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ARMA Austin Spring Education Seminar

Bill Manago, VP Information Governance

28 March 2012


©2010 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

©2010 KPMG, LLP, a US Limited Liability Partnership and a member firm of the KPMG network of independent member firms affiliated with KPMG International,

a Swiss cooperative. All rights reserved. Printed in the United States. KPMG and the KPMG logo are registered trademarks of KPMG International, a Swiss cooperative


Abstract

have vast quantities of electronic information.

calls for reducing the risks and the costs associated with storing the massive amounts of data that maybe stockpiling in your organization.

All Organizations

Good governance


Agenda

The Past and Future of RIM

Information Governance

Generally Accepted Records Management Principles

Big Data and Big Content

The Cloud

Defensible Deletion

Auto-Classification

The Boardroom – Are You Ready


Objectives

In the session, learn how to:

• Tackle the unmanaged “stuff”, including legacy data - without increasing risks to your organization and

• Address the legal and practical aspects of managing “digital landfills”


We Created Ways to Remember

Important “Stuff”


Tools Used to Remember - Evolved


Now We Can Remember all Kinds of “Stuff”

• Unmanaged file systems

• Thousands of SharePoint sites

• Multiple ECM systems

• Millions of documents with many duplicates

• Mobile devices

• Social media sites


Building, Storing Corporate Memories

Business Applications and Data Repositories

Building Multiple Mountains of Data

SharePoint Email Shared Drives


Interesting Fact - Future Watch

http://rmfuturewatch.blogspot.com/2007/06/records-vs-information.html


Interesting Fact: 10:1 Ratio


Interesting Fact - Digital information created, Exabytes


Explosion of Digital Information

– Wal-Mart's data warehouse has 600 terabytes

– Chevron Oil accumulates 2 terabytes daily

– IDC estimates 1800 exabytes will be created annually by 2011

– 1 exabyte is 50,000 years of DVD movies

– 1,800 exabytes = 90,000,000 years of movies

– Equivalent to 1.8 trillion gigabytes

– Fill 57.5 billion 32 GB Apple iPads


Interesting Facts - Digital information created, Exabytes


Can Data Centers Keep Up?

• The number of servers (virtual and physical) worldwide will grow by a factor of 10,”

• Amount of information managed by enterprise data centers will grow by a factor of 50

• Number of files the data center will have to deal with will grow by a factor of 75,

• Number of IT professionals in the world will grow by less than a factor of 1.5

• The demand for physical storage space will continue to increase,

• Increased automation to allow small staff to manage immense volumes of data.


Personalize It

What are your personal statistics:

• Emails sent?

• Emails received?

• Emails deleted? (excluding spam)

• Documents save to ‘C’ drive?

• Documents saved to ‘Shared’ drive?

• Documents saved to EDMS?

• Declare as records?


Delete: The Virtue of Forgetting in the Digital Age

• by Viktor Mayer-Schonberger professor of Internet Governance and regulation at Oxford University

• The overabundance of cheap storage on hard disks means that it is no longer economical to even decide whether to remember or forget. "Forgetting – the three seconds it takes to choose – has become too expensive for people to use,"

• Argues that digital storage devices (cameras, mobiles, computers) should automatically delete information that has reached its expiration date.

• We set up institutions of memory to help usremember important things

• They risk being drowned out by stuff online

Novel idea – automatically delete stuff that

has reached an expiration date!


What Is the Size of Your Digital Landfill?

The Digital Landfill

Enterprise Search Engine


It Is Not All Rubbish

Valuable data

Record material

Needed operational data

Financial data

Evidence

How can we manage this digital data explosion?


Three Imperatives to Manage Data Explosion

1 - It Takes a Village

• RIM, IT, and Legal will need to transform their existing relationships with the business units.

• It will take all competent hands in an organization to deal with information creation, storage, management, security, retention, and disposal in an enterprise.

• Dealing with the digital universe is not just a technical problem, it is a management problem.


Three Imperatives to Manage Data Explosions

2 - Enforced Information Governance Policies

Organizations will need to spearhead the development of organization-wide policies for information governance:• Information security• Information retention• Data access• Privacy, and• Compliance

Implement GARP!


Life Cycle Management to All Content


It Is OK to Destroy

• Destruction is an acceptable stage in the information life cycle

• An organization may destroy or delete information when there is no continuing value or need to retain it or no duty to preserve

• Systematic deletion of electronic information is not synonymous with evidence spoliation

• It is ok to systematically delete redundant, outdated, and transient (ROT) data


Three Imperatives to Manage Data Explosions

3 - Automation, Automation, Automation

Organizations will need to rush new tools and standards into their structure

• Storage optimization• Unstructured data search• Data analytics• Resource pooling• Virtualization• Management • Security tools

All will be required to make the information infrastructure as flexible, adaptable, and scalable as possible.


Finding Needles


What Is the Solution?

Are there tools, in place today, that we can use to tame the digital universe?

Can we turn our information growth into economic growth?


Early Computers Had Limited Capabilities

• Computers could only do what they were programmed to do

• Remember Garbage In, Garbage Out?


Modern Computers Can Process Data

• Read text files• View video files• Listen to audio files• Index all

• Form a conceptual understanding of data


• Memorable words used for retrieval of information– Common words like articles or conjunctions are dismissed leaving only

“keywords”– Boolean Rules complicated– Limited to what you know

Keyword Search

“The dog and the cat run away”

“dog cat run away”

ANDOR)Apple AND computer tree Macintosh Jobs SteveNOT OR ( )(( )


Conceptual Understanding

Furry, four-legged creature Man’s best friend Comes in flavors like Dalmation,

Chihuahua, Great Dane… Plays fetch

Concept: Dog

http://www.big-dog-clothing.com/dog-tips/getting-a-bernese-mountain-dog/


0

Keyword

• Query: “popular around the world, primarily for their unusually upright, waddling pace and (compared to other birds) lack of fear of

humans. Their striking black and white plumage is often likened to a tuxedo suit and generates humorous remarks”

+ ETC…

Keyword

Allowing the user to hone in on information

• Query: “penguin”

Conceptual Search

Autonomy


Manual Classification


Manual Classification

Time Action

3 seconds Keep or Delete?

3 seconds Record or Non-Record?

3 -10 seconds Select Category/Classification

5 seconds Enter Metadata

5 seconds Review/Save Profile

Who has the time?

Who has the inclination?


Auto Classification Is Key


Facts About Classification

Every manual classification forced on your

users will cost your organization 17 cents in

productivity

4

3

2Wide-spread adoption of archiving or

records management in your organization

will lead to large, measurable productivity

loss

4

Compliance professionals hold the incorrect

assumption that humans are the best option

for piece by piece decision-making

3

Results of human-reliant filing are

inconsistent and inaccurate, resulting in

effective accuracy of 50%, at best2

ImplicationsFacts

Unstructured content makes up 80% of the

volume of information in the average

enterprise and that segment is growing

30% annually

1

Business users find forced manually

classification “burdensome” and at least

50% will not participate

Deploying an archiving or records

management initiative is increasingly

important, large scale and difficult problem

1

Humans provide, at best, marginally better

accuracy in executing classification, in

controlled tests


Critical Dimensions of Classification

Cost (per doc):

Accuracy:

Consistency:

Manual Automated

50% 80 - 90%

$ 0.17 < $ 0.01

<50% 100%


Auto-Classification Techniques

Cost Savings

Productivity

Accuracy

Manual

Classification

Authoring Templates

Rules Based

Classification

Context Based

Classification

Multiple

Methods

Simple Rules

Complex Policies

Consistent Participation & Enforcement


Rules Based Auto-Classification Systems

• If sender is ___ then file here _____

• If subject contains __ then file here ____

• If body contains ___ then file here ______

• If, then propositions

• User defined rules (desktop)

• Organization defined rules (server)


“Trained” Auto-Classification Systems

• Train categorization engines to recognize records using small document sets

• Match content of documents against the document set

• Uses topics, relevancy, user profiles, and keywords

• May include dynamic rules for classification

• Based upon natural language


Contextual Clustering Systems

• Recognizes and displays relevant relationships between data points and divides the results into contextual groups, while its clustering functionality classifies unstructured information into thematic groups, identifying the major topics in documents, and recommends structure for classification

• Based upon mathematical equations, formulas, statistics

• Language independent


Apply Policies to Content

• Duplicates

• De-Duplicate

• Hold

• Delete

• Retention

• Use it or Lose It

• Move

• Manage In Place


Use It or Lose It Policy

• Implement policies and procedures to encourage users to complete and declare their works in progress or to delete them after a specified period of time of inactivity.

• Schedule the deletes to happen automatically after a specified grace period.

• Schedule declaration automatically where possible.


Gradually Reduce that Mountain of Data


Legally Defensible Program

• Normal Course of Business• Policy Based• Applied/Performed Consistently• Uniform Across the Enterprise• Repeatable• Auditable


What Is the End Game?

Control and Visibility over ALL Enterprise Information


What Are The Benefits?

• Reduced Risks

• Cost Savings– Data Storage

• Time Savings– How long for users to search and find data

• eDiscovery Savings– Less ESI to review– Less ESI to produce


Summary

Reduce Your Digital Landfills

• Digital landfills are easy to create• Digital landfills were designed to keep, not

destroy, data• Digital landfills can be disposed of by simply

deleting them when the data is no longer required

– Defensible manner– Policy driven– Enforced, consistent– Process is repeatable– Process is auditable


Summary

Find the Value in Your Digital Landfills:

Use automation to: • Locate your data

• Index your data

• Classify your data

• Destroy your unneeded data

DATA


The Leader in Meaning Based Computing

http://www.autonomy.com/


Meaning Based Computing (MBC)

http://www.autonomy.com/

Autonomy is the acknowledged leader in the rapidly growing area of MBC. MBC refers to the ability to form an understanding of all information, whether structured, semi-structured or unstructured, and recognize the relationships that exist within it.

This allows computers to harness the richness of human information, bringing meaning to all data, regardless of what or where it is.

Through sophisticated functionality and analytics, MBC automates manual operations in real-time to offer true business value.


Information Governance Solutions

Provides visibility into information risk

• Understands meaning to analyze all information and identify both known and unknown behavior

• Detects the subtleties necessary to identify collusion, insider trading, speculation, and complaints

• Operates across all formats including audio, email, IM and social networks, in any language

• Enables a single set of policies to be applied across systems and allows automation


Media

Reuters

Bloomberg

LexisNexis

CNN

Knight Ridder

Martha Stewart Omni.

Wolters Kluwer

BBC

BskyB

National Public Radio

McGraw Hill

Reed Elsevier

HBO

Forbes

Associated Newspapers

Belga NV

Shanghai News Agency

Rai

Channel 4

Condé Nast

HarperCollins

Energy

Total Fina Elf

Norsk Hydro

BP

US Dept of Energy

Halliburton

GE Energy Services

SPE.org

MOL

Encana

Devon Energy

IT

IBM

Intel

Logical

OpenMarket

Seagate

Oracle

Symantec

Finsiel

Cebit

OTEnet

Juniper Networks

Wipro

Oracle

Accenture

HP

BEA

Sun

Sybase

Unisys

Brio

Vignette

Cap Gemini

EMC Corporation

Epiphany

Cisco Systems

McAfee

Legal

Freshfields

White & Case

Butterworths

Law Society

Addleshaw

Linklaters

Allen & Overy

Slaughter & May

Baker & McKenzie

Professional Services

PWC

AMR Research

Butler Group

Choicepoint

Manufacturing

General Motors

BAE Systems

Nestle

Volkswagen

Chrysler

Skanska

Agilent

Philip Morris

Ford Motor Company

Goodyear

Aluminium Pechiney

Boeing

Lexmark

Texas Instruments

Agilent Technologies

Philips

DTI

Arup

Frito-Lay

Kohler

Eastman Kodak

John Deere

Mercedes-Benz

Nissan

Sony

Teleco

T-Mobile

Alcatel-Lucent

Sprint

Qwest

MCI Worldcom

Sonera

AT&T

Telia

BT

Telecom Italia

3

Vodafone

Government

US Dept. Of Defence

US Dept. Of Health

NASA

UK Police Forces

US Army

DERA

Swiss Army

Port of Singapore

Customs & Excise

UK Cabinet Office

UK COI

UK MODPharmaceutical

Astra Zeneca

Novartis

GlaxoSmithkline

Organon

SAIC

Saludalia

LocusMedicus

Pfizer

Roche

BlueCross/Shield

Monsanto

Financial

Citigroup

Royal SunAlliance

Dresdner Kleinwort

Fidelity

HSBC Investment

Lloyds TSB

Danske Bank

Bank of Montreal

New York Life

ABN Amro

AMP Henderson

Darier Hentsch

Goldman Sachs

Banco de Espana

Schroders

UBS

Fireman’s Fund Insurance

Merrill Lynch

Barclays

Credit Suisse

Commerzbank

Legal and General

Abbey

Bank of America

JPMorganChase

Wachovia

E-Commerce

Tesco

RadioShack

BUT

Safeway.com

Napster

Toys R US

The NewsMarket

Albertsons

Over 20,000 Customers


KeyView IDOL and OEMs

• IDOL supports all operating systems, with native support

across 400+ repositories, 1,000+ file formats

• The only FRCP-compliant technology

• Used by virtually every major software sector

& competitor, 400+ OEM agreements

– Hundreds of millions of installs

“KeyView IDOL Filter and Export SDKs offer superior

overall performance and robustness. Further, we felt the

technical support was second to none.”


Bill Manago, CRM

Director,

Information Governance Solutions

Autonomy

[email protected]

www.Autonomy.com

Questions & Answers

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