USING PREDICTIVE ANALYTICS FOR DATA-DRIVEN DECISIONS

Quiz

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Which course do students hate the most?

What is the sexiest job today?

Data Scientist

What Has Changed?Why Is Predictive Analytics a Hot Topic?

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The time for decision-making has SHORTENED!!!More real-time, on-the-job, data-driven decision-making

Explosion of Multi-Dimensional DataWhy Is Predictive Analytics a Hot Topic?

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Advanced analytics helps you organize the world of big, multi-dimensional data into actionable knowledge

Multi-source, multi-dimensional data has hidden patterns

Advanced analytics reveals the underlying patterns and allows us to make predictions and other actionable decisions

Explosion of Multi-Dimensional DataWhy Is Predictive Analytics a Hot Topic?

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High Dimensional Data

Identify combinations of the data that have distinct monetizable characteristics

The Cube

Slice and dice the data along neatly cut dimensions

Explosion of Multi-Dimensional DataWhy Is Predictive Analytics a Hot Topic?

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High Dimensional Data

Identify clusters Identify patterns and exceptions Identify marginal effects of outcomes

Business Benefit: Better marketing & targeting Revenue growth or loss prevention More effective resource allocation

The Cube

OLAP like reports High level of aggregation Drill down to details

Business Benefit: Get to the bottom of issues If sales are declining, which region or

product is causing it

How Does Predictive Modeling Work?

Copyright 2007, Information Builders. Slide

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Detect a pattern

Trend

Outlier

Cluster

Detect which

variables explain It

Not important

Important

Marginally

important

Detect variable

relative importance

Variable weight

Data-Driven Decisions Are Not Solely About New Technology

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Goal of Data-Driven Decisions

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Goal of Data-Driven Decisions

Predictive Analytics SystemNeed more than a modeling factory

Integrating Data

• Access to 100s of data sources

• Seamless inclusion of new sources for new analyses

• Merging, filtering, aggregating, deriving, transforming, sampling

• Embed data quality

• Often 2/3 of the effort!

Designed for the Analyst

• No coding or scripting

• Graphical user interface

• Workbench for advanced analytics

• Stats analysis, visualizations, transforms, models for pattern discovery and model testing

• Rapid model creation!

Data Access Predictive Modeling Results Deployment

SocialHot

BadFeedback

Self-Service for Everyone

• Automated information delivery

• Interactive smart statements

• Interactive portal experience

• Dashboards, ad hoc reporting,

• Feeding downstream apps

• Deliver predicted results for action!

Optimizing Decisions via Predictive Modeling

Increase products

used per customer

Increase prices /

fees

Decrease

processing costs

Improve collections/recovery rate

Proactive retention of profitable customers

Increase switching costs

Target more profitable segments

Increase cross / up sell volume

Differential Tariffing

Increase fee based income

Risk based pricing

Increase share of wallet

Decrease marketing costs

Decrease transaction processing costs

Decrease new account processing costs

Decrease customer service costs

Decrease delinquency rate

Decrease default rate

Increase activation rate

Decrease campaign cycle time

Increase Response Rate

Increase

Profits

Increase

revenues

Decrease

costs

Increase customer

acquisition

Increase customer retention

Grow customer lifetime

value

Decrease operating

expenses

Decrease charge-offs

Related ProgramsOrganizational Objectives

Manufacturing And Logistics – Predictive Part Failure

Use Case: Airline Maintenance Dashboard alerting station manager of likelihood of maintenance issues on specific aircraft, when they arrive and is the part in stock or not.

Impact: Whether it vehicles transporting goods, service or people; or machines on a plant floor, predicting the likelihood of part failure keeps operations running smoothly and improves service and saves on costs

Healthcare – Patient Volume and Staffing

Use Case: One of a Hospital’s biggest areas of expense are labor costs that are directly related to patient volume. Patient volume is impacted by a number of factors, CDC Alerts, Weather conditions, Lunar Cycles, Special events etc.

Impact: Predicting patient volume can help the hospital optimize staffing levels, which helps better manage labor costs and improves the patients overall experience because they are less likely to wait for service.

Healthcare – Predictive Readmission Performance

Use Case: Predict and Score Patients Most Likely to Readmit based on Previous Clinical History based on Demographics, Consumer Habits and Clinical Factors

Impact: Per CMS readmissions within 30 days for many conditions will not reimbursed therefore it is incumbent on hospitals to proactively reduce readmissions and ED “Frequent Flyers.” Improved discharge procedures and transitions to post acute care.

Insurance - Claim Analysis and Fraud Detection

Use Case: Both Warranty and Insurance Claims have a mix of structured and unstructured data that are useful for identifying fraud

Impact: Being able use both types of data in your analysis will help organizations become more efficient in identifying possible fraud or abuse.

Higher Education – Student Retention

Use Case: Successful enrollment management includes retaining current students. Often institutions have not used available data to understand who stays and who leaves.

Impact: The ability to identify and develop profiles of students who are most likely to leave your school and then recommend intervention strategies to reduce student attrition

Government - Predictive Policing

Use Case: Local agencies such as police departments can leverage advanced, real-time analytics to provide actionable intelligence.

Impact: Understand criminal behavior, identify crime/incident patterns, and uncover location-based threats.

Use Data to Drive Better Business Decisions

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Goal

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Thank you

The value of your information assets is maximized when you implement: (1) a fully integrated data experience, (2) a systematic data quality and integrity validation, (3) pervasive business intelligence, and (4) robust analytics for every decision maker.