Figure out if ELE is for you. Straight answers on what ELE is, who it’s built for, and how contributing members actually work together. Still have a question? Contact us.

Alter Domus

HumanSide

Session Focus: Build on a  3-step AI workflow model presented by<a href="https://www.ele.llc/members/julia-meyer"> Julia Meyer</a> and <a href="https://www.ele.llc/members/rebecca-benson">Becca Benson</a> at our October 2025 conference by validating the underlying business problem with human context and committing to practical next steps that stick.
This hands-on AI Practical Lab builds directly on last month’s AI workflow challenge, shifting the focus from generating better outputs to ensuring we’re solving the right problem—before accelerating with AI.
Using the same challenge from last month’s <a href="https://www.ele.llc/insights/ai-practical-lab-ai-powered-workflows" target="_blank" rel="noopener">✨ AI Practical Lab: AI-Powered Workflows</a>, talent learners in this lab will refine the 3-step model, surface root causes, and apply ELE’s Four-Step Model to clarify why a problem exists—and what action is truly worth committing to. The emphasis is on human judgment, shared context, and practical decision-making so AI-enabled work translates into outcomes that actually stick.
This lab introduces ELE’s Four-Step Model as a practical way to move from clarity to commitment—keeping humans at the center of AI-enabled work.
<img class="aligncenter wp-image-44484" src="https://wp.ele.llc/wp-content/uploads/2025/12/Four-Step-Model-for-AI-Workflows-ELE-4-Cs.jpg" alt="ELE's 4 C Model for AI Workflows" width="900" height="506" />
&nbsp;
<blockquote>"AI gives us amazing options, but I need to see the big picture. How is this actually moving the needle for the business?" -- <a href="https://www.ele.llc/members/keri-kersten" target="_blank" rel="noopener">Keri Kersten</a></blockquote>
This discussion offered a timely reminder: most capability gaps don’t start with a learning problem—they start with a clarity problem.
As <a href="https://www.ele.llc/members/nicole-defalco" target="_blank" rel="noopener">Nicole DeFalco</a> put it,

<blockquote data-path-to-node="3,0,1">
"Clients don’t come to us with problems—they come to us with solutions wrapped in assumptions."
</blockquote>
That framing resonated because it reflects the daily reality talent leaders face. We’re often handed a fully formed request—train this, roll that out, scale it fast—and rewarded for speed, not scrutiny. But when we rush to deliver, we risk solving the wrong problem beautifully.
The most powerful moments came from slowing down and asking harder questions:

<ul data-start="873" data-end="1111">
 	<li data-start="873" data-end="917">
What business outcome is actually off?
</li>
 	<li data-start="918" data-end="1030">
What evidence says this is a skills issue—and not incentives, workload, role design, or market conditions?
</li>
 	<li data-start="1031" data-end="1111">
What would people need to do differently in real work for results to change?
</li>
</ul>
That shift—from order-taker to problem framer—is where team capability actually starts.
Another insight landed hard: training can’t compensate for an environment that discourages the very behaviors we’re trying to build. If KPIs, job design, time pressure, or incentives pull people in the opposite direction, no amount of content will stick. Capability has to be designed into the work itself.
The group also challenged the instinct to “train everyone.” Instead, the conversation moved toward targeted pilots with high-impact cohorts—designing with the people closest to the outcome, learning fast, and scaling only once behavior change is visible. That’s not slower; it’s smarter.
AI showed up not as a content engine, but as a thinking partner—helping leaders rehearse stakeholder conversations, pressure-test assumptions, and surface blind spots before committing resources. Used this way, AI didn’t replace judgment; it sharpened it.
And as <a href="https://www.ele.llc/members/angelica-janina-stilling" target="_blank" rel="noopener">Angelica Stilling</a> summed up succinctly,

<blockquote data-path-to-node="3,0,1">
"Clients don’t come to us with problems—they come to us with solutions wrapped in assumptions."
</blockquote>
That line captured the discipline required of leaders right now—not more activity, not faster delivery, but clearer thinking.
For talent leaders, the takeaway is straightforward but demanding: Building team capability isn’t about delivering better learning. It’s about designing the conditions where learning shows up as different decisions, actions, and results.
If your team is busy building programs but struggling to move the needle, the most impactful move may be to pause—and ask better questions before you build anything at all.
&nbsp;

&nbsp;

&nbsp;

✨ AI Practical Lab: Humans Solving the Right Problem — ELE’s Four-Step Model

learning strategy

Digital &amp; AI

tracey.wik

performance improvement

mike.kester

edward.desrosiers

leadership development

anton.maletich

marty.murrillo

Performance Improvement

diana.anderson

ai practical lab

Workforce Transformation

future ready teams

nicole.defalco

angelica.janina.stilling

Behavior Change

capability building

Strategic L&amp;D

AI-enabled learning

1Q2026

organizational performance

dustin.brewer

human-centered learning

amy.p.wilkins

team capability

learning in the flow of work

talent experience design

trusted advisor mindset

problem framing

AI as thought partner

confidence capability clarity

design thinking for talent

evidence-based learning

This AI practical lab provided a crucial blueprint for Talent and L&amp;D leaders looking to move past simple AI experimentation and toward disciplined, enterprise-grade workflows. The core theme was this: Generative AI is not a strategy replacement, but a force multiplier that radically redefines team capacity. The lab demonstrated a focused, three-step AI workflow model presented by<a href="https://www.ele.llc/members/julia-meyer"> Julia Meyer</a> and <a href="https://www.ele.llc/members/rebecca-benson">Becca Benson</a> at our October 2025 conference—Clarify, Create, Customize—which ensures human expertise remains in the critical stages of problem definition and cultural refinement. The implication is profound: AI promises to unlock unprecedented productivity, allowing HR to finally operate at the speed of the business, provided leaders enforce a "human-in-the-loop" quality standard.

<img class="aligncenter size-full wp-image-44448" src="https://wp.ele.llc/wp-content/uploads/2025/03/Three-Step-Model-for-AI-Workflows-ELE.jpg" alt="Three-Steap Model for AI Workflows (ELE)" width="690" height="356" />

👂ELE’s POV: Ed gets into the core tension: Is the accelerated adoption of GenAI in L&amp;D a necessary breakthrough for speed—or a reckless path that risks bypassing trust?

<audio controls="controls" data-mce-fragment="1"></audio>
<h3 data-path-to-node="2">Key Takeaways for Senior HR Leaders</h3>
<ul data-path-to-node="3">
 	<li>
The 10x Capacity Shift is Real: The most striking finding was the demonstrable power of an AI-augmented team. As <a href="https://www.ele.llc/members/edward-desrosiers" target="_blank" rel="noopener">Ed DesRosiers</a> revealed during the lab’s case study:

<blockquote data-path-to-node="3,0,1">
"With AI, our team of two created 10 times the deliverables of an 8-person team working the traditional way." This forces a re-evaluation of current capacity plans and resource allocation.
</blockquote>
</li>
 	<li>
AI Demands Higher-Level Thinking: AI elevates your team from producers to strategic partners. As <a href="https://www.ele.llc/members/marty-murrillo" target="_blank" rel="noopener">Marty Murrillo</a> stated:

<blockquote data-path-to-node="3,1,1">
"AI amplifies you, it doesn't replace you. You are the thought leader; AI is simply your thought partner." The focus shifts entirely to defining strategy and ensuring quality.
</blockquote>
</li>
 	<li>
Strategy Must Precede Speed: The "Clarify" step of the 3C model is non-negotiable. You must define the audience, challenge, and success metrics before generating content to avoid creating high-volume noise.
</li>
</ul>
<h3 data-path-to-node="4">Practical Actions to Take Immediately</h3>
<ul data-path-to-node="5">
 	<li>
Mandate the "Customize" Quality Gate: Stop content from going to the client or employee without a human refining the tone, ensuring cultural fit, and applying nuance.
</li>
 	<li>
Challenge "Solutioneering": Before a team asks an AI tool to "Create" a solution, demand proof that they completed the strategic diagnosis. If they can’t articulate the business need, halt production.

<blockquote data-path-to-node="5,1,1">
"AI gives us amazing options, but I need to see the big picture. How is this actually moving the needle for the business?" -- <a href="https://www.ele.llc/members/keri-kersten" target="_blank" rel="noopener">Keri Kersten</a>
</blockquote>
</li>
 	<li>
Invest in an AI Stack, Not Just a Single Tool: Audit your tool ecosystem (e.g., NotebookLM for research, Copilot for drafting, Canva for design) to ensure it supports the entire Clarify-Create-Customize workflow seamlessly.
</li>
</ul>
The era of the AI-powered workflow demands a new kind of leadership—one that is disciplined, strategic, and focused on impact. By implementing the "Clarify, Create, Customize" structure, you can harness the staggering productivity gains of generative AI while ensuring your Talent and L&amp;D functions remain grounded in human-centered design and strategic business alignment. This isn't about working harder; it’s about leading smarter.
The urgency of this evolution is echoed by other experts; as <a href="https://www.ele.llc/members/michael-vaughan" target="_blank" rel="noopener">Mike Vaughan</a> recently argued on LinkedIn, <a href="https://www.linkedin.com/posts/michaelsvaughan_ai-wont-help-ld-unless-we-let-go-of-what-share-7404581161945214976-b3-P?utm_source=share&amp;utm_medium=member_android&amp;rcm=ACoAAAAyK2cBgiwsMpK9fDqZM0mahKsHVCHm_Y8" target="_blank" rel="noopener">AI Won't Help L&amp;D Unless We Let Go of What Got Us Here.</a>
Let's continue this conversation on the ELE <a href="https://www.ele.llc/idea-exchange" target="_blank" rel="noopener">Idea Exchange</a> and share the non-negotiable quality controls you're putting in place for AI-generated content!

✨ AI Practical Lab: AI-Powered Workflows

future of work

leadership

digital transformation

upskilling

talent development

colin.hahn

keri.kersten

Adding Value

wendi.barlow

employee experience

guillermo.gutierrez

organizational development

learning trends

ChatGPT

AI tools

HR future

AI in HR

GenAI

Workforce Strategy

generative AI

talent-talk

agile HR

Human Resources

HR Tech

susan.c.guest

owen.burns

4Q2025

CHRO

L&amp;D strategy

roberto.seif

AI in L&amp;D

mike.hoyt

AI workflows

capacity building

human in the loop

LAK Group

Human Synergistics

Session Focus: <a href="https://www.ele.llc/members/angie-zeigler">Angie Zeigler</a> will build on the foundation of the Chicago keynote to explore in greater depth why values often fail to translate into behavior. She will lead a peer discussion on identifying the cultural forces that quietly accelerate or undermine performance.
For talent leaders, the biggest culture risk isn’t unclear values—it’s the widening gap between the values on the wall and the behaviors employees experience every day.
In this follow-up live discussion, Angie Zeigler, head of culture practice with LAK Group, builds on the Human Synergistics keynote to explore why well-intentioned values initiatives stall—and what actually drives culture change at scale. Drawing on decades of research and real organizational data, Angie shares practical stories of how organizations that prioritize and reward specific, constructive behaviors are significantly more successful in closing the engagement gap.
This discussion is designed for leaders who want to move beyond culture statements and into the real work of aligning values, behaviors, and results.
Human Synergistics' research makes visible what most leaders sense—but struggle to diagnose.
<img class="aligncenter size-full wp-image-44495" src="https://wp.ele.llc/wp-content/uploads/2025/11/CHIE2025-Kern-Keynote-80-vs-25-percent-slide.jpg" alt="Michael Kern presenting a slide showing a contrast between “&gt;80%” and “&lt;25%” to illustrate gaps between stated values and lived behaviors." width="1920" height="1133" />
What this data reveals is uncomfortable—but actionable. Most organizations believe they are values-driven, yet fewer than a quarter consistently experience those values in daily work. That gap isn’t cultural “noise”—it’s a performance signal.
In this discussion, leaders will examine how everyday behaviors, systems, and incentives quietly reinforce—or undermine—the culture they say they want, and where small, targeted shifts can create outsized impact.
Who Should Join
This discussion is designed for leaders responsible for shaping culture, performance, and behavior at scale—across HR, talent, learning, and the business. If you’re wrestling with gaps between stated values and what actually gets rewarded, or trying to understand which behaviors accelerate performance—and which quietly undermine it—you’ll be in good company.

How This Works
Each discussion runs for 50 minutes and blends a short framing insight with open, peer-driven exchange.
There are no slides to sit through and no pitches—just focused conversation designed to surface what’s working, what’s not, and what leaders are trying next as culture and performance collide in real organizations.

Join the ELE Conversation
These every-other-Friday discussions are part of ELE’s ongoing peer exchange for leaders shaping talent and work in the AI era. Come ready to listen, contribute, and learn alongside peers testing ideas in real organizations and sharing what they’re learning.
Recordings are posted to <a href="https://www.ele.llc/insights">ELE Insights</a> within 2–4 business days.

From Values to Behavior: Navigating Superheroes and Saboteurs

single-event

Your Teams

Learning Circles

innovation

angie.zeigler

Complimentary

online event

complimentary event

Culture Change

employee engagement

collaboration

accountability

Engagement &amp; Culture

continuous learning

reskilling

L&amp;D

matt.sernaker

organizational culture

HR leaders

Strategic HR

workplace adaptation

knowledge sharing

Culture Transformation

Values Alignment

actionable insights

practical strategies

employee trust

practical insights

leadership behavior

cindy.pinkstaffmiller

cathleen.cooke

performance culture

cultural diagnostic data

targeted intervention

organizational systems

HR processes

culture risk

culture reality check

AI and learning

AI reskilling

reframing hr

ELE Group, LLC

Journyz

This innovation sprint kickoff provided a powerful launch to ELE’s new Executive Innovation Sprint model — a peer-powered framework for co-creating solutions that matter.

<blockquote data-start="576" data-end="660">
“When senior leaders co-create across industries, they don’t just solve problems — they build the muscles of agile leadership together.” — <a href="https://www.ele.llc/members/dirk-tussing" target="_blank" rel="noopener">Dirk Tussing</a>
</blockquote>
The sprint kicked off with an important exercise: defining the precise area of opportunity in high-performance coaching where AI could deliver the most value.
During this kick-off on Zoom, two problems were identified as a potential opportunity to experiment:
<ol>
 	<li>Post-Training Coaching</li>
 	<li>Job Performance Coaching</li>
</ol>
For this kick-off sprint, the group voted and ELE would like to dive deeper into using AI to improve Post-Training Coaching.

To deeply understand the chosen challenge, two separate breakout groups then developed detailed problem definitions, which solidified the scope of the sprint.

<a href="https://www.ele.llc/members/cindy-pinkstaffmiller" target="_blank" rel="noopener">Cindy Miller</a>’s Breakout Room’s Problem Definition Post-Training Coaching
In our current environment, post-training coaching is not happening. As evidenced by XYZ, we face the impact of behavior change not occurring and a low ROI on training. The lack of post-training coaching is due to several potential root causes: managers do not know their employees are attending training, managers do not know what is being taught in the training, there is no set expectation around post-training coaching, managers do not know what to coach, managers do not know what good coaching looks like, or managers do not know how to do the behaviors themselves—so they feel unable to provide feedback or coaching. Therefore, we have the opportunity to provide context to managers about what is being taught in training and to provide examples of what to coach on post training, among other support.

<a href="https://www.ele.llc/members/matthew-eade" target="_blank" rel="noopener">Matthew Eade</a>’s Breakout Room’s Problem Definition Post-Training Coaching
In our current environment, post-learning coaching is inconsistent and heavily dependent on manager availability, as evidenced by engagement surveys, customer feedback KPIs, and high turnover rates. The impact is that employees—especially new hires in large, distributed teams and healthcare environments—struggle to apply newly acquired skills, leading to lower performance and missed opportunities for growth. The root cause is limited manager bandwidth and conflicting priorities, which prevent on-the-job feedback and support. Therefore, there is an opportunity to explore scalable, context-driven solutions—such as AI-powered coaching tools—that can provide real-time, personalized feedback and bridge the coaching gap when managers are unavailable..

<hr data-start="1738" data-end="1741" />
At the October 20th Talent Development Conference, this idea took root. The spirit of agility came alive at the October 31st virtual event, which provided a powerful launch to ELE’s new Executive Innovation Sprint model — a peer-powered experience designed to help leaders practice innovation, not just talk about it.
In true ELE fashion, this first sprint brought together senior leaders from across industries to tackle a shared challenge. After thoughtful discussion and a live vote, the group narrowed the focus from Performance Coaching to Post-Learning Coaching—exploring how AI can make feedback continuous, scalable, and deeply human.
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<div class="markdown prose w-full break-words dark:prose-invert light"><img class="aligncenter wp-image-43834" src="https://wp.ele.llc/wp-content/uploads/2025/03/ELE-Solutions-Biggest-Impact-Slide-2.jpg" alt="SOLUTION EXCHANGE | Biggest impact on the most people" width="834" height="433" /></div>
</div>
</div>
</div>
<div>
<h3>Defining the Challenge: Post-Learning Coaching</h3>
The first sprint tackled the performance gap that happens after learning: why employees so rarely apply what they’ve learned once the workshop ends.
<blockquote data-start="1055" data-end="1135">
“Define the problem well, or the solution won’t be usable.” — <a href="https://www.ele.llc/members/deepa-kartha" target="_blank" rel="noopener">Deepa Kartha</a>
</blockquote>
Using a defendable-problem framework, participants surfaced a shared reality:
<ul>
 	<li>Post-learning coaching is inconsistent and depends too much on manager availability.</li>
 	<li>Limited time and unclear expectations erode follow-through.</li>
 	<li>The opportunity? Use AI to extend coaching capacity and deliver personalized, real-time feedback when managers can’t.</li>
</ul>
<blockquote data-start="1493" data-end="1582">
“Learning ROI is lost when post-learning coaching doesn’t happen.” — <a href="https://www.ele.llc/members/nicole-defalco" target="_blank" rel="noopener">Nicole DeFalco</a>
</blockquote>
The conversation reframed AI as a performance enabler, not a threat — a way to make feedback timely, scalable, and rooted in real behavior change.


<hr data-start="1738" data-end="1741" />

<h3 data-start="1743" data-end="1798">🔍 Key Takeaways for Talent Development Leaders</h3>
<ul>
 	<li>Innovation is a leadership skill. Sprints enable leaders to practice agility by solving real problems together across various industries.</li>
 	<li>AI amplifies and scales coaching. Viewed as a performance enabler, AI helps make feedback timely and human.</li>
 	<li>Post-learning coaching drives results. Training builds knowledge; coaching ensures it sticks and delivers impact.</li>
 	<li>Short sprints, faster progress. In 2–3 weeks, executives design, test, and refine solutions that scale.</li>
 	<li>Insights become playbooks. Each sprint’s results feed the <a href="https://www.ele.llc/idea-exchange" target="_blank" rel="noopener">ELE Idea Exchange</a>—where members share, adapt, and apply what works.</li>
 	<li style="list-style-type: none;"></li>
</ul>

<hr data-start="2430" data-end="2433" />

<h3 data-start="2435" data-end="2476">⚙️ Practical Actions to Apply Now</h3>
<ol data-start="2478" data-end="3066">
 	<li data-start="2478" data-end="2611">
Run a 2–3 week mini-sprint inside your organization to tackle a specific challenge like improving post-learning application.
</li>
 	<li data-start="2612" data-end="2718">
Audit your feedback flow. Identify where and why coaching stops between training and performance.
</li>
 	<li data-start="2719" data-end="2834">
Pilot AI coaching tools. Test digital nudges or conversational AI to provide scalable, real-time feedback.
</li>
 	<li data-start="2835" data-end="2943">
Measure what matters. Track engagement and behavior change before and after coaching interventions.
</li>
 	<li data-start="2944" data-end="3066">
Capture and share learnings. Document insights to strengthen your organization’s innovation and coaching culture.
</li>
</ol>
</div>
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🔁 <a href="https://docs.google.com/presentation/d/1qFs__kIJsCLH6ynAeNopOsz6PHEpub9ntpAmvuJt588/edit?mc_cid=e7686c688f&amp;mc_eid=621cbc8540&amp;slide=id.p1#slide=id.p1" target="_blank" rel="noopener noreferrer">ELE Solution Exchange Overview</a>

<img class="aligncenter wp-image-43751" src="https://wp.ele.llc/wp-content/uploads/2025/08/S1-High-Performance-Coaching-with-AI.jpg" alt="🔄 ELE Solution Exchange: High-Performance Coaching with AI" width="834" height="433" />

</div>
</div>
</div>
</div>
</div>
</div>
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The High-Performance Coaching with AI innovation sprint reminded us that technology doesn’t replace leaders — it amplifies them.

When we define problems clearly, collaborate across boundaries, and use AI to make coaching continuous, learning becomes performance. The next phase will be a 2–3 week experiment centered on AI-supported Post-Learning Coaching, testing how scalable, data-driven feedback can accelerate learning transfer and performance.

As these sprints unfold, insights, toolkits, and outcomes will be shared on the <a href="https://www.ele.llc/idea-exchange" target="_blank" rel="noopener">ELE Idea Exchange</a>—so every member can learn, adapt, and apply what works inside their own organization. Because at ELE, innovation isn’t theory — it’s a shared practice that turns insight into action.

</div>
</div>
</div>
</div>
</div>

Kick-off: ELE Innovation Sprints | High-Performance Coaching with AI

design thinking

dirk.tussing

newton.moore

matthew.eade

Coaching

matt.donovan

audrey..hackley

L&amp;D innovation

scott.tang

lauren.marder

Coaching Culture

AI Coaching

learning impact

deepa.kartha

ali.glaser

executive innovation sprint

post-learning coaching

learning transfer

peer co-creation

talent development leaders

human and AI collaboration

learning roi

continuous experimentation

scalable feedback

digital transformation in learning

data-driven coaching

Skillsoft

EmpathAI Learning Solutions

The modern corporate reality is simple: your employees are drowning in a sea of training options, yet starving for clarity and direction. The sheer volume of content, much of it irrelevant, actively slows down enterprise agility and wastes talent investment.

In this highly interactive session, leaders from Skillsoft and Empath.AI Learning Solutions tackled the chaos head-on, sharing a practical framework for designing smarter, simplified learning ecosystems that accelerate workforce readiness. The core challenge is clarifying what's "must-have" vs. "build-your-skillset" to create clear career momentum.
<h3>Key Takeaways for Talent Leaders:</h3>
<ul>
 	<li>The Clarity Framework: Attendees rolled up their sleeves to co-create practical career and skill maps for key enterprise roles. The key learning was how to ruthlessly filter content to define the essential path (mandatory knowledge) and separate it from the growth path (optional, personalized skill-building).</li>
 	<li>AI as the Simplicity Engine: The session explored how adaptive learning and AI-driven personalization are the primary tools for simplification. Instead of managing a large course catalog, L&amp;D can leverage AI to instantly curate content that is relevant at the moment of need, ensuring employees get guidance, not just more options.</li>
 	<li>The Plug-and-Play Template: Participants walked away with a tangible, plug-and-play template to immediately streamline development paths in their organizations. This template is the blueprint for moving away from generic content assignments toward a skills-based ecosystem designed to scale and evolve with emerging business needs.</li>
</ul>
This session proved that effective, modern L&amp;D is defined not by how much content you have, but by how skillfully you simplify the path for your people, directly fueling enterprise agility.

Simplifying Training | Designing Smarter Learning Ecosystems for Enterprise Agility

Integrated Talent Management

workforce readiness

future of learning

adaptive learning

CHIE2025

yolanda.mangram

skills-based learning

HR Technology

Learning Ecosystems

heber.sambucetti

integrated talent

enterprise agility

AI personalization

skill maps

plug and play template

career momentum

talent investment

clarity framework

content curation

operational simplicity

insightsoftware

Upsurge Advisors

Goal: In this 45-minute breakout session, participants will utilize The L&amp;D Detective Kit as their primary source of truth for frameworks and tools, exploring how AI-enabled methods can help talent leaders become detectives of impact rather than order-takers for training. Together, we’ll apply the Detective questions to real business scenarios, draft a Performance Impact Blueprint, and reflect on how AI and human insight combine to measure what matters most.

🔁 <a href="https://docs.google.com/presentation/d/1qFs__kIJsCLH6ynAeNopOsz6PHEpub9ntpAmvuJt588/edit?mc_cid=e7686c688f&amp;mc_eid=621cbc8540&amp;slide=id.p1#slide=id.p1" target="_blank" rel="noopener noreferrer">ELE Executive Innovation Sprints Proposal</a>

🔄 ELE Executive Innovation Sprint: L&D Detective Kit | For Measuring Real Impact

Analytics

laura.jones

Talent Strategy

performance impact

Data-Driven L&amp;D

practical frameworks

L&amp;D impact

measuring performance

AI enabled methods

business scenarios

L&amp;D analytics

human insight

performance measurement

Froedtert ThedaCare Health

Goal: In this 45-minute breakout, participants will experience a taste of the ELE Work/Life Blueprint and reflect on how design thinking can make reskilling personal, scalable, and business-aligned.

Every HR leader knows reskilling at scale is an enterprise priority—but traditional, one-size-fits-all approaches rarely deliver impact. The Work/Life Exchange Blueprint introduces a five-step, design-thinking framework that makes reskilling personal, practical, and scalable:

1️⃣ Discover — map where energy, skills, and growth opportunities intersect.

2️⃣ Design — generate multiple “what’s next” scenarios, short- and long-term.

3️⃣ Prototype — test small, low-risk skill applications that generate real data.

4️⃣ Exchange — share insights, borrow ideas, and refine through peer feedback.

5️⃣ Blueprint — tell your story, build your support team, and co-create a living plan (not a static PDP).

Grounded in design-thinking principles from Designing Your Work Life by Bill Burnett and Dave Evans, this ELE-built model simplifies reskilling at scale by moving from HR-led programs to frontline-owned growth — turning learning into impact.

📚 Related Reading: <a href="https://www.ele.llc/members/bookshelf/designing-your-work-life" target="_blank" rel="noopener noreferrer">Designing Your Work Life on ELE’s Bookshelf</a>

🔁 <a href="https://docs.google.com/presentation/d/1qFs__kIJsCLH6ynAeNopOsz6PHEpub9ntpAmvuJt588/edit?mc_cid=e7686c688f&amp;mc_eid=621cbc8540&amp;slide=id.p1#slide=id.p1" target="_blank" rel="noopener noreferrer">ELE Executive Innovation Sprints Proposal</a>

What’s Next: Following this initial ideation, on <a href="https://www.ele.llc/events/reskilling-128" target="_blank" rel="noopener noreferrer">November 14th we’ll host a virtual exchange to refine business requirements</a> before recruiting 4–6 members for our first Solution Sprint.

🔄 ELE Executive Innovation Sprint: Simplifying Reskilling/Upskilling to Scale | Turning Upskilling into Impact

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