Challenge 

Everyone wants learning that makes a difference. But too often, measurement shows up at the end—after delivery—when it’s hardest to see what changed, why it mattered, or what to do next.

This approach reframes learning measurement as a design choice, not a reporting requirement. When outcomes are defined early, teams can intentionally align learning experiences with confidence, behavior change, and business goals—before a single asset is built.

Solution 
The most effective learning measurement starts before learning begins. In practice, this means:

• Clarifying what success needs to look like up front
• Identifying which outcomes learning can realistically influence
• Choosing indicators that support course‑correction during delivery, not just evaluation after the fact

One practical approach is to plan measurement alongside the learning plan itself. Using tools like statements of work or design briefs, teams can align early on:

• Desired outcomes
• Signals of progress
• Roles and ownership for tracking and sustainment

This shared planning step creates clarity across learning designers, facilitators, and business partners—and reduces downstream rework.

Rather than adding evaluation at the end, measurement can be planned alongside design—using Kirkpatrick levels as a way to tell the story of progress from attendance → reaction → learning/confidence → behavior → results.

A key example was how the team measured confidence (as a predictor of behavior) at three points in time during the a recent learning project:

• Before learning (baseline)
• During learning (after self‑directed web‑based training, before practice)
• After learning (after facilitated hands‑on practice)

This made it possible to see real change over time and identify who might need additional support.

Key Decisions

A small number of early decisions have an outsized impact on learning measurement:

• Be explicit about ownership
  Learning teams help define success and indicators. Business partners own long‑term application and sustainment—with a clear handoff between roles.
• Design measurement into the work
  Measurement is most effective when it’s planned at the same time as the learning experience—not added later.
• Look for leading indicators
  Signals like learner confidence or readiness can predict behavior change well before business results are visible.
• Track progress, not just outcomes
  Comparing before, during, and after data helps teams understand momentum and learning progression.

Impact

When learning measurement is treated as part of the design process teams see meaningful shifts:

• Learner uncertainty surfaces earlier and can be addressed through iteration
• Learning experiences better support readiness and real‑world application
• Business partners gain clearer visibility into how learning contributes to outcomes
• Teams develop a shared language for discussing learning value and impact

Rather than slowing delivery, early measurement planning enables faster adjustment, stronger alignment, and more confident decision‑making.

For your next initiative, what’s one outcome you could define—and begin measuring—earlier to better align learning design with business results?

Challenge 

When implementing a new learning platform, it’s tempting to let a single team define the structure and roll it out across the organization. But what if the platform needs to serve diverse teams with different needs, frameworks, and terminology? How do you create a shared foundation that works for everyone without forcing teams into a one-size-fits-all approach?

During our AI-enable learning experience platform pilot, our operations Learning & Development team faced exactly this challenge. Six distinct user groups across the organization each had their own evaluation frameworks, skill definitions, and quality assessment approaches. The team needed to create a single skills taxonomy that could serve everyone while aligning with multiple existing organizational frameworks and criteria.

Without a collaborative approach, the result could have been a fragmented system with duplicate skills, inconsistent terminology, and siloed practices that limited the platform’s effectiveness and scalability.

 Solution 

Our work began by defining a “how might we?” guiding question: How might we collaborate cross-departmentally to grow our AI-enabled learning practice and create a universally applicable skills framework?

The L&D team took a deliberately collaborative approach, creating two interconnected initiatives that fostered honest assessment, creative idea-sharing, and diverse stakeholder input.

Our platform community of practice demonstrates how creating space for diverse perspectives and building upon each other’s ideas leads to stronger, more sustainable solutions. The collaborative skills taxonomy provides a holistic approach to skills development, supporting hands-on practice in a safe learning environment—a capability that benefits learners across all six participating teams.

Building a Collaborative Skills Taxonomy

I facilitated a comprehensive mapping effort to align our skills taxonomy with multiple organizational frameworks. Rather than choosing one framework or creating something entirely new, we:

1. Mapped existing frameworks: Documented how different teams’ evaluation criteria, speech analytics models, and quality assessments related to each other
2. Engaged diverse stakeholders: Reached out beyond pilot participants to include the Member Experience Office and Ops Business Intelligence team, ensuring the taxonomy reflected a wide range of expertise
3. Collaborated on universal language: Worked together to replace siloed, team-specific terminology with universally applicable skill terms

Through collaborative assessment and iterative refinement, the group consolidated overlapping concepts. For instance, three separate skill categories— “Care Gap Closure,” “Identifying/Addressing/Managing Care Gaps,” and “Identifying and Closing Care Gaps”—were combined into a single, clearer category: “Care Gap Resolution.”

The result is a three-tiered framework that serves all teams:

PARENT: Core competencies addressing customer needs (“I’m competent to meet customer needs for…”)
CHILD: Skill sets needed to meet core competencies (“Meeting expectations in these skills helps me progress towards core competencies”)
TASKS: Realistic, variable scenarios that can be tagged with multiple skills

Creating the Platform Community of Practice

Rather than dictating how teams should use our platform, the team established a cross-functional Community of Practice that brought together all six user groups.

I led our teams through a collaborative exercise to define the community’s foundation together:

• Purpose: A forum for cross-departmental collaboration, knowledge sharing, and innovation
• Participants: Admins, super admins, developers, and anyone creating content in or for Bright
• Value: Peer support, troubleshooting, sharing best practices, sparking new ideas, and providing diverse perspectives for constructive feedback
• Cadence: Quarterly meetings with a Teams channel for ongoing support and fast-track decisions when needed

The community actively builds upon each other’s ideas. For example, when the L&D team created test genAI conversations, a different program team took the concept further, improving the L&D team’s original genAI conversation templates with innovative ways to integrate scenario data. The L&D team is now adopting these enhanced practices, demonstrating how the community creates space for ideas to evolve.

The collaborative skills taxonomy is maintained through the community of practice, with color-coding showing which team requested each skill, ensuring transparency and shared ownership. The group reviews proposed changes collectively, documents decisions, and maintains flexibility for urgent updates between quarterly meetings.

Challenge

This project had a strong vision with dual aims, and a tight timeline. A data tool was under review and leadership was introducing a new investment coaching framework to support the tool. Learners were supervisors who need to both understand and practice the coaching framework and the tool before using it to support the customer experience team.  Because the tool was under review, quick deployment was essential; learners needed to understand and use these resources immediately and effectively, to enable accurate tool evaluation.

After collecting and reviewing project materials, we created a statement of work and met to get consensus on a guiding question and outcome goals: 

How might we introduce and sustain the investment coaching model in a meaningful and memorable way, in order to support effective tool evaluation?

• Create a learning plan that both introduces the framework and offers hands-on practice in a facilitated session
• Support supervisors to standardize coaching feedback for the CX team
• Enable supervisors to understand and practice the investment coaching framework

Process

Working collaboratively with nine cross-departmental stakeholders from VP to SME, we collaborated for consensus on project goals and deliverables. I led an empathy mapping session to identify learner needs, and a RACI session to identify and agree on project roles and responsibilities. I used an expanded collaborative project board to map the self-directed and hands-on facilitated sessions, learning plan, and sustainment work. We met for weekly stakeholder sessions to report progress and track approvals and I worked one-on-one with project stakeholders to refine content and keep the project on track.

I created a detailed learning plan collaborating with a training lead, managed learner testing, and supported an iterative process to refine learning materials, prototyping and refining as we progressed.

Key Decisions 

Using tools from design thinking, learning experience design, project management and change enablement, we made key team decisions to situate and sustain our work.

• Empathy-driven from concept through delivery – we used empathy mapping and created a feedback loop to understand and capture willingness and attitude shift before, during, and after training.
• Thoughtful scoping – starting with how might we’s and concluding with sustainment planning gives the team a holistic perspective and enables smooth transitions to ongoing work.
• Learning design + execution partnership – collaborating with training lead for complete solution package delivery, including implementation documentation and guidelines and support.
• Learning design + sustainment partnership – collaborating with experience and transformation lead to transition into sustainment as the team moves into decision-making for tool evaluation, adoption and long-term needs.

Impact 

We delivered a comprehensive learning plan, a self-directed learning experience in Workday with individualized content generation, four facilitated hands-on sessions, and a tool quick reference guide (PDF). We also delivered a Mural board presentation template, run-of-show template, and PowerPoint presentation template to support hands-on sessions. All materials aligned with a stakeholder-approved look and feel based on brand identity for cohesive, engaging learning experience.

Using rapid development practices and tools, we proceeded from concept to delivery in under 4 weeks.

Project impacts and insights include:

• The self-directed learning experience introduces the tool and scaffolds learning through direct experience, encouraging learners to gather questions and materials to support and personalize the hands-on practice session.
• Learner feedback shows improved tool confidence, with 64% of learners reporting they were not confident to use the tools before learning interventions; 93% identify as confident after learning.
• Working with an engaged, cross-departmental set of stakeholders including project sponsor gave the project traction to proceed at a rapid yet supported pace.

Challenge

When we’re focused on solving problems, it’s natural to rely on our own perspectives and assumptions about what stakeholders need. What if there was a simple way to step into a stakeholder’s or customer’s shoes and truly understand their world before diving into solutions?

It’s easy to overlook or assume the needs of our customers, our teams, and people who are grappling with change, because they are not always participants in our project meetings. One way to expand our problem-solving process is by using empathy maps. Empathy mapping asks us to gather observations and research about what stakeholders and members see, hear, think, feel, say, and do.

Empathy maps can also be a tool to invite responses to our problem statement, change or clarify our problem statement, and help us create a better “how might we?”.

Solution 

How might we use empathy to better understand stakeholder and member needs?

• Use a shared document or collaborate in person: Use the tools you have for optimal collaboration, including Mural or MS Whiteboard, PowerPoint, or real sticky notes in person.
• Consider and include all stakeholders: Mapping both stakeholders and members is helpful. You might create multiple empathy maps for each project.
• Gather input: What do our observations and research tell us about what stakeholders and members see, hear, think, feel, say,and do?
• Draw from observations and research: Use what you know, whether from direct observation or data from research.
• Use what you learn to inform your work: Analyze what the team gathers and assess it against the existing problem statement. Are we solving the right problem, based on what we know? How might we use this information to create a more targeted and effective solution?

Challenge

We need to imagine, build, and use AI tools for learning in ways that are sustainable for humans because information and work landscapes are changing. Companies are racing to implement AI tools and products; it can be difficult to prioritize and implement solutions where AI truly brings value. We can envision that roles and ways of working will shift dramatically as we embark on this rapid transformation.

As learning experience designers and leaders, we can create a focused space amid the disruption of change by leaning into our design-thinking approach, considering: 

How might we approach AI tools for learning in ways that are human-centered and supportive of learner success?

What is Human-Centered AI?

Human-centered AI (HCAI) refers to the development of artificial intelligence (AI) technologies that prioritize human needs, values, and capabilities at the core of their design and operation. 

Traditional AI emphasizes task automation for efficiency. In contrast to traditional AI, Human-Centered AI aims to augment human capabilities rather than replace them.
^{– Interaction Design Foundation}

Imagine a learning platform that uses AI to provide personalized learning recommendations. The platform, which we will call “LearnFast,” uses machine learning algorithms to analyze the learner’s behavior, such as course completion rates and assessment scores, to suggest relevant learning content. However, LearnFast doesn’t consider the learner’s goals or offer collaborative ways to learn; it simply provides a list of recommended courses without context or explanation.

Now, imagine a learning platform that uses AI to provide personalized learning pathways and coaching. This platform, which we will call “LearnGrow,” is designed with a human-centered approach to learning. When a learner interacts with LearnGrow, they have agency to set their own goals and objectives. The platform offers real-time feedback and coaching and encourages social learning and collaboration.

LearnFast is focused solely on providing automated learning recommendations, while LearnGrow’s human-centered AI takes a more holistic approach to the learner’s growth and development.

We can consider and apply HCAI design principles to support learner success during AI transformation. 

• Balance between Automation and Human Control 
• Empathy and Understanding the User
• Ethical Considerations and Bias Mitigation
• User Involvement in the Design Process
• Accessibility and Inclusivity
• Transparency and Explainability
• Continuous Feedback and Improvement

Ideas
Interested in working this way? Here are some tips and tools:

• Apply Human-centered AI (HCAI) design principles like empathy, bias mitigation, accessibility and inclusivity, continuous feedback, and transparency when creating design solutions
• Use a human-centered design thinking approach when developing solutions;empathize, ideate, design, prototype and test while defining problems and imagining “how might we?”
• Consider LX design approaches like empathy mapping, storytelling, and centering learner agency to better understand and support learner needs during AI design, transitions, and change
• Collaborate and share as we learn by connecting to discuss ideas, challenges, and solutions.

Gartner (2024, May 15). Case Study: Human-Centric Generative AI Strategy. https://www.gartner.com/document/5431263

Gartner (2024, June 25). Podcast: The Role of AI in a Human-Powered Enterprise. https://www.gartner.com/en/podcasts/thinkcast/the-role-of-ai-in-a-human-powered-enterprise

IBM Research (2022, March 31). What is Human-Centered AI?https://research.ibm.com/topics/human-centered-ai

Interaction Design Foundation – IxDF. (2024, January 11). What is Human-Centered AI (HCAI)?https://www.interaction-design.org/literature/topics/human-centered-ai

Resources

Who is talking about HCAI and where can I learn more? 

Empathy maps can also be a tool to invite responses to our problem statement, change or clarify our problem statement, and help us create a better “how might we?”.

Empathy mapping is a method that responds to the following “how might we?”: How might we use empathy to better understand learner and member needs, in order to create a more aligned design process and more inclusive design solution?

Solution 

Curious about working this way? Here are some tips and tools:

• Use a shared whiteboard: create in any shared whiteboard. 
• Consider and include all stakeholders: Mapping learners and members is helpful since they are not always present in our meetings, but it can also be useful to map all stakeholders.
• Gather input: What do our observations and research tell us about what learners or members say, think, do, and feel?
• Draw from observations and research: Use what you know, whether from direct observation or data from research.
• Use what you have learned to inform your work: Analyze what the team gathers and assess it against the existing problem statement. Are we solving the right problem, based on what we know? How might we use this information to create a more targeted and effective learning design?

Challenge

Designing learning experiences is a collective effort between learning experience (LX) designers and stakeholders, including subject matter experts (SMEs) and business partners. LX designers serve as project leads and learner advocates, but it can be challenging to create a solution that supports the learner while balancing business goals and stakeholder needs. It’s easy to get caught up in the development part of the design process, or not dig deep enough into stakeholder needs to correctly define the problem. Without continual feedback to refine and correct our assumptions, we run the risk of designing a solution that doesn’t truly align with learner or stakeholder needs.

Solution

Using a design thinking process offers a way to ground our work in empathy in order to better define the design problem, and follow a non-linear framework for ideation, prototyping, and testing that is rapid and flexible.

Curious about working this way? Here are some tips and tools:

• Start with empathy: LX designers are learner advocates. What do we know about the learner context and learner needs, and how can we balance the needs of all stakeholders, including business goals, during the design process? Our team uses empathy maps to build empathy that generates new perspectives.
• Use the power of convergent and divergent thinking: A design thinking process allows both convergent and divergent thinking, which increases creativity and is results-oriented.
• Create a learner-centered problem statement and build a compelling “How might we?”: The problem statement and “how might we?” are touchpoints we come to again and again as we ideate, prototype, and test. These ground our creative work and center it on actionable results.
• Be human-centered and keep learning: Using an empathetic, flexible, and iterative approach means we are continually challenging our assumptions and aligning our goals with the learner.

Resources 

What is design thinking?
https://www.interaction-design.org/literature/topics/design-thinking

Creating problem statements
https://www.interaction-design.org/literature/topics/problem-statements

As our project team was tackling a new learning experience design with a large amount of resources, an interesting question emerged: how might we collect and share project insights and information in a way that is more agile and visual than traditional storyboards, while building collaboration, trust, and consensus among stakeholders?

Solution 

Working with input from stakeholders and the design team, I created a collaborative storyboard template that is a hub for project details, content, and resources, shows project milestones, and includes collaborative team tools. 

Curious about working this way? Here are some tips and tools:

• Use a digital whiteboard: Our team is trained in human-centered design practices, so using a digital whiteboard page is a familiar way to collaborate and allows rapid changes to be made during team meetings. Our template was created in Mural, but could be created in any shared whiteboard. Design facilitators collect low-fidelity information for each section of the project and share with stakeholders at each check-in. Stakeholders can see the project develop in real time and can access the board between check-ins for a live project update, allowing for transparency and consensus.
  
• Include project details and links to all content: Make the page a project hub and one-stop shop for all project info.
  
• Include milestones: Create a visual indicator of milestone progress, so stakeholders can see where the project is at a glance. Note important dates and reference during check-ins.
  
• Use the space for rapid development: Work out what content is needed where, address questions as they come up, and move content easily and flexibly before beginning design in a learning authoring tool. Include wireframe tools like tagging with learning elements and blocking out for content flow. 
  
• Show progress: Mark sections as approved and begin designing in a learning authoring tool while other sections are still in review.
  
• Include design frameworks: list LX design frameworks for quick reference during stakeholder sessions.
  
• Include empathy and teambuilding tools: create collaborative empathy maps and a space to get consensus on roles and responsibilities.

Proud to share that I am a certified practitioner of Human-Centered Design.

The work we did in the LUMA program solidified my human-centered and co-design toolsets, enriching my ability to help my team identify the right problems and design solutions that people want and need. 

A company-wide commitment to human-centered approaches is effective because it encourages a collaborative way of working beyond specified design roles. Our design team and internal clients are building a common language for creative problem-solving that is already leading to faster, better collaboration with visible results. 

Grateful to be doing this work and looking forward to continuing to build my learner research and participatory design skills.