Earley & Associates, Inc. | Classification: CONFIDENTIAL USE, NO REPRINTS Copyright © 2014 Earley & Associates, Inc. All Rights Reserved.
Knowledge management Through Search-Based Applications
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About Me
[email protected] @sethearleyContact me:
• Founder & CEO, Earley & Associates• 20 years experience building
content and knowledge management systems
• Author, speaker & industry influencer
Seth Earley
Earley & Associates, Inc. | Classification: CONFIDENTIAL USE, NO REPRINTS Copyright © 2014 Earley & Associates, Inc. All Rights Reserved.
The Challenge of Search
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What a Search Engine Sees
Topic of this page is PlayStation 3,
correct?
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What a Search Engine Sees
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Topical Analysis of Page Content
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Metadata is Essential
What we give to the search engine…
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Metadata is Essential
What the search engine sees…
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Metadata is Essential
What properties can be inferred?
Title Author Created Date
Modified Date
File Type
…
Overview of SharePoint 2013 Preview Installation and Configuration
Alex Yarrow
06/21/2012
10/16/2012
docx …
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Metadata is derived or applied
DEF Company
Support
ABC Company
ABC shall provide first level technical support to all Licensed Product end users and/or
Sublicensed Product customers/users. DEF will provide second level support. DEF shall provide to ABC a primary and a secondary support person to
act as the primary interface with ABC’s technical and customer support team. DEF shall provide
direct technical support to ABC for all uses of the DEF Software. Support level definitions and
responsibilities are set forth in Exhibit C. An “SLA Failure” as defined in Exhibit C shall qualify as a
Release Condition sufficient to authorize the Escrow Agent to release to Source Code to ABC pursuant to Section 7 and the Escrow Agreement.
LicenseContent Type =
Organization =
ABCcustomers
customer supportcustomer support team
DEFDEF software
end usersescrow agreement.
escrow agentexhibit c
licensed product
release conditionsection 7
secondary supportSLA
SLA failuresoftware
source codesupport level
sublicensed producttechnical support
Topic =
Forward Index – Words per documentInverted Index – Documents per word
Explicit metadata
Used to derive implicit metadata
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Search index points to document
12
34
Forward Index – Words per documentInverted Index – Documents per word
A search index becomes derived metadata
about a collection of documents
Term Document
Acme 1, 2, 3, 4
customers 2, 3
escrow 3, 4
exhibit c 2
license 1, 4
…etc …etc
In which documents do these words occur?
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Truth #1.
We have to change our definition of search.
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Truth #2.
Search algorithms are getting better,
but they cannot infer human
context & intent.
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Truth #3.
Taxonomy, metadata and information
architecture are key aspects of search.
Image credit: http://boxesandarrows.com/files/banda/developing_and_creatively_leveraging_hierarchical_metadata_and_taxonomy/ricci_01.gif
Metadata
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Truth #4.
Search is increasingly looking like navigation.
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Truth #5.
Search is messy.
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“…search terms are short, ambiguous and an approximation of the searcher’s real information need…”
Source: http://research.microsoft.com/~ryenw/papers/WhiteCONTEXT2002.pdf Ryen W. White, Joemon M. Jose and Ian Ruthven
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1-Unpredictable 2-Aware 3-Competent 4-Synchronized 5-Choreographed
Metadata Processes
chaotic tagging practices with no taxonomy
custom metadata, use of listsenterprise taxonomy replicated
in site columns & managed metadata
document sets, term store, & attributes used effectively to
group, aggregate, sort, & filter assets
contextualized/ personalized metadata with auto-population
of values & quality audits
IA / User Experience
haphazard creation sites with inconsistent content models
and poor site experience
more consistent stable departmental sites with little
cross site structure
site collection consistency, reference metadata with
content relevant to specific groups and audiences
cross collection consistency, enforced metadata standards
context dependent user experience
integration of structured and unstructured information from multiple systems dynamically
presented to support user tasks
Search Integration random document generatorsome tuning of search with
content tagging
scopeable search with consistent but uncontrolled
tagging
faceted search with taxonomy-governed tagging
search based application with associative relationships (related search), tuned
algorithms, facets, and metrics driven use cases
User Proficiency and Content
Practices
poor or minimal usage, lack of awareness of capabilities or
content practices
early adopters and power users using out-of-box features, little
control of content
departmental collaboration with basic content control
cross-team project-oriented collaboration with information
lifecycle management
automated workflows and reporting for compliance with enterprise content standards
Governanceinformation sprawl, lack of
vision, no intentional decision making
awareness of challenges, activity is monitored but not
constrained
assigned responsibilities, oversight and communications
infrastructure in place
intentional decision making, resource allocation, change
controls in effect
agenda-driven business leadership and stakeholder
engagement to effect continuous process
improvement
Findability Model: Maturity in Search, IA & Content Management
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What is a Search Based Application?
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Search cannot be “bolted on” to a project or an application…
institutional awareness has to be designed into the fabric of the
tool.
Search Based Applications require integrated design methods – around user, process, task,
content, inputs, outputs, use cases and scenarios – in order to optimize the search experience.
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From: http://www.domorewithsearch.com
Example SBA’s
“Search Based Application”? Or “Application”?
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What are Search Based Applications (SBA’s)?
• Disparate locations• Structured and unstructured • Aggregated content• Integrated into user experience
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What makes an application a “search based application”?
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Success with Search Based Applications
• Content/Data Structure
• Business processes
• Holistic perspective
• Current state score card (heuristic assessment)
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Developing SBAs requires an integrated information strategy
• Why develop SBAs? How will this benefit the organization?
• What needs to be in place in order to be successful?
• SBA’s consider content, data, structure and business processes from a holistic perspective.
• This presentation will point out critical elements of a successful SBA development program and lay out a high level plan for developing them.
An analysis and heuristic evaluation of the current search and content environment has been performed.
Opportunities for improvement have been identified in four specific areas: Information Architecture User Experience Search Integration Development of Search Based applications
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LESS STRUCTURE MORE STRUCTURE
Chaotic Processes Controlled Processes
Problem solvingCollaboration
Accessing informationAnswering questions
Knowledge Creation Knowledge Reuse
ENTERPRISE KNOWLEDGE MANAGEMENTSpans Structured and Unstructured Processes
CL
AS
S o
f TO
OL
BlogsRecords
ManagementDocument
Management
Process ManagementWikis
Collaborative Spaces
Instant Messaging
Email Management
Web Content Management
Learning Management
Digital Asset Management
My SitesCentralized Publishing
The Content Continuum
SharePoint Span of Control
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Unfiltered Reviewed/Vetted/Approved
Lower Value Higher Value
Lower Cost
Higher Cost
RELATIVE VALUE OF CONTENT
Not all content is of equal value
TY
PE
OF
CO
NT
EN
T
(More difficult to access)
(Easier to access)
Formal Tagging/Organizing Processes
Message text
External News Example deliverables
Discussion postings
Interim deliverables
Content Repositories
Success Stories
Benchmarks
Approved Methods
Best Practices
Social tagging (“folksonomy”)
Structured tagging
(taxonomy)
The Content Continuum
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Application Construct Less Structure More Structure
Nature of Process Chaotic Processes Controlled Processes
Knowledge Management Knowledge Creation Knowledge Reuse
Purpose/Application Problem Solving/Collaboration Accessing Information/Answering Questions
SharePoint Span of Control My Sites Enterprise Publishing
Class of Tool Collaboration/Communication Workflow/Document Management
The Content Continuum
Information Construct Unfiltered Filtered
Cost Lower Cost Higher Cost
Value Lower Value Higher Value
Editing/Vetting Informal Formal
Tagging Folksonomy Taxonomy
Ease of Access Low High
Type of Content News/Messaging/Interim Deliverables Best Practices/Approved Methods/Reference Materials
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Information and Access are Heterogeneous
Search/Tagging/Taxonomy Application Integration Framework
Data Sources
Access Mechanisms
BI Integration
Auto categorization/Clustering
Entity Extraction
Faceted Search
Semantic Search
Business Intelligence
Customer Relationship Mgt
Document repositories Custom databases and applications
Intranets/web pages
Product Lifecycle Management Digital Asset
Management
Data Warehouses
MessagingERP Systems
Ontology Navigation
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Organizational Governance and Process Infrastructure
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Designing for Content in Context
Audience Analysis
Content Analysis
Content Authoring
& Publishing Processes
Content Types,
Metadata Schemas
& Taxonomy Design
Workflow &
System Integration
Solution
Architecture Design
Search Based Applications
(Content in Context)
Workstreams
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Improving the Search Experience | User Task Scenario
Peter ThompsonCustomer Service Agent
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Improving the Search Experience | User Task Scenario
TA concepts that Peter must navigate and disambiguate to put together a common transaction.
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Ambiguous Query “retirement” presents options to disambiguate
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Ambiguous Query “retirement” presents options to disambiguate
Query guidance suggests terms
based on search scenarios and top searches
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Ambiguous Query “retirement” presents options to disambiguate
Related search concepts (new
query) dependent on selected search
query
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Ambiguous Query “retirement” presents options to disambiguate
Best Bets presents landing pages for priority
terms
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Ambiguous Query “retirement” presents options to disambiguate
Faceted refinement
based on content model and specific to
search term concept
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Ambiguous Query “retirement” presents options to disambiguate
Associative terms are role
based
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Ambiguous Query “retirement” presents options to disambiguate
Experts presented based
on domain expertise
(mapped to search query)
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Needed Activities for Search Disambiguation
Element Model Tuning Principle
Query guidance Taxonomy and thesaurus with role specific related search terms
Top queries, tasks, user scenarios, business goals
Narrower terms based on taxonomy
Related queries Triggered based on related terms from thesaurus
Scenario driven “you are asking for ‘a’ but you really want ‘b’
Ontological relationships of terms in domain model
Best Bet Primary landing page for ambiguous terms
Due to high overhead, limit to top 100 significant terms
Scenario driven, hand tuned
Context specific refiners Content object model Fine tune content object model based on use cases and user scenarios
Tasks are driven by detailed use cases derived from Concept of Operations
Role based associative term searches
Ontology, job roles, audiences
Similar to related queries but based on query results (post processing)
Entity extraction mapped to associative relationships and dependent on role
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Enterprise Strategy
Business Unit Objectives
Increase customer satisfactionIncrease customer satisfaction
Improve retentionImprove retention
Increase wallet shareIncrease wallet share
Business Processes
Customer SupportCustomer Support Web Channel Sales
Web Channel Sales
Customer Relationship Management
Customer Relationship Management
Call Center Knowledge
base
Call Center Knowledge
baseE Commerce
System
E CommerceSystem
Processes enable objectives
L I N K
A G
E
Customer Acquisition Customer Acquisition
Grow top line revenueGrow top line revenue
Content supports processes
Objectives align with strategy
Content Sources
Working here (tools, technology, IA,
taxonomy, search, etc)
Measuring here (micro level -
effects)
Measuring here (macro level -
outcomes)
Aligning enterprise strategy with enterprise data
CEO: “Show me how will this project increase our revenue.”
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Taxonomy & Information Architecture
DITA publishing
Developed Avatar application
Search Driven Help | Allstate Business Insurance
fin
an
cia
l
se
rv
ic
es
Business Challenge
ABI needed to make it easier for field agents to research and write (sell) business policies. Many agents focus on consumer insurance and are unfamiliar with business insurance offerings.
Agents have difficulty finding relevant help and how-to information
Providing agent help by phone is costly and becomes overused
Process for creating content and making it easy to find not effective
Approach
ABI’s vision for the proposed system included an avatar-based user experience
E&A’s comprehensive solution included …
Separate requirements definition and specification phase, with conceptual feasibility plan
Taxonomy developed for tagging in CMS and search in help application
User interaction model and wireframes clarified vision for client and development team
CMS selection and implementation. Content conversion of PDF and MS Word to DITA
Development of search application using text-to-speech via interactive avatar character
Governance model, change management and ongoing system support
Outcome
Search based application that provides quick, relevant results that can be communicated as text or spoken word through a custom Avatar user interface
ABI planning to open up new lines of business to infrequent users (agents)
Plan to reduce manual help desk operations by 80% in first 6 months after system goes live
New DITA-based content management system serves as foundation for future multi-channel delivery of relevant real-time content
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m
an
uf
ac
tu
rin
g• Business Challenge
Desired to improve efficiency and streamline product-related information delivery to enable field service engineers to better support equipment on-site at customer locations globally.
Required a solution that:
Managed formal and collaborative content authoring processes.
Enabled metadata, taxonomy and social tagging for improved findability.
Protected customer and internal intellectual property.
Dynamically delivered relevant content in context.
• Approach
Development of process models outlining information flow for formal and collaborative publishing mechanisms including workflow design.
Design of solution architecture including site collections, subsites, lists/libraries, content types, metadata and taxonomy.
Design of a search-based application constructed on top of SharePoint 2010, Microsoft Fast Enterprise Search, Smartlogic Semaphore and BA Insight.
• Outcome
Enabled engineers to search and find product and spare part information across multiple data sources through a single, simple interface.
Offered collaborative features for engineers to engage, provide feedback and share knowledge and best practices with their peers.
Achieved a 50% reduction on time spent searching for information reducing time spent by 18,000 per week saving almost $100mm.
Named to the InformationWeek 500 as a top technology innovator for 2012.
Global, Secure Content Delivery
Solution Architecture, Process & Content Modeling
Search-Based Application & User Experience
Applied Rapid Knowledge (ARK) Portal | Applied Materials
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Contact
Seth EarleyCEO
_____________________________EARLEY & ASSOCIATES, Inc.Cell: 781-820-8080Email: [email protected] Web: www.earley.com Follow me on twitter: @sethearleyConnect with me on LinkedIn: www.linkedin.com/in/sethearley