SlideShare uma empresa Scribd logo
1 de 28
Baixar para ler offline
GIVE THE PEOPLE WHAT THEY WANT:
A THOUGHTFUL APPROACH TO KM TECHNOLOGY
Midwest KM Symposium 2020
By: Todd Fahlberg and Madison Jaronski
May 19, 2020
@EKCONSULTING
MADISON JARONSKITODD FAHLBERG
KM Technical Consultant Senior KM Analyst
Areas of expertise:
KM Technical Strategy &
Implementation, Enterprise Search,
and Semantic Technologies
Areas of expertise:
KM Strategy, User-Centric Design,
and Gamification
EK AT A GLANCE
60%
40%
STABLE CLIENT BASE
50+ EXPERT CONSULTANTS
CommercialFederal
7 AREAS OF FOCUS
▪ KNOWLEDGE MANAGEMENT STRATEGY & DESIGN
▪ TAXONOMY & ONTOLOGY DESIGN
▪ CONTENT & BRAND STRATEGY
▪ TECHNOLOGY SOLUTIONS
▪ AGILE TRANSFORMATION
▪ CHANGE MANAGEMENT
▪ KNOWLEDGE GRAPHS, SEMANTIC MODELING, AND ARTIFICIAL
INTELLIGENCE 25+ COUNTRIES
GLOBAL REACH
WITH CLIENTS IN
BASED IN DC
KNOWLEDGE MANAGEMENT
INVOLVES THE PEOPLE,
PROCESS, CULTURE, AND
ENABLING TECHNOLOGIES
NECESSARY TO CAPTURE,
MANAGE, SHARE, AND FIND
INFORMATION.
DECONSTRUCTING KM
PEOPLE
• Flow of knowledge
through the
organization.
• Knowledge holders
and knowledge
consumers.
• Understanding of state
and disposition of
experts.
PROCESS
• Existence and
consistency of
processes.
• Awareness of and
adherence to
processes.
• Quality of processes.
CONTENT
• State and location of
content.
• Consistency of
structure and
architecture.
• Dynamism of content.
• Understanding of
usage (analytics).
CULTURE
• Senior support and
comprehension.
• Willingness to share,
collaborate, and
support.
TECHNOLOGY
• Maturity of “KM
Platform” or ”KM
Ecosystem”.
• Integration with and
between systems.
• Usability and user-
centricity.
@EKCONSULTING
KM ECOSYSTEM - LOGICAL ARCHITECTURE
Content Management System
Used to author, organize, manage, and publish content on a web interfaceCentralized UI
Repository Layer
Web Content
Management
Enterprise
Search
Learning
Management
Analytics Layer
Taxonomy
Management
Document
Management
Instant
Messaging
Findability Layer
Ontology
Management
Collaboration Layer
Content Creation Layer
Document
Sharing
Annotation /
Feedback
Chat Bot
Team
Workspaces
Reporting Usage Metrics Content Metrics
Governance Layer Workflows Records Schedule Access Controls Information Audit
WYSIWYG Editor Digital Asset Editing
Alerts /
Notifications
Recommendations
APIs
Displayed below are the layers needed for a best in class Knowledge
Management and Information Management Ecosystem.
Knowledge
Graph
Customer
Relationship
Management
Digital Asset
Management
Component
Content
Management
Metadata Layer Auto-Tagging / Auto-Classification Auto-Categorization
@EKCONSULTING
Why KM Technology Efforts Fail
▪ Missing Vision
▪ Mistaken Faith in Capabilities
▪ Lack of End User Engagement
▪ Too Much Theory, Not Enough Business
▪ Excessive Complexity
▪ Insufficient Understanding of Current Technology
Ecosystem
▪ Lack of Sustainment / Governance
WHY WE NEED TO BE THOUGHTFUL
@EKCONSULTING
BE DELIBERATE WITH KM
ASSESS PROGRESS
AND ADJUST
UNDERSTAND
THE BUSINESS
DRIVERS
PUT KM IN TERMS
OF RESULTS
LEVERAGE AN
ITERATIVE
APPROACH
ACTIVE COMMUNICATION
AND DIALOGUE
@EKCONSULTING
PHASE ONE:
GATHERING REQUIREMENTS AND
DEFINING PERSONAS
Because of a Knowledge Graph…
Recommendation Engine
Use Cases
TOP-DOWN ANALYSIS
• Human-driven, facilitated workshops, focus groups, and
interviews with end-users, initiative stakeholders, and
administrators of the potential technology solution.
• This approach is designed to create buy-in and achieve
alignment for the enterprise components of the solutions,
while ensuring all stakeholders are appropriately
represented and “heard.”
BOTTOM-UP ANALYSIS
• Deep analysis of individual documents/data, document/data sets,
and existing applicable repositories or systems.
• This approach is designed to ensure initiative stakeholders
possess a firm understanding of the existing technology
ecosystem as well as the content (data or documents) that will be
ingested by the potential solution.
@EKCONSULTING
DEFINING REQUIREMENTS
FUNCTIONAL REQUIREMENTS:
-------
Identifying what a technology should do,
or challenge it should solve, is a critical
first step to take when defining
requirements.
Functional requirements
are postured to not only validate the
strength of a technology but to also
measure non-technical users’ ability to
understand and utilize a platform with
minimal training.
-------
Examples:
• Live editing (collaboration)
• Report generation
TECHNICAL REQUIREMENTS:
-------
Understanding how a technology should
perform is just as important as functional
requirements to ensure the solution
meets user needs and limits disruption to
the organization’s ecosystem.
Technical requirements are complex in
nature as they are unlike functional
requirements because they cannot easily
be demonstrated to normal users.
-------
Examples:
• Hosting location (on-prem or cloud)
• Programming language
EXPLORATORY REQUIREMENTS:
-------
Selecting technology using present-time
requirements leaves the possibility open
for a selection to be made based off
reactionary decision making.
Exploratory requirements provide insight
to a solution’s community, the vendor’s
business model, and requirements that
may not naturally be defined as functional
or technical.
-------
Examples:
• Pricing Model (cost per user)
• Sustainability (support, scalability)
@EKCONSULTING
PERSONAS & USER STORIES
PERSONAS:
Put a face and a name to the users we are
working with and designing a vision for.
Talking about personas as real people helps us
better understand their goals, frustrations, and
their motivations.
As a <role of the user>, I want <desired feature> so that <the why/end-goal>.
USER STORY:
Short, simple description of a business need or function requirement written from the perspective of the end user.
Helps deliver the highest value early in development by focusing on incremental user needs and facilitating
communication and collaboration.
@EKCONSULTING
PHASE TWO:
LEVERAGING DATA DRIVEN
EVALUATIONS
EVALUATION PROCESS OVERVIEW
Various activities exist to validate solutions against Functional, Technical, and Exploratory requirements.
The most effective methods include solution demonstrations and proof of concepts (PoC).
@EKCONSULTING
DEVELOP VENDOR
RATING RUBRIC
Define Participants for
Demo and PoCs
CONDUCT VENDOR
DEMONSTRATIONS
Prepare vendors for
demonstrations
SUB-TASKS
TASKS
PERFORM PROOF OF
CONCEPTS
ORGANIZE FINDINGS
Complete Demo Rating
Rubric
Complete PoC Rating
Rubric
Analysis & Research
Vendor Demonstrations
Demo Rating Sheets
PoC Rating Sheets
Requirements Evaluation
VENDOR GRADING RUBRIC
A Vendor Grading Rubric provides
those that are validating requirements
a centralized location to capture their
feedback.
The rubric is leveraged during
demonstrations and interactions with
the vendor or solution to compare and
contrast findings.
@EKCONSULTING
PROOF OF CONCEPT RUBRICVENDOR DEMONSTRATIONS RUBRIC
Objective
Transform demonstratable requirements into an easily
consumable list of instructions to inform the context of each
session.
Best Practices
§ Remove sales-talk from the meeting
§ Prep the vendor in advance
§ Develop and align the vendor demonstration script with the
vendor demonstration rubric being utilized by the audience
Sample Validation Criteria
§ Ability to Meet Requirements
§ Meets Requirement and Appears User-Friendly
§ Meets Requirement
§ Meets Requirement After Development Work
§ Does Not Meet Requirement
Objective
Provide a contextualized environment that enables end-users to
test and validate a solution against requirements.
Best Practices
§ Ensure PoC environment and requirements are aligned and
meet communicated expectations
§ Test in advance of asking others to conduct validation
Sample Validation Criteria
§ Platform User Friendly Evaluation
§ This Requirement Was Easy To Validate
§ I Had Trouble Validating This Requirement
§ I Experienced Extreme Difficulty Validating This
Requirement
§ Not Applicable
“Things that are easy to use should be easy to explain” @EKCONSULTING
PHASE THREE:
COMBINING QUANTITATIVE AND QUALITATIVE
DATA TO MAKE HOLISTIC DECISIONS
QUANTITATIVE VS QUALITATIVE
@EKCONSULTING
QUANTITATE DATA is defined as the value of data in
the form of counts or numbers where each data-set
has a unique numerical value associated with it.
Examples:
• Vendor Demonstration Results
• Proof of Concept Rubric Results
QUALITATIVE DATA is defined as the data that
approximates and characterizes and can be
observed and recorded.
Examples:
• Interview, Focus Group, and Workshop
Anecdotes
• Observational Analysis Notes
• Personas & User Stories
Simultaneously leveraging qualitative and quantitative data can
help you uncover both ‘the what’ and ‘the why.’
MOSCOW PRIORITIZATION APPROACH
MoSCoW Approach
§ Must Have: Critical to the business process /
solution / end-user(s). If not, the KM Technology is
considered a failure.
§ Should Have: Important, but not crucial for the KM
Technology. Considered top “nice-to-haves.”
§ Could Have: Desirable, but not necessary for the
KM Technology. Considered low “nice-to-haves.”
§ Won’t Have: Least critical or even not aligned with
the KM Technology goals and overarching strategy.
Absolutely necessary for
success.
Wouldn’t be helpful. Lets
not do it.
Nice to have, but can
wait.
Necessary, but not
immediately.
MUST SHOULD
WON’TCOULD
@EKCONSULTING
3D VALUE PRIORITIZATION
Business Value vs. Technical Complexity
vs. Foundational Value
§ Business Value: Likelihood of increasing
revenue and/or productivity. Degree to which
aligned with Brand.
§ Technical Complexity: Cost, time, and effort.
Ability to integrate with existing systems.
Performance, scalability, and productivity.
§ Foundation Value: Likelihood of increasing
operational efficiency and collaboration. Degree
to which aligned with organization goals.
@EKCONSULTING
4D VALUE PRIORITIZATION
Business Value vs. Technical Complexity vs. Foundational Value
vs. Employee Value
§ Employee Value: Likelihood of increasing engagement as a result of increased
relevant functionality and content as well as accessibility.
@EKCONSULTING
KEY CONSIDERATIONS
FOR KM TECHNOLOGY
PROCUREMENT
▪ Confirm & Validate technology and security requirements
▪ Prioritize the needs of the end-users
▪ Consider cost over 3-5 years versus initial purchase price
@EKCONSULTING
PHASE FOUR:
CRAFTING AN IMPLEMENTATION STRATEGY
FOR SUCCESS AND ADOPTION
SAMPLE KM TECHNOLOGY IMPLEMENTATION ROADMAPGovernance&
Workflow
Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Month 8
Design/Prioritize
Assess Existing Taxonomy
Create Wireframes
Conduct User Testing
Sprint 1
Branding UI/UX
Ongoing Testing and Iteration
Sprint 2
Sprint 4
Sprint 8
UI/UX Design
Sprint 3
Design and Validate Taxonomy
SystemConfigurationSiteDesign
Sprint 7Sprint 6
Sprint 5
@EKCONSULTING
Finalize Implementation Roadmap
Define IT & Business Owners
Validate Implementation Strategy
Secure Resources
Prepare Environment
BUILDING A CHANGE PLAN
ADDRESS
FEAR / CONCERNS
• During change, people most
fear what they are going to
lose.
• What are professionals afraid
of losing?
• How can we tell them “we hear
this is important to you?”
CREATE ENERGY &
DEMO
• Why KM will make people’s
lives easier everyday.
• Who can get this message
across and how will they get
this message across?
• Where and when can we
demo?
PRIORITIZE
TRANSITION SUPPORT
• Too much effort dedicated to
creating the “new thing.” Too
little effort given to transitioning.
• This is where/why 70% of
change management initiatives
fail.
DOUBLE LOOP
LEARNING
• We need a mode of receiving
feedback and reporting out
what we did with the feedback.
When building a Change Management Plan to
support the implementation, adoption, and
continuous training of your KM technology, it is
important to consider these four components.
Your Change Plan should also be designed to:
Align with the strategic goals of the organization.
Define measurable goals that can be tracked over time.
Engage business users from the outset and maintain
their engagement at every stage.
@EKCONSULTING
COMMUNICATIONS AND TRAINING PLAN
C-SUITE EXECUTIVES &
EXECUTIVE SPONSOR BUSINESS OWNER
TECH LEAD END-USERS
IDENTIFY KEY
STAKEHOLDERS & USERS
COMMUNICATIONS TRAINING
@EKCONSULTING
The truth is, no major technology investment is a
turnkey solution. Planning, communication, and
commitment are essential to organization-wide
adoption.
Components of Communications Plan:
• Identification of Key Stakeholders and Users
• Identification of KM Tool Champions
• Document Key Information & Draft
Supporting Communications
• Initial Announcements
• Major Implementation Milestones
• Training Schedules
• Requests for Feedback
• Build a Timeline / Map Communications
• Incentivize / Double Feedback Loop
Prior to implementation, create a training plan that
anticipates the needs and reactions of system
users.
Components of a Training Plan:
• Identify all users and define each of their
unique learning needs
• Review/Identify a training budget
• Design the training to include:
• Business rationale
• Explanation of how their
participation/role will make themselves
and the organization successful
• Take a blended approach (classroom
and on-the-job training)
• Opportunities for feedback
• “Test-drive” the training to “power-users” / KM
Tool Champion Team
• Deploy training
• Provide informal and formal continuous
learning opportunities
WE’LL BE ANSWERING QUESTIONS NOW
Q A&
THANKS FOR LISTENING
Q & A SESSION
TFAHLBERG@ENTERPRISE-
KNOWLEDGE.COM
LINKEDIN/IN/TFAHLBERG
Todd Fahlberg
TWITTER/@THETODDOLOGY
MJARONSKI@ENTERPRISE-
KNOWLEDGE.COM
LINKEDIN/IN/MADISON-JARONSKI
Madison Jaronski
TWITTER/@JARONSKIMADI

Mais conteúdo relacionado

Mais procurados

Agile Comes to You (Mironov, Bellevue)
Agile Comes to You (Mironov, Bellevue)Agile Comes to You (Mironov, Bellevue)
Agile Comes to You (Mironov, Bellevue)Enthiosys Inc
 
Leveraging KM as the Foundation for AI
Leveraging KM as the Foundation for AILeveraging KM as the Foundation for AI
Leveraging KM as the Foundation for AIEnterprise Knowledge
 
KM Showcase: Conference View and Knowledge Management 2020 and Beyond
KM Showcase: Conference View and Knowledge Management 2020 and BeyondKM Showcase: Conference View and Knowledge Management 2020 and Beyond
KM Showcase: Conference View and Knowledge Management 2020 and BeyondEnterprise Knowledge
 
Knowledge Management Organization and Leadership
Knowledge Management Organization and LeadershipKnowledge Management Organization and Leadership
Knowledge Management Organization and LeadershipEnterprise Knowledge
 
Successful Processes for Selecting a Content Management System: How to Become...
Successful Processes for Selecting a Content Management System: How to Become...Successful Processes for Selecting a Content Management System: How to Become...
Successful Processes for Selecting a Content Management System: How to Become...Scott Abel
 
What's in a name? Not your org chart.
What's in a name? Not your org chart.What's in a name? Not your org chart.
What's in a name? Not your org chart.Enterprise Knowledge
 
OmnichannelX 2021: How to Make Content a Maintainable Business Asset Through ...
OmnichannelX 2021: How to Make Content a Maintainable Business Asset Through ...OmnichannelX 2021: How to Make Content a Maintainable Business Asset Through ...
OmnichannelX 2021: How to Make Content a Maintainable Business Asset Through ...Enterprise Knowledge
 
Taxonomy 101: Presented at Taxonomy Boot Camp 2019
Taxonomy 101: Presented at Taxonomy Boot Camp 2019Taxonomy 101: Presented at Taxonomy Boot Camp 2019
Taxonomy 101: Presented at Taxonomy Boot Camp 2019Enterprise Knowledge
 
KM SHOWCASE 2020 - "Lessons Learned Building a Knowledge Graph" - Chris Marino
KM SHOWCASE 2020 - "Lessons Learned Building a Knowledge Graph" - Chris MarinoKM SHOWCASE 2020 - "Lessons Learned Building a Knowledge Graph" - Chris Marino
KM SHOWCASE 2020 - "Lessons Learned Building a Knowledge Graph" - Chris MarinoKM Institute
 
Leveraging KM and the Foundation for Artificial Intelligence
Leveraging KM and the Foundation for Artificial IntelligenceLeveraging KM and the Foundation for Artificial Intelligence
Leveraging KM and the Foundation for Artificial IntelligenceEnterprise Knowledge
 
So you want to be a knowledge management consultant?
So you want to be a knowledge management consultant?So you want to be a knowledge management consultant?
So you want to be a knowledge management consultant?Joe Raimondo
 
KM SHOWCASE 2020 - "Knowledge Pros: the heroes of personalization programs ev...
KM SHOWCASE 2020 - "Knowledge Pros: the heroes of personalization programs ev...KM SHOWCASE 2020 - "Knowledge Pros: the heroes of personalization programs ev...
KM SHOWCASE 2020 - "Knowledge Pros: the heroes of personalization programs ev...KM Institute
 
KM SHOWCASE 2020 - Keynote Address - Zach Wahl
KM SHOWCASE 2020 - Keynote Address - Zach WahlKM SHOWCASE 2020 - Keynote Address - Zach Wahl
KM SHOWCASE 2020 - Keynote Address - Zach WahlKM Institute
 
KM SHOWCASE 2020 - "Securing Explicit and Tacit Knowledge" - Dr. Cindy Young
KM SHOWCASE 2020 - "Securing Explicit and Tacit Knowledge" - Dr. Cindy YoungKM SHOWCASE 2020 - "Securing Explicit and Tacit Knowledge" - Dr. Cindy Young
KM SHOWCASE 2020 - "Securing Explicit and Tacit Knowledge" - Dr. Cindy YoungKM Institute
 
Let's Play! Gamifying KM to Increase Adoption
Let's Play! Gamifying KM to Increase AdoptionLet's Play! Gamifying KM to Increase Adoption
Let's Play! Gamifying KM to Increase AdoptionEnterprise Knowledge
 
KM SHOWCASE 2020 - "HR Transformation Meets the Digital World" - Shavanna Jagrup
KM SHOWCASE 2020 - "HR Transformation Meets the Digital World" - Shavanna JagrupKM SHOWCASE 2020 - "HR Transformation Meets the Digital World" - Shavanna Jagrup
KM SHOWCASE 2020 - "HR Transformation Meets the Digital World" - Shavanna JagrupKM Institute
 
FUTURE READY HR: STRATEGIES FOR POSITIVE WORKPLACE CULTURE
FUTURE READY HR: STRATEGIES FOR POSITIVE WORKPLACE CULTUREFUTURE READY HR: STRATEGIES FOR POSITIVE WORKPLACE CULTURE
FUTURE READY HR: STRATEGIES FOR POSITIVE WORKPLACE CULTUREHuman Capital Media
 
Workshop: Strategies and Tactics To Improve Your Broken Search Experience (Gr...
Workshop: Strategies and Tactics To Improve Your Broken Search Experience (Gr...Workshop: Strategies and Tactics To Improve Your Broken Search Experience (Gr...
Workshop: Strategies and Tactics To Improve Your Broken Search Experience (Gr...Digital Workplace Experience
 

Mais procurados (20)

Agile Comes to You (Mironov, Bellevue)
Agile Comes to You (Mironov, Bellevue)Agile Comes to You (Mironov, Bellevue)
Agile Comes to You (Mironov, Bellevue)
 
Leveraging KM as the Foundation for AI
Leveraging KM as the Foundation for AILeveraging KM as the Foundation for AI
Leveraging KM as the Foundation for AI
 
KM Showcase: Conference View and Knowledge Management 2020 and Beyond
KM Showcase: Conference View and Knowledge Management 2020 and BeyondKM Showcase: Conference View and Knowledge Management 2020 and Beyond
KM Showcase: Conference View and Knowledge Management 2020 and Beyond
 
Knowledge Management Organization and Leadership
Knowledge Management Organization and LeadershipKnowledge Management Organization and Leadership
Knowledge Management Organization and Leadership
 
Semantic Use Cases
Semantic Use CasesSemantic Use Cases
Semantic Use Cases
 
Successful Processes for Selecting a Content Management System: How to Become...
Successful Processes for Selecting a Content Management System: How to Become...Successful Processes for Selecting a Content Management System: How to Become...
Successful Processes for Selecting a Content Management System: How to Become...
 
What's in a name? Not your org chart.
What's in a name? Not your org chart.What's in a name? Not your org chart.
What's in a name? Not your org chart.
 
OmnichannelX 2021: How to Make Content a Maintainable Business Asset Through ...
OmnichannelX 2021: How to Make Content a Maintainable Business Asset Through ...OmnichannelX 2021: How to Make Content a Maintainable Business Asset Through ...
OmnichannelX 2021: How to Make Content a Maintainable Business Asset Through ...
 
Taxonomy 101: Presented at Taxonomy Boot Camp 2019
Taxonomy 101: Presented at Taxonomy Boot Camp 2019Taxonomy 101: Presented at Taxonomy Boot Camp 2019
Taxonomy 101: Presented at Taxonomy Boot Camp 2019
 
KM SHOWCASE 2020 - "Lessons Learned Building a Knowledge Graph" - Chris Marino
KM SHOWCASE 2020 - "Lessons Learned Building a Knowledge Graph" - Chris MarinoKM SHOWCASE 2020 - "Lessons Learned Building a Knowledge Graph" - Chris Marino
KM SHOWCASE 2020 - "Lessons Learned Building a Knowledge Graph" - Chris Marino
 
Leveraging KM and the Foundation for Artificial Intelligence
Leveraging KM and the Foundation for Artificial IntelligenceLeveraging KM and the Foundation for Artificial Intelligence
Leveraging KM and the Foundation for Artificial Intelligence
 
So you want to be a knowledge management consultant?
So you want to be a knowledge management consultant?So you want to be a knowledge management consultant?
So you want to be a knowledge management consultant?
 
KM SHOWCASE 2020 - "Knowledge Pros: the heroes of personalization programs ev...
KM SHOWCASE 2020 - "Knowledge Pros: the heroes of personalization programs ev...KM SHOWCASE 2020 - "Knowledge Pros: the heroes of personalization programs ev...
KM SHOWCASE 2020 - "Knowledge Pros: the heroes of personalization programs ev...
 
KM SHOWCASE 2020 - Keynote Address - Zach Wahl
KM SHOWCASE 2020 - Keynote Address - Zach WahlKM SHOWCASE 2020 - Keynote Address - Zach Wahl
KM SHOWCASE 2020 - Keynote Address - Zach Wahl
 
KM SHOWCASE 2020 - "Securing Explicit and Tacit Knowledge" - Dr. Cindy Young
KM SHOWCASE 2020 - "Securing Explicit and Tacit Knowledge" - Dr. Cindy YoungKM SHOWCASE 2020 - "Securing Explicit and Tacit Knowledge" - Dr. Cindy Young
KM SHOWCASE 2020 - "Securing Explicit and Tacit Knowledge" - Dr. Cindy Young
 
Let's Play! Gamifying KM to Increase Adoption
Let's Play! Gamifying KM to Increase AdoptionLet's Play! Gamifying KM to Increase Adoption
Let's Play! Gamifying KM to Increase Adoption
 
KM SHOWCASE 2020 - "HR Transformation Meets the Digital World" - Shavanna Jagrup
KM SHOWCASE 2020 - "HR Transformation Meets the Digital World" - Shavanna JagrupKM SHOWCASE 2020 - "HR Transformation Meets the Digital World" - Shavanna Jagrup
KM SHOWCASE 2020 - "HR Transformation Meets the Digital World" - Shavanna Jagrup
 
FUTURE READY HR: STRATEGIES FOR POSITIVE WORKPLACE CULTURE
FUTURE READY HR: STRATEGIES FOR POSITIVE WORKPLACE CULTUREFUTURE READY HR: STRATEGIES FOR POSITIVE WORKPLACE CULTURE
FUTURE READY HR: STRATEGIES FOR POSITIVE WORKPLACE CULTURE
 
Slalmd2014 cid presentation
Slalmd2014 cid presentationSlalmd2014 cid presentation
Slalmd2014 cid presentation
 
Workshop: Strategies and Tactics To Improve Your Broken Search Experience (Gr...
Workshop: Strategies and Tactics To Improve Your Broken Search Experience (Gr...Workshop: Strategies and Tactics To Improve Your Broken Search Experience (Gr...
Workshop: Strategies and Tactics To Improve Your Broken Search Experience (Gr...
 

Semelhante a Give the People What They Want: An Approach to Thoughtful KM Technology

Product Management 101: Techniques for Success
Product Management 101:  Techniques for SuccessProduct Management 101:  Techniques for Success
Product Management 101: Techniques for SuccessMatterport
 
2019 10-23 24 fiware summit @berlin
2019 10-23 24 fiware summit @berlin2019 10-23 24 fiware summit @berlin
2019 10-23 24 fiware summit @berlinMIDIH_EU
 
Why it's time to rethink your approach to Enterprise Architecture
Why it's time to rethink your approach to Enterprise ArchitectureWhy it's time to rethink your approach to Enterprise Architecture
Why it's time to rethink your approach to Enterprise ArchitectureLeanIX GmbH
 
Impact Driven Delivery
Impact Driven DeliveryImpact Driven Delivery
Impact Driven DeliveryinUse
 
Maryann Werner - Work Portfolio
Maryann Werner - Work PortfolioMaryann Werner - Work Portfolio
Maryann Werner - Work PortfolioMaryann Werner
 
Building a Complete View Across the Customer Experience on Oracle BICS
Building a Complete View Across the Customer Experience on Oracle BICSBuilding a Complete View Across the Customer Experience on Oracle BICS
Building a Complete View Across the Customer Experience on Oracle BICSShiv Bharti
 
Workflow technology: Managing roles and staff resources better to meet your s...
Workflow technology: Managing roles and staff resources better to meet your s...Workflow technology: Managing roles and staff resources better to meet your s...
Workflow technology: Managing roles and staff resources better to meet your s...Associations Network
 
What Does Full-on Personalization Look Like and How Do I Get There? Sitecore ...
What Does Full-on Personalization Look Like and How Do I Get There? Sitecore ...What Does Full-on Personalization Look Like and How Do I Get There? Sitecore ...
What Does Full-on Personalization Look Like and How Do I Get There? Sitecore ...Sean Rusinko
 
Connecting the Dots: Creating a Sales Driven Organization
Connecting the Dots: Creating a Sales Driven OrganizationConnecting the Dots: Creating a Sales Driven Organization
Connecting the Dots: Creating a Sales Driven OrganizationIngram Micro Cloud
 
Your Roadmap, Your Product Story & Datadriven Product Management
Your Roadmap, Your Product Story & Datadriven Product ManagementYour Roadmap, Your Product Story & Datadriven Product Management
Your Roadmap, Your Product Story & Datadriven Product ManagementProduct School
 
Advancing the analytics maturity curve at your organization
Advancing the analytics maturity curve at your organizationAdvancing the analytics maturity curve at your organization
Advancing the analytics maturity curve at your organizationRamkumar Ravichandran
 
Agile, Automated, Aware: How to Model for Success
Agile, Automated, Aware: How to Model for SuccessAgile, Automated, Aware: How to Model for Success
Agile, Automated, Aware: How to Model for SuccessInside Analysis
 
3 Challenges of Building Complex Dashboards with Open Source Components
3 Challenges of Building Complex Dashboards with Open Source Components3 Challenges of Building Complex Dashboards with Open Source Components
3 Challenges of Building Complex Dashboards with Open Source ComponentsRyan MacCarrigan
 
Seal Infotech Consulting Profile
Seal Infotech Consulting ProfileSeal Infotech Consulting Profile
Seal Infotech Consulting ProfileSeal Infotech
 
EIS-PM-Devt-Services-Boot Camp_Combined (1)
EIS-PM-Devt-Services-Boot Camp_Combined (1)EIS-PM-Devt-Services-Boot Camp_Combined (1)
EIS-PM-Devt-Services-Boot Camp_Combined (1)Thomas Squeo
 
Digital alpha technologies inc
Digital alpha technologies incDigital alpha technologies inc
Digital alpha technologies incDigital Alpha
 
Enterprise Architecture, Project Management & Digital Transformation
Enterprise Architecture, Project Management & Digital TransformationEnterprise Architecture, Project Management & Digital Transformation
Enterprise Architecture, Project Management & Digital TransformationRiaz A. Khan, OpenCA, TOGAF
 
Building an Adoption Plan: Turning it on(Part 2 of 2)
Building an Adoption Plan: Turning it on(Part 2 of 2)Building an Adoption Plan: Turning it on(Part 2 of 2)
Building an Adoption Plan: Turning it on(Part 2 of 2)Cisco Canada
 
UX STRAT 2018 | Flying Blind On a Rocket Cycle: Pioneering Experience Centere...
UX STRAT 2018 | Flying Blind On a Rocket Cycle: Pioneering Experience Centere...UX STRAT 2018 | Flying Blind On a Rocket Cycle: Pioneering Experience Centere...
UX STRAT 2018 | Flying Blind On a Rocket Cycle: Pioneering Experience Centere...Joe Lamantia
 

Semelhante a Give the People What They Want: An Approach to Thoughtful KM Technology (20)

Product Management 101: Techniques for Success
Product Management 101:  Techniques for SuccessProduct Management 101:  Techniques for Success
Product Management 101: Techniques for Success
 
2019 10-23 24 fiware summit @berlin
2019 10-23 24 fiware summit @berlin2019 10-23 24 fiware summit @berlin
2019 10-23 24 fiware summit @berlin
 
Why it's time to rethink your approach to Enterprise Architecture
Why it's time to rethink your approach to Enterprise ArchitectureWhy it's time to rethink your approach to Enterprise Architecture
Why it's time to rethink your approach to Enterprise Architecture
 
Impact Driven Delivery
Impact Driven DeliveryImpact Driven Delivery
Impact Driven Delivery
 
Maryann Werner - Work Portfolio
Maryann Werner - Work PortfolioMaryann Werner - Work Portfolio
Maryann Werner - Work Portfolio
 
Building a Complete View Across the Customer Experience on Oracle BICS
Building a Complete View Across the Customer Experience on Oracle BICSBuilding a Complete View Across the Customer Experience on Oracle BICS
Building a Complete View Across the Customer Experience on Oracle BICS
 
Workflow technology: Managing roles and staff resources better to meet your s...
Workflow technology: Managing roles and staff resources better to meet your s...Workflow technology: Managing roles and staff resources better to meet your s...
Workflow technology: Managing roles and staff resources better to meet your s...
 
What Does Full-on Personalization Look Like and How Do I Get There? Sitecore ...
What Does Full-on Personalization Look Like and How Do I Get There? Sitecore ...What Does Full-on Personalization Look Like and How Do I Get There? Sitecore ...
What Does Full-on Personalization Look Like and How Do I Get There? Sitecore ...
 
Connecting the Dots: Creating a Sales Driven Organization
Connecting the Dots: Creating a Sales Driven OrganizationConnecting the Dots: Creating a Sales Driven Organization
Connecting the Dots: Creating a Sales Driven Organization
 
Six Sigma Qfd
Six Sigma QfdSix Sigma Qfd
Six Sigma Qfd
 
Your Roadmap, Your Product Story & Datadriven Product Management
Your Roadmap, Your Product Story & Datadriven Product ManagementYour Roadmap, Your Product Story & Datadriven Product Management
Your Roadmap, Your Product Story & Datadriven Product Management
 
Advancing the analytics maturity curve at your organization
Advancing the analytics maturity curve at your organizationAdvancing the analytics maturity curve at your organization
Advancing the analytics maturity curve at your organization
 
Agile, Automated, Aware: How to Model for Success
Agile, Automated, Aware: How to Model for SuccessAgile, Automated, Aware: How to Model for Success
Agile, Automated, Aware: How to Model for Success
 
3 Challenges of Building Complex Dashboards with Open Source Components
3 Challenges of Building Complex Dashboards with Open Source Components3 Challenges of Building Complex Dashboards with Open Source Components
3 Challenges of Building Complex Dashboards with Open Source Components
 
Seal Infotech Consulting Profile
Seal Infotech Consulting ProfileSeal Infotech Consulting Profile
Seal Infotech Consulting Profile
 
EIS-PM-Devt-Services-Boot Camp_Combined (1)
EIS-PM-Devt-Services-Boot Camp_Combined (1)EIS-PM-Devt-Services-Boot Camp_Combined (1)
EIS-PM-Devt-Services-Boot Camp_Combined (1)
 
Digital alpha technologies inc
Digital alpha technologies incDigital alpha technologies inc
Digital alpha technologies inc
 
Enterprise Architecture, Project Management & Digital Transformation
Enterprise Architecture, Project Management & Digital TransformationEnterprise Architecture, Project Management & Digital Transformation
Enterprise Architecture, Project Management & Digital Transformation
 
Building an Adoption Plan: Turning it on(Part 2 of 2)
Building an Adoption Plan: Turning it on(Part 2 of 2)Building an Adoption Plan: Turning it on(Part 2 of 2)
Building an Adoption Plan: Turning it on(Part 2 of 2)
 
UX STRAT 2018 | Flying Blind On a Rocket Cycle: Pioneering Experience Centere...
UX STRAT 2018 | Flying Blind On a Rocket Cycle: Pioneering Experience Centere...UX STRAT 2018 | Flying Blind On a Rocket Cycle: Pioneering Experience Centere...
UX STRAT 2018 | Flying Blind On a Rocket Cycle: Pioneering Experience Centere...
 

Mais de Enterprise Knowledge

Overview of Taxonomies and Artificial Intelligence
Overview of Taxonomies and Artificial IntelligenceOverview of Taxonomies and Artificial Intelligence
Overview of Taxonomies and Artificial IntelligenceEnterprise Knowledge
 
Nonprofit KM Journey to Success: Lessons and Learnings at Feeding America
Nonprofit KM Journey to Success: Lessons and Learnings at Feeding AmericaNonprofit KM Journey to Success: Lessons and Learnings at Feeding America
Nonprofit KM Journey to Success: Lessons and Learnings at Feeding AmericaEnterprise Knowledge
 
DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...
DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...
DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...Enterprise Knowledge
 
Scaling Knowledge Graph Architectures with AI
Scaling Knowledge Graph Architectures with AIScaling Knowledge Graph Architectures with AI
Scaling Knowledge Graph Architectures with AIEnterprise Knowledge
 
Making Knowledge Management Clickable
Making Knowledge Management ClickableMaking Knowledge Management Clickable
Making Knowledge Management ClickableEnterprise Knowledge
 
Building for the Knowledge Management Archetypes at Your Company
Building for the Knowledge Management Archetypes at Your CompanyBuilding for the Knowledge Management Archetypes at Your Company
Building for the Knowledge Management Archetypes at Your CompanyEnterprise Knowledge
 
Knowledge Graphs are Worthless, Knowledge Graph Use Cases are Priceless
Knowledge Graphs are Worthless, Knowledge Graph Use Cases are PricelessKnowledge Graphs are Worthless, Knowledge Graph Use Cases are Priceless
Knowledge Graphs are Worthless, Knowledge Graph Use Cases are PricelessEnterprise Knowledge
 
Introducing the Agile KM Manifesto.pdf
Introducing the Agile KM Manifesto.pdfIntroducing the Agile KM Manifesto.pdf
Introducing the Agile KM Manifesto.pdfEnterprise Knowledge
 
Road Maps & Roadblocks to Federal Electronic Records Management
Road Maps & Roadblocks to Federal Electronic Records ManagementRoad Maps & Roadblocks to Federal Electronic Records Management
Road Maps & Roadblocks to Federal Electronic Records ManagementEnterprise Knowledge
 
Building an Innovative Learning Ecosystem at Scale with Graph Technologies
Building an Innovative Learning Ecosystem at Scale with Graph TechnologiesBuilding an Innovative Learning Ecosystem at Scale with Graph Technologies
Building an Innovative Learning Ecosystem at Scale with Graph TechnologiesEnterprise Knowledge
 
Identifying Security Risks Using Auto-Tagging and Text Analytics
Identifying Security Risks Using Auto-Tagging and Text AnalyticsIdentifying Security Risks Using Auto-Tagging and Text Analytics
Identifying Security Risks Using Auto-Tagging and Text AnalyticsEnterprise Knowledge
 
Taxonomy in the Age of Personalization
Taxonomy in the Age of PersonalizationTaxonomy in the Age of Personalization
Taxonomy in the Age of PersonalizationEnterprise Knowledge
 
Climbing the Ontology Mountain to Achieve a Successful Knowledge Graph
Climbing the Ontology Mountain to Achieve a Successful Knowledge GraphClimbing the Ontology Mountain to Achieve a Successful Knowledge Graph
Climbing the Ontology Mountain to Achieve a Successful Knowledge GraphEnterprise Knowledge
 
JPL’s Institutional Knowledge Graph II: A Foundation for Constructing Enterpr...
JPL’s Institutional Knowledge Graph II: A Foundation for Constructing Enterpr...JPL’s Institutional Knowledge Graph II: A Foundation for Constructing Enterpr...
JPL’s Institutional Knowledge Graph II: A Foundation for Constructing Enterpr...Enterprise Knowledge
 
Learning 360: Crafting a Comprehensive View of Learning by Using a Graph
Learning 360: Crafting a Comprehensive View of Learning by Using a GraphLearning 360: Crafting a Comprehensive View of Learning by Using a Graph
Learning 360: Crafting a Comprehensive View of Learning by Using a GraphEnterprise Knowledge
 
Making KM Clickable: The Rapidly Changing State of Knowledge Management
Making KM Clickable: The Rapidly Changing State of Knowledge ManagementMaking KM Clickable: The Rapidly Changing State of Knowledge Management
Making KM Clickable: The Rapidly Changing State of Knowledge ManagementEnterprise Knowledge
 
How to Quickly Prototype a Scalable Graph Architecture: A Framework for Rapid...
How to Quickly Prototype a Scalable Graph Architecture: A Framework for Rapid...How to Quickly Prototype a Scalable Graph Architecture: A Framework for Rapid...
How to Quickly Prototype a Scalable Graph Architecture: A Framework for Rapid...Enterprise Knowledge
 
Translating AI from Concept to Reality: Five Keys to Implementing AI for Know...
Translating AI from Concept to Reality: Five Keys to Implementing AI for Know...Translating AI from Concept to Reality: Five Keys to Implementing AI for Know...
Translating AI from Concept to Reality: Five Keys to Implementing AI for Know...Enterprise Knowledge
 
Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020Enterprise Knowledge
 
Designing an Organization’s KM Journey
Designing an Organization’s KM JourneyDesigning an Organization’s KM Journey
Designing an Organization’s KM JourneyEnterprise Knowledge
 

Mais de Enterprise Knowledge (20)

Overview of Taxonomies and Artificial Intelligence
Overview of Taxonomies and Artificial IntelligenceOverview of Taxonomies and Artificial Intelligence
Overview of Taxonomies and Artificial Intelligence
 
Nonprofit KM Journey to Success: Lessons and Learnings at Feeding America
Nonprofit KM Journey to Success: Lessons and Learnings at Feeding AmericaNonprofit KM Journey to Success: Lessons and Learnings at Feeding America
Nonprofit KM Journey to Success: Lessons and Learnings at Feeding America
 
DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...
DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...
DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...
 
Scaling Knowledge Graph Architectures with AI
Scaling Knowledge Graph Architectures with AIScaling Knowledge Graph Architectures with AI
Scaling Knowledge Graph Architectures with AI
 
Making Knowledge Management Clickable
Making Knowledge Management ClickableMaking Knowledge Management Clickable
Making Knowledge Management Clickable
 
Building for the Knowledge Management Archetypes at Your Company
Building for the Knowledge Management Archetypes at Your CompanyBuilding for the Knowledge Management Archetypes at Your Company
Building for the Knowledge Management Archetypes at Your Company
 
Knowledge Graphs are Worthless, Knowledge Graph Use Cases are Priceless
Knowledge Graphs are Worthless, Knowledge Graph Use Cases are PricelessKnowledge Graphs are Worthless, Knowledge Graph Use Cases are Priceless
Knowledge Graphs are Worthless, Knowledge Graph Use Cases are Priceless
 
Introducing the Agile KM Manifesto.pdf
Introducing the Agile KM Manifesto.pdfIntroducing the Agile KM Manifesto.pdf
Introducing the Agile KM Manifesto.pdf
 
Road Maps & Roadblocks to Federal Electronic Records Management
Road Maps & Roadblocks to Federal Electronic Records ManagementRoad Maps & Roadblocks to Federal Electronic Records Management
Road Maps & Roadblocks to Federal Electronic Records Management
 
Building an Innovative Learning Ecosystem at Scale with Graph Technologies
Building an Innovative Learning Ecosystem at Scale with Graph TechnologiesBuilding an Innovative Learning Ecosystem at Scale with Graph Technologies
Building an Innovative Learning Ecosystem at Scale with Graph Technologies
 
Identifying Security Risks Using Auto-Tagging and Text Analytics
Identifying Security Risks Using Auto-Tagging and Text AnalyticsIdentifying Security Risks Using Auto-Tagging and Text Analytics
Identifying Security Risks Using Auto-Tagging and Text Analytics
 
Taxonomy in the Age of Personalization
Taxonomy in the Age of PersonalizationTaxonomy in the Age of Personalization
Taxonomy in the Age of Personalization
 
Climbing the Ontology Mountain to Achieve a Successful Knowledge Graph
Climbing the Ontology Mountain to Achieve a Successful Knowledge GraphClimbing the Ontology Mountain to Achieve a Successful Knowledge Graph
Climbing the Ontology Mountain to Achieve a Successful Knowledge Graph
 
JPL’s Institutional Knowledge Graph II: A Foundation for Constructing Enterpr...
JPL’s Institutional Knowledge Graph II: A Foundation for Constructing Enterpr...JPL’s Institutional Knowledge Graph II: A Foundation for Constructing Enterpr...
JPL’s Institutional Knowledge Graph II: A Foundation for Constructing Enterpr...
 
Learning 360: Crafting a Comprehensive View of Learning by Using a Graph
Learning 360: Crafting a Comprehensive View of Learning by Using a GraphLearning 360: Crafting a Comprehensive View of Learning by Using a Graph
Learning 360: Crafting a Comprehensive View of Learning by Using a Graph
 
Making KM Clickable: The Rapidly Changing State of Knowledge Management
Making KM Clickable: The Rapidly Changing State of Knowledge ManagementMaking KM Clickable: The Rapidly Changing State of Knowledge Management
Making KM Clickable: The Rapidly Changing State of Knowledge Management
 
How to Quickly Prototype a Scalable Graph Architecture: A Framework for Rapid...
How to Quickly Prototype a Scalable Graph Architecture: A Framework for Rapid...How to Quickly Prototype a Scalable Graph Architecture: A Framework for Rapid...
How to Quickly Prototype a Scalable Graph Architecture: A Framework for Rapid...
 
Translating AI from Concept to Reality: Five Keys to Implementing AI for Know...
Translating AI from Concept to Reality: Five Keys to Implementing AI for Know...Translating AI from Concept to Reality: Five Keys to Implementing AI for Know...
Translating AI from Concept to Reality: Five Keys to Implementing AI for Know...
 
Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020
 
Designing an Organization’s KM Journey
Designing an Organization’s KM JourneyDesigning an Organization’s KM Journey
Designing an Organization’s KM Journey
 

Último

UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfUiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfDianaGray10
 
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAAnypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAshyamraj55
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdfPedro Manuel
 
COMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a WebsiteCOMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a Websitedgelyza
 
UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8DianaGray10
 
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IES VE
 
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.YounusS2
 
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Will Schroeder
 
Comparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioComparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioChristian Posta
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfAijun Zhang
 
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online CollaborationCOMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online Collaborationbruanjhuli
 
20230202 - Introduction to tis-py
20230202 - Introduction to tis-py20230202 - Introduction to tis-py
20230202 - Introduction to tis-pyJamie (Taka) Wang
 
NIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopNIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopBachir Benyammi
 
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1DianaGray10
 
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfJamie (Taka) Wang
 
Introduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxIntroduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxMatsuo Lab
 
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...DianaGray10
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesMd Hossain Ali
 

Último (20)

UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdfUiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
UiPath Solutions Management Preview - Northern CA Chapter - March 22.pdf
 
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAAnypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdf
 
COMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a WebsiteCOMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a Website
 
UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8
 
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
 
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.
 
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
 
201610817 - edge part1
201610817 - edge part1201610817 - edge part1
201610817 - edge part1
 
Comparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioComparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and Istio
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdf
 
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online CollaborationCOMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
 
20230202 - Introduction to tis-py
20230202 - Introduction to tis-py20230202 - Introduction to tis-py
20230202 - Introduction to tis-py
 
NIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopNIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 Workshop
 
20150722 - AGV
20150722 - AGV20150722 - AGV
20150722 - AGV
 
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
 
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
activity_diagram_combine_v4_20190827.pdfactivity_diagram_combine_v4_20190827.pdf
 
Introduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptxIntroduction to Matsuo Laboratory (ENG).pptx
Introduction to Matsuo Laboratory (ENG).pptx
 
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
Connector Corner: Extending LLM automation use cases with UiPath GenAI connec...
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
 

Give the People What They Want: An Approach to Thoughtful KM Technology

  • 1. GIVE THE PEOPLE WHAT THEY WANT: A THOUGHTFUL APPROACH TO KM TECHNOLOGY Midwest KM Symposium 2020 By: Todd Fahlberg and Madison Jaronski May 19, 2020
  • 2. @EKCONSULTING MADISON JARONSKITODD FAHLBERG KM Technical Consultant Senior KM Analyst Areas of expertise: KM Technical Strategy & Implementation, Enterprise Search, and Semantic Technologies Areas of expertise: KM Strategy, User-Centric Design, and Gamification
  • 3. EK AT A GLANCE 60% 40% STABLE CLIENT BASE 50+ EXPERT CONSULTANTS CommercialFederal 7 AREAS OF FOCUS ▪ KNOWLEDGE MANAGEMENT STRATEGY & DESIGN ▪ TAXONOMY & ONTOLOGY DESIGN ▪ CONTENT & BRAND STRATEGY ▪ TECHNOLOGY SOLUTIONS ▪ AGILE TRANSFORMATION ▪ CHANGE MANAGEMENT ▪ KNOWLEDGE GRAPHS, SEMANTIC MODELING, AND ARTIFICIAL INTELLIGENCE 25+ COUNTRIES GLOBAL REACH WITH CLIENTS IN BASED IN DC
  • 4. KNOWLEDGE MANAGEMENT INVOLVES THE PEOPLE, PROCESS, CULTURE, AND ENABLING TECHNOLOGIES NECESSARY TO CAPTURE, MANAGE, SHARE, AND FIND INFORMATION.
  • 5. DECONSTRUCTING KM PEOPLE • Flow of knowledge through the organization. • Knowledge holders and knowledge consumers. • Understanding of state and disposition of experts. PROCESS • Existence and consistency of processes. • Awareness of and adherence to processes. • Quality of processes. CONTENT • State and location of content. • Consistency of structure and architecture. • Dynamism of content. • Understanding of usage (analytics). CULTURE • Senior support and comprehension. • Willingness to share, collaborate, and support. TECHNOLOGY • Maturity of “KM Platform” or ”KM Ecosystem”. • Integration with and between systems. • Usability and user- centricity. @EKCONSULTING
  • 6. KM ECOSYSTEM - LOGICAL ARCHITECTURE Content Management System Used to author, organize, manage, and publish content on a web interfaceCentralized UI Repository Layer Web Content Management Enterprise Search Learning Management Analytics Layer Taxonomy Management Document Management Instant Messaging Findability Layer Ontology Management Collaboration Layer Content Creation Layer Document Sharing Annotation / Feedback Chat Bot Team Workspaces Reporting Usage Metrics Content Metrics Governance Layer Workflows Records Schedule Access Controls Information Audit WYSIWYG Editor Digital Asset Editing Alerts / Notifications Recommendations APIs Displayed below are the layers needed for a best in class Knowledge Management and Information Management Ecosystem. Knowledge Graph Customer Relationship Management Digital Asset Management Component Content Management Metadata Layer Auto-Tagging / Auto-Classification Auto-Categorization @EKCONSULTING
  • 7. Why KM Technology Efforts Fail ▪ Missing Vision ▪ Mistaken Faith in Capabilities ▪ Lack of End User Engagement ▪ Too Much Theory, Not Enough Business ▪ Excessive Complexity ▪ Insufficient Understanding of Current Technology Ecosystem ▪ Lack of Sustainment / Governance WHY WE NEED TO BE THOUGHTFUL @EKCONSULTING
  • 8. BE DELIBERATE WITH KM ASSESS PROGRESS AND ADJUST UNDERSTAND THE BUSINESS DRIVERS PUT KM IN TERMS OF RESULTS LEVERAGE AN ITERATIVE APPROACH ACTIVE COMMUNICATION AND DIALOGUE @EKCONSULTING
  • 9. PHASE ONE: GATHERING REQUIREMENTS AND DEFINING PERSONAS
  • 10. Because of a Knowledge Graph… Recommendation Engine Use Cases TOP-DOWN ANALYSIS • Human-driven, facilitated workshops, focus groups, and interviews with end-users, initiative stakeholders, and administrators of the potential technology solution. • This approach is designed to create buy-in and achieve alignment for the enterprise components of the solutions, while ensuring all stakeholders are appropriately represented and “heard.” BOTTOM-UP ANALYSIS • Deep analysis of individual documents/data, document/data sets, and existing applicable repositories or systems. • This approach is designed to ensure initiative stakeholders possess a firm understanding of the existing technology ecosystem as well as the content (data or documents) that will be ingested by the potential solution. @EKCONSULTING
  • 11. DEFINING REQUIREMENTS FUNCTIONAL REQUIREMENTS: ------- Identifying what a technology should do, or challenge it should solve, is a critical first step to take when defining requirements. Functional requirements are postured to not only validate the strength of a technology but to also measure non-technical users’ ability to understand and utilize a platform with minimal training. ------- Examples: • Live editing (collaboration) • Report generation TECHNICAL REQUIREMENTS: ------- Understanding how a technology should perform is just as important as functional requirements to ensure the solution meets user needs and limits disruption to the organization’s ecosystem. Technical requirements are complex in nature as they are unlike functional requirements because they cannot easily be demonstrated to normal users. ------- Examples: • Hosting location (on-prem or cloud) • Programming language EXPLORATORY REQUIREMENTS: ------- Selecting technology using present-time requirements leaves the possibility open for a selection to be made based off reactionary decision making. Exploratory requirements provide insight to a solution’s community, the vendor’s business model, and requirements that may not naturally be defined as functional or technical. ------- Examples: • Pricing Model (cost per user) • Sustainability (support, scalability) @EKCONSULTING
  • 12. PERSONAS & USER STORIES PERSONAS: Put a face and a name to the users we are working with and designing a vision for. Talking about personas as real people helps us better understand their goals, frustrations, and their motivations. As a <role of the user>, I want <desired feature> so that <the why/end-goal>. USER STORY: Short, simple description of a business need or function requirement written from the perspective of the end user. Helps deliver the highest value early in development by focusing on incremental user needs and facilitating communication and collaboration. @EKCONSULTING
  • 13. PHASE TWO: LEVERAGING DATA DRIVEN EVALUATIONS
  • 14. EVALUATION PROCESS OVERVIEW Various activities exist to validate solutions against Functional, Technical, and Exploratory requirements. The most effective methods include solution demonstrations and proof of concepts (PoC). @EKCONSULTING DEVELOP VENDOR RATING RUBRIC Define Participants for Demo and PoCs CONDUCT VENDOR DEMONSTRATIONS Prepare vendors for demonstrations SUB-TASKS TASKS PERFORM PROOF OF CONCEPTS ORGANIZE FINDINGS Complete Demo Rating Rubric Complete PoC Rating Rubric Analysis & Research Vendor Demonstrations Demo Rating Sheets PoC Rating Sheets Requirements Evaluation
  • 15. VENDOR GRADING RUBRIC A Vendor Grading Rubric provides those that are validating requirements a centralized location to capture their feedback. The rubric is leveraged during demonstrations and interactions with the vendor or solution to compare and contrast findings. @EKCONSULTING
  • 16. PROOF OF CONCEPT RUBRICVENDOR DEMONSTRATIONS RUBRIC Objective Transform demonstratable requirements into an easily consumable list of instructions to inform the context of each session. Best Practices § Remove sales-talk from the meeting § Prep the vendor in advance § Develop and align the vendor demonstration script with the vendor demonstration rubric being utilized by the audience Sample Validation Criteria § Ability to Meet Requirements § Meets Requirement and Appears User-Friendly § Meets Requirement § Meets Requirement After Development Work § Does Not Meet Requirement Objective Provide a contextualized environment that enables end-users to test and validate a solution against requirements. Best Practices § Ensure PoC environment and requirements are aligned and meet communicated expectations § Test in advance of asking others to conduct validation Sample Validation Criteria § Platform User Friendly Evaluation § This Requirement Was Easy To Validate § I Had Trouble Validating This Requirement § I Experienced Extreme Difficulty Validating This Requirement § Not Applicable “Things that are easy to use should be easy to explain” @EKCONSULTING
  • 17. PHASE THREE: COMBINING QUANTITATIVE AND QUALITATIVE DATA TO MAKE HOLISTIC DECISIONS
  • 18. QUANTITATIVE VS QUALITATIVE @EKCONSULTING QUANTITATE DATA is defined as the value of data in the form of counts or numbers where each data-set has a unique numerical value associated with it. Examples: • Vendor Demonstration Results • Proof of Concept Rubric Results QUALITATIVE DATA is defined as the data that approximates and characterizes and can be observed and recorded. Examples: • Interview, Focus Group, and Workshop Anecdotes • Observational Analysis Notes • Personas & User Stories Simultaneously leveraging qualitative and quantitative data can help you uncover both ‘the what’ and ‘the why.’
  • 19. MOSCOW PRIORITIZATION APPROACH MoSCoW Approach § Must Have: Critical to the business process / solution / end-user(s). If not, the KM Technology is considered a failure. § Should Have: Important, but not crucial for the KM Technology. Considered top “nice-to-haves.” § Could Have: Desirable, but not necessary for the KM Technology. Considered low “nice-to-haves.” § Won’t Have: Least critical or even not aligned with the KM Technology goals and overarching strategy. Absolutely necessary for success. Wouldn’t be helpful. Lets not do it. Nice to have, but can wait. Necessary, but not immediately. MUST SHOULD WON’TCOULD @EKCONSULTING
  • 20. 3D VALUE PRIORITIZATION Business Value vs. Technical Complexity vs. Foundational Value § Business Value: Likelihood of increasing revenue and/or productivity. Degree to which aligned with Brand. § Technical Complexity: Cost, time, and effort. Ability to integrate with existing systems. Performance, scalability, and productivity. § Foundation Value: Likelihood of increasing operational efficiency and collaboration. Degree to which aligned with organization goals. @EKCONSULTING
  • 21. 4D VALUE PRIORITIZATION Business Value vs. Technical Complexity vs. Foundational Value vs. Employee Value § Employee Value: Likelihood of increasing engagement as a result of increased relevant functionality and content as well as accessibility. @EKCONSULTING
  • 22. KEY CONSIDERATIONS FOR KM TECHNOLOGY PROCUREMENT ▪ Confirm & Validate technology and security requirements ▪ Prioritize the needs of the end-users ▪ Consider cost over 3-5 years versus initial purchase price @EKCONSULTING
  • 23. PHASE FOUR: CRAFTING AN IMPLEMENTATION STRATEGY FOR SUCCESS AND ADOPTION
  • 24. SAMPLE KM TECHNOLOGY IMPLEMENTATION ROADMAPGovernance& Workflow Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Month 8 Design/Prioritize Assess Existing Taxonomy Create Wireframes Conduct User Testing Sprint 1 Branding UI/UX Ongoing Testing and Iteration Sprint 2 Sprint 4 Sprint 8 UI/UX Design Sprint 3 Design and Validate Taxonomy SystemConfigurationSiteDesign Sprint 7Sprint 6 Sprint 5 @EKCONSULTING Finalize Implementation Roadmap Define IT & Business Owners Validate Implementation Strategy Secure Resources Prepare Environment
  • 25. BUILDING A CHANGE PLAN ADDRESS FEAR / CONCERNS • During change, people most fear what they are going to lose. • What are professionals afraid of losing? • How can we tell them “we hear this is important to you?” CREATE ENERGY & DEMO • Why KM will make people’s lives easier everyday. • Who can get this message across and how will they get this message across? • Where and when can we demo? PRIORITIZE TRANSITION SUPPORT • Too much effort dedicated to creating the “new thing.” Too little effort given to transitioning. • This is where/why 70% of change management initiatives fail. DOUBLE LOOP LEARNING • We need a mode of receiving feedback and reporting out what we did with the feedback. When building a Change Management Plan to support the implementation, adoption, and continuous training of your KM technology, it is important to consider these four components. Your Change Plan should also be designed to: Align with the strategic goals of the organization. Define measurable goals that can be tracked over time. Engage business users from the outset and maintain their engagement at every stage. @EKCONSULTING
  • 26. COMMUNICATIONS AND TRAINING PLAN C-SUITE EXECUTIVES & EXECUTIVE SPONSOR BUSINESS OWNER TECH LEAD END-USERS IDENTIFY KEY STAKEHOLDERS & USERS COMMUNICATIONS TRAINING @EKCONSULTING The truth is, no major technology investment is a turnkey solution. Planning, communication, and commitment are essential to organization-wide adoption. Components of Communications Plan: • Identification of Key Stakeholders and Users • Identification of KM Tool Champions • Document Key Information & Draft Supporting Communications • Initial Announcements • Major Implementation Milestones • Training Schedules • Requests for Feedback • Build a Timeline / Map Communications • Incentivize / Double Feedback Loop Prior to implementation, create a training plan that anticipates the needs and reactions of system users. Components of a Training Plan: • Identify all users and define each of their unique learning needs • Review/Identify a training budget • Design the training to include: • Business rationale • Explanation of how their participation/role will make themselves and the organization successful • Take a blended approach (classroom and on-the-job training) • Opportunities for feedback • “Test-drive” the training to “power-users” / KM Tool Champion Team • Deploy training • Provide informal and formal continuous learning opportunities
  • 27. WE’LL BE ANSWERING QUESTIONS NOW Q A& THANKS FOR LISTENING Q & A SESSION