Download - Business Analytics XIME 2012 Module1
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Introduction to Business Analytics
- For XIME
Prithvijit RoyCEO & Founder, BRIDGEi2i Analytics Solutions
January 2012
@ 2012 BRIDGEi2i Analytics Solutions Pvt. Ltd. All rights reserved
mailto:[email protected]:[email protected]:[email protected] -
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CXOs tough balancing act
Improve
Performan
ce
Maximize
Return
Mitigate
Risk
Increasing
Agility
Maximize Lifetime Value of acustomer engagement
through promotions/loyalty
Proactive crisis management by
predicting natural catastrophes over
the next 5 yearsPredicting employee attrition in the
BPO industry to minimize service
disruptions
POS fraud detection in a credit
card industry
Optimize Resource
Efficiency
&
Maximize Yield
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What is Analytics?
Analytics often involves studying past historical data to research
potentialtrends, to analyze the effects of certain decisions or
events, or to evaluate the performance of a given tool or scenario.
The goal of analytics is to improve the business by gaining
knowledge which can be used to makeimprovements or changes.*
* As defined by Business Dictinorary.com
http://www.businessdictionary.com/definition/historical-data.htmlhttp://www.businessdictionary.com/definition/research.htmlhttp://www.investorwords.com/10666/potential.htmlhttp://www.businessdictionary.com/definition/trend.htmlhttp://www.investorwords.com/210/analyze.htmlhttp://www.investorwords.com/9552/effect.htmlhttp://www.businessdictionary.com/definition/decision.htmlhttp://www.businessdictionary.com/definition/events.htmlhttp://www.investorwords.com/9612/evaluate.htmlhttp://www.businessdictionary.com/definition/performance.htmlhttp://www.businessdictionary.com/definition/tool.htmlhttp://www.businessdictionary.com/definition/scenario.htmlhttp://www.businessdictionary.com/definition/goal.htmlhttp://www.businessdictionary.com/definition/improve.htmlhttp://www.businessdictionary.com/definition/business.htmlhttp://www.businessdictionary.com/definition/knowledge.htmlhttp://www.investorwords.com/10256/make.htmlhttp://www.businessdictionary.com/definition/improvements.htmlhttp://www.businessdictionary.com/definition/changes.htmlhttp://www.businessdictionary.com/definition/changes.htmlhttp://www.businessdictionary.com/definition/improvements.htmlhttp://www.investorwords.com/10256/make.htmlhttp://www.businessdictionary.com/definition/knowledge.htmlhttp://www.businessdictionary.com/definition/business.htmlhttp://www.businessdictionary.com/definition/improve.htmlhttp://www.businessdictionary.com/definition/goal.htmlhttp://www.businessdictionary.com/definition/scenario.htmlhttp://www.businessdictionary.com/definition/tool.htmlhttp://www.businessdictionary.com/definition/performance.htmlhttp://www.investorwords.com/9612/evaluate.htmlhttp://www.businessdictionary.com/definition/events.htmlhttp://www.businessdictionary.com/definition/decision.htmlhttp://www.investorwords.com/9552/effect.htmlhttp://www.investorwords.com/210/analyze.htmlhttp://www.businessdictionary.com/definition/trend.htmlhttp://www.investorwords.com/10666/potential.htmlhttp://www.businessdictionary.com/definition/research.htmlhttp://www.businessdictionary.com/definition/historical-data.html -
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Emerging trends
Explosion ofdigital
information
Better storageand computing
power
Real-timedecisions in a
dynamicenvironment
Demonstratedimpact ofanalytics
New levers fordifferentiation
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Data, information, insights, impact
The analytics JOURNEYData unrefined and factual.Dell sold a laptop to Customer A for $1000
Information data that has meaning for a user.
Total revenues for Dell from sale of notebooks
in Q1 is $200 Mn (What)
Insights is a combination of information,experience and analysis.
Total revenue from sale of notebooks have
seen a 10% fall because of an 12% fall in traffic
to the store (Why & What)
ImpactActionable Intelligence.
Targeted web marketing campaigns toincrease traffic (How)
Why is this transformation important?
Looks like youve got all the data
where is the hold up?
...helps take informed decisions
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The Analytics journey
What happened?
When?
How much?
Why it happened?
What will happen next?
How to operationalize?
How to sustain?
Capture relevant data
Identify key metrics
Design & generate reports
Identify drivers & trends
Understand behavior
Predict outcomes
Build & implement strategies
Enterprise-wide adoption
Metrics & reporting
Descriptive statistics
Visualization
Underlying trends
Predictive models
Optimization
Real time decisions tools
Change management
Institutionalization
INFORMATION INSIGHTS IMPACT
INPUT OUTCOME
Internal & External Data with
structured /unstructured content
Accelerated Growth, Risk
Mitigation, Cost Reduction
Destination
Analytics
Maturity of
Firm
Business
Problem
Addressed
Analytics Play
Business analytics is increasingly being adopted by companies in
decision making to multiply business value based on data
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The Analytics spectrum
Degree of Intelligence
StandardReports
Ad hocReports
PredictiveModeling
Query/Drill down
Forecasting/Extrapolation
Optimization
CompetitiveAdvantage
StatisticalAnalysis
What happened?
How many, how often, where?
Where exactly isthe problem?
Why is this happening?
What if the trend continues?
What actions are needed?
What will happen next?
Whats the best way for it to happen?
BusinessIntelligence
BusinessAnalytics
Source: Adapted from Davenport, Competing on Analytics
To make analytics relevant for businesses it is important to translate it into
applications
Alerts
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Diaper & beer StoryData Mining Discovery
1. Largest chain of large
discount department
stores in the US
2. World's largest public
corporation by revenue
($408 billion)
3. More than 8,969 retailunits under 55
different banners
Walmart placed Diaper & Beer together on the shelves
POS Data Loyalty Card
Data
Diapers Beer Young
American
Fathers
Shopping
between 5-7
pm
http://www.google.co.in/imgres?imgurl=http://www.j2softsolutions.com/image/pos1.jpg&imgrefurl=http://www.j2softsolutions.com/Products.aspx&h=300&w=300&sz=47&tbnid=eNECW8LM7cZUgM:&tbnh=116&tbnw=116&prev=/images?q=point+of+sale&zoom=1&q=point+of+sale&hl=en&usg=__bFpZCBjFZ9QVI_2dgEJV5JJaXeM=&sa=X&ei=MHddTZXcOMmXtwfTlez_Cg&ved=0CEAQ9QEwAghttp://www.google.co.in/imgres?imgurl=http://4.bp.blogspot.com/_6Y-NXZmDcxU/SqBNlzOGw4I/AAAAAAAAGG0/L3ZyK1ceDes/s320/walmart_card.gif&imgrefurl=http://arcticcompass.blogspot.com/2009/09/those-pesty-id-cards-everyone-will-have.html&usg=__T_T3NeLHZQjBIafsNi_YNHn_0r8=&h=250&w=303&sz=37&hl=en&start=1&zoom=1&um=1&itbs=1&tbnid=bodR0PJzYKusjM:&tbnh=96&tbnw=116&prev=/images?q=walmart+loyalty+card&um=1&hl=en&sa=N&tbs=isch:1&ei=T3ddTaC6Dc6ctwe4wMjJCghttp://www.google.co.in/imgres?imgurl=http://4.bp.blogspot.com/_6Y-NXZmDcxU/SqBNlzOGw4I/AAAAAAAAGG0/L3ZyK1ceDes/s320/walmart_card.gif&imgrefurl=http://arcticcompass.blogspot.com/2009/09/those-pesty-id-cards-everyone-will-have.html&usg=__T_T3NeLHZQjBIafsNi_YNHn_0r8=&h=250&w=303&sz=37&hl=en&start=1&zoom=1&um=1&itbs=1&tbnid=bodR0PJzYKusjM:&tbnh=96&tbnw=116&prev=/images?q=walmart+loyalty+card&um=1&hl=en&sa=N&tbs=isch:1&ei=T3ddTaC6Dc6ctwe4wMjJCghttp://www.google.co.in/imgres?imgurl=http://upload.wikimedia.org/wikipedia/commons/thumb/d/d6/Wall_clock.jpg/300px-Wall_clock.jpg&imgrefurl=http://commons.wikimedia.org/wiki/Commons:Featured_picture_candidates/Log/March_2006&usg=__aa2M8HdeQ--B2SAx6UjeJp52M8k=&h=310&w=300&sz=22&hl=en&start=3&zoom=1&um=1&itbs=1&tbnid=YUT9Qdwa8jKzLM:&tbnh=117&tbnw=113&prev=/images?q=clock&um=1&hl=en&tbs=isch:1&ei=fnldTfC7HYW3tgeW8LHRCghttp://www.google.co.in/imgres?imgurl=http://www.wired.com/news/images/full/diaper3_f.jpg&imgrefurl=http://www.wired.com/science/discoveries/news/2004/04/63182&usg=__7GjX1VXiyotpFf0DU5_1Oo2uvvM=&h=375&w=500&sz=31&hl=en&start=5&zoom=1&um=1&itbs=1&tbnid=pn5G1CO_i59JiM:&tbnh=98&tbnw=130&prev=/images?q=diapers&um=1&hl=en&tbs=isch:1&ei=3nddTenFC4HXtgfc2YzDCghttp://www.google.co.in/imgres?imgurl=http://cropandsoil.oregonstate.edu/sites/default/files/news/beer-styles1.jpg&imgrefurl=http://www.gondwanaclub.net/beer-cans&usg=__FXz9TkHFmsLa5O7IX3NJNjyCQkA=&h=314&w=311&sz=26&hl=en&start=2&zoom=1&um=1&itbs=1&tbnid=GJ2X5xKvvm4iuM:&tbnh=117&tbnw=116&prev=/images?q=beer&um=1&hl=en&tbs=isch:1&ei=l3ddTdDyBIGFtgfiopHDCghttp://www.google.co.in/imgres?imgurl=http://4.bp.blogspot.com/_6Y-NXZmDcxU/SqBNlzOGw4I/AAAAAAAAGG0/L3ZyK1ceDes/s320/walmart_card.gif&imgrefurl=http://arcticcompass.blogspot.com/2009/09/those-pesty-id-cards-everyone-will-have.html&usg=__T_T3NeLHZQjBIafsNi_YNHn_0r8=&h=250&w=303&sz=37&hl=en&start=1&zoom=1&um=1&itbs=1&tbnid=bodR0PJzYKusjM:&tbnh=96&tbnw=116&prev=/images?q=walmart+loyalty+card&um=1&hl=en&sa=N&tbs=isch:1&ei=T3ddTaC6Dc6ctwe4wMjJCghttp://www.google.co.in/imgres?imgurl=http://www.j2softsolutions.com/image/pos1.jpg&imgrefurl=http://www.j2softsolutions.com/Products.aspx&h=300&w=300&sz=47&tbnid=eNECW8LM7cZUgM:&tbnh=116&tbnw=116&prev=/images?q=point+of+sale&zoom=1&q=point+of+sale&hl=en&usg=__bFpZCBjFZ9QVI_2dgEJV5JJaXeM=&sa=X&ei=MHddTZXcOMmXtwfTlez_Cg&ved=0CEAQ9QEwAghttp://upload.wikimedia.org/wikipedia/commons/1/16/US_map_-_geographic.pnghttp://www.google.co.in/imgres?imgurl=http://www.featurepics.com/FI/Thumb300/20081118/Young-American-Male-Holding-Coffee-Mug-Thumbs-969035.jpg&imgrefurl=http://www.featurepics.com/online/Young-American-Male-Holding-Coffee-Mug-Thumbs-969035.aspx&usg=__PizM-2zJq2vu0tQYQJhBLR4c9DY=&h=449&w=299&sz=22&hl=en&start=3&zoom=1&um=1&itbs=1&tbnid=DB53F3J5M9c7pM:&tbnh=127&tbnw=85&prev=/images?q=young+american+male&um=1&hl=en&tbs=isch:1&ei=8HhdTdGJB9STtwez9p3GCg -
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Enablers for successful Analytics
BUSINESS CONTEXT
Pillars of the analytics bridge
TECHNOLOGY
ADOPTION
ANALYTICS RIGOR PEOPLE PRACTICE CULTURE
Handling big data
Cutting-edge statistical
techniques
Analytics embedded in
decision making
Industry & functional
understanding
Company priorities
Change management
Enterprise data linkage
Analytics tools
Data privacy andcompliance
Attract analytical talent
Develop / retain talents
Knowledgemanagement
Information based
decisions
Structured innovation
Implementation focus
Multiplying returns from analytics requires a balanced focus
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Functional
applications
Targeted acquisition Lifecycle valueenhancement
Customer experiencemanagement
Enhance retention
Customerintelligence
Market intelligence Maximize return onmarketing investment
Digital media effectiveness
Marketingeffectiveness
Price setting Discount optimization
Price realization
Priceoptimization
Sales forecasting
Sales force planning
Sales force enablement
Saleseffectiveness
Customer riskmanagement
Fraud detection Portfolio risk assessment
Riskmanagement
Procurement spendoptimization
Human resourceeffectiveness
Customer service planning
Operationsplanning
BUSINESS
CONTEXT
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Industry
applications
Banking & Financial Services
Cross Sell / Up-Sell
Credit Risk Management
Customer ExperienceManagement
Insurance
Lead Generation
Claims Management
Capital Adequacy
Public Sector
Service Quality Management
Education Program Effectiveness
Revenue Management
Telecom
Revenue Assurance
Churn Management
Asset Optimization
Retail & Consumer Goods
Market Mix & PromoOptimization
Increase Customer Loyalty
Assortment Planning
Technology
Product Usage Experience
E-commerce effectiveness
Pricing Optimization
BUSINESS
CONTEXT
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Data types
Financial Information
Revenue, Order, Shipment, Margin
Marketing Spends and Cost information
Pricing, deal, special discounts etc
List price, catalogue, people cost
Marketing Targeting Information
Campaign targeting, cost & response
Leads and opportunities
Channel and RoI information
Web traffic data
Support & Touch Point Information
Support Contracts
Call Center data
Warranty and Support Satisfaction data
Product Usage Data
External Information
Company financials and profile
Consumer demographics
Market Research data Channel and Partner feedback data
Market Tracking data
Illustration Data available to Marketing function of a typical technology company
TECHNOLOGY
ADOPTION
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Data linkages
TECHNOLOGY
ADOPTION
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Analytics tools
SAS The most popular tool in the data analysis space
IBM SPSS
Powerful tool used very highly in market research space.
Insightful Miner
Well respected statistical tools, now moving into mining
Oracle
Integrated data mining into the database
Angoss
One of the first data mining applications (as opposed to tools). Good for Decision Tree analysis
IBM Unica
Great mining technology, focusing less on analytics and more on campaign operations
SPlus , R
Open source. Mostly used in academic and research reasons. Less costly, includes new techniques
TECHNOLOGY
ADOPTION
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Handling big data
Data Consolidation
Merging diverse data
Managing Granularity of data
Univariate Analysis
Missing Value Imputation
Mean / Median / Mode Imputation
Special missing values
Regression Imputation
Outlier Treatment
Delete / ImputeCapping of values
Creating Final data for analysisCreate New Derived VariablesSampling for analysisCleaning
ANALYTICS
RIGOUR
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TESTING OF HYPOTHESIS & ASSESS DRIVERS CLASSIFICATION INTO HOMOGENEOUS SEGMENTS
Statistical testing of hypothesis
and estimation of parameters ,
building business cases and
analysis of key drivers
Identify homogeneous segments
based on key attributes behaving
in similar manner ( cluster, tree &
machine learning techniques)
PREDICTION OF EVENTS FORECASTING OF KEY METRICS
Prediction of certain business
events ( sales, attrition, cost,
risk etc.) based on attributes
impacting the same
Forecasting of key metrics based on
trend and patterns observed over
time and patterns in key influencing
attributes
SIMULATION OF SYSTEMS OPTIMIZATION OF SPECIFIC OBJECTIVE
Simulation of scenarios to
assess variability of business
metrics based on assumptions
on key external factors
Optimization of business objective
based on multiple operative
constraints
TechniquesANALYTICS
RIGOUR
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Skill development
StatisticsMathematicsEconometric
s
ComputerScience
databases,programing
Datavisualization
skills
Adaptabilityto
continuouschange inanalytics
Businesscontext todrive ROI
fromanalytics
PEOPLE
PRACTICE
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Implementation focus
13-Jan-12
RECOMMENDATION
ENGINESCORING
SERVICE
CUSTOMER
ANALYTICS
PRODUCT
ANALYTICS
MODELS +
CUSTOMER, PRODUCT
DATA
SUPPLY CHAIN
SERVICESUPPLY CHAIN
ANALYSIS
MARKETING
& PRODUCT
MANAGEMENT
MARKETIING
-Internal /
External sources
SUPPLY
CHAIN
Internal / External
sources
MARKETING
DATA
PRODUCT
DATA
REALTIME
DATA
CALL CENTER
WEB STORE
PUBLIC/PRIVATE
ADMINISTRATION
RULES & METADATA
Availability Lead TimeOverstock
CustomerPropensity
ProductAssociation
ConfigurationMargin Product Families
Product Hierarchies
MARKETING
SERVICE
PRODUCT
SERVICE
CampaignsCatalogs
SUPPLY CHAIN
DATA
SALES
CLIENT BUSINESS MGR
Data selection /collection Data preparation/ modeling Pattern discovery / deployment Monitoring andimprovement
INTERNAL DATA
- Customer Touch points
- Business Performance
Data
- Transactional Data
EXTERNAL DATA
- Prospect Demographics
- Survey Data
- Web, Publications
CULTURE
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Why bother about analytics?
Analytics is mission critical last remaining source of differentiation
Competing on Analytics, by Thomas Davenport
Some companies have built their very businesses on their ability to
collect, analyze, and act on data.
Analytics competitors are the leaders in their varied fieldsconsumer
products finance, retail, and travel and entertainment among them .
Super Crunchers, by Ian Ayers
In the past, one could get by on intuition and experience. Times have changed.
Today, the name of the game is data. Steven D. Levitt, author of Freakonomics
Data-mining and statistical analysis have suddenly become cool.... Dissecting
marketing, politics, and even sports, stuff this complex and important shouldn't be
this much fun to read Wired
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THANK YOU
Linkedin - http://www.linkedin.com/company/bridgei2i-analytics-solutions
Facebookhttp://www.facebook.com/pages/BRIDGEi2i-Analytics-Solutions/127891620624459
Twitter - @BRIDGEi2i
Webwww.bridgei2i.com
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