1. AutoClassification 101 What is AutoClassification and Why Should I Care?
Housekeeping: (Elise?)
All on mute.
Use chat box if you need to reach to moderators
Will hold Q&A at the end, but if you have a question at any time, go ahead and type into the question box as it comes up and we’ll get to as many as we can
We are recording this webinar. At the conclusion, we will send the link to the recording, a copy of the slides, and a feedback survey link to all registrants.
Thank you for attending! (Hand off to Julie)
Wednesday, November 15, 2017
1:00pm Eastern

2. Facilitators Sandra E. Serkes President & CEO
(Julie) Introductions
Julie and Sandy introduce themselves with enough fodder to establish credibility as SMEs
Sandra E. Serkes
President & CEO
Valora Technologies, Inc.
Julie J. Colgan, CRM, IGP
Sr. Dir. Strategy & Innovation
DTI Global

3. We Live in a Sea of Information
Client 1: 30 TB of stored
The typical large corporation has: servers, shared file servers, archive servers, loose desktop, mobile & social media files
Client 2: 125,000 “obsolete” files
Client 3: 400,000 contracts
(Julie) Define the problem and how we got here

4. High Cost of Not Finding Information
Knowledge workers spend from 15% to 35% of their time searching for information. (IDC 2004, 2009, Delphi Group 2011, Working Council of CIO’s, Ford, AIIM)
Knowledge workers spend more time recreating existing information than they do creating new information that does not already exist.
Some studies indicate 90% of time knowledge workers are recreating information that already exists. (IDC, “High Cost of Not finding Information”, 2004)
Only 21% of respondents said they found the information they needed 85% to 100% of the time. (IDC 2001)
(Julie) Briefly touch on the risks of not fixing the problem
Inefficient operations
Non-compliance (laws, regs, outside counsel guidelines)
Legal exposure
Exacerbates breach response and potential for serious reputational damage and costs
At $0.52 per minute x 25% of your time = $62.40 every single day!
That’s $16,473 per person per year!

5. What is AutoClassification?
AutoClassification = Rich Metadata + Rules
Computer software that performs automated analysis and disposition of file/document content
Software contains recognition algorithms for
Document Type
Content analytics
Indexing & Tagging
Recommended locations & naming
“Middleware” that sits between file locations (storage) and file uses (applications), providing an intelligent filter and control system for all content.
(Julie) Define autoclassification at the very highest level (level setting with audience)

6. AutoClassification as Traffic Cop
Data Silos
File shares
Personal/ Group Work Product
Databases, Repositories &
Collaborative Cloud Apps
Traffic Cop
Data Needs
Julie: This is the case because there isn’t anything that is enabling the translation of data into actionable information. That’s where autoclassification comes in. Autoclassification tools, like Valora’s Powerhouse and Black Cat, takes the context and content of data so organizations can make eyes-wide-open decisions about it (and preferably do it an automated way … but that’s a topic for a future webinar in this series).
Without the insight autoclassification brings to the table, it’s impossible to make sense of all of that data on scale.
Retention & Legal Hold
Data Lifecycle Planning & Mgmt
Search & Retrieval
Data Privacy & Security
Migration & Archival

7. (this is Valora’s story, too)
About Valora
Bedford, MA software firm specializing in machine-assisted document processing capabilities (aka analytics)
World experts in the automated analysis, indexing, mining and presentation of content
20 staff, 200+ clients, 1,500,000+ pages every week
Customers: corporate legal departments, government agencies, and their professional advisory colleagues (law firms & consultancies)
Objective: to overtake traditional information repository creation (manual data entry), management, analysis (search, review) and workflow (retention, production, routing) with high quality, low cost, scalable technology & best practices in analytics.
(Julie) So Sandy, technologies that can do “file analysis” have been around for years, many of them arising out of the onset of eDiscovery as an industry in the mid-2000s. Is that where Valora also got it’s start?
(Sandy) Talks about Valora heritage, dealing with the tough file types and culling requirements
(Sandy) Built technology to help create structure around unstructured content via rich metadata creation – reduce the need for Valora staff to do classification manually.
The power of Big Data is the story about the ability to compete and win with few resources and limited dollars.
- Forbes, March 2012
(this is Valora’s story, too)

8. What is Rich Metadata? Creation Date Signature Date Effective Date
Last modified date
File extension (file type)
Path name
Hash value
Author
Custodian
Content Owner
Recipient
Copyees (CC & BCC)
Assignee
Signatories Patient Name
Creation Date
Signature Date
Effective Date
Last Activity Date
Expiration Date
Destruction Date
Language
PII present
Word & page count
Tone/Sentiment
Security Level
Attachment Range
Legal Hold
Audience
Brand
Employee
Document Type
(Julie) Yes, so let’s talk about that – the role of metadata in our ability to make smart decisions about content. Tell me more about what Valora does and how that is different and brings more value than just using document properties, for example. Why isn’t system generated metadata enough?
(Sandy) Talks about reasons why properties aren’t enough – that we need to look inside the document (unless file name tells you what the content is, you have no idea what it is … and who trusts file names?? Have to look inside)

9. How does AutoClassification Work?
Processing (aka Intake) is ingesting data or processing in place
Creating OCR for scanned images or applying redactions
Extracting text for native files &
Speech to text for audio/video files or translating content to English
Re-ordering or re-aligning pages
Tagging (aka Coding, Indexing, Sequencing) is the process of extracting key information and attributes about each document
Document Type, Important Dates, File/Content/DocType attributes
Key Names, Phrases, Topics, Keywords, Themes
Relation to other documents (duplicate, related, attached, contradictory, etc.)
Disposition (rules) is the process of creating a destination or status for each document
Retention status & duration
Folder (taxonomy) location
Labelling & keywords display
native
text
text
fielded data
Sandy gives brief overview of how it works.
fielded data
disposition

10. AutoClassifying an email with data mining (analytics)
Author
Doc Type &
Implied attachment
range
Matter indicator
& validation
Author Validation
& Contact Info
Sandy: Let’s go through a few examples or use cases … first
Implied matter:
Passaro ( )

11. AutoClassifying “Junk”
(aka R.O.T.)
“Watch list” terms
Date
+ No further content
+ Heavy graphics
+ 4,000 ID copies
Sandy … Now ROT
Implied status:
Junk/Remove All

12. AutoClassifying a Contract
DocType = Contract
Effective Date = 2/1/2005
Party One = Office of the
Commissioner of Insurance
Party Two = AMI Risk Consultants, Inc.
Keywords = Actuarial Services
Term = 1 year
Renewals = two 1year terms
Sandy – Now contracts

13. Understanding Context: Wonder if anyone would mind…
Sandy – so important to capture the context … straight text analysis won’t give you the whole picture.

14. 10 Use Cases for AutoClassification
Migration (fix metadata and general clean-up as part of effort to move data from one location to another)
Remediation (fixing bad/no metadata, overall file organization)
Upgrade (same idea as above, but due to some system or platform upgrade)
Compliance/Monitoring (needing a filter on communications/docs to monitor for topics, phrases, PII, etc.)
Security (identify, protect, and suppress sensitive data)
Orphaned Data ( /files leftover from departed staff, acquired or divested departments, old records)
Conversion (converting paper file to electronic/imaging, and adding additional smarts to that activity - unitization, coding, etc.)
Litigation/Investigation (analyzing files for responsive/relevant content, attempting to find patterns of behavior)
Repository/Knowledge Management (store documents by topic, keywords and content)
Workflow (bring documents & files into a corporate workflow via portal, bounce, server crawl, etc.)
(Julie) So the ROT use case is a popular one. I think the phrase “defensible deletion” has been around for about at least the last 5-7 years, if not more. But what other use cases are popular targets for autoclassification technologies? (Sandy and Julie) Talk through some of the use cases and why we see clients asking for them
Key use cases include: Conversion, Orphaned Data, Security
Leave migration as last one to discuss so it flows to next question …
(Julie) With this migration use case, it begs an important point - It’s not enough to just know what information you have, you have to then be able to do something about it. Migration is an obvious one, but so are most, if not all, of the other use cases.
(Sandy) Finding things is only the beginning! What orgs need to do is act on that insight.
+ 1 more: GDPR Compliance (ensuring proper treatment of PII for EU Citizens’ data)

15. Intake – PowerHouse – Output
PH Web Portal
Hosted Metadata
Repository
OCR/Text Extraction
Translation/
Transcription
Unitization
Coding/Tagging
Rules/Disposition
Redaction
Exceptions
Journaling
Scanned Paper Files
Folder Taxonomy
Transatlantic Corp.
2016 IP Matters
CX4 redesign
Caro Prototype
(Julie) Another key aspect, and one that has been mostly elusive to-date is the ability to operationalize this kind of work. Until now, most initiatives around these kinds of things have been project driven. And while there are certainly important reasons to take on projects, for me as a Certified Records Manager, I need to find a way to embed this capability into the day-forward management of content. Thoughts about that?
(Sandy) Gives her thoughts
Shared Server Poll
Cloud File Storage
HR Database
Billing System
ERP

16. (Julie) Ok, shifting gears a bit, let’s talk about who the stakeholders are around autoclassification, and what their stake is. CONSIDER SHOWING EDRM IGRM MODEL ON SLIDE?
(Julie) Julie talks through the IGRM stakeholders and discusses who cares about what and how autoclassification helps them get where they want to go. Sandy to chime in as she is inspired.
(Julie) So Sandy, in your experience, which of these stakeholders is most likely to champion autoclassification investments, and why?
(Sandy) Sandy says whatever she says and Julie chimes in as inspired
(Julie) Do you find that budget exists for autoclassification technology and services, or is this something net new to hit folks’ budgets that they should start planning for?
(Sandy) Sandy shares her thoughts on budget

17. Closing Comments
What is AutoClassification?
Software that performs automated analysis and disposition of file/document content using advanced techniques such as “entity extraction”
An intelligent filter and control system for all content
The precursor step to automated disposition of content
Why should I care?
Get rid of the junk
Save on storage costs
Leverage and re-use valuable information
Find and manage official records to policy
Meet compliance obligations for
Retention
Protection
Coming up next … Part 2: Creating Structure From Unstructured Data January 17, pm Eastern
Closing Comments
Parting thoughts
Set up for next in the series – deep dive into metadata

18. Valora Technologies, Inc.
Q&A
For more information:
Valora Technologies, Inc.
101 Great Road, Suite 220
Bedford, MA 01730
DTI
2 Ravinia Dr. Suite 850
Atlanta, GA 30346

19. Where to Get More Info on AutoClassification
Info & advice from Valora & DTI
Read Valora’s blog
Download Valora’s White Papers, Articles & Datasheets
Visit Valora’s YouTube Channel for recorded demos, Q&A, etc.
Join us for our continued web series parts 2, 3, & 4!
Info & advice from other sources
Join the Information Coalition (it’s free) that hosts InfoGovCon each year
Visit the Information Governance Initiative website
See the EDRM Information Governance Reference Model
Check out the Predictive Coding & Analytics in eDiscovery and the GRC LinkedIn group
Score yourself on the ARMA InfoGov Maturity Model