Big Data Analytics Key Note

7/30/2019 Big Data Analytics Key Note

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2012 IBM Corporation

Big Data AnalyticsImproving the way we live and work

Deepak AdvaniVP, Business Analytics Products & Solutions

August 16, 2012


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Imagine if you could

track disease outbreaks

across country borders in real

time?


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catch money laundering before it

happens?


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apply social relationships of

customers to prevent churn?


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identify at-risk students

before they drop out of

school?


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Respondents who say analyticscreates a competitive advantage

57%increase

Organizations achieving

a competitive advantage withanalytics are

2.2xmore likely tosubstantially outperform theirindustry peers

Ratio of respondents who indicated analytics creates a competitiveadvantage to those who indicated it did not and the likelihood theyalso indicated their organizations was substantially outperformingtheir competitive peers. The ratio was 2.0 to 1 in 2010.

Analytically sophisticated companies outperform their competition

2010

58%2011

37%

Analytics has evolved from business initiativeto business imperative

Source: The New Intelligent Enterprise, a joint MIT Sloan Management Reviewand IBM Institute of Business Value analytics researchpartnership. Copyright Massachusetts Institute of Technology 2011


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Why Business Analytics MatterThe Need for Analytics is Pervasive Across Business and Industry

The healthcare industryspends $250 - $300 billion on healthcarefraud, per year. In the US alone this is a $650 million per dayproblem.1

One rogue trader at a leading global financial servicesfirm created

$2 billion worth of losses, almost bankrupting the company.

5 billion global subscribers in the telco industryare demandingunique and personalized offerings that match their individuallifestyles.2

$93 billion in total sales is missed each year because retailersdont have the right products in stock to meet customer demand.

Source: 1.Harvard, Harvard Business Review, April 2010.

2,IBM Institute for Business Value, The Global CFO Study, 2010.



The need for progress is clear

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projected growth inworldwide energyconsumption between 2008

and 2035.1

53% proportion of worldwide CO2emissions created by powergeneration, the largest human-made

source.3

170 billion kilowatt-hours wasted each yearby consumers due to insufficientpower usage information.2

1 U.S. Energy Information Administration, International Energy Outlook 2011, September 2011; http://205.254.135.24/forecasts/ieo/pdf/0484(2011).pdf

2 Ontario Energy Board, Ontario Energy Board Smart Price Pilot Report, (Prepared by IBM Global Business Services and eMeter Strategic Consulting for the Ontario Energy Board), July 2007.

3 The Climate Group, SMART 2020: Enabling the low carbon economy in the information age, 2008 ;http://www.smart2020.org/_assets/files/02_Smart2020Report.pdf
http://www.smart2020.org/_assets/files/02_Smart2020Report.pdfhttp://www.smart2020.org/_assets/files/02_Smart2020Report.pdf



Three key trends are driving this movement:

The emergence ofBig Data

The shift of power tothe consumer

Pressure to do morewith less



Meter readings per day in atypical smart meter project

Volume Velocity Variety

500million

Big Data presents a huge new opportunity for Energy & Utilitycompanies if they can harness it

Ingest 3,000 times more

meter readings to betterunderstand and managethe electric distribution

grid

Analyze weather data to

place a wind turbine toimprove its performancewhile extending its useful

life

Analyze all types of asset

performance information tooptimize maintenance

activities and extent usefullife of the assets

From instrumented smart grid,weather forecasts, documents80%

datagrowth

Weather modeling data foroptimizing siting of wind turbines4

petabytes



Applications for Big Data Analytics

Homeland Security

FinanceSmarter Healthcare Multi-channel sales

Telecom

Manufacturing

Traffic Control

Trading Analytics Fraud and Risk

Log Analysis

Search Quality

Retail: Churn, NBO


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Predictive AnalyticsPolice Use Analytics to Reduce CrimeVideo


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Challenges facing utilities and energy providers

Consumers demanding adifferent model

Generation of vastquantities of data

Increasingly high power costs

Environmental concerns

Fluctuating, volatiledemand

Inadequate infrastructure

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Energy and utilities organizations are working toward a smarterenergy value chain to promote responsibility and efficiency

Transformation of

the utility network

Transform customeroperations

Improve generation

performance


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Improve GenerationPerformance

- Align organization and processes to deliver theright products and solutions to each customer

- Enable more efficient customer sales andservice interactions

- Minimize fraud

Transform the UtilityNetwork

- Improve generation efficiency and reduceoperating expenses

- Maximize power generation uptime throughpredictive maintenance

- Reduce outages and downtime- Optimize maintenance and operational activities- Time of use pricing flexibility- Comply with information privacy and retention

regulations

Smarter Analytics for Energy and UtilitiesIndustry Imperative Smarter Analytics Outcome Where Weve Done It

Transform CustomerOperations

Reduced energyconsumption by ananticipated 20%; controlcosts using real timemonitoring

Decreased productioncosts by 1-2% resultingin a savings of 50,000- 100,000 per day

Reduced frequencyand duration of poweroutages



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Word spread virally of the victory with Twitter reaching

11.7M, 30,121 blog mentions, and 15,025 forum posts

On February 14, 2011, IBM Watson changed history


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2012 IBM Corporation17

Putting the pieces together at point of impactcan be life changing

Symptoms

UTI

Diabetes

Influenza

Hypokalemia

Renal Failure

no abdominal painno back painno coughno diarrhea

(Thyroid Autoimmune)

Esophagitis

pravastatinAlendronate

levothyroxinehydroxychloroquine

Diagnosis Models

frequent UTI

cutaneous lupus

hyperlipidemiaosteoporosis

hypothyroidism

Confidencedifficulty swallowing

dizziness

anorexia

feverdry mouth

thirst

frequent urination

Family

History

Graves Disease

Oral cancerBladder cancerHemochromatosisPurpura

Patient

History

Medication

s

Findings

supine 120/80 mm HG

urine dipstick:leukocyte esterase

urine culture: E. Coli

heart rate: 88 bpm

SymptomsFamily

History

Patient HistoryMedicationsFindings

Extract Symptoms from record Use paraphrasings mined from text to handlealternate phrasings and variants

Perform broad search for possible diagnoses Score Confidencein each diagnosis based on

evidence so far

Identify negative Symptoms Reason with mined relations to explain away

symptoms (thirst is consistent w/ UTI)

Extract Family History Use Medical Taxonomies to generalize medical

conditions to the granularity used by the models

Extract Patient History Extract Medications Use database of drug side-effects Together, multiple diagnoses may best explain

symptoms Extract Findings: Confirms that UTI was present

Most Confident Diagnosis: DiabetesMost Confident Diagnosis: UTIMost Confident Diagnosis: EsophagitisMost Confident Diagnosis: Influenza



Real-time projectionsof hurricane path

Dynamically updatedrisk assessment

for assets inprojected path

Correlate combined risk andimpending weather threats to

optimize inventory anddetermine supply chain

recommendations



Top Solution Areas

Retain Customers

Understand what makesyour customers leave,and what makes themstay

Keep your bestcustomers happy

Take action to preventthem from leaving

Acquire Customers

Understand who yourbest customers are

Connect with them in theright ways

Take the best actionmaximize what you sellto them

Grow Customers

Understand the best mixof things needed by yourcustomers & channels

Maximize the revenuereceived from yourcustomers & channels

Take the best action

every time to interact

PredictiveCustomerAnalytics Manage Operations

Maximize the usage ofyour assets

Make sure your assetsare in the right place atthe right time

Identify the impact ofinvestment in various

areas of assets

MaintainInfrastructure

Understand whatcauses failure in yourassets

Maximize uptime ofassets

Reduce costs of upkeep

Secure Operations

Improve the security ofyour assets

Identify unanticipatedattack patterns onassets

Quickly respond with the

best action whensecurity is compromised

PredictiveOperationalAnalytics Detect Suspicious

Behavior

Identify fraudulentpatterns

Reduce false positives

Identity collusive andfraudulent merchants andemployees

Identify unanticipatedtransaction patterns

Mitigate Risk

Identify leaks

Increase compliance

Leverage insights in criticalbusiness functions

Prevent Fraud

Take action in real time toprevent abuse

Reduce Claims HandlingTime

Alert clients of transactionfraud

PredictiveThreat &RiskAnalytics

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Top Solution Areas

Retain Customers

Understand what makesyour customers leave,and what makes themstay

Keep your bestcustomers happy

Take action to preventthem from leaving

Acquire Customers

Understand who yourbest customers are

Connect with them in theright ways

Take the best actionmaximize what you sellto them

Grow Customers

Understand the best mixof things needed by yourcustomers & channels

Maximize the revenuereceived from yourcustomers & channels

Take the best action

every time to interact

PredictiveCustomerAnalytics Manage Operations

Maximize the usage ofyour assets

Make sure your assetsare in the right place atthe right time

Identify the impact ofinvestment in various

areas of assets

MaintainInfrastructure

Understand whatcauses failure in yourassets

Maximize uptime ofassets


Secure Operations

Improve the security ofyour assets

Identify unanticipatedattack patterns onassets

Quickly respond with the

best action whensecurity is compromised

PredictiveOperationalAnalytics Detect Suspicious

Behavior

Identify fraudulentpatterns

Reduce false positives

Identity collusive andfraudulent merchants andemployees

Identify unanticipatedtransaction patterns

Mitigate Risk

Identify leaks

Increase compliance

Leverage insights incritical business functions

Prevent Fraud

Take action in real time toprevent abuse

Reduce Claims HandlingTime

Alert clients of transactionfraud

PredictiveThreat &RiskAnalytics

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Grow Customers

Understand the best mix ofthings needed by yourcustomers & channels

Maximize the revenue receivedfrom your customers &channels

Take the best action every timeto interact

Improved 1:1 Marketing

Individual customer profiles using over 30data points from ATM, phone, Web, andbranch interactions

Decreased direct marketing costs by 18% Increase in overall ROI: 600%

Maintain InfrastructureUnderstand what causes failurein your assets

Maximize uptime of assets


Predictive Maintenance

Observation of the entire car fleets repairperformance in real time

High data complexity: analyzing 20Ksignals via 10K DTCs

Reduction of 25% Repeat Repair

Prevent FraudTake action in real timeto prevent abuse

Reduce ClaimsHandling Time

Alert clients oftransaction fraud

U.S. Border Patrol Resource Optimization

Deploying mobile analytics in the hands ofborder officers

Indentify high-risk cars crossing the borderprior to search

Optimize the deployment of border officers



Making the planet smarter

Smarter Healthcare

Yorkshire Water moved from reactive to proactivemaintenance

supplying around 1.24 billion liters of drinking water each dayUplift in predictability in identifying areas at risk from floodingReducing incidents of other causes f looding and improving

customer service and satisfaction

Improved proactive blockage detection rates by 25-30%

Smarter Education

Marwell Wildlife, a conservation charity, helped secure afuture for an endangered species

Determining the main threats facing the Grevys zebra in the wildUnderstanding critical ecosystems interactionsInvestigating the relationship between nomadic herdsmen andGrevys zebra

Working with communities to implement conservation measuresthat address threats and protect key resources

Smarter Water

Baruch College focused on student successes

Increased applications to its business school by 7.1 %, whenother schools were seeing significant decreases

Achieved a 21 % annual increase in transfer students

Decreased dropouts significantly by using predictive analytics toimprove the placement of freshmen in introductory classes

Sequoia Hospital reached record survival rates

Reduced mortality rate for cardiac surgery to 1.7% in 2008 from3.8% in 2003

Best record nationally for survival from valve replacement overthe past six consecutive years

Reduced doctors diagnostics requests from several weeks to

near real-time speed



83%

Others

95%

Standouts

Getting closer to customers

14%moreGetting closer to customer

People skills

Insight and intelligence

Enterprise model changes

Risk management

Industry model changes

Revenue model changes

88%

81%

76%

57%

55%

54%

51%

Dimensions to focus on over the next 5 years

Our customers wantpersonalization of services andproducts. It is all about the marketof one.

Tony TylerCEO, Cathay Pacific Airways, Hong Kong

To surprise customers requiresunexpected ideas throughinteractions of people with diverseperspectives.

Shukuo IshikawaPresident and CEO, Representative Director,

NAMCO BANDAI Holdings, Inc. Japan

Source: IBMs 2010 Global CEO Study Capitalizing on Complexity (1,541 CEOs, 60 nations, 33 industries)

Getting closer to the customer is the TOP priority


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ResearchProduct

Purchase Product

Get CustomerService

AdvocateProduct

Marketing

Sales

Support/Services

Feedback Management

Social Intelligence

The customer experience has changed dramatically

UseProduct

Up/Cross Sold


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The Baseline of Customer Analytics Applied Mathematics

Statistics: Ask a Question of a Sample to Generalize to the Universe

A Sample of Data A Universe of Things That Generate Data


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Taking Customer Analytics to the Next Level with Predictive Analytics

Predict the Behavior of the Next Case with a Model

A Universe of Data

Attributes: Married, 2 kids Lives in Suburbs of Chicago Owns two Cars 47 years old

Drinks Scotch

A Predictive Model

Predicted Attributes: Upper Middle Income Owns a minivan Likes Van Halen Likes Johnnie Walker Black

Works long hours Commutes

Predicted Behavior Wants to Buy a Sports car! Buys Car Washes! Buys Chardonnay

Vacations where its warm


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Bringing these pieces together Analytics is a Lifecycle

Capture

Data

Collection

Act

DeploymentTechnologies

Predict

Platform

Pre-built Content

StatisticsTextMining DataMining

BusinessRules


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Getting a More Accurate Picture: All the Data Matters

Behavioral data

- Orders- Transactions- Payment history- Usage history

Descriptive data

- Attributes- Characteristics- Self-declared info- (Geo)demographics

Attitudinal data- Opinions- Preferences- Needs & Desires

- Survey results- Social Network Data

Interaction data- E-Mail / chat transcripts- Call center notes- Web Click-streams

- In person dialogues

Traditional

High-value, dynamic

- source of competitive differentiation


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Data at the Heart of Predictive Analytics

Behavioral data

- Orders- Transactions- Payment history- Usage history

Descriptive data

- Attributes- Characteristics- Self-declared info- (Geo)demographics

Attitudinal data- Opinions- Preferences- Needs & Desires

Interaction data- E-Mail / chat transcripts- Call center notes- Web Click-streams

- In person dialogues

Traditional

High-value, dynamic

- source of competitive differentiation

Who? What?

Why?How?


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Micro-targeting: the move beyond 1 on 1 is accelerating. However, consumersare moving from opt-out to opt-in, regaining control over their personal data

Consumers instrumentation and mobility create additional opportunities (time &spatial data dimensions) for more accurate targeting (context-aware decisions right place & right time) through a plethora of touch points through digitalmedia

Social media has dramatically changed the purchase influence cycle exponentially replicating word of mouth, to the power of 10,000 Customeropinions accessible and free to millions and in a matter of seconds

Integrated analytics: promoting holistic contextual decisions integrating supply-

chain data, personal demand data and risk management Brand equity is struggling to remain a guiding light through the global and

multiplicity of access; differentiation is realized through a customer experiencedriving loyalty

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Future Trends

Big Data Analytics Key Note

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