Search is an essential component of the digital workplace. The Digital Workplace is an ecosystem of information that is managed in multiple systems, exposed in multiple experiences, and needs to meet the needs of a wide range of users. This information drives decision-making, analytics, and knowledge sharing across the organization. When your information architecture, taxonomies, and metadata are implemented across the enterprise, the power of AI driven search is unlocked.

2. Gary Carlson
GARY CARLSON
Principal & Co-Founder,
Factor
EMPOWERING AI IN THE DIGITAL WORKPLACE
• Experience
Large scale enterprise information management, taxonomies,
metadata projects
• Industries
E-commerce, manufacturing, life sciences
• Interest
Organizational change in complex information environments
The intersection of search, AI, KM, etc with taxonomies, ontologies,
and knowledge graphs

3. ABOUT FACTOR
Factor is an Enterprise Information
Architecture, UX and Taxonomy
Consultancy.
We help customers gain control of their
information ecosystems by unifying
content and information across
business units, processes and
technologies.
This improves outcomes, data quality
and facilitates easier implementation of
Search, AI, Analytics, Knowledge
Management, and experiences

4. Enterprise Information Architecture
supports unified definition of
information across …
Systems Processes Workflows

5. Enterprise
Multiple ● Systems
● Organizational units
● Personas
● Workflows
● Interfaces
● Regulatory and Compliance
requirements

6. Let us tell you a
story...

7. ●18+ technology systems in the
marketing stack
●$2B+ annual marketing spend
Fortune 50 Technology
Manufacturing Company

8. ● Unable to assess effectiveness of
marketing campaigns without
‘mob’ of people
● Data was unreliable despite
spending tens of millions of
dollars on best of breed
technology marketing stack
● Extremely difficult to drive
analytics across campaigns or
systems
● No central repository for
modeling campaign definitions.
Fortune 50 Technology
Manufacturing Company

9. What we found:
“A drunken bowl of
spaghetti”
Fortune 50 Technology
Manufacturing Company

10. What we built
Systems at Play Information Model
Campaign
Industry
Geography
Audience
Location
Funnel Stage
Target
Expiration Date
Taxonomies Metadata
Collaboration
On-site search
MDM
CRM
DAM 1
DAM 2
Personalization
Analytics
Google Analytics
Community
Management
Tag Management
Jira
.com CMS
TV
SEO
Media
Email
Data Lake
PIM
Ad Server
Demand Management
Platform

11. What is an Information Layer?
● It’s how you define your content, data, and other
information assets.
● It’s the information that gets implemented in your
technical layer and expressed in your experience
layer.
● It drives your customer experience, your digital
marketing, operational efficiency, business
analytics, and more.
● A unified information layer allows your
organization to align around one voice and a
common vocabulary.

12. How we built it
Business
Goals
UX Assessment
Competitive Assessment
User Research
Taxonomy & Metadata
Assessment
Analytics Assessment
Content Assessment
Governance/Workflow
Assessment
Technical Systems
Assessment
Evaluate current
state, capabilities and
pain points
Map Existing
Information Assets
and Analytics
Technologies,
Systems and Tools

13. Results
● Increased data quality within and across systems
● Ability to build and expand Search and AI
● Better and more timely information for business decisions
● Easier and faster onboarding of new systems, business units, and
acquisitions
● Transparency and governance

14. Enterprise IA Directly Transfers to
Search and AI
Everything that goes into building
an enterprise information
architecture model has a direct
impact on AI powered search
● Clean and consistent data within
and across systems
● Information better aligned with
organizational goals
● Governance and maintenance

15. Lucidworks Fusion Directly Supports
Enterprise IA
A virtuous cycle. Core Fusion
functionality provides key insights
into the strength and health of
information. These insights, when
incorporated into the information
layer help increase the overall health
and quality of your information.
● Entity Extraction
● Search Analytics
● Clustering and category identification
● Machine Learning
● Recommendations
● Document classification
● Testing
● Head / Tail analysis

16. Questions?

17. THANK YOU