Zd sap - predictive analytics - 3-26-13 r1

Richard R. Lee, Executive Consultant The Speyside Group

Predictive Analytics: From Back Office to Front Office

PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase

Professional Profile

Richard Lee – “Executive Consultant in Business Informatics & Advanced Analytics”

I Guide & Advise Senior Executive Teams in their pursuit of “The Predictive Enterprise”

Worked in many “Information-driven Verticals” over long consulting career;• Banking & Insurance• Utilities• Consumer Goods & Retail• Telecoms• Government• Technology

pre·dic·tive Adjective• “Relating to or having the effect of predicting an event or

result”

a·nal·y·sis Noun• “Detailed examination of the elements or structure of

something, typically as a basis for discussion or interpretation.”

Predictive Analytics:

“Modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future, or otherwise unknown, events.”

What is Predictive Analytics??


The Evolution of Analytics

80’s Statistical Analysis

90’s Descriptive Analysis

00’s Predictive Analysis

10’s Embedded Analysis

4 © 2011 Ziff Davis, Inc. - All Rights Reserved.


Predictive Analytics & Big Data(1)

Traditionally, Predictive Analysis was focused on well-defined data sets• Customer Churn & Up Sell/Cross Sell• Risk & Fraud• Actuarial (Claims & Underwriting)

Finely Tuned Models were employed• Extensive A/B & Champion Challenger

Testing/Development• Maintained by PhD Statisticians, Actuaries and Decision

Scientists

Analysis was time consuming and always “after the fact”• Months to Years of Development & Optimization




Creating a “Real-time Predictive Enterprise” is the goal of every “Analytics Centric” organization today.• Forward Looking pervasive use of all Information aka Big

Data• Embedded Real Time Analysis of Customer Behavior,

Opportunities & Risks and Sources of Competitive Advantage

• Leveraging deep knowledge of the Past and the Present to “Predict” with high accuracy “what will happen next” and to exploit this knowledge in real time to;– Delight the Customer & Win his/her Loyalty– To Mitigate Risks while Maximizing Opportunities– To Clearly Differentiate your Services & Products from the

Competition– To Maximize your Operational Efficiencies and Productivity.




Critical to the Success of the “Predictive Enterprise” is the pervasive use of all Information Resources across your Enterprise by an Analytics-driven Executive Team and Workforce”• Big Data & the deep historical data repositories working in a

“collective fashion” to present a 360° view.• Predictive Analytics engines embedded in Enterprise

Applications• Analytics Tools are available for everyone to exploit from

anywhere.• Deep competencies in Analytics to support Front Line Users

and Analysts.

Creating and Driving “A Culture of Analytics” across the Enterprise should be the CEO’s #1 Priority & Responsibility.



Industry Segments: Banking & Insurance

Banking & Insurance are the most mature segments in terms of using Predictive Analytics.• Customer Insights & Opportunities• Fraud & Risk Management• Quantitative Finance• Pricing and Claims

Case Study in Detail – North American P&C Insurer• Transformational Approach• Move from “Backwards looking” to “Predictive view” of all

aspects of the business.• Goal was “Near Real Time, Holistic Management”• Predictive Analysis embedded in all business functions.


Moments of Truth

I buy/renew

I license

I claim

I amend

I cancel

P&C Insurer

Analytically-Optimized Business Processes

Customer Insights

Predictive Claims

Underwriting

Competitive Pricing

Financial Oversight

Licensing

Analytics- Driven Foresight

CustomerLTV

Attractive Products

Retention and

Upsell/Cross Sell

FraudMitigation

Best Offers(Claims)

ERM/Solvency II

Customer Experience

EmployeeEngagement

Risk Assessment

COE

Business Intelligence Advanced Analytics Performance & Risk Mgmt.

Enterprise Information Subject Areas & Analytical Models

The Customer

Information Delivery

Information Integration

Information Sources (Structured & Unstructured)

Information Foundation

Broker

StrategicGoals

Improve Customer Perception

Improve Employee

Experience

Maintain Financial Security

Predictive Insurance

9


Predictive Claims Processing

Predictive Analysis:• Customer Behaviours, Linkages, etc.• Current claims activities• Claims history• External data (Partners, MD, BI, Gov.

3rd parties, etc.)

FirstNotification

of Loss (FNOL)

Predictive Claims

Platform(Embedded)

Fast Track

Request Additional

Information

SIU

Suspect

Service

Information Infrastructure

Create:• Intelligently scripted/generated questions• Empower Knowledge Workers • Drive Operational Excellence• Delight the Customer

Claims Application Environment


Other Industry Verticals:

Predictive Analysis has/is becoming pervasive in virtually all Industry Segments;• Fast Moving Consumer Goods & Retail• Healthcare• Government• Energy & Utilities• Transportation• Telecommunications• Entertainment• Publishing• Etc., etc.

Leaders within each of these Verticals have created unique Sources of Competitive Advantage for their organization as they have become “Predictive Enterprises”.



The Democratization of Analytics

How do we “move Predictive Analysis from the Back Office to Your Office?• For far too long PA has been the domain of the so-called “data

geeks” and “Bayesians”. – We need to make PA more pervasive by moving it to everyone’s

“Work Platform” e.g. Desktop, Laptop, Tablet, Smart Device, etc.– We must bootstrap everyone’s skills and knowledge to be

“Analytics Literate”

• We must “unleash the power of all of our sources of Information” to create unique and actionable insights for everyone to leverage.– We must move away from “batch driven & IT-lead “ to a “real-time

& Business-lead” Operational Model for delivering Information-based, Analytics-driven Outcomes.

– We must build Governance into all Analytics endeavors as we have done with our Information-related ones, using a holistic approach.


Looking Forward

The distant future as seen from 10-years ago has become manifest already;• Smart Devices and Embedded Applications have accelerated the

“inflection point” for creating massive streams of Information (aka Big Data) and the Pervasive use of Analytics to drive decision making.

Predictive Analysis will be embedded in all Enterprise Applications and Services going forward. • Decision Making at the Point of Contact is paramount.• An integrated view of the Customer is essential to “Delighting him or

her”• Windows of Opportunity are shrinking to zero.

Creating a “Culture of Analysis” along with Delivering “Analytics as a Service” to Everyone is the Critical Path• A, integrated, long-range Analytics Strategy is the key to driving a

successful outcome to this Top Down Vision.


Summary and Hand-Off

Predictive Analytics is a mature discipline, but currently confined to an “elite community of analysts” in most, if not all Enterprises.

The so-called “Democratization of Analytics” will remove these barriers to broad Enterprise Adoption.

A long-range, business driven Analytics Strategy (aligned with the Organization’s overall strategy) is required to insure a successful “Transformation into a Predictive Enterprise”• People, Process, Technology & Culture

A critical first step in this transformational journey is “To Move PA from the Back Office to Your Office”

Documents

Zd sap - predictive analytics - 3-26-13 r1