executives, and that is a significant
reason why we’re successful,” says Krishnakumar
Ramasubramanian, head of business intelligence and
analytics at Max Life Insurance, a large carrier based in
India.
Looking beyond cultural considerations, Indian
business leaders appear to understand the financial
commitments needed to successfully infuse business
initiatives with data and analytics. Over the next two
years, nearly three-quarters of them plan to invest
$10 million or more for data and analytics resources.
This shows a growing financial commitment to data
and analytics--in the past two years, only about half of
the companies spent similar amounts.
Indian companies still have work to do when it comes
to advancing their data and analytics strategies. But
recognizing lingering cultural and collaboration issues
and making appropriate financial investments will keep
firms moving in the right direction.
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KEY FINDINGS
• Nearly half of Indian firms already have an enterprise-wide advanced analytics strategy
• But many Indian companies struggle with advanced analytics governance policies
• A priority in India is expanding training to improve the creation of operating models
Smooth collaboration among stakeholders is also essential
for effective operating models, which provide frameworks
for enabling enterprise, departmental, and line-of-business
analytics to work together. Unfortunately, only a little
more than a quarter of Indian enterprises see this level
of governance in their organizations. Most see progress
only within certain departments and business lines or say
enterprise-level data and advanced analytics groups are
still emerging.
Related to this is the ability of organizations to implement
enterprise-wide data governance standards, something
that’s being accomplished by 40% of the leaders in
India. This is important for fostering greater trust in the
accuracy and security of corporate data. “In the past,
most of our decisions were based on gut feeling, but as
we’re maturing, we’re moving to a point where we are
relying more and more on data to inform our decisions,”
says Chetan Agarwal, executive vice president of IT at
Lodha, a real-estate developer based in Mumbai.
WHICH BEST DESCRIBES YOUR ORGANIZATION'S CURRENT STATUS REGARDING THE ORGANIZATION AND GOVERNANCE OF DATA ANALYTICS?
36% 28% 22% 13%
1%
Data and analytics groups are well-established
in departmentsor lines of business
Enterprise, department and
lines-of-business data and analytics
groups exist and are well-aligned
Enterprise-level data and
analytics group are emerging
Some informal data analytics
groups exist in departments or
lines of business
No organization
exists
OPERATING MODEL
INITIATIVESSTRATEGY
HIGH STAKES, HIGH REWARDS: OPERATING MODEL | 11
He adds that reliance on analytics increases as people
become more confident in the quality of corporate data,
which comes from having solid policies around data
management.
The close alignment of data and analytics teams is a
foundation for effective operating models. Forty-nine
percent of Indian companies use their enterprise analytics
teams to create an organization-wide strategy for
data and analytics. This is important for many reasons,
including because it demonstrates a commitment by
senior executives to having data-driven approaches that
underlie business initiatives going forward.
The research shows that to improve operating models
going forward, Indian leaders must expand training and
make data and advanced analytics a part of operating
models. To do this, organizations should focus more
ENTERPRISE ANALYTICS
closely on recruiting, developing and retaining individuals
who can serve as analytics “leaders” in various parts of
the business. Executives should also define what it means
to the organization to have more of an analytics mindset
and culture. No operating model will succeed long term
without corresponding focus on creating a culture where
analytics practitioners can apply their craft and thrive.
Increasing adoption rates among employees is another top
priority for enhancing analytics maturity. To promote wide
acceptance and adoption of advanced analytics among
business people, the resource must be accessible and easy
to use. This means offering tools that present findings
in highly visual formats that are well integrated within
the primary applications business people use to perform
their jobs. After all, if a solution is difficult to navigate and
presents information that’s not clear to a business user,
they’ll be less likely to adopt it.
74%
Technology
Selecting,
implementing,
managing
common
technology
platform and
tools
51%
Development
Building models
and other assets
that can be
leveraged across
the business
49%
Strategy
Setting the
overall firm-level
data and
analytics
strategy and
plan
40%
AdvancedAnalytics
Analytics
Working on use
cases that
require skills not
resident in the
businesses
40%
Data
Implementing
data gover-
nance/standards
used across the
organization
17%
PortfolioManagement
Management
Selecting
projects, making
investment
allocation
decisions
12%
Measurement
Putting in place
standards for
value measure-
ment,
If your organization uses some form of enterprise-level analytics team
(in addition to capabilities that exist within business units),
what is the primary purpose of this team?
RECOMMENDATIONS
12 | © 2017 EYGM LIMITED. ALL RIGHTS RESERVED.
1 Clearly define an operating model that brings
advanced analytics resources close to each line of
business and function.
2 Support the model with an enterprise-level analytics
team charged with setting the overall strategy for data
and advanced analytics.
3 The team should also implement enterprise-wide
data governance standards to foster greater trust in the
accuracy and security of corporate data.
WHAT ARE YOUR TOP PAIN POINTS WHEN CREATING A DATA AND ANALYTICS OPERATING MODEL?
Lack of training across functions
31%
Data and analytics has not historically
been part of an operating model
30%
Lack of adoption/engagement by employees
29%
Lack of change management acumen
28%
Lack of alignment/collaboration across functions
27%
Lack of data and analytics proficiency
within many functions
27%
Lack of data/knowledge management sharing
26%
A data and analytics operating model would
disrupt existing models too much
24%
Lack of data and analytics leaders at the
business-unit level
24%
Lack of vision/buy-in from top
levels of management
20%
Technology is not integrated
20%
We do not have mature data and analytics
15%
HIGH STAKES, HIGH REWARDS: INITIATIVE DESIGN | 13
KEY FINDINGS
• Improving partner and vendor relationships are top goals for advanced analytics initiatives in India
• Executives must better align the IT department, the data and advanced analytics team, and business peopleto improve data strategies
When executives reach the point of designing the
specifics of business initiatives, they must make a series
of critical decisions that will guide their use of data
and advanced analytics and ultimately determine the
success of the project. This starts with defining the
specific business outcomes leaders hope to achieve.
The goals that ranked highest among Indian
respondents were increased quality and more targeted
interactions with partners and vendors. Indian
executives cited this area in greater numbers than their
global peers, showing partner and vendor relationships
is a clear regional concern in the subcontinent.
Other goals show a bias toward practical matters, such
as the desire for increased sales or revenues and higher
rates of customer satisfaction. The high rankings aren’t
surprising, after all, they’re the main focus of business
executives everywhere. But progressive leaders are
also looking to employ advanced analytics in strategic
ways, too. Twenty-eight percent see opportunities for
developing new products and services with the aid of
advanced analytics.
It will take more than just an attitudinal change to move
these companies forward. Behind the scenes, they must
also significantly improve their methods for developing
initiative designs. However, this is another area where
Indian firms appear to be ahead. An impressive 71%
of the respondents say they always or very often use
consistent methods for data and analytics initiative
designs. Globally, just 47% of executives report this level
of consistency.
Indian respondents have another advantage—36% say
their data and analytics and business groups work
together highly effectively. Only 16% globally share this
status.
But Indian companies have work to do in other areas.
Nearly half of them say a top pain point is the lack
of alignment among the IT department, the data and
analytics team, and business people. A similar number
report trouble from a lack of people with analytics skill
sets to define an appropriate approach to designing
analytics initiatives. In addition, many say problems arise
because desired business outcomes are not well defined
at the start.
INITIATIVEDESIGN
ANALYTICSPRODUCTION
INITIATIVES
Enable common enterprise view of customers
Encourage rapid and constant innovation
More effectively deploy our people
Accelerate decision-making
Transform operating modelsIncre
ase
qualit
y a
nd m
ore
tar
get
ed in
tera
ctio
ns w
ith p
artn
ers a
nd vendors
33%
Incre
ase
sale
s or
reve
nues
30%
Dev
elo
p n
ew p
roduct
s/se
rvic
es
28%
Incre
ase c
ust
om
er s
atis
fact
ion/
rete
ntio
n
27%
Imp
rove
curr
ent pro
duc
ts/s
ervi
ces
26%
Imp
rove
and s
trea
mlin
e in
tern
al o
pera
tions/c
ut costs 23%
Dee
per
mar
ket in
sigh
ts
21%
Tran
sform
bus
ines
s m
odels
2
1%
19%
19%
19%
15%
14%
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WHAT SPECIFIC BUSINESS OUTCOMES IS YOUR ORGANIZATION TRYING TO ACHIEVE THROUGH THE APPLICATION OF DATA AND ANALYTICS?
HOW OFTEN DO YOU USE CONSISTENT METHODS/APPROACHES FOR DATA AND ANALYTICS INITIATIVE DESIGN (PROJECTS TARGETING A SPECIFIC USE CASE)?
0
10
20
30
40
50%
SOMETIMES5%
27%ALWAYS
FAIRLY OFTEN22%
1%NEVER
44%VERY OFTEN
Note: Due to rounding, numbers presented may not total 100
RECOMMENDATIONS
HIGH STAKES, HIGH REWARDS: INITIATIVE DESIGN | 15
Lack of collaboration between IT, data and analytics team and the business team 46%
Lack of people with analytics skill sets to define an appropriate to approach the problem 46%
Desired business outcomes not well defined at the start 40%
Technology needs not considered early enough 38%
Lack of clear and engaged sponsorship 36%
Lack of consistent methods/processes 35%
Unclear responsibilities across functions 33%
Not enough focus on who the ‘user’ will be and how the analytics will change what they do 25%
Other 1%
WHAT ARE YOUR TOP PAIN POINTS WHEN DESIGNING DATA ANALYTICS INITIATIVES?
1 Develop and apply consistent processes and a
common nomenclature for designing advanced
analytics initiatives. This should be balanced
with creating an environment for cost effective
experimentation and investigation, which allows teams
to ultimately choose the best use cases.
2 Ensure that stakeholders define strategic objectives
and desired business outcomes and closely align
proposed initiatives to these goals. Focus on a better
definition of a strategic outcome such as driving
better engagement with customers. That goal should
then translate into initiatives that evaluate, streamline,
improve or otherwise reimagine customer engagement
across all channels.
3 Carefully think through the competencies and roles
that are needed across analytics, IT and business teams
– ensure there is joint responsibility and accountability
for addressing a specific initiative. Assess the current
skills across these teams to ensure that the right mix
actually exists to drive initiatives in a way consistent with
industry-leading practices.
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KEY FINDINGS
• Earlier is better when applying advanced analytics to business development
• Indian executives are ahead of their global peers in the use of advanced analytics among senior business leaders
• Lack of skills is a significant roadblock to activating analytical insights
Intervention design is when stakeholders translate
goal-setting, modeling, and methodology development
into new business decisions or processes. Critical
for success at this stage is determining when in the
development process companies design how to apply
analytics to best realize the value of their efforts. Doing
so as early in the process as possible is ideal since this
allows the most time for validating initiatives based
on available data, rather than simply relying on gut
feel. However, only 29% of Indian executives claim
this level of early intervention, while about a quarter
of respondents say deciding how to apply analytics
comes after starting data collection and knowing what’s
possible. Another 28% say they make this decision only
after they know what type of analytics will be applied.
Sixteen percent overall still wait until after they’ve built
their models, indicating an area that requires further
attention.
On the plus side, Indian firms are ahead of those in other
regions in the use of data and analytics among senior
business leaders. Fifty-seven percent of top executives in
India turn to data and analytics for more than half of their
decision-making. This contrasts with international results,
where only 45% of senior executives show a similar
commitment to analytics. The bottom line: executives in
India are more likely to capitalize on advanced analytics
for decision-making than their counterparts in other
countries.
When senior executives see the competitive advantages
of analytics and lead by example, it encourages people
throughout the organization to use analytics more
extensively, says Rahul Shandilya, senior vice president of
IT and analytics for the automotive and farm equipment
sectors at Mahindra and Mahindra in Mumbai.
INTERVENTION DESIGN
ANALYTICSPRODUCTION
ANALYTICSCONSUMPTION
HIGH STAKES, HIGH REWARDS: INTERVENTION DESIGN | 17
However, companies in India still face structural
challenges that impair intervention design. For example,
45% say the biggest roadblock to greater adoption and
consumption of analytics insights is poor integration of
this resource within current processes. The firms also
face personnel problems. More than a third of the Indian
respondents say that the people who need to take the
action do not have the required skills.
Indian firms have an advantage in how extensively senior
leaders embrace advanced analytics. But to further
capitalize on this and other strengths, Indian firms must
make adopting analytics and improving the skills of
people throughout the organization top priorities in the
months ahead.
WHEN IN THE PROCESS DO YOU TYPICALLY DESIGN HOW THE ANALYTICS WILL BE APPLIED (WHAT ACTIONS WILL BE TAKEN TO REALIZE VALUE)?
WHAT PERCENTAGE OF THE TIME DO SENIOR BUSINESS LEADERS INCLUDE DATA ANALYTICS IN THEIR DECISION-MAKING ABOUT DESIGNING AND EXECUTING STRATEGIES?
When we are designing the use case at a high
level
29%
After we have determined what type of analytics will be applied
28%
After we have started data collection and know
what is possible
26%
After we have built models and determined
what insights can be generated
16%
SOONER LATER
0-25%
26%-50% 36%
51%-75% 38%
More than 75% 19%
8%
Note: Due to rounding, numbers presented may not total 100
Note: Due to rounding, numbers presented may not total 100
45%
Business Process
The analytics
insights are not
well integrated
into current
processes
36%
Skills
People who
need to take the
action to not
have the
required skills
31%
Organization
Design
Interaction
between various
people/groups
does not
function well
31%
User
Design
How the
individual
‘interfaces’ with
the analytics is
not well
designed
30%
Data
Data used for
analytics is not
of high quality
or not trusted
24%
Incentives
Actions the
analytics suggest
are not aligned
to current
employee
incentives
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WHAT ARE THE BIGGEST CHALLENGES WITH DRIVING ADOPTION/CONSUMPTION OF ANALYTICS INSIGHTS?
1 When business initiatives are being developed, apply
advanced analytics as early as possible—preferably
when designing use cases at a high level. This enables
stakeholders to shape and test the validity of initiatives
based on available data rather than pure instinct.
2 Closely integrate the output of advanced analytics
into business processes. Otherwise, organizations
risk wasting time and resources developing insights
without any assurance of realizing their value.
3 While the growth of predictive analytics and
machine learning may increase reliance on automated
decisions, human insights will remain a vital element
when making strategic and operational decisions.
Continue to invest in resources that support both the
art and science of using analytics effectively.
RECOMMENDATIONS
HIGH STAKES, HIGH REWARDS: MEASUREMENT AND LEARNING | 19
KEY FINDINGS
• Less than a third of Indian firms use well-defined metrics to gauge enterprise-wide performance of advanced analytics
• Indian companies struggle with communicating business outcomes to the stakeholders
• Addressing measurement and communication challenges remains a high priority
In the end, the value of resource investments devoted to
devising and activating advanced analytics strategies must
be evaluated for how well they support desired business
outcomes. But many companies still struggle to quantify
the benefits of data-driven business initiatives. For
example, only 31% of Indian executives say the enterprise-
wide performance of advanced analytics is managed
consistently and use a well-defined set of financial and
non-financial measures. A significant percentage of the
others struggle with delivering consistent performance
measurements across functions and lines of business.
Successfully aligning measurements to the definitions of
business outcomes that were developed during the early
WHICH BEST DESCRIBES HOW VALUE IS MEASURED WHEN DEMONSTRATINGTHE IMPACT OF DATA ANALYTICS ON YOUR ORGANIZATION?
MEASUREMENT AND LEARNING
ANALYTICS CONSUMPTION
OUTCOMES
2%
Performance of analytics is managed consistently globally using
a well-defined set of financial and non-financial measurest
Performance of analytics is measured and managed, but
inconsistent across functions and lines of business
Analytics initiatives are managed as a portfolio with risk weighted
value assessments impacting resource allocation decisions
Definition of business outcomes is typically established
up front, but measurement is often difficult
No visibility into the value created from analytics initiatives
31%
26%
25%
16%
20 | © 2017 EYGM LIMITED. ALL RIGHTS RESERVED.
HOW EFFECTIVE IS YOUR ORGANIZATION AT IMPLEMENTING TEST AND LEARN PROCESSES THAT THEN IMPACT ANALYTICS MODELS AND SUGGESTED ACTIONS?
Communication of business outcomes to the stakeholders 36%
Too many factors influence the business outcome (cannot isolate the actions from analytics) 34%
Capturing required data is difficult/too costly 32%
Lack of clear responsibility for business outcomes 30%
Expected performance outcomes are not well defined 27%
Lack of trust in the data 20%
Lack of trust in the measurement process 20%
Don’t know/unsure 1%
Other 0%
WHAT ARE THE BIGGEST CHALLENGES TO MEASURING VALUE REALIZATION?
Highly Ineffective
8%
Ineffective
5%
Neither Ineffective
or Effective
9%
Effective
43%
Highly Effective
35%
HIGH STAKES, HIGH REWARDS: MEASUREMENT AND LEARNING | 21
stages of projects is another trouble spot.
Thirty-five percent of Indian executives say they’re
highly effective at implementing test and learning
processes that then impact analytics models and
suggested actions. But nearly a quarter of their
peers admit to being ineffective or at best say their
effectiveness is a wash.
The underlying reasons for these breakdowns are
varied, and cut across technical and cultural issues.
Indian companies struggle with communicating
business outcomes to the stakeholders. Complexity
is a problem—more than a third say too many factors
influence the business outcome. Financial constraints
are another concern—32% say capturing required data
is difficult or too costly.
Leaders who are responsible for guiding their
organizations to more data-driven cultures must
make addressing measurement and communication
challenges a high priority.
1 Create a strategy for measuring performance
that defines a common language and processes for
collecting and analyzing outcome data.
2 Develop detailed metrics that measure the tangible
results of data-driven business initiatives.
3 Set specific targets for business growth, gains in
revenues and profits, and other important goals, such
as reducing risk. Then continuously track progress
toward reaching these goals.
RECOMMENDATIONS
22 | © 2017 EYGM LIMITED. ALL RIGHTS RESERVED.
A FOUNDATIONFOR FUTURE SUCCESS
To stay competitive and remain market leaders in their respective markets,
enterprises everywhere are increasing their commitments and investments in
advanced analytics. Indian leaders are seeing a pay-off from these efforts. In
particular, senior executives in India are more likely than others to replace gut-
feel decision-making with insights gained from their rich data reserves.
However, problems with stakeholder collaboration and corporate-wide
governance policies are holding back the further maturing of advanced
analytics initiatives in the subcontinent. Addressing these shortcomings
must be a top priority for Indian executives going forward—to stay ahead of
competitors globally and use advanced analytics as a strategic advantage for
developing tomorrow’s successful business initiatives.
HIGH STAKES, HIGH REWARDS: CONCLUSION | 23
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© 2017 EYGM Limited. All Rights Reserved.
EYG no. 01096-163GBL
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