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IBM SPSS Modeler

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What is Predictive Analytics?

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Why is predictive analytics important to your organization

„The median ROI for the

projects that incorporated

predictive technologies was

145% compared with

median ROI of 89% for

those projects that did not” - source: IDC, „predictive

Analytics and ROI: Lesson from

IDC’s Financial Impact Study”

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Advanced Analytics Focuses on the Prescriptive & Predictive

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Predictive Analytics can use ALL Available Data

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 media

Interaction data - Email / chat transcripts - Call center notes

- Web click-streams - In person dialogues

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Predictive Customer Analytics

Acquire customers:

Understand who your best customers are

Connect with them in the right ways

Take the best action maximize what you sell to them

Grow customers:

Understand the best mix of things needed by your customers and channels

Maximize the revenue received from your customers and channels

Take the best action every time to interact

Retain customers:

Understand what makes your customers leave and what makes them stay

Keep your best customers happy

Take action to prevent them from leaving

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Predictive Operational Analytics

Manage operations:

Maximize the usage of your assets

Make sure inventory and resources are in the right place at the right time

Identify the impact of investment

Maintain infrastructure:

Understand what causes failure in your assets

Maximize uptime of assets

Reduce costs of upkeep

Maximize capital efficiency:

Improve the efficiency and effectiveness of your assets

Reduce operational costs

Drive operational excellence in all phases: procurement, development, availability and distribution

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IBM SPSS Predictive Analytics

Acquire

Grow

Retain

Predictive

Customer Analytics

Predictive

Threat & Fraud Analytics

Monitor

Detect

Control

Predictive

Operational Analytics

Manage

Maintain

Maximize

Etc…

IBM Research

Collaboration and Deployment Services

Analytic Server

& Catalyst Modeler

Decision Management

Social Media

Analytics

Data

Collection Statistics

Analytic Answers

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IBM SPSS Modeler Overview

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Business understanding

Data understanding

Data preparation

Modeling

Evaluation

Deployment

Data Mining Methodology – CRISP-DM

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IBM SPSS Modeler

• Easy-to-use, interactive interface without the

need for programming

• Automated modeling and data preparation

capabilities

• Access ALL data – structured and

unstructured – from disparate sources

• Natural Language Processing (NLP) to

extract concepts and sentiments in text

• Entity Analytics ensures the quality of the

data and results in more accurate models

• Leverage existing investment in Cognos,

Netezza, InfoSphere and System Z

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Monte Carlo Simulation

Generate simulated data

Fit distributions from existing data

Evaluate the simulation

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Classification and Prediction

Help to predict a result:

• Will a customer buy or leave

• Does transaction fit a known pattern of fraud

• Expected inventory levels

• Forecast number of widget purchases

Techniques included

• Decision Trees

• Bayesian Networks

• Neural Networks

• Decision List

• Statistical Models

• Time Series

• Self Learning Response Models

• Support Vector Models

• Nearest Neighbor Models

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Extend the Use of R

Build and score R models through Modeler GUI

Scale R execution by leveraging database

vendor provided R engines

Use R processes and generate output

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Delivering the Next Best Action

with Modeler

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Analytical Decision Management

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Decision management is an innovative business discipline that

combines a variety of techniques to optimize actions and outcomes

• Provide front-line employees

and systems with

recommended actions

• Empower real-time and

adaptive decisions

accommodating changing

conditions

• Optimize actions with

resource constraints, aligning

execution with strategy

Optimized decisions

+ + Business

rules Optimization Predictive

analytics

All data

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Automated Transactional Decisions and Actions Using Predictive

Analytics, Rules, Scoring and Optimization

Level Points

Low risk > -5

Medium risk > +1

High risk > +8

Front line staff and systems

benefit from recommendations,

offers and dashboards wherever

they are needed

Access ALL

data

• Structured

• Unstructure

d

• social

media

• business

intelligence

• performanc

e

managemet

t data

Rules Predictive analytics

Simulation and

optimization

Scoring

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Data Preparation

SPSS Modeler SPSS Modeler

Import Data

Cognos Package

Author Report

Create Report / Dashboard

SPSS Modeler and Cognos BI

Create Predictive Insight

Report / Dashboard

Consume Analytics Export Data

Cognos Package

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Thank You

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