1. AI-generated content
2. Customized feedback and coaching moments
3. Surveys, data, and debrief conversations

1. AI-Generated Content

Let’s start with multi-modal learning content generation. We’re exploring ways that you can use AI to help generate content or use your existing documents or Sharable Content Object Reference Model (SCORM) files as the starting point. From there, it can be quickly transformed into learning resources of any length or format. You can edit the content produced, with multimedia options for text, images, graphics, and videos—or even slides.

This is an easy way to keep fit-for-purpose learning content engaging, diverse, and always relevant. And it’s one we plan to launch in early 2026.

2. Customized Feedback and Coaching Moments

Degreed Maestro is about more than conversations with AI. It’s about creating high-impact, comprehensive learning experiences. To do that, we’re exploring multi-step AI experiences that combine multiple formats to provide the learner with opportunities for improvement, such as customized feedback or mini coaching moments.

For example, after practicing a sales call with Maestro, it would provide scores and feedback based on my performance, showing me what I did well and what I need to improve. It would also provide mini coaching moments or a chance to replay and practice the specific things I need to work on. 

3. Surveys, Data, and Debrief Conversations

We’re also excited about a new way to use Maestro through natural, AI-powered debrief conversations. These encounters can drive learning and reflection while surfacing valuable insights along the way. 

Instead of formal surveys that produce fatigue and rushed, incomplete answers, Maestro can weave smart questions into everyday conversations or draw insights from existing ones with no extra effort required. In these settings, people tend to share more openly and in greater depth than they would in a traditional survey, especially when they know their responses can remain confidential. 

In one example, we asked employees how they’re using AI in their roles via a quick conversation with Maestro. Maestro gathered the responses and created a live dashboard to aggregate the results. From there, we could even chat with it about the data to explore further trends. 

This approach makes it straightforward to establish a baseline understanding of an individual employee’s skills, needs, and experiences, to then tailor learning to individual needs. The measurement of impact available afterward uncovers a depth and richness of insight that’s simply out of reach with traditional methods. It’s real-time understanding that was previously invisible. 

Stay Updated

Imagine what you could achieve with that level of clarity about employees, their needs, and the impact of your learning programs. We’d love your feedback as we keep exploring, so follow me on LinkedIn or sign up for our AI Experiments Lab newsletter to stay updated on our latest tests.

The post AI-Generated Content, Coaching, and Interactive Data appeared first on Degreed.

Completion rates prove it got done, and compliments prove employee satisfaction, but they don’t prove learning effectiveness. Execs want tangible evidence that the investment paid off. You need to show that people retained the information and are ready to use it on the job. And if it didn’t work, you need to identify where more learning is needed. 

So, what’s the answer? Test it.

Quizzes, a new experience within Degreed Maestro, enable you to quickly create and deploy AI-generated quizzes to ensure knowledge retention and measure learning effectiveness. So, next time your execs ask if it worked, you have relevant data to support your answer.

The Old Way: Manual Quiz Creation

Seeing the value of quizzes? Easy. Executing them manually, accurately, and at scale? Difficult.

Creating and deploying quizzes at scale is traditionally manual and incredibly time-consuming. It often requires extensive input from busy subject matter experts (SMEs) to draft questions, which is an inefficient use of their high-value expertise and often delays deployment. 

Reliance on manual creation and SME availability makes it difficult to scale and maintain up-to-date quizzes. This is more true now than ever, given that the skills and knowledge employees need are constantly changing. 

The New Way: AI-Generated Quizzes

With Maestro quizzes, admins can create quizzes in minutes, drastically reducing the time and effort spent. Through a text-based conversation with Maestro, you can guide Maestro to create a custom quiz on any topic and adjust parameters, like the number of questions and difficulty level. It can also create quiz questions based on existing documentation. This is a simpler way to harness the knowledge of SMEs without having to involve them in manual question generation. 

After employees finish the quiz, in-app reports enable admins to gauge their level of knowledge retention. These reports help identify consistently incorrect answers and, therefore, knowledge gaps where more learning is needed.

The quizzes are directly connected to the Degreed platform, allowing you to manage workflows like assigning quizzes or reporting on results. That makes it easy to identify where more learning is required so you can create more effective experiences that close knowledge gaps, learning more across the business.

Create Business Value

Real-world Applications for Quizzes

Example: Preparing for a Product Launch

During a new product launch, your revenue teams are inundated with information: value props, product functionality, go-to-market strategies. It’s a lot to take in, and it’s difficult to gauge whether your people are ready. 

With Maestro quizzes, you can evaluate whether your people have a grasp on key components of your new product. You can even create different quizzes for different audiences, since the information your sales team needs to remember is different from what your implementation team needs to know. By using existing documentation, you can generate quizzes focused on these different audiences within minutes. 

Example: Checking Long-Term knowledge Retention for AI Transformation 

Many organizations have ambitious targets for adopting AI in the business. This knowledge likely doesn’t exist at scale within the business, so organizations need extensive training and upskilling. By embedding a quiz at the beginning and at the end of a pathway, you can measure how much the workforce learned about implementing AI, so you can tie learning back to strategic business initiatives.  

Example: New Customer Onboarding Process

Quizzes can reinforce process and procedure updates. If you’ve launched a new customer onboarding procedure, employees need to remember the correct process, what to do, and what not to do. You’ll have visibility into their readiness and procedural sticking points that may require extra training.

Quizzes As Part of a Larger Learning Journey

Quizzes are powerful by themselves, but are enhanced when combined with other learning initiatives, such as pathways or academies. By including quizzes at the end of these experiences, you can evaluate the effectiveness of those programs and identify where they may need new or different content. 

Embedding quizzes inside Degreed also improves the learner experience, providing a UI that is consistent across experiences. And it helps you consolidate tech, reducing cost and administrative load with fewer platforms to maintain.

The post Create AI-Generated Quizzes to Measure Learning Effectiveness appeared first on Degreed.

Instead, that skill-building depends on context. AI needs information like:

• Who’s the learner and what is their skill level?
• What does “ready” look like for their role?
• What are the foundations of learning science and how are they applied in this situation?

MCP (Model Context Protocol) brings that context and relevancy.

Think of it like this: You could use an old school map without a GPS. But it’s more difficult and less personalized to where you are. 

Think of MCP as the GPS for AI learning. 

Instead of adding “AI features” into a portal, MCP simplifies integrations, giving AI access to information in other tools and databases and providing a consistent, governed way to tap into the right context from Degreed and connected systems—wherever those AI models live, whatever platform they’re built on. In the GPS analogy, this allows for real time rerouting to avoid traffic, recommendations of nearby attractions, and overall route intelligence. 

Through the MCP interface, AI has access  to broader contextual information to provide more targeted, personalized learning in real time.

With MCP, AI can move from generating content to providing learning context that helps drive capability, so that employees and businesses can develop and apply new skills more quickly.

What Is MCP? What Role Does It Play in Learning?

MCP, is the connective layer inside Degreed, built to make AI learning assistants truly useful at building capabilities. It gives any approved AI agent—like ChatGPT, Claude, Copilot, or an internal assistant—a governed, real-time snapshot of what matters for learning and performance, including:

• The learner’s skills, goals, and role
• Historical learning and skill data from Degreed 

Think of Degreed MCP as a “context envelope.” With that envelope in place, AI becomes a much more accurate support in the learning process. It can analyze all data related to the employee to provide the right learning at the right time.

How MCP Works in the Flow of Learning

On Tuesday morning, a sales manager opens Copilot and types: “Help my team get ready for Friday’s product pitch.”

Without MCP…

Copilot can find sales decks, playbooks, and pitch documentation, but it can’t tell who’s presenting, what skills they are missing, or how to help them improve.

With MCP…

Degreed and Maestro to bring missing context into view: who’s on the team, what each person already knows, and where they need coaching to tune up their skills.

Together…

Copilot surfaces the right materials, messaging, product overviews, and client data, while Maestro adds AI-native coaching conversations that guide each rep through practice modules and feedback loops that strengthen their delivery.

The manager then assigns everything directly in chat, and MCP writes the updates back to Degreed—so every skill, coaching activity, and readiness metric stays governed, current, and measurable.

There’s no extra portal needed or re-prompting required to remind the AI who’s who. The context and personalization from this exercise follow the learner from tool to tool, so the assistant stays helpful across technologies and the data remains secure.

What MCP Does for L&D, HR, and IT

Faster time to readiness: Onboarding ramp plans automatically adapt to each role, person, and deadline.
Higher adoption: Learning appears inside the tools people already use and is tailored to their needs.
Auditability: Every learning and skill action is governed and explainable.
Data you can trust: Degreed remains the single source of truth; MCP simply surfaces that data in real time.

Built to Fit your Tech Stack, Not Replace It

MCP works across your tech ecosystem, connecting signals from platforms like Workday, Salesforce, and any LMS, without duplication. It’s vendor-neutral and least-privileged by default, which means that MCP only accesses the minimum data and permissions necessary to perform its function—nothing more. Use your AI of choice, and your governance and security rules will still apply.

As Nikki Helmer, Chief Product Officer at Degreed, shared during Vision, “MCP doesn’t just make AI sound smarter. It helps it make smarter decisions—ones that align learning to business goals, reduce risk, and build real readiness.”

The post Announcing Degreed MCP: The Moment AI Learning Gets Its GPS appeared first on Degreed.

This becomes easier with the right tools, integrated to meet your needs. Take Degreed and Workday. Together, Degreed and Workday create a unified skills ecosystem that turns insight into action. The integration helps you close skill gaps faster, adapt to change, and align development directly with business priorities.

Turn Skill Gaps into Growth Opportunities

In many organizations, skill data is scattered across multiple platforms. That slows workforce planning and creates a mismatch between talent and business needs. The Workday and Degreed integration solves that by connecting skill data in both directions, creating a single, reliable source of truth.

It also replaces generic, one-size-fits-all learning with highly personalized experiences. By combining Workday’s role and performance insights with Degreed’s AI-powered curation, personalized experiences, and 80+ content providers, employees get the right learning at the right time.

Whenever the market shifts, agility becomes a competitive advantage. Shared taxonomies, labor market intelligence, and real-time skill validation make it possible to pivot quickly and confidently. Most importantly, every learning activity can be tied directly to measurable outcomes—linking Degreed activity with business targets in Workday, like retention, productivity, and promotion rates—so you can prove ROI, not just report on activity.

Proof in Action: State Street

State Street uses Degreed to assess and grow skills, then syncs validated skills to Workday only when proficiency is met. The results:

• Employees who spend 5–10 hours/month learning in Degreed report higher engagement.
• 300K+ Validated Skill Ratings powering internal mobility
• 97% User Activation, driven by integration into internal mobility
• 72% Monthly Active Use (and growing)

Your Advantage

Our Skills and Learning integrations have a Workday Design Approved badge. That means they are reviewed and approved by Workday, built in close collaboration with the Workday Product team, and guided by real client use cases. Together, we deliver one source of truth for HR and L&D, a connected and personalized employee experience, and the agility to pivot quickly, measure impact, and invest in what works.

Don’t wait for skill gaps to slow your growth. Discover how Workday + Degreed can help you close them. Imagine the impact you could see in just 90 days.

The post Use Workday and Degreed Data to Fill Your Skill Gaps appeared first on Degreed.

What happens when one of the world’s most trusted financial institutions decides it’s time to realign its skill development strategy?

At State Street, the answer was clear: Build an enterprise-wide, data-driven, executive-backed foundation for workforce agility and internal mobility—embedded in the company’s annual business strategy and talent action plans.

With more than 50,000 employees globally and 11% of the world’s financial assets flowing through its systems daily, State Street needed a more strategic approach to skill development, one that could keep pace with evolving business demands and employee expectations.

“The business came to us and said, ‘We have no way of seeing what skills employees have. We have no way of understanding where our skill gaps are, where we need to upskill, where we need to reskill,’” said Laura Sullivan, Vice President, Talent Development.

That challenge sparked the launch of SkillsFIRST. More than an HR initiative, it’s a key lever putting skills at the core of performance, retention, and career advancement. Powered by Degreed and integrated into Workday, SkillsFIRST is helping leadership align talent supply with business critical needs—and empowering employees to take ownership of their skill development.

From Limited Insight to Connected Capability

Before launching SkillsFIRST, State Street lacked a unified view of its workforce capabilities, while employees sought greater clarity around growth paths and more targeted development support.

Rather than licensing costly inference tools, State Street used Degreed and Workday to build its own Skills Library, customized using a blend of industry benchmarks and internal expertise. With input from subject matter experts, learning teams defined seven core skills for each role and created tailored Role Plans in Degreed.

How the Degreed–Workday Integration Functions at State Street

At State Street, the integration between Degreed and Workday forms the backbone of the company’s skills-first strategy—bridging employee development with strategic talent planning.

The process begins in Degreed, when employees explore curated learning content and engage with the personalized Role Plans. Employees are encouraged to assess their proficiency using the Degreed eight-point scale, and then to initiate structured career development conversations by requesting manager input on their ratings.

Skills will ultimately be moved to Workday to power a range of critical HR capabilities including skills matching for open positions, internal job recommendations, and strategic workforce planning—all grounded in real-time evidence of capability from Degreed.

This integration ensures that career development isn’t just aspirational—it’s operational, measurable, and deeply connected to business outcomes.

Strategic Impact That Scales

In just the first year of implementation, State Street has seen meaningful results:

• Millions of dollars saved avoiding costly, third-party skill inference and talent marketplace tools.
• 50% of employees onboarded into SkillsFIRST
• 1,200 additional internal promotions in six months
• 11% increase in employee engagement scores tied to career development
• 34% of internal hires supported through SkillsFIRST data, avoiding costs of external hiring
• 21,000+ monthly skill ratings generating rich talent insights for planning and learning

These outcomes reflect more than a technology shift—they signal a cultural commitment to transparency, growth, and mobility.

Key Lessons for Talent Leaders

For HR, Talent, and L&D leaders looking to operationalize skills, State Street’s journey offers proven strategies:

• Begin with clear business objectives, not just system capabilities.
• Build shared language through a unified skills library and role plans.
• Integrate platforms to turn skills data into workforce intelligence.
• Empower employees to participate in—and benefit from—the process.

By positioning skills as the connective tissue across performance, planning, and development, State Street has redefined how a complex global organization can unlock potential and stay future-ready.

Learn more.

SkillsFIRST didn’t just transform learning at State Street—it improved retention, boosted engagement, enabled internal mobility, and delivered measurable cost savings.

Find out how a similar approach could accelerate outcomes at your organization. Let’s talk.

The post Skill Development at Scale: What State Street Is Doing Differently appeared first on Degreed.

For enterprise leaders navigating transformation—whether it’s rolling out agentic AI, automating legacy processes, or entering new markets—the pressure to reskill fast is real.

The upshot? Skill data isn’t just an HR metric. It’s a strategic asset.

That said, many organizations are flooded with skill data yet starved for action. That’s where Degreed Skills+ can make a big difference. It doesn’t just surface skills. It uses them to create positive outcomes.

Step No. 1: Pinpoint Skill Supply and Strategic Gaps

Let’s say your CEO is investing heavily in agentic artificial intelligence to accelerate your product roadmap. HR and L&D leaders must identify skill gaps, define a build-buy strategy, and upskill the right people—fast.

Degreed Skills+ is designed for interoperability, not isolation. Integrations with platforms like Workday, SAP, and 80+ content providers help you streamline—instead of complicate—your data landscape.

Skills+ brings clarity to chaos by ingesting taxonomies from across your ecosystem—for example your HRIS, LXP, LMS, or talent marketplace—and using AI to normalize everything. That means cleaning up duplicates, aligning synonyms, and even generating skill descriptions and skill level definitions to reflect how your organization talks about and measures growth.

You stay in control of your taxonomy. The AI suggests, but you approve.

This reduces manual maintenance, increases reporting accuracy, and empowers IT and HR teams to move from data cleanup to strategic planning.

The result is high-fidelity skill data that reveals your true skill supply, pinpoints critical gaps, and gives you the visibility to align learning and talent development to workforce planning.

Step No. 2: Personalize Development at Scale

Once the gaps are clear, the next step is putting learning into action.

Skills+ powers highly personalized development across Degreed Learning. How? Because skills are embedded into the fabric of the platform. Search results, mentors, recommended experiences and more are tailored to each employee’s skill profile.

You can also create targeted Plans—on topics like “AI Fundamentals” or “Responsible Data Practices”—so employees know exactly what the organization wants them to learn.

Skills-powered automations—rules-based workflows designed to help the business deliver training, updates, and nudges at key employee moments—ensure essential content is assigned and followed up with nudges.

And Degreed Maestro, our AI purpose-built for learning, instantly generates custom Pathways based on employees’ unique goals, roles, or gaps—making learning feel personal and purposeful.

This isn’t just about consumption. It’s also about alignment—between business needs and individual growth.

Step No. 3: Measure Skill Growth and Prove Impact

Once the learning is in motion, how do you prove it’s working?

Degreed offers multiple ways to validate skill growth including AI-driven skill reviews, manager feedback, and robust analytics dashboards that help you compare current skill levels to skill levels before learning, so leaders get a live view of progress.

This closes the loop between strategy and execution—and gives you the confidence to report back to the business with real metrics, not just anecdotes.

From Complexity to Confidence

What once felt like a massive, messy problem is now a structured, data-driven process.

Degreed gives your people:

• A clear view of what skills they have and need.

• Personalized development aligned to business goals.

• Real, measurable progress in areas that matter.

Skills+ helps advance workforce development into something that’s not just efficient, but also strategic, approachable, and effective.

Find out more.

Let’s chat about how Degreed Skills+ can help you develop the skills your workforce needs next.

The post Turn Skill Data Into Workforce Action with Degreed Skills+ appeared first on Degreed.

At most organizations, this requires breaking down silos. Indeed, upskilling and reskilling takes cross-functional teamwork—a meeting of the minds among HR, IT, the C-suite, and of course L&D.

Do this effectively and you’ll get the skill data and insights you need to drive big business impact. 

“Every road trip is better with a copilot,” note the industry analysts at Deloitte. “High-performing organizations ensure the L&D function, leaders, and stakeholders are all accountable for a successful journey. They aren’t just along for the ride—the business understands the right questions to ask to improve the trip.”

Let’s take a closer look at two key steps you can take to promote cross-functional teamwork and bring powerful learning to life.

Step No. 1: Build a cross-functional team focused on business objectives.

If you’re a savvy business leader, you understand aligning agile and scalable workforce development priorities with the business is crucial.

So how can you get there? Making sense of learning and skill data is critical, because you can use that data to inform L&D decision-making.

But before you can turn insights from those juicy analytics into action, you and your stakeholders must come together to align programs and unify technologies.

Picture a global organization that integrates its learning, HCM, and talent marketplace platforms to streamline skills development. HR provided the direction, IT integrated the platforms to connect learning data across teams. And leadership supported the initiative because the desired outcomes were directly tied to strategic business goals.

This partnership allowed the organization to deliver personalized learning at scale, track ROI, and ensure the workforce stayed aligned with business needs.

Step No. 2: Embrace data and enact a skills-based learning strategy.

The best learning and technology strategies are guided by analytics. By understanding trends, skill gaps, and learning behaviors, your company can uncover actionable insights. Instead of guessing, you can take a proactive approach by using real-time data to identify emerging skill demands.

Imagine an IT department tasked with preparing an organization for AI adoption. By using skill data to assess current capabilities, IT can determine which employees need upskilling in areas like machine learning, automation, and AI ethics. This precision ensures that learning resources are allocated where they’ll have the most impact, while employees gain the confidence and expertise they need to lead innovation.

The Future of Your Workforce Strategy

For your company to compete in a world where technology and skills are constantly evolving, unifying learning systems and leveraging data are no longer optional—they’re essential. Cross-functional teamwork across HR, IT, L&D, and the C-suite ensures your organization’s learning strategy is flexible, responsive, and future focused.

Learn more.

Let’s chat about your skill-building strategy. Schedule a personalized one-on-one call with an expert at Degreed today.

Make skill data your business differentiator. Check out The Ultimate Skill Data Handbook.

The post Unlocking Potential with Data—and Cross-Functional Teamwork appeared first on Degreed.

Similarly, the experts at Training Industry said skill matrices can be “a game-changer for organizations.”

Skill matrices can serve as a key building block of the skills-based organization, laying the foundation for a winning, skills-first approach to running a successful business.

What is a skills matrix?

Often created as a grid, table, chart, or list, it’s a representation of the skills an employee has or needs for a particular role. Skill matrices help companies identify skill gaps, upskill their people, fill positions, and more.

At Exness, an innovative implementation of skill matrices has certainly been a game changer. When the Cyprus-based fintech company, a Degreed client, won a 2024 Degreed Visionaries Award last month, taking home Gold for Learning Innovator of the Year, we jumped at the chance to interview the L&D team and take a deeper dive into how the recent application of skill matrices company-wide transformed learning there.

To get all the details, we sat down for a Q&A with Dmitry Shevchenko, Online L&D Manager; Masha Komarova, Talent Development Manager; and Denis Kasalinskii, Senior Online Learning Specialist.

The Exness Story: Pivots, Collaboration, & Engagement

Degreed: We’re going to talk a lot about skill matrices today. But first, let’s set the stage. What did the learning landscape look like at Exness three years ago before all the positive change created by your award-winning program?

Shevchenko: We had a very simple learning management system (LMS) with internally developed courses. At the same time, our employees had quite diverse needs. We’re a technical company and have a lot of technical people, a lot of customer-facing people. We needed to supply our employees with a learning system that would satisfy very diverse learning needs. We wanted a platform that could be integrated easily with other content libraries, could integrate with different platforms, and could take content from external resources because it doesn’t make sense to develop internal content for most of the topics we need. For example, Python. There are so many good courses on Python on the internet, so why should we create our own if we can just push something external?

During this time, we also realized that it’s not enough to provide employees with just content. We wanted to have a platform, a framework that could analyze learning needs, analyze the current situation, skill proficiencies, and match content to actual learning needs. So we started looking for other solutions and chose Degreed.

Degreed: About a year into your Degreed implementation, you made a big strategy pivot that led to the skill matrices program that won you this award. What were the reasons for that pivot?

Shevchenko: We faced a few primary challenges. The company was growing quickly and the structure was becoming more complex. We realized there were employees with different positions and titles who were actually performing the same functions. And as we grew at all role levels, from junior to senior, we realized that understanding varied skill requirements was crucial. We responded by implementing skill matrices to provide clear competency frameworks for each level and ensure that training aimed at each type of role would be targeted and effective. 

Prior to this, we were reactively providing training services for the training requests we fielded, for example, a request from managers or in response to a problem that had been identified. These requests came to us scattershot, from individual employees or managers. We didn’t have a tool to identify a common growth area valid for, say, an entire division.

Komarova: Certain job families, if you will, are not located in one division but instead are spread across the corporate structure. For example, designers, programmers, and project managers. These are people who are working for different teams but doing similar jobs. Moreover, job naming was not under proper control. It was all up to the manager’s discretion. We had a huge list of unique job titles that needed to be condensed because the nature of the roles was pretty much the same. 

It created unclarity. If you were working as a programmer, you might not see a role like yours on a team you’d like to join. But in fact, that role did exist. Or you might see a role you want to apply for but in reality, it’s not the job you expected it to be.

To understand and clean up the roles we naturally began to map skills to them.

Degreed: Okay, so that’s what led to the formalization of skill matrices. Let’s talk about that more. What did this new direction really look like? How does it work?

Shevchenko: Our approach today integrates skill matrices and data-driven insights to create a focused, adaptive approach to employee development. Skill matrices identify skill gaps, while data analytics helps us to define organizational learning needs proactively. Continuous monitoring ensures learning remains relevant and aligned with both individual career goals and organizational objectives. This approach not only enhances employee skills but also fosters a culture of continuous learning, directly contributing to measurable business outcomes like improved performance and innovation.

Degreed: How did you implement your skill matrices program?

Shevchenko: To create each matrix, we pulled in a number of expert collaborators, and it took several approval rounds. A significant part of the strategy involved preparing the technical infrastructure. We uploaded all the matrices into Degreed as Role Plans, structured them, and developed a middleware Python script. This script, running weekly, automatically assigns the relevant skills matrix to active employees via API, ensuring continuous alignment. All told, we developed 590 custom Role plans with targeted skills that cover most roles at Exness. 

In addition, we’ve streamlined skill assessments. Employees annually self-assess against a skills matrix and role plan of 8 to 5 skills, followed by a manager’s review. This identifies skill gaps, leading to developmental one-to-one meetings, the creation of individual development plans, and training agreements.

For more precise skill assessment, we incorporated third-party tests. For example, a custom middleware script assigns a Business English skill rating based on external placement test results, enhancing the accuracy of our skill data. We also conducted comprehensive training and workshops for HR business partners, managers, and employees, focusing on the importance of assessments, the assessment processes, and the next steps.

We also integrated Degreed with the Greenhouse hiring platform, which streamlined our internal recruitment, enabling consistent skill taxonomy usage and simpler vacancy matching. This also motivates employees to keep their profiles updated, aiding recruiters in their candidate searches. In addition, we built custom dashboards in Google Looker Studio to supplement Degreed Advanced Analytics, categorizing skills with Chat GPT-4 assistance. This allows for robust data analysis and informed decision-making for future learning goals.

Degreed: And the results?

Shevchenko: Approximately 85% of employees now have a valid skills matrix. This has led to increased Degreed profile updating and skill rating activities. We’ve seen 65% of employees rate all skills in their skills matrix, with 40% receiving complete skill ratings from managers. 

Overall it’s contributed to impressive growth in learning activity. Our number of viewed items is 88% higher and our amount of completions is 42% higher.

We’re also much less reactive. We’re proactive. Our Global L&D team now bases decisions on concrete skill assessment data. This year, we tailored centralized training not just on division heads’ perceived needs but on authentic data from employees, which has made the training we provide more relevant. Our learning initiatives are now more precise and impactful. 

For instance, detecting a surge in GoLang search queries led to the timely release of a relevant plan, coinciding with a major project transitioning from Python to GoLang. This plan quickly became one of our most utilized resources. In addition, we’ve even used skill data from the program to help recruit participants in our “Exness Masters” program. It’s made up of 25 subject matter experts from around the company who curate content and do peer-to-peer training.

Degreed: What lessons did you learn along the way? Do you have any advice for anyone else attempting this approach?

Shevchenko: Involving managers and field experts in developing skill matrices proved essential. And holding targeted, face-to-face workshops for diverse groups helped us to engage employees and communicate change. We emphasized the project’s significance and mutual benefits, which we believe boosted participation rates and the accuracy of skill assessments.

Kasalinskii: We also create activities to increase engagement. Every month we do knowledge sessions across the company. Sometimes it’s special for a particular division or department. Sometimes we just announce that this month we’ve organized an open knowledge session, so everyone who’s interested can enroll. At the end of every quarter, we try to calculate who is the top active online learner on Degreed. And we present them with our branded hoodie. We created our own L&D brand “Learning Never Stops.”

The main point here is that we do it constantly. If you do it constantly, it’ll work.

The post Enter the Skills Matrix: How the Exness Strategy Won Gold appeared first on Degreed.

Individuals and their managers certainly provide valuable viewpoints on skills, which is why Degreed offers proficiency ratings through Self Ratings and Manager Ratings. Skill assessments are another key source of validation. In Degreed, this happens via our dynamic skill-assessment questionnaire, Skill Review, and integrations with 3rd-party accreditation tools.

A missing piece in our skills rating process was peer perspectives and peer evaluations. Team members who work closely with an individual on daily tasks have unique insights into how that individual uses skills on the job, and those insights should be captured. 

Degreed clients have already experienced the benefits of using our skill insights and rating solutions to dive into their employees’ skill data, and they’re looking for more.

“We can start connecting people’s peer-reviewed skill confidence levels with usage and business performance data,” said Peter Manniche Riber, Head of Digital Learning at Novo Nordisk. “We can drive conscious skill development across the company and plan for the right learning interventions based on user preferences, behavior and business needs — automated.”

This is why we’ve created Peer Ratings. Available now, Peer Ratings allows individuals to receive feedback on their skills directly from their peers, providing L&D leaders with a 360-degree view of their people’s skills.

Peer Ratings: A Closer Look

Peer Ratings is the latest addition to Degreed’s offerings that focus on helping organizations understand people’s skill levels. It enables individuals to request feedback from their peers on specific skills. 

Similar to Self Ratings and Manager Ratings, Peer Ratings provides a data point about an individual’s level of proficiency in a specific skill, but this time from the perspective of close-working colleagues.

This unique perspective provides valuable data around skill strength, and rounds out an individual’s skill profile to reflect feedback from peers, managers, themselves and assessments, resulting in a 360-degree view of that person’s skills.

How does Peer Ratings work?

Receiving feedback from peers is incredibly simple. Users select a skill then choose a peer whose feedback they’d like. The peer will receive a notification to fill out a rating and, once complete, the user will see the details of the rating.

With Peer Ratings, learners are able to:

• Request ratings from their peers
• Rate their peers when sent a request
• View a summary of their Peer Ratings
• View the details of each Peer Rating
• View their average Peer Rating level

Managers also gain visibility, helping them more fully understand  the skills and skill levels within their teams.

Graphic: Peer Ratings + Manger Ratings + Self Ratings + Ratings from Assessments = 360-degree skill profile (AKA – actionable data)

What This Means for the Business 

The skill data that comes from Peer Ratings and other sources is essential in tackling the challenges businesses face. 

According to a study from Deloitte, 89% of executives say skills are becoming more important for the way organizations define work, but only 18% strongly agree their workforce is using their skills and capabilities to their fullest potential.

How can skills be maximized if individual workers and their organizations’ L&D professionals don’t know what skills they have? They can’t. That’s why robust skill profiles that combine skill assessments with self, peer and manager ratings are key to maximizing workforce potential, and therefore business potential. 

Creating the workforce your business needs starts with understanding the workforce you have. Once you uncover that knowledge, you can truly drive impact.

What This Means for L&D

Well-informed skill profiles help L&D professionals tackle common challenges. 

For example, learning teams need to make sure the learning opportunities they provide are impactful. By uncovering skill proficiencies and skill gaps, L&D can target development where it matters most. Doing so not only produces better results but also can help identify what learning resources aren’t needed at the moment, so L&D can be more cost efficient.

A full skill profile helps with another core L&D task: leadership development. The data from Peer Ratings and other skill data sources helps L&D uncover where more learning resources are needed so they can support effective leadership at their organization.

Another area of interest for L&D professionals is creating a learning and positive workplace culture. Our 2021 research report How the Workforce Learns uncovered the common attributes found in a positive learning culture. In one interesting discovery, the report found individuals whose skills were assessed by peers were 75% more likely to rate their learning culture as positive.

For L&D leaders to create a positive culture of lifelong learning, it’s essential they create “an environment with psychological safety where individuals receive guidance on their development.” That’s why we recommend L&D introduce 360-degree skill assessments that invite peers to give feedback, in combination with skill assessments, manager ratings, and self ratings.

And of course, all this data supports reskilling and upskilling initiatives, so L&D can develop the workforce the business needs.

What This Means for the Employee 

As skills become increasingly important to the way work is defined and opportunities are allotted, it’s vital people showcase their expertise. With a robust skill profile that includes data points like those from Peer Ratings, employees are equipped with the information they need to highlight their strengths and address any areas in need of improvement. 

Let’s look at an example:

Marisa works as a data analyst for a software company, which has been hurting for creative new approaches to their product offering. The L&D department is looking internally to upskill or reskill someone into for a Product Manager role, and Marisa expresses interest. She discusses this with her manager and finds out which skills are most important. Marisa then completes a Self Rating and a skill assessment with Skill Review to provide data points that speak to her level of expertise in those skills. 

Marisa wants to take it a step further by adding additional perspectives on her strengths, so she asks her manager and a couple of teammates to rate her skill levels. 

All these data sources combine to create a 360-degree view of Marisa’s skills.

Now that Marisa has a complete skill profile, she can see she’s strong in certain skills like “Critical Thinking” but weak in “Product Design.” With this knowledge, she works with her manager to identify upskilling opportunities that will increase her proficiency in “Product Design.”  

Not only is Marisa closer to achieving her aspirations, the L&D team was able to support the business in a key initiative and the organization is benefiting from developing talent from within.

Bringing It All Together

Peer Ratings is the next essential step in rounding out an individual’s skill profile. A complete view into a worker’s skill data can have a tremendous impact on the lives of your people, the efficiency of your L&D team and the business results you’re working toward.

Want to learn more? Schedule a personalized Degreed demo today.

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At CredSpark, we work with hundreds of L&D leaders to ensure they’re maximizing opportunities to gain employee insights and have a strategic plan for using the data they get back. While no two companies are using an LXP in exactly the same way, they’re all trying to measure the impact of their work. 

Whether you’re just getting started by defining a learning measurement and evaluation strategy or tweaking something already in place, asking a few key questions can help you capture accurate, complete and actionable data. 

Fair warning: Few organizations can confidently say they’re checking each box. Fewer still have a strategy that ensures data related to all five areas is collected in a coherent, efficient manner. But that shouldn’t stop you from getting started on improvements.

Key No. 1: Know how your people respond to your content.

Getting learner feedback is important in every learning context, but perhaps most of all with adults. Find out if they’re able to access and process the learning you’ve created for them, as well as how they feel about the experience.

Key No. 2: Know if your people are actually learning

How sticky is your learning? It’s easy to default to multiple-choice questions as an evaluation tool, but they rarely reflect how knowledge is used in the real world. A more authentic evaluation strategy will include recall-based quizzes and a mix of more sophisticated assessments. Most importantly, don’t neglect reflective self-assessments; for example, use confidence-based scoring or prompt users to categorize incorrect answers so they can think more deeply about their learning. With the right framework, reflective assessments can be your most powerful measurement tools. 

Key No. 3: Know if learning is being applied. 

Evaluating the impact of learning requires a thoughtful and comprehensive longitudinal approach. But if you really want to know if your employees are changing their behavior over time, you’ll need to set up a way to measure that. For example, are you tracking how scores on assessments align with performance reviews? 

Key No. 4: Know if your learning materials are comprehensive and complete.

It can be hard to discriminate between content that’s popular versus content that’s effective. No matter how good your instructional designers are or how savvy your subject matter experts, it’s worthwhile to put a feedback loop in place to ensure your employees can tell you how they’re experiencing your content. Ideally, that includes using a universal measure like the Net Promoter Score (NPS), so you can look across content and departments. 

Key No. 5: Collect data you can act on.

Designing an evaluation strategy means knowing what questions to ask and when, plus knowing what the answers enable you to do. For example, a robust tagging system for your content can help you trace spikes or dips in performance in particular areas — so you can intervene and ensure your content is fully and completely preparing your people. 

Let’s get practical: Dos and Don’ts 

When you’re creating your measurement strategies:

DO

• Take an ecosystem approach to evaluation and assessment: All kinds of data points should feed back to a central location, where they can be synthesized and analyzed. Ask each learning group to provide its plan for each of the five key points above. They don’t have to use the same tools or even the same approach, but they all need to be measuring the same things. 

• Gather feedback as close to the learning experience as possible, while people have it fresh in their minds and can articulate what would make the experience better. Quantitative feedback should be captured regularly — at the moment of learning and again over time, so you can see how learning is retained and applied. 

• Trust your employees, and make sure they know they can trust you. Treat your people like partners. Offer them ways to take control of their learning, and to help you know what’s working for them (and what’s not).

• Have a plan for any data you’re collecting: Where will it live? What will you do with it? Who needs to see it? When? How? How often? These are all questions that can inform your data strategy. Your data strategy needs to progress in lockstep with your learning strategy, not trail behind as an afterthought.

DON’T

• Ask questions if you can’t do anything about the answers. It’s tempting to ask people if they liked or benefited from something. But what happens if they say no? Will you be able to make changes? Remember, trust is key. 

• Assume numbers are the end-all and be-all. It can be tempting to use the data you have to draw the conclusions you need; the harder-but-better choice is to look at your data and ask if it can support your conclusions. If a person completes a lot of learning, does that mean they have learned? If a person receives good reviews but does not perform as well on assessments, does that mean they haven’t learned? The smartest companies make quantifiable data just one input into employee evaluations, as tempting as it might be to lean more on pretty round numbers. 

What’s next?

All Degreed clients have access to CredSpark, an embedded assessment and survey tool. CredSpark helps learning teams execute their measurement strategies. An even more powerful feature set is available with CredSpark+. 

No matter the tools used, creating and implementing an overarching plan to collect, analyze and act on learning data isn’t easy. It also won’t happen organically: It takes a top-down, strategic approach from leadership, and it must come with a strong signal that assessment and evaluation is taken so seriously that the least importance will be given to data that’s easiest to gather. Instead, show you’re using assessment and evaluation data to understand the pulse of your organization. Spikes or outliers can help direct your attention to certain areas or people, but in and of themselves those data points are just signals, not summations. 

Finally, in the world of adult learning, trust might be the most important factor. Harness your data to help you cultivate, monitor and deepen trust by being open and transparent about goals and progress. Invite your people to be a part of that process. And always, always, always be asking questions of your employees. Their success is your success, so talk with them early and often to ensure you’re set up to achieve that success together.

Casey Cornelius is Head of Content & Client Services at CredSpark.

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