Everyone has an opinion about how to categorize data: information security, records managers, compliance, privacy, business owners. In this session you will learn why information classification is important, how to build a classification scheme that supports all use cases, and how to maintain it over the life of the system. A particular focus will be on the potential benefits of using “big buckets” to make this effort more manageable. Learn about the current state of Information Management in AIIM’s latest report: http://info.aiim.org/2017-state-of-information-management

1. DATA CATEGORIZATION
YOU CAN LIVE WITH
Presented by
Monica Crocker, CRM, PMP

2. Speaker Introduction and Session Overview
• Speaker
• Session Overview
– Define Data Categorization
– Describe a Data Categorization Development
approach
– Discuss some “gotchas”
• What does Data Categorization mean to you?

3. Why Do You Care?
• Because others care: Information Security,
Privacy, BCP, Users, Compliance, Auditors, etc.
• Information is only useful if findable
• Categories can be applied at different levels:
enterprise, division, application, table, field
• Full text searching doesn’t work
• Consistency is critical to system and process
integrity

4. Data Categorization and Taxonomy
• Taxonomy = A system of classifying things based
on their relationships; often from more general to
more specific
• Data Categorization = A way to categorize content
(classification)
• Together = A way to get to information
• Note: Data = Information
• Information = Structured and Unstructured

5. Ways to Categorize Information
• By level of risk: critical, confidential, public
• Subject – requires a robust cross-reference of synonyms/preferred
terms/related terms and doesn’t support information security and
retention requirements
• Organizational – doesn’t hold up to re-orgs or support cross-
functional content and processes
• Functional – supports information security and retention
requirements and is intuitive
• A hybrid of the last two, with subject incorporated into metadata,
may be the best

6. Other Related Terminology
• Metadata – Data about data, or in this case, information
• Index values – the actual metadata values associated with a
particular item
• Key words – user defined values in a keyword field or search terms
used in a full text search
• Text mining – using a statistical inventory of the full contents of a
library of items to define common terms
• Auto-classification – using analysis of the text and metadata
associated with content to automatically assign index values to it,
particularly classification values

7. Good Metadata/Classification Criteria
• Should support all the governance needs for it
• Should describe the content itself, within its context
• Should allow users to search with the information they
already have
• Should be enough metadata to identify each item
uniquely AND NO MORE
• Should be immutable (not change over the life of the
item)
• Should be intuitive/understood by a novice

8. Things to Avoid
• Folders
• Team member names (except in the Author field)
• Status fields
• Due dates (work triggers)
• Technology specific terms (“PDF” files)
• Duplicating data from another system
• Too many labels

9. Model Development Process
• Define scope…how will the information be used
and by whom? What policies and regulations
apply?
• Gather Subject Matter Experts/Stakeholders
• Start with your Business Classification Scheme or
Functional Hierarchy
• Determine any system limitations
• Research existing (prebuilt) models

10. Model Development Process:
Enterprise-wide
Collect all existing organization models
including: Records Retention Schedule,
Organizational Charts, Security classifications,
Information inventories, Budget, File plans,
Business process documentation

11. Build Model
• Determine how it will be documented
• Build a thesaurus
• Figure out how to handle items that don’t fit –
create new category or categorize as “other”
• Decide if you will supplement it with folksonomy
(keywords, comments) or tagging
• Define ongoing responsibilities

12. Implement Model
• Test
– Can users find what they need to do their jobs?
– Does everything fit?
– Can you apply policy/regulations?
• Modify
• Implement
• Update and Review – REGULARLY

14. Handout Exercises
1. Put the items on your list into groups and name
the groups. And come up with a name for
everything together.
2. Pick one of your groups and define fields
someone might use to find items in that group
(maximum of 10).
3. Review your results – anything you want to
change?

15. Conclusion
• It’s just another big standardization project
with potential for significant impact on
business productivity
• It requires varied SMEs
• Questions?

16. • monica.crocker@wellsfargo.com
• @rec_rocker