Private Equity: Powering Alpha Via AI, Analytics & Automation

Digital Business
Private Equity: Powering Alpha Via
AI, Analytics & Automation
Embedding a data-driven approach that relies on the latest digital technologies,
tools and techniques can help to increase the value of portfolio companies and
enable them to transform – which can be critical while formulating exit strategies.
Executive Summary
The private equity (PE) industry has had a great run in
the last decade and seen rapid growth in assets, with
net asset value increasing seven times since 2002.1
Moreover, fundraising has hit record highs globally
as private market capital growth has outpaced public
market capitalization over the previous two decades.
Limited partners (LPs) have poured money into this asset
class, not only for diversification but also to tap growth
pockets across the globe.
However, the private markets industry’s success is creating
challenges as funds pour in in unprecedented amounts.
Industry dry powder is at record highs ($2 trillion).2
Company valuations have moved up as PE firms look to
invest in attractive, well-run companies. Valuations are
rising with deal multiples recording an average of 11.1x,
in 2018 from 9.6x in 2015 (see Figure 2, page 4). This is
posing a new set of challenges for PE firms. Combine
these industry-specific challenges with the larger
disruption in business models and business change across
industries and the challenge becomes even greater.
Cognizant 20-20 Insights
January 2020

PEfirmsneedtodeployunprecedentedsumsof
money,acquirestakesatrelativelyhighervaluations
andgenerateprofitableexits,whilehelpingportfolio
companiesnavigateindustrymakeovers.Clearly,
sustainingthesuccessofrecentyearswillbedifficult--
PEfirmswillneedtoworkmuchharderandgenerate
Alpha3
acrosstheportfolio–withoutbettingsolelyon
linearrevenuegrowthtosupporttheirexitstrategies.
One area that PE firms significantly underleverage
is automation, analytics and artificial intelligence
(AI), or the 3As. This is surprising, since the 3As
are becoming a mainstream phenomenon across
industries and geographies, enabling early
adopters to propel growth, reduce costs and
enhance operational efficiencies. (For more on the
mainstreaming of AI, read our white paper “Making
AI Responsible – and Effective.”)
A larger focus on digital technologies, including
the shift to cloud and automated processes, is
likely to be one of the key game changers for the
PE industry going forward. By focusing on the 3As,
the PE industry can create an exciting new avenue
for Alpha generation, one that holds significant
promise for them as well as their portfolio
companies. PE firms that learn from the industry
leaders, identify use cases and create a platform for
data-driven decision-making, and move decisively
in this direction, will stand to outperform their
rivals. Companies that do not take a data-driven
approach, and by extension a digital transformation,
will be left behind.
Interestingly, the value of the 3As will not be
restricted to Alpha generation for the portfolio
alone. It can be a critical differentiator in the
lifecycle of a PE’s investment process too, including
deal qualification, bid pricing, due diligence
processes and executing exit strategies.
To succeed, PE firms will need to set up a digital
transformation office to help portfolio companies
and themselves achieve promised outcomes. This
paper addresses the need, importance and impact
of the 3As for the PE business.
2 / Private Equity: Powering Alpha Via AI, Analytics & Automation

An industry in flux
When it comes to fundraising, private markets have
never had it better. Assets under management
(AUM) are at all-time highs at $5.8 trillion, and
money is coming in from a wide range of limited
partners, especially into private equity.
While this is a resounding vote of confidence for
private capital (and private equity) as an asset
class, this has also resulted in excess liquidity in the
ecosystem, with industry dry powder now at record
highs too, as Figure 1 reveals.4
Global private capital dry powder (in billions) 2006-2018
768
952
1,066 1,055
982 1,002
943
1,226 1,222
1,352
1,563
1,739
2,095
Dec. 06 Dec. 07 Dec. 08 Dec. 09 Dec. 10 Dec. 11 Dec. 12 Dec. 13 Dec. 14 Dec. 15 Dec. 16 Dec. 17 June 18
Figure 1

Originating deals that provide a profitable exit after
five years will be increasingly difficult as entry-
level valuations are already high and it is unclear
if these high valuations can be sustained over the
next decade. Betting on sustained, linear growth
in revenues is also likely to be simplistic and almost
naïve in an era with ongoing business model
changes, the entry of new players across industries
(aided by technology), and the massive digital
overhauls by incumbents -- as well as aggressive
plans by well-funded digitally native startups.
Therefore, PE plays are increasingly focused on
ensuring that portfolio companies continue to
maintain and accelerate profitable growth, optimize
processes and expand their business footprint. This
is where sharpening Alpha generation strategies
becomes so critical.
To do this, portfolio companies must apply digital
technologies such as cloud, automation, machine
learning (ML) and AI to deliver the highest Alpha in
their investment portfolios.
Private equity deal multiples continue to rise
Global median private equity multiples, 2007-18
Deal valuations have soared as too much money chases relatively few quality assets (see Figure 2).5
Data source: PitchBook
11.3
12x
10x
5x
0
8.9
6.4
7.8
9.1
8.6
9.0
10.0 9.6 9.8
10.4
11.1
4.7
4.1
3.2
3.5
4.4
4.3 3.8
4.3
4.5 4.8 5.0
5.5
6.6
4.7
3.2
4.3 4.6 4.3 5.2 5.6 5.1 5.0 5.4
5.5
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Debt/EBITDA
Equity/EBITDA
Valuation/EBITDA
Figure 2

The age of analytics
Technology acceleration over the last five years has
provided proper impetus for PE firms to consider
applying the 3As to their businesses:
❙❙ Analytics and cloud infrastructures are available
on demand, making it possible to scale up and
down quickly.
❙❙ Costs are variable and payable on usage (or
some other metric) basis.
❙❙ Open-source platforms and libraries are
reducing the cost of technological experiments,
negating the upfront investment required in
expensive licenses.
❙❙ Industrialization in processes, including data
sciences, have reduced the reliance on people
and cut model building time by up to 90%.
❙❙ Mainstream applications of varied types of
analytical techniques on diverse data sets --
structured, unstructured, and the Internet of
Things (IoT) -- are available.
❙❙ The availability of new and alternative data is on
the rise, which adds to the potency of analytics
models.
This has created a perfect storm for 3A adoption.
Over time, we expect 3A interventions to be
mainstream in all top, proactive PE firms. By getting
out ahead, these firms should lead the pack in
portfolio value creation.
Investments in 3A initiatives do not require
high investments upfront, barring some core
investments, and experiments can be set up quickly
by leveraging cloud infrastructures that allow for
quick data uploads, analysis and modeling. (Note:
This paper does not address the “how” part of the
equation – i.e., how PE firms can execute a plan to
leverage data and create insights.)

There are caveats, however:
❙❙ An important prerequisite for 3A intervention
is the availability, quality and sanctity of
the data available in an organization. This is
typically a challenge in most companies as data
sits in disparate systems, is widely accessed
and distributed across departments, lacks a
governance framework to ensure quality, has
inconsistent definitions, etc. This is a challenge
that cannot be wished away, but firms that
want to compete on data and analytics need
to address this problem head on. Addressing
data quality problems need not always be a
multimillion-dollar project but one that can be
addressed in pockets, on a case by case basis.
Companies must also take this opportunity to
start capturing new data, digitizing existing data
and incorporating alternate data sources (free or
paid) into the ecosystem.
❙❙ Not every cloud, ML, or automation project
will succeed. Success is a function of many
variables including the use case itself. However,
success rates have improved as the industry
has matured, especially in functional areas that
have been tackled many times over, such as
campaigns, risk, fraud, collections, etc. Challenges
often arise in new problems and while working
with new data sets; those need to be carefully
selected to ensure success. In our experiences,
we have found the overall return on investment
(ROI) of 3A investments to be very high.
The monetary value of the 3As
The 3As can add value across the PE investment lifecycle through:
❙❙ Deal identification and conversion.
❙❙ Portfolio value creation.
❙❙ Exit strategies.

By instituting a data and insights-driven decision-making culture,
the portfolio company can transform and remain fit for growth
long after the PE firm divests its stake. This legacy, by itself, can be
a compelling pitch for a potential company to be a part of a PE’s
portfolio.
Deal identification and conversion
Intelligent process automation (IPA), robotic
process automation (RPA) and analytics can
make the job of sifting through mountains of data
to identify potential targets more time and cost
efficient during deal identification. Evaluating
customer perception of products and services,
market penetration, and growth potential of a
target company is now a lot easier as the web offers
a treasure trove of data to analyze for insights.
The internet provides real customer feedback on
brands, products, services, competitive positioning,
pricing, etc. and can be an invaluable tool as
originating partners make investment decisions.
Besides, firms can also evaluate the digital readiness
of the target company in the pre-investment phase
by studying their digital presence, performance
and effectiveness. If these lag behind competitors
in an industry that is shifting to digital, then these
findings provide a fact-based view into business’s
potential upsides.
On a similar note, the ability to crawl and extract
data from the web and apply natural language
processing (NLP) to a variety of data sources can
automate legal due diligence on promoters and
directors of target companies.
Two Six Capital, a San Francisco-based firm,
has helped PE firms in the U.S. to determine
appropriate and stretch valuations during
investment due diligence.6
In competitive bid
scenarios, analytics and data science can help
estimate the upper limit of the bid value based on
potential revenues that a PE can generate from
existing customers, based on different metrics such
as customer lifetime value (CLTV), average revenue
per user (ARPU), product penetration, etc. This can
provide a distinct information edge to the PE firm,
as it seeks to win deals with a highly competitive bid,
while at the same time not being saddled with the
winner’s curse (i.e., overpaying). Although most PE
firms perform such analysis, a robust data-driven
approach will lend more credibility to the bid.
DealconversionprobabilitycanincreaseifthePEcan
pitchitsabilitytohelpthepromoter/management
transformthecompanyonthebackofthe3As.While
valuation,equitydilution,dealstructure,etc.matter
enormously(andagrowthpartnerisinvaluable),any
companymanagementandboardwillvalueaninvestor
thathelpsitnavigateitsdigitaltransformation.By
institutingadataandinsights-drivendecision-making
culture,theportfoliocompanycantransformand
remainfitforgrowthlongafterthePEfirmdivestsits
stake.Thislegacy,byitself,canbeacompellingpitchfor
apotentialcompanytobeapartofaPE’sportfolio.

Portfolio value creation
AlmostalllargePEfirmshaveoperatingteams/
valueoptimizationgroupsthatseektoincreasethe
valueofportfoliocompanies.Valuecreationhas
traditionallybeenobtainedviainterventionssuch
asinductingmanagementexpertise,providing
accesstonewmarkets,launchingnewproductlines,
offeringaccesstonewchannels,enablingstrategic
partnerships,fundinggrowth,automationandvendor
consolidation,andmore.WhileleadingPEfirmsare
nowlookingatdigitalasavaluecreator,itisfairtosay
thattheyarestillintheinfancyofthisjourney.Several
largefirmshavesetupexperimentalteamsandare
testingthebusinessimpact.
Thistentativeapproachissurprisinggiventheimpact
thatdigitalishavingacrosstheindustry,butweexpect
PEfirmstowakeuprapidlytothepossibilitiesofthe
3As.Figure3illuminatesthereasonswhy.7
Insight-driven use cases create value by either supporting growth
(topline) or reducing costs (bottom line)
Figure 3
Use cases Use cases
Assortment optimization Predictive maintenance
Cross-and upsell Marketing spend effectiveness
Chum prevention Demand planning
Pricing Fraud prevention
Stock and replenishment optimization Bad debt management
Promotion optimization Workforce planning
Space and shelf optimization Supply chain optimization
Reference impact+
Reference impact+
Sales
impact
Retail
impact
Cost
reduction
Bottom line
2.0%
1.5%
2.0%
2.0%
1.5%
1.5%
20-50%
of call center costs
5-10%
of marketing costs
20-30%
ofwarehousingcosts
1-5%
of fraud loss
10-20%
of bad debt loss
10-20%
of service costs
10-30%
of logistics costs
1.0 ppt
1.0 ppt
0.5 ppt
1.0 ppt
Impact values not additive and only achieved in case of investment and change management
+ Based upon 100+ reference cases; realization over 1-3 years
Source: McKinsey Advanced Analytics
While use cases for the 3As across industries and processes are numerous and diverse, they can
broadly be classified into three domains – revenues, cost and efficiency.

Revenue generation
SeveralmarketresearcherssuchasGartnerindicate
adistinctshifttodigitalinmarketingspend,where
measurementandattributionofrevenuesisrelatively
better,customerbehavioriscollectedinrealtime,and
organizationsbenefitfrommoregranulardata.8
Allof
theaboverequiresfirmstocapturetheclickstream
data,buildarchitecturestoleveragereal-timeuse
casesandapplyanalyticstosegmentandpersonalize
experiences.
NetflixandAmazonhavefamouslyleveraged
algorithmstorenderpersonalizedcontentto
consumerstoboostsalesandup-andcross-sellmore
productsbyleveragingadjacencies.Asbusiness
shiftsonline,moredataisavailableforanalysisand
itispossible,withtherightintervention,toidentify
consumersegmentsandunderstandtheirbrowsing
andpurchasebehaviors.Digitalhasmadereal-time
targetedmarketingpossible,sincecustomerscanbe
individuallyidentifiedandserved.
3Ainterventionsarepowerfulacrosstheentiresales
andcustomerlifecyclejourney(seeFigure4).
The impact of 3As across the customer journey
Figure 4
There is scope for optimization in each step of this (sample) journey. Analytics can enable
effective segmentation, and help organizations understand promotion effectiveness, consider
optimal product mix, and optimize multichannel marketing budgets to understand the who,
what and why of customers.
ACQUISITION
Customer segmentation
& acquisition analytics
Offer optimization
Activation strategies
Usage campaigns &
spend modeling
Response/risk
models and revenue
optimization
Lifetime value
management
Cross-sell/upsell
analytics
Usage campaigns
Retention analytics
CUSTOMERENGAGEMENT
GROWTH MATURITY SATURATION & DECLINE

We worked with a North American-based
specialty retailer to enrich customer data, link
taxation data with customer demographics and
improve campaign effectiveness, leading to a 14%
improvement in response rate. We have helped
clients across the spectrum:
❙❙ A leading North American insurer improved
qualified prospect identification by 45%.
❙❙ A financial services company provided
personalized campaigns and targeting to 97% of
known customers.
❙❙ A global automotive manufacturer drove higher
cross-sell and upsell business by analyzing
consumer behavior patterns.
If a PE firm has to start small, then personalization is
the place to start. It provides direct topline impact
and therefore valuation impact for a portfolio
company and PE respectively. PE firms that do not
help their portfolio companies in each of these areas
are leaving a lot of growth, and money, on the table.
Cost & loss reduction
Automationistypicallythebiggestleversincost
reduction,especiallyinprocess-intensiveactivities.
Whileroboticsandautomationhavebeenadoptedby
largemanufacturingfordecades,IPAandRPAhave
gainedsteaminrecentyearsinmostpeople-based
processes.
InastudyonthedeploymentofIPAacrossIndustries,
McKinseyidentifieda20%to25%annualrun-rate
costefficiency,anincreaseinstraightthrough
processingandanROIthat’softenintripledigits.9
IPAhastrulyarrived,especiallywiththeadventof
advancedprogramminglanguages,AI-enabled
naturallanguageprocessing(NLP)andnatural
languagegeneration(NLG).Well-established
companiessuchasAutomationAnywhere,Blue
PrismandUIPath(amongotherstoday)offerrobust
platformsandsolutions.
Takefinanceprocessesasanexample.Several
companieswithwhomweworkhavereapedbenefits
ofautomationintheprocessofhandlinginvoices,
processingthem,markingthemforpayments,making
decisionsonearlypayments(basedonearlybird
discounts,etc.)suchthattheentireprocure-to-pay
processcanbeoptimized.Firmsleverageanalytics
tooptimizespends,identifyinganomaliesandexcess
payments,aswellastoavoidpenalties.
Similarly,processescoveringclientonboarding,
KnowYourCustomer(KYC),reconciliations,claims,
andmorearepeople-intensivewithmultiplemanual
interventions,allofwhichareprimecandidatesfor
automation.Withincreasedsophisticationinoptical
characterrecognition(OCR)technologies,image
recognitionandNLP,combinedwithrule-based
automation,thereissignificantscopeinoptimizing
costsinmanualprocesses.Thebiggestimpact,
though,isinfraudreduction,whetherit’sclaimsfraud
ininsuranceorvariouskindsoffraudperpetratedin
banking.Fraudalgorithmshelppreventhundredsof
millionsofdollarsofpotentialfraudannually.
Wehelpedalargemultinationalmanufacturing
conglomeratethatmanages80,000invoices
annuallytoreduceerrorsinmanualprocessing
andslashhandlingtimeby50%byemploying
anRPAsolution.Wealsoworkedwithadigital
advertisingagencytodesignandimplementan
NLP-basedautomationtooltocreateadextensions,
identifyappropriateadplacementsandimprove
effectiveness.Theclientrecordeda10%improvement
inclick-throughratesand50%productivitygains.
Thesearethetypeof3AinitiativesthatPEfirms
shouldbringtotheirportfoliocompanies.

Operational efficiency gains
Improvedbusinessefficiencyresultsfromthe
reducedfrictionintheend-to-endlifecycleofvarious
processes.Forexample,PEfirmsneedtoinstillin
portfoliocompaniesthat:
❙❙ Client onboarding should be convenient, easy
and quick without compromising on KYC and
customer validation requirements.
❙❙ Collection processes must increase the
propensity to recover past dues while ensuring
customer care and legal compliance.
❙❙ Call center operations should be customer-
centric and retain high net promoter scores
(NPS) while reducing operating metrics such
as mean time to resolve (MTTR), average hold
times and the number of agents.
❙❙ Supply chain networks should work seamlessly
so that movement of goods are streamlined
without capacity buildups in fleets and people
and without excess inventory or stockouts.
❙❙ Financial services firms must identify and
mitigate multiple dimensions of risk without
compromising customer experience,
convenience and speed.
❙❙ IT teams need to provision an infrastructure
that is scalable, robust, secure, and resilient
with minimal latency, yet be democratic (for
information access), allow self-service, and be
cost-effective.
Automation,analyticsandAIplayalargepartin
addressingtheseseeminglyconflictingobjectives.
OCRandimagerecognitionalgorithmsensurethat
onboardingprocessesarestreamlinedwhileasingle
masterdatamanagement(MDM)platformbrings
togetherallcustomerandproductinformationto
avoidduplication.Financialservicescompanies
tacklefinancialexposure(fundedandnon-funded)
byrunningriskandpurchasepropensityalgorithms
inrealtimeviacloudplatforms,therebyensuring
in-contextoffersforcustomers.Similarly,cloud-based
microservices-basedarchitecturesallowforquick
access,scalabilityandsecuritywhilekeepingcostsin
check.
ArecentMcKinseyreportontheimpactofanalytics
incontactcentersconcludesthatcompaniesthat
leverageadvancedanalytics:10
❙❙ Reduce average handle time by 40%.
❙❙ Increase self-service containment rates by 5%
to 20%.
❙❙ Cut employee costs and boost conversion rate
on service-to-sales calls by nearly 50%.
❙❙ Improve customer satisfaction and employee
engagement.
Weworkedwithalifesciencesfirmtooptimizeits
entireprocure-to-payprocessesandweedout
inefficienciesintheprocessthroughacombination
ofautomation,analyticsandAI.Theclientimproved
invoicestraight-through-processingratesby
68%,optimizedfinanceprocessesandenabled
prioritizationofpaymentstoavailearlypayment
discounts,leadingtoseveralmilliondollarsinsavings.
Asnotedabove,reducingoperatingcoststhrough
the3AsaredisciplinesthatPEfirmscanandshould
bringtotheirportfoliocompanies.

Exits
Thecumulativeimpactofapplyingthe3Asacross
thesethreethemesistheoverallimprovementin
growthrates,costsandoperationalprocesses.Allof
thesehaveadirectimpactoncompanyvaluation.
Allotherthingsbeingequal,acompanythatdisplays
strongerdigitalmaturity(initsuseofcloud,analytics
andAI)willcommandahighervaluationpremium
comparedtoitscounterparts.Thisisevidentin
themarketvaluationtrends.AJune2019articlein
HarvardBusinessReviewnoted:11
❙❙ A 7% to 21% positive valuation impact for
companies that have implemented digital
initiatives over those that did not.
❙❙ Valuation benefits of going digital improve over
time, rising by 4% to 12% over the two years
following the launch of digital initiatives.
❙❙ An investor can make a 5% risk-adjusted annual
return (or Alpha, in finance speak) on a trading
strategy that considers whether firms report
digital activities.

The time is ripe for PE firms to institute an in-house digital
transformation office that will have a mandate to drive digital
change in all portfolio companies.
Looking forward: Green shoots in the PE industry
The good news is that some leading PE firms
have begun investing, albeit in a very small way, in
analytics, AI and automation. True North, an India-
based and India-focused PE firm, took the lead in
the first quarter of 2018 when it created Actify Data
Labs, a subsidiary with a $10 million investment
to focus on the 3As exclusively for its portfolio
companies.12
This was possibly the first instance of a
PE firm making a large dedicated investment in this
space in India if not globally.
In our experiences, many large PE firms are at
an experimentation phase and are making small
investments to gauge the impact on portfolio
operations. In November 2018, Temasek Holdings
announced the setting up of experimental pods
to focus on AI and blockchain technologies, which
it sees as long-term trends impacting multiple
industries and geographies.13
Conversations with
PE firms indicate that many have begun creating
small seed teams or are in the process of setting
up such seed teams dedicated to digital initiatives.
We see this as a trend that will gain momentum and
become mainstream over the next 18 to 24 months.
The PE industry needs to find new ways to generate
Alpha and add value to its portfolio companies
beyond the traditional routes that it has taken so
far. The time is ripe for PE firms to institute an in-
house digital transformation office that will have
a mandate to drive digital change in all portfolio
companies. This office will focus on the entire
digital spectrum, from the shift to cloud to process
redesign, while focusing on the 3As as a key lever.
PE firms that are able to reinvent their roles and
relationships with portfolio companies are likely to
achieve a higher degree of success.

Endnotes
1 Private equity includes buyouts, large PE firms and late-stage VCs. Private markets also includes private debt, real estate
and mezzanine funds, among others.
2 https://www.investopedia.com/terms/d/drypowder.asp.
3 Alpha refers to the excess returns generated by the investment manager, over a reference rate of return/benchmark index.
4 Naomi Feliz, “Alternatives in 2019: Private Capital Dry Powder Reaches $2tn,” Preqin Insights, January 28, 2019, https://
www.preqin.com/insights/blogs/alternatives-in-2019-private-capital-dry-powder-reaches-2tn/25289.
5 “Private markets come of age,” McKinsey Global Private Markets Review 2019.
6 Mary Kathleen Flynn, “Private equity firms embrace big data: Two Six Capital, Oak Hill, Clarion,” Mergers & Acquisitions,
September 20, 2018, https://www.themiddlemarket.com/news/due-diligence-meets-big-data-two-six-capital-oak-hill-
clarion-among-pioneers.
7 “Achieving business impact with data,” Digital/McKinsey, April 2018.
8 The Gartner CMO survey 2018-19 (a survey of 600 marketing leaders) noted that marketing technology (or martech)
now accounts for 29% of all marketing expenses, up from 22% just two years ago. Roughly 14% of all a CMO spend is on
personalization, while 25% of the total budget is on areas such as paid search, organic search, web and mail.
9 “Intelligent process automation: The engine at the core of the next-generation operating model,” McKinsey Global, March
2017.
10 “How advanced analytics can help contact centers put the customer first,” McKinsey& Company, February 2019, https://
www.mckinsey.com/business-functions/operations/our-insights/how-advanced-analytics-can-help-contact-centers-
put-the-customer-first.
11 Suraj Srinivasan and Wilbur Chen, “Research: Investors Reward Companies That Talk Up Their Digital Initiatives, Harvard
Business Review, June 18, 2019, https://hbr.org/2019/06/research-investors-reward-companies-that-talk-up-their-
digital-initiatives.
12 Swaraj Singh Dhanjal, “True North floats subsidiary focused on analytics, AI, commits $10 million investment,” livemint.com,
January 17, 2018, https://www.livemint.com/Companies/qFYBAcYQcqqQsQ7Uzn4q4I/True-North-floats-subsidiary-
focused-on-analytics-AI-commi.html.
13 Joyce Koh, “Temasek Will Explore AI and Blockchain Deals,” Bloomberg.com, November 21, 2018, https://www.bloomberg.
com/news/articles/2018-11-22/temasek-to-explore-ai-blockchain-deals-with-experimental-pods.
References
• “Private markets come of age” McKinsey Global Private Markets Review 2019. Mckinsey & Company, February 2019.
• “Intelligent process automation; The engine at the core of the next- generation operating model,” McKinsey Global, March
2017.
• Cognizant customer intelligence offering overview, https://www.cognizant.com/ai/pdf/customer-intelligence-offering-
overview.pdf.
• “How advanced analytics can help contact centers put the customer first,” McKinsey& Company, February 2019, https://
www.mckinsey.com/business-functions/operations/our-insights/how-advanced-analytics-can-help-contact-centers-
put-the-customer-first.
• “Global Private Equity Report 2019,” Bain & Company, 2019, https://www.bain.com/insights/topics/global-private-equity-
report/.
• “Global Private Equity Report 2018,” Bain & Company, 2018, https://www.bain.com/insights/global-private-equity-
report-2018/.

About the author
Vasant Rao
Assistant Vice President, AI & Analytics Unit, Cognizant Digital Business
Vasant Rao is an AVP in Cognizant’s AI & Analytics Practice. With 22-plus years of experience in business
and analytics across multiple geographies, he leads the company’s data science technologies sub-practice
globally, and is also responsible for driving advanced AI interventions in business processes for clients. He
has focused on building innovative AI and analytics products and solutions and has spearheaded critical
initiatives on growth and talent engagement at Cognizant. He holds an MSc in Finance from London
Business School, CFA charter from CFA institute and an MBA from Mumbai University. Vasant can be
reached at Vasant.Rao@cognizant.com | https://www.linkedin.com/in/vasant-rao/.

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what customers demand in the digital age. Through IoT we connect the digital and physical worlds to make smart, efficient and safe products, operations
and enterprises. Leveraging data, analytics and AI we drive intelligent decisions and anticipate where markets and customers are going next. Then we use
those insights, combining design and software to deliver the experiences that consumers expect of their brands. Learn more about how we’re engineer
ing the modern enterprise at cognizant.com/digitalbusiness.
About Cognizant
Cognizant (Nasdaq-100: CTSH) is one of the world’s leading professional services companies, transforming clients’ business, operating and technology
models for the digital era. Our unique industry-based, consultative approach helps clients envision, build and run more innovative and efficient business-
es. Headquartered in the U.S., Cognizant is ranked 193 on the Fortune 500 and is consistently listed among the most admired companies in the world.
Learn how Cognizant helps clients lead with digital at www.cognizant.com or follow us @Cognizant.
World Headquarters
500 Frank W. Burr Blvd.
Teaneck, NJ 07666 USA
Phone: +1 201 801 0233
Fax: +1 201 801 0243
Toll Free: +1 888 937 3277
European Headquarters
1 Kingdom Street
Paddington Central
London W2 6BD England
Phone: +44 (0) 20 7297 7600
Fax: +44 (0) 20 7121 0102
India Operations Headquarters
#5/535 Old Mahabalipuram Road
Okkiyam Pettai, Thoraipakkam
Chennai, 600 096 India
Phone: +91 (0) 44 4209 6000
Fax: +91 (0) 44 4209 6060
APAC Headquarters
1 Changi Business Park Crescent,
Plaza 8@CBP # 07-04/05/06,
Tower A, Singapore 486025
Phone: + 65 6812 4051
Fax: + 65 6324 4051

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