"Knowledge management" may be making a comeback — the term we heard about in the early “noughts,” a formal system that helps manage what an organization knows. Developments in artificial intelligence and database technology have brought the promises of knowledge management back into the forefront. In this webinar, John and Kelle will cover the “what’s old is new” topic of knowledge management, including: Its history and definition How it applies to Big Data and analytics Its connection to machine learning and the findings from analytics How to manage the influx of data

1. The First Step in Information Management
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Produced by:
MONTHLY SERIES
In partnership with:
Big Data as a Gateway to Knowledge Management
November 1, 2018

2. Welcome to Today’s Discussion
▪ Overview of knowledge management
▪ Scope of current knowledge management technologies
▪ Analytics and big data use cases
▪ Knowledge management and future usage
▪ Best practices and key takeaways
▪ Q&A
pg 2© 2018 First San Francisco Partners www.firstsanfranciscopartners.com

3. Overview of Knowledge Management
pg 3© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
Late 90s
We don’t know
what we don’t
know
Orgs need to be
self-learning
Davenport/Prusac
Ikujiro Nonaka
Business
Drivers
Overwhelming wave of data volume
Unstructured data
Loss of organization knowledge and wisdom via
aging workforce. Stop expertise "walking out of
the door."
Reuse valuable knowledge, and stop
"reinventing the wheel.” Use best practice to
improve consistency and quality.

4. Overview of Knowledge Management
pg 4© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
Solution
Areas
Human Capital
Management
Organizational Learning
Collaboration
Knowledge Identification
and Dissemination
Extending BI capabilities
Extending BI
Capabilities
Unstructured Information
Usage
Actionable Use of
Information
Identification/Tracking of
Knowledge and Info Assets
Closed Loop Agents (AI, ML)

5. Knowledge Management and Future Usage
pg 5© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
“ Knowledge Management turns
the potential capacity of raw
“connected and collaborative
intelligence”, i.e. all those brains
at the end of the computer, into
a “collective know-how” that will
improve operations,
competitiveness and value. ….. It
is a SUM of information assets,
…and most importantly, the un-
captured, tacit expertise and
experience resident in the
minds of people.”
“ Knowledge management is
a discipline that promotes an
integrated approach to
identifying, capturing,
evaluating, retrieving, and
sharing all of an enterprise's
information assets. ... The
one real lacuna of this
definition is that it, too, is
specifically limited to an
organization's own
information and knowledge
assets. “
▪ The context,
metadata and
the relationships
are as important
as the values of
the records.
John Ladley Wikipedia

6. Where Did It Go?
pg 6© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
It was too hard to
change behavior.
Everything devolved to
technology.
The technology that
organizations wanted
to employ was
Microsoft’s SharePoint.
It was too time
consuming to search
for and digest stored
knowledge.
Google
KM never incorporated
knowledge derived
from data and analytics
Source: Tom Davenport, Wall Street Journal, “Whatever
Happened to Knowledge Management?” June 24, 2015

7. Knowledge Management Technology – Driven by Analytics
pg 7© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
Knowledge Management Technology
KNOWLEDGE
INVENTORY
GOOGLE
AI
WATSON
OPENCV
METADATA
ALATION
DATA
MANAGEMENT
GRAPH
HADOOP
IMMUTA
PODIUM
COLLABORATION
AND WORKFLOW
SHAREPOINT
COLLIBRA
DOCUMENT
MANAGEMENT
DRUPAL
CONTENT AND
DIGITAL
MANAGEMENT
CONFLUENCE
CANTO

8. Analytics and Big Data Use Cases
▪ Gain visibility across all data
categories, classifications, nooks
and crannies
▪ Achieve the summit of
understanding tacit knowledge
▪ Capture work using AI and
related technologies across
complicated communities with
large volumes of data = a use
case for KM
pg 8© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
John Ladley, Making EIM Work for Business, 2010, Morgan Kaufman

9. Knowledge Management Factors and Use Cases
▪ Blurs with AI and machine learning
▪ Still retains old challenges that AI needs to
take to heart (data quality/data
movement/context)
▪ Future
− You still need to apply what people ALREADY
KNOW
− You need to understand what remains tacit
− Accessible
− Navigable
− Contextual
pg 9© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
FutureAnalytics
Knowledge
Management
Machine Learning
Artificial Intelligence
Well Managed Data
Supply Chain

10. Analytics and Big Data Use Cases
pg 10© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
Data
Meaning
and
Context
BI & Reports
Experience
Knowledge
Base
-----------
Store
insights as
to what
happened in
response to
information,
and enable
action and
responses
Knowledge
MapInsight
Content
Meaning
and
Context
Tagged
New Information
Big
Data Analytics
Meaning
and
Context
New Context
New Information
New
Insight
Analytics
New Information
Tagged
Experience

11. Future Uses — Sample Architecture
▪ Graph for knowledge
mapping and metadata
▪ Document database for
document storage and use
▪ Hadoop or other NoSQL for
merging and analyzing
varied content
▪ Columnar for handling
Vintage area BI and
Reporting
▪ Add place to “store” learned
behaviors and data
supporting AI
pg 11© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
Contemporary Area
1
Data Life
Cycles
Data Management
Data Usage
“WORK”
Vintage Area
Legacy BI and Reporting
Data Warehouse, ODS,
Mart
ETL,
EAI,
Msg,
Copy
Data Lake
Advanced Analytics
RDBMS, SQL,
Columnar, Transactional
Metadata
Logical DW
Data Sources
Knowledge Graph
BIVisualization
Document
“Abstraction
Engine”
“Knowledge Lake”
Hadoop
Work Collaboration

12. Knowledge Management “Area”
Capture, retain and share knowledge and enable collaboration
Knowledge Management and the Operating Framework
pg 12© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
SUPPORTING PROGRAMS
Organizational Change
Management
Data Governance
Human Capital / Workflow /
Collaboration
Enterprise Architecture
Data
Operational Areas
IT / AppDev
Knowledge
Bases
Collaboration
/ workflow
Support innovative efforts
• New Digital content
and products
• Disruptive
technologies (IoT)
• Data monetization
Support conventional
efforts
• Content management
• ERP
• Analytics
• Disruptive regulations
(GDPR)
Other efforts
• Bootstrap innovation projects
• Manage large initiatives
• Content management & tagging
• Search
• Expertise location Analytics
Process Capabilities

13. Unstructured Tacit
Knowledge Management Supports Organizational Learning and Human Capital Development
pg 13© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
Structured
Sources
AI / Analytics Models, Knowledge Abstraction
Conclusion
AI “closed
loop” rule
Knowledge
Graph
LEARNING
CAPTURED
LEARNING
ACTION
Un
structured
Explicit
?

14. Best Practices
▪ Focus on practical applications
− It is good to know what you know
− All industries can benefit from knowledge management, while some still
require it:
▪ Complex manufacturing - Aerospace
▪ High risk, high human interaction – Energy, Healthcare
▪ Service – Help Desk
▪ Balance AI-driven “closed loop” vs. human interactions
▪ Use AI and Big Data as the platform of interactions and activity tracking
pg 14© 2018 First San Francisco Partners www.firstsanfranciscopartners.com

15. Key Takeaways
pg 15© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
KEEP IN MIND…
▪ Big Data, Analytics and AI allow for a pragmatic gateway to
knowledge management-like activity
▪ “Learning organizations” require a lot more than just
technology, and are probably a long way off
▪ Understand that AI might be intended to replace, but it should
initially supplement and help manage tacit knowledge
▪ Knowledge management, in the academic view, is far away
and is a capability rather than a functional area

16. Please Share Your Questions and Comments
MONTHLY SERIES

17. Thank you for joining us today!
Our Thursday, December 6
#DIAnaltyics webinar is:
Trends and Predictions for 2019
.
John Ladley @jladley
john@firstsanfranciscopartners.com
Kelle O’Neal @kellezoneal
kelle@firstsanfranciscopartners.com