Analytics Over View

8/3/2019 Analytics Over View

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© 2009 IBM Corporation1

Redpill MBPS Analytics Over view



© 2009 IBM Corporation

Building a smarter planet

2

1. What is Analytics?

2. IBM Analytics





3

Analytics is defined by various people in different ways

Reporting / MIS?

Statistics?

OperationsResearch?

DatabaseMarketing?

Optimization?

Programs /Campaigns?

DataManagement?

PredictiveModeling?





4

We define analytics as follows:

“…driving business resultsthrough the study of business data usingmathematical and statistical analysis

for decision-making ”





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1. What is Analytics?

2. IBM Analytics





7 + +INSTRUMENTED INTERCONNECTED INTELLIGENT

“IBM s Smarter Planet agenda has analytics at its core,making it the industry's most comprehensive vision

for the future direction of business analytics…”

Dynamic InfrastructureSmart Work

New Intelligence Green & Beyond

SMARTER PLANETWITH ANALYTICS


http://slidepdf.com/reader/full/analytics-over-view 7/22 © 2009 IBM Corporation


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Analytics value proposition is focused ondelivering business results using customer data

Domain expertise &knowledge of industry

and client-specificbusiness challenges

Integrated approachcombining all

components required todeliver results

Global deliverycapability with a hybridon-site & offsite model

Technology agnosticmodel to ensure easy

adaptation andflexibility

Business resultsto the client and

quick time tomarket




9

IBM s capabilities exist along the entire Analytics value curvedriving different business benefits

Data ManagementETL – Consolidation of data

BenchmarkingKey Performance Indicators (KPIs) / SLA s agreed upon by stakeholders

Advanced AnalyticsSegmentation, Predictive modeling and Optimization

Time and Resources

Value andImpact

AnalysisMulti-dimensional analysis so one can “slice and dice”

Basic ReportingRegulatory reporting that is reasonably automated

Smarter DataManagement

SmarterReporting

SmarterPerformanceManagement

SmarterInsights

SmarterBusiness

Impact

Efficiency

Effectiveness

BusinessImpact




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Our Differentiator…Smarter Way of doing analytics

Traditional Analytics

IBM Assets

IBM

INTEGRATEDANALYTICS …

CombiningTraditional &Asset-Based

AnalyticsIBM Market

Intelligence Group

IBM ClientBusiness Value

Group

IBM ResearchLabs

IBM Centre forBusiness

Optimization




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Our recent acquisitions have further strengthened IBM s AnalyticsCapabilities

Market Leader as the PredictiveAnalytics Software

SPSS Software has capabilitiesto build Analytical Solutions for

– Customer Profitability

– Customer Acquisition andRetention

– Demand Forecasting

– Employee Hiring and Retention

– Fraud Detection …

Redpill Solutions is a boutiqueanalytics firm

The firm specializes in – End to End Customer

Management Services

– Strategy related services like „Go -To Market Strategy , based onCustomer Research andInnovation for new customertrends




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To deliver an improved out put

DataManagement

Reporting

Benchmarking

Analysis

AdvancedAnalytics

Complex, One-OffProblem Analysis

CognosBI Tool

OAEText Mining Tool

SIMPLEPatent Analytics

LinkageDiscoveryVoice Analytics

DatastageData Management

TABIAccelerated BI

DIOSInventory

Optimization

COBRAWeb Analytics

SNOWSC Network

Optimization

SPSS RedPill

Research/ CBOSpecialized Tools

FAMSClaims Tool

CELMMarketingOptimization

... and many more

Tool & Service

Assets

Tool-based

Assets

Assets

F u n c

t i o n a

l C a p a b

i l i t i e s





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Acquisition

Segmentation

Portfolio Management

IVR Analytics

Churn Management

Customer Management

Analytics

Finance & Administration Analytics

Human Resources Analytics

Supply ChainManagement

Analytics

Industry Specific Analytics

Reporting

Risk Management

SpendManagement

…Spanning different problem areas across industries

Customer profiling to identify right set of customers for targeted campaigns

Devising customer acquisition strategies and developing customized offerings based on analysis ofinternal / external data

Screen out ‘bad customers’ during acquisition process through Predictive modeling

Analytics-led Cross-sell campaigns to derive maximum value out off the current customer base

Reporting & Analysis around IVR Effectiveness to assess Customer Experience and identifyingmarketing opportunities

Understanding business drivers for churn and accordingly devising retention strategies for proactively retaining high-value customers

Manage risks across customer lifecycle using application / behavior scorecards

Comprehensive spending profile enabling negotiations with the supply market, and driving bottomline savings

Web / Portal analytics to facilitate customer analysis, increasing traffic and enhancing conversions

Suite of End-to-End reporting and dash boarding solutions to drive quick and effective decision-making

Web Analytics





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Illustrative Examples on Solutions *

* - Partial List





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Attrition Management : Proactively retain potentially high valuecustomer s through attrition scorecard & strategy

Identify customers to be retained by the bankthrough profitability estimates

Results in decrease in attrition as well as

increase in revenues

2

4

A decision tree / scorecard to predict thecustomer base who are likely to attrite

1

Devise retention strategies for the selectedcustomer base (who may attrite)3

Customerbehavior &

productholdingpatterns

Cross- sellModel

Top- upPropensity

model

Check with bankofficers

30%decrease inAttrition

$ 50KincreaseinRevenues/ Program

19 nodes

• Amount of Credit/ Amount of debit(last 3 months)

• Principal Paid ratio• Disbursal Amount/

EMI• Worst DPD in last 6

months• …• …

7 Key Decision Variables Profits, USD/Customer

Best Worst

Decile

1 2 3 4 5 6 7 8 9 10

-350

-100-60-30-10100200

400

800

1,200

Most profitablecustomers

Customers who areover promoted with

no returns

Customers who can be allowed toattrite due to low returns





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Segmentation : Identify key segment opportunities by combining internaland external customer data

Results in market share gain & efficienttracking of performance

Estimate potential & design go to marketstrategy

M a r k e t D a t a

I n t e r n a l D

a t a

Customer segmentsin the market

Customer segmentswithin existingcustomer base

Ideal positioning

External Segments Internal Segments

W a l l e t s i z e

( m a r k e t )

W a l l e t s i z e

( c l i e n t s )

Yearly turnover

Expected $revenue / marketshare fromopportunity

How tocapture theopportunity

Opportunity

• Incremental marketshare

• Incremental revenue• Cash flows

• Segments strategy• Mktg & Dist Strategy• Campaigns &

promotions• Focus on analytics to

balance risk

Ideal positioning

Targets tied to estimated marketshare gainHigher market shareIncreased stickiness

Identify and profile market & internalcustomer segments

Map internal segments to market toidentify opportunity & ideal positioning





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Cross-sell/up-sell : Cross- sell relevant products to „good customersthrough the use of behavior score-card and propensity models

Identify key attributes thatdetermine customers likely to

take x-sell / top-up offers

R

a n k

o r d e r e d

2Identify „good customers based on

behavior score

1

Example score-bands for a regional bank • Loan Tenor • Ever Top-up • Ratio of loan-balance

& loan disburse amount

• Loan balance • Vintage of customer • …

Same bank other

product owners

Partner companycustomers

Same bank cardowners

Find the customer baseyou want to run cross-sell

campaigns on

3

8%12%

18%

Bottom9th8th7th6th

4%

5th

6%

4th3rd2ndTop

46%

Deciles – withoutPredictive modeling

Modeleddata

76%

100%Rank ordercustomersbased on thepropensity torespond to thecampaign

Larger target base, with lower riskresulting in revenues and cost-

savings

Increased

Target Base

Reduced

„Bad rate

30K

0.6%

Before After

4

5





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Reporting & Automation Solution

People AnalystsTechniciansStatisticians

TechnologyCognos, Brio, Hyperion, BODatastageMS Excel / VBA, MS AccessSAS / SPSS

InfrastructureServers, StorageFirewall, Internet, etc.Softwares

Analysis Services

Calculation, Formatting,

Consolidation,Reconciliation of Data

Report Creation

Data Services

Data Extraction

Data cleansing andconsolidation

Automation Services

Ad-hoc Queries

Report Automation

Generation of Reports andGraphs

Hosting Services

Hardware

Software

Network

Benefits:Process Standardization leading to Sustainability and enhanced Efficiency

Easy Real-time Access and User-FriendlyDrill-up & Drill-down CapabilitiesMechanism to analyse and drive further insights enhancing Process Effectiveness





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Problems Addressed

Lack of visibility into what is beingpurchased across the entire companyBuying power is not fully exploitedSpend data not readily available and/or

accurate to support suppliermanagementMultiple specifications for commoditieswithin the same functionsPrices vary among same itemsSmall proportion of negotiable spend isunder agreement

A comprehensivespending profileenablesnegotiations withthe supplymarket, anddrives bottom-line savings

Identify datasources

Cleanse andconsolidate

data

CategorizeSpend

DeliverSpend

Analysis

Data required areusually found in amultitude ofrepositories andsystems.

Comprehensiveview of allexpenditures,including buyingLocations -entities, segment,business units

Categorizespend intohierarchicalgroups of goodsand services thatreflect supplymarket structure

Process

Spend split by – direct versus indirect

– capital expenditure versus expense – materials versus services

Spend profile by – Invoice type – Commodity/service by supplier – Commodity by division/operating unit and

buying location – Number of suppliers by commodity/service

Spend Analysis SolutionProvides an effective tool for consolidating company-wide data, establishing baselinesand anchoring strategic sourcing decisions.





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ObjectiveForecast Cash flow t + Xperiod based on historicalcollection performance trends

Data Requirement3 years daily cash received

Capacity utilized

BenefitEnables Operations team toidentify the gap betweenprojected cash collections andtarget

Forecast Cash Flow

ObjectiveQuantify and Develop plan toaddress the gap betweenprojected cash collectionsand target

Data RequirementCash Forecast & targets

BenefitEnables Operations team toproactively address anydeficit by prioritizingresources / segments

ObjectiveCategorize the customersbased on historical paymentbehavior

Data Requirement~ 3 years transactional levelpayment data at a customerlevel

BenefitEnables differential servicingstrategies from a

Contact Channel

Contact Frequency

ObjectiveImplement Collectiontreatment strategies

Data RequirementAccount level treatmentstrategies

Benefit

Increased Cash FlowImproved CollectionsefficiencyEnhanced CustomerSatisfaction

Lower Operating costs

Identify the gaps(projected and target) Segment Optimize Efforts

Increasing collection effectiveness without increasing operatingexpenses by adopting a “smarter” targeting strategy based on Customer risk scoring.

Business Objective Impact / Benefits

Improving cash collectionsReducing DSO

Improving agent performance

Collections Solution





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Thank You

Analytics Over View

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