IBM,אורן עייש

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Optimize Business Insights with IBM Content Analytics

Business Overview and Introduction

Oran Aish ECM & Content Analytics Solution Leader

IBM Israel, Global Business Services

23/07/2012

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Agenda

• The Growing Need for Content Analytics

• Business Drivers for Content Analytics

• IBM Content Analytics Overview

• Q&A

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We have numerous competitors in this converging market

But competitors lack our integrated mix of NLP, text mining and content classification capabilities

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Agenda




• Q&A

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Content Analytics Use Cases

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IBM Content Analytics adds value to…

Automotive Quality Insight

•Analyzing: Tech notes, call logs, online media

•For: Warranty Analysis, Quality Assurance

• Benefits: Reduce warranty costs, improve customer

satisfaction, marketing campaigns

Crime Analytics

• Analyzing: Case files, police records, 911 calls…

• For: Rapid crime solving & crime trend analysis

• Benefits: Safer communities & optimized force deployment

Healthcare Analytics

•Analyzing: E-Medical records, hospital reports

•For: Clinical analysis; treatment protocol optimization

•Benefits: Better management of chronic diseases;

optimized drug formularies; improved patient outcomes

Insurance Fraud

• Analyzing: Insurance claims

• For: Detecting Fraudulent activity & patterns

• Benefits: Reduced losses, faster detection, more

efficient claims processes

Customer Care

•Analyzing: Call center logs, emails, online media

•For: Buyer Behavior, Churn prediction

•Benefits: Improve Customer satisfaction and retention,

marketing campaigns, find new revenue opportunities

Content Assessment

•Analyzing: File shares, Sharepoint, multiple content

repositories

•For: Content Decommissioning or Smarter Archiving

•Benefits: reduce storage costs, repurpose IT assets,

save on energy consumption, reduce risk exposure

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Solution components:

IBM GBS Application Innovation

Service (AIS); IBM GBS BAO

IBM ITS Delivery

IBM DB2 9.7, I

IBM Content Analytics

IBM WebSphere Application

Server

IBM Tivoli Storage Manager,

v6.1, Tivoli Monitoring V6.2

IBM Power Servers

“Speed plus accuracy are the keys to competitiveness.”

The Need:

The regulation and legislative database business is one of the client’s most

important business areas. With more than 1,200 of the country’s 1,800 local

governments as clients, the company needed to improve the accuracy and

speed of its regulation update service in order to stay ahead of new

competitors and technology improvements.

The Solution:

The company transformed its regulation management and updating system

with the help of natural language analysis technology and advanced search

technology. The new regulation revision system can automatically recognize

changes to regulations, updating them automatically, replacing a time-

consuming, error-prone human process.

What Makes it Smarter:

Automatically amends legislation and regulations by analyzing the meaning

of revisions, almost instantly integrating revisions to the original legislation

texts

Improve accuracy in regulation revision, and represents a significant

improvement in the speed of regulation revision

Shortens the lead-time to bring new updated legislation to clients (local

governments) by 50%

Legislative Document Revision Company Advanced natural language analysis and smarter searching speed regulation revision

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Japanese computer services company Analyzes multichannel customer input for improved service

The need:

A Japanese computer services company receives over 10,000 instances of customer

input monthly as it provides onsite support and support center services. The company

kept precise correspondence logs, but they were difficult to summarize and analyze.

To improve service quality and increase its understanding of customer needs, the

company needed to analyze the large and growing volume of input.

The solution:

The company implemented a text analytics solution to combine customer input with

other data so it could anticipate and detect failures of individual products and products

deployed in combination. The solution makes that possible, while also enabling the

company to run various analyses with many conditions, to respond more quickly than

competitors to service requests, and to report findings to customers.

What makes it smarter:

Analyzes customer input data and detects potential problems gathered from

multiple channels to help the company understand customer needs to

significantly improve service quality

Integrates data from onsite service and support center calls; manages and

analyzes more than 10,000 inputs per month from all over Japan

Manages all digitized data—including inquiries, requests and complaints received

via phone and email—to present a single, unified view

Text analysis provides new

customer insights for greater

competitiveness.

Solution components:

IBM® WebSphere®

Application Server

IBM System x®

IBM Content Analytics

IBM Global Technology

Services

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Massive recall of vehicles often makes the headlines…

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For example, in early May 2009, we found defects of a specific car model were significantly increasing from March to April.

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We can quickly drill into details of the defects for this model and see the issues are related to rust.

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Several month after our finding, we saw this potential problem was making headlines

http://usnews.rankingsandreviews.com/cars-trucks/daily-news/091009-Toyota-Tundra-Investigated-For-Severe-Frame-Rust-Problems/

http://wheels.blogs.nytimes.com/2009/10/08/safety-agency-is-looking-into-rust-issue-on-toyota-tundra/?hp

http://jalopnik.com/5376116/nhtsa-opens-investigation-into-tundra-frame-rust-reports

































































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Is it worth not knowing?

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Agenda




• Q&A

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Delivery of Insight to Users, Systems and Processes

Industry Solutions

Business Intelligence Predictive Systems

ECM Advanced Case Mgt

Solution and Modeling Tools

IBM Content

Analytics Studio

IBM

Content Classification

External and Internal Information Sources

Sources

Analysis

Exploration

Interactive Assessment and Discovery of Business Insight

IBM

Content

Analytics

IBM Content Analytics Approach

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Automatically

Extracted and

Analyzed

Concepts, Entities,

Relationships,

Meta Data and

Classifications

Views, Filters and

Thresholds

Search Query Exploration

Visualization with Drill Down for Exploration and Assessment

The Interactive Discovery User Interface Explained

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User Interface Overview

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Connections View

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Connections View

Identify relations between “FORD”, “blow” and “FIRESTONE”

• Show relationship between multiple facet values • Connections between nodes represents correlation between two facet values • Color of line represents the importance of correlation index (red is the

highest)

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Sentiment Analysis

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Sentiment Table

- Lists values of selected facet with its overall sentiment

- Shows the numbers of positive/ambivalent/negative documents and their percentage

Sentiment Table

- Lists values of selected facet with its overall sentiment

- Shows the numbers of positive/ambivalent/negative documents and their percentage

Selecting any facet value displays an

evaluation of sentiment for that facet

Selecting any facet value displays an evaluation of

sentiment for that facet

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IBM Content Analytics Perspectives

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Supported Languages

IBM,אורן עייש

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