1. Contenidos generados con IA.
2. Comentarios constructivos personalizados y minisesiones de coaching.
3. Encuestas, datos y conversaciones reflexivas.

1. Contenidos generados con IA

Comencemos por la generación de contenidos de aprendizaje multimodales. Estamos analizando cómo se puede usar la IA para generar contenidos o para aprovechar documentos o archivos SCORM (sigla en inglés de “modelo de referencia para objetos de contenido compartible”) como punto de partida. Estos se pueden transformar rápidamente en materiales de aprendizaje de cualquier longitud o formato. A su vez, el resultado se puede modificar y convertir en texto, imágenes, gráficos y videos (o incluso diapositivas).

Este es un método simple para que los contenidos de aprendizaje útiles sean siempre interesantes y diversos y mantengan su vigencia. Planeamos ponerlo en marcha a principios de 2026.

2. Comentarios constructivos personalizados y minisesiones de coaching

Degreed Maestro no es un simple chat con IA. Se pensó para ofrecer experiencias de aprendizaje integrales y trascendentes. Para lograrlo, estamos probando experiencias de IA de varios pasos y en distintos formatos (es decir, comentarios constructivos personalizados y minisesiones de coaching) para darles a los aprendices la oportunidad de mejorar.

Por ejemplo, si un empleado ensaya una llamada de ventas, Maestro lo puede calificar con una puntuación y opinar sobre su desempeño: señalar qué hizo bien y qué aspectos hace falta pulir. También le puede ofrecer una minisesión de coaching o la posibilidad de reproducir la charla y practicar las cuestiones particulares en las que debe trabajar. 

3. Encuestas, datos y conversaciones reflexivas

Otra novedad que nos entusiasma mucho es una nueva forma de usar Maestro para charlar reflexionando en un mano a mano con la IA. Estos encuentros pueden incentivar el aprendizaje y la comprensión y, al mismo tiempo, permiten obtener datos estadísticos valiosos. 

A diferencia de las encuestas formales, que cansan y se responden de manera apresurada e incompleta, Maestro puede incluir preguntas inteligentes en las conversaciones cotidianas o extraer estadísticas de charlas anteriores sin que se necesiten más intervenciones. En ese contexto, el personal suele expresarse con más soltura y profundidad que en las encuestas tradicionales, sobre todo si sabe que sus respuestas son confidenciales. 

Por ejemplo, en una conversación breve con Maestro les preguntamos a los empleados cómo usan la IA en su rol. Maestro recabó las respuestas y generó un tablero sincronizado para combinar los resultados. Partiendo de esa base, hasta teníamos la oportunidad de chatear sobre los datos para analizar futuras tendencias. 

Con este abordaje, es fácil contar con una noción básica de las habilidades, necesidades y experiencias de cada empleado y, luego, adaptar los programas de aprendizaje en función de eso. Las repercusiones de las iniciativas se cuantifican al instante y, con eso, se pueden elaborar estadísticas exhaustivas y sustanciosas que no estaban a nuestro alcance con los métodos tradicionales. Se trata de análisis en simultáneo que antes eran imposibles. 

Mantente al día

Imagina todo lo que podrías lograr si tuvieras ese grado de claridad sobre tus empleados, lo que necesitan y los resultados de tus programas de aprendizaje. Nos encantaría conocer tu opinión mientras seguimos investigando. Sígueme en LinkedIn o suscríbete al boletín del laboratorio de experimentos de IA para no perderte ninguna novedad.

The post Contenidos generados con IA, coaching y datos interactivos appeared first on Degreed.

Las tasas de finalización demuestran que los empleados cumplieron con el programa, y sus halagos, que quedaron conformes; pero estos dos factores no evidencian que realmente hayan aprendido algo. Los ejecutivos quieren pruebas tangibles de que la inversión valió la pena. Debes demostrarles que los empleados retuvieron la información y están listos para aplicarla a su trabajo. Y si no fue así, debes reconocer qué aspectos hay que reforzar. 

Entonces, ¿cuál es la respuesta? Ponlos a prueba.

Los cuestionarios, la nueva función de Degreed Maestro, te permiten crear e implementar preguntas generadas por IA con rapidez para verificar la retención de los conocimientos y cuantificar la eficacia de los programas de aprendizaje. Así, la próxima vez que los ejecutivos te pregunten si tu iniciativa dio resultado, tendrás los datos necesarios para justificar tu respuesta.

El método anterior: crear los cuestionarios manualmente

¿Entender la ventaja de los cuestionarios? Fácil. ¿Prepararlos manualmente, con precisión y a gran escala? Complicado.

Preparar e implementar cuestionarios a gran escala siempre fue una tarea manual que lleva muchísimo tiempo. Por lo general, para redactar las preguntas hay que recurrir a expertos en las distintas materias, y suelen estar ocupados. No es una forma eficiente de aprovechar sus valiosos conocimientos especializados y, además, como hay que esperarlos, se demora la implementación. 

Cuando se depende de las tareas manuales y de la disponibilidad de los expertos en cada materia, es difícil diseñar cuestionarios a gran escala y mantenerlos actualizados. Hoy, esa realidad es más patente que nunca, ya que las habilidades y los conocimientos que necesitan los empleados cambian todo el tiempo. 

El método nuevo: generar los cuestionarios con IA

Con Maestro, los administradores pueden preparar cuestionarios en cuestión de minutos y reducir de manera drástica el tiempo y el esfuerzo que se necesitan para hacerlo. Chateando con Maestro, puedes orientarlo para que elabore un cuestionario personalizado sobre cualquier tema y adaptar los parámetros que desees, como la cantidad de preguntas y el grado de dificultad. Maestro también puede redactar preguntas en función de documentos que ya tengas. Esta es una manera más simple de aprovechar los conocimientos de los expertos en cada materia sin tener que pedirles que elaboren consignas. 

Una vez que los empleados terminan el cuestionario, los administradores analizan los informes de la aplicación y evalúan en qué medida retuvieron los conocimientos. Estos informes permiten saber qué preguntas se responden de manera incorrecta con más frecuencia y, así, sobre qué temas faltan conocimientos y se debe reforzar el aprendizaje.

Los cuestionarios están conectados directamente con la plataforma de Degreed, por lo que puedes gestionar diferentes actividades desde allí, como asignarlos o elaborar informes sobre los resultados. De esta manera, es fácil detectar qué conocimientos hay que repasar más, de modo que puedas plantear experiencias de aprendizaje más eficaces para subsanar esas deficiencias, lo cual beneficia a toda la empresa.

Ventajas para la empresa

Casos de uso concretos de los cuestionarios

Ejemplo: prepararse para el lanzamiento de un producto

Se está por lanzar un nuevo producto, y tus equipos de estrategias de crecimiento tienen un exceso de información: propuestas de valor, funcionalidades del producto, tácticas de comercialización. Hay muchos conocimientos que asimilar, y es difícil determinar si el personal está preparado. 

Con los cuestionarios de Maestro, puedes evaluar si los empleados tienen una noción de los componentes principales de tu nuevo producto. Hasta puedes crear distintos cuestionarios para diferentes grupos, ya que la información que debe recordar tu equipo de ventas no es la misma que necesita el equipo de implementación. Si usas documentos que ya tienes, puedes generar cuestionarios especiales para cada grupo en cuestión de minutos. 

Ejemplo: verificar la retención de los conocimientos a largo plazo para la transformación en torno a la IA 

Muchas empresas se plantean objetivos ambiciosos cuando deciden adoptar IA en sus procesos. Seguramente, los conocimientos necesarios no están tan difundidos en la empresa, por lo que se deben llevar adelante programas de capacitación y upskilling exhaustivos. Al incluir un cuestionario al inicio y al final de un itinerario, puedes cuantificar cuánto aprendió el personal sobre la implementación de la IA y, después, correlacionar el programa de aprendizaje con las iniciativas estratégicas de tu empresa.  

Ejemplo: nuevo proceso para el onboarding de los clientes

Los cuestionarios sirven para memorizar las novedades de los procesos y procedimientos. Si pusiste en práctica un nuevo procedimiento para el onboarding de los clientes, los empleados deben recordar el proceso correcto, qué hacer y qué no. De esta manera, podrás ver si están preparados y para qué aspectos específicos tal vez necesitan más capacitación.

Los cuestionarios como parte de un proceso de aprendizaje más amplio

Por sí solos, los cuestionarios son muy útiles, pero si se los combina con otras iniciativas de aprendizaje, como los itinerarios o las academias, se potencian. Al incluir cuestionarios al final de estos programas, puedes evaluar su eficacia y detectar qué contenidos convendría renovar o cambiar. 

Por otro lado, cuando se integran cuestionarios en Degreed, la experiencia de los aprendices es óptima, ya que la interfaz de uso es la misma en todas partes. Además, eso te permite unificar tecnologías y, por ende, bajar los costos y la carga administrativa, ya que hay menos plataformas para gestionar.

The post Genera cuestionarios con IA para cuantificar el aprendizaje appeared first on Degreed.

Para poder cultivar esas competencias, se necesita contexto. La IA necesita la siguiente información:

• ¿Quién es el aprendiz y qué nivel de habilidad tiene?
• ¿Qué condiciones debe cumplir para asumir una función?
• ¿Cuáles son las bases de la ciencia del aprendizaje y cómo se aplican a esta situación?

El protocolo de contexto para modelos (MCP, por su sigla en inglés) aporta el contexto pertinente.

Digámoslo de esta forma: antes usábamos los mapas de toda la vida, que no tenían GPS; pero orientarnos nos resultaba más difícil y menos personalizado. 

El MCP viene a ser el GPS de los programas de aprendizaje asistidos por IA. 

Este protocolo no agrega “funciones de IA” a un portal, sino que simplifica las integraciones: la IA puede acceder a la información almacenada en otras herramientas y bases de datos y contextualizarla de modo sistemático y controlado extrayéndola de Degreed o de otros sistemas vinculados, independientemente de dónde se alojen esos modelos de IA y en qué plataforma se hayan desarrollado. Siguiendo la analogía del GPS, recalcula la trayectoria en el acto para evitar embotellamientos, recomienda lugares de interés cercanos y mejora el itinerario en sí. 

Gracias a la interfaz de MCP, la IA tiene acceso a una base de información contextual más amplia y facilita experiencias de aprendizaje más específicas, personalizadas y sincronizadas.

Esto le permite dejar de generar contenido y empezar a proporcionar contexto didáctico a fin de estimular ciertas aptitudes, de modo que los empleados y las empresas puedan adquirir nuevas habilidades y aplicarlas con más rapidez.

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

Como aparato conectivo dentro del ecosistema de Degreed, el MCP está pensado para que las soluciones de aprendizaje asistido por IA ayuden de verdad a adquirir competencias. Les da a los agentes de IA autorizados (como ChatGPT, Claude, Copilot o cualquier otro asistente interno) un panorama controlado e inmediato de lo más importante para facilitar el aprendizaje de los empleados y propiciar su eficacia, por ejemplo:

• las habilidades, los objetivos y el rol del aprendiz;
• su historial de aprendizaje y sus datos sobre habilidades de Degreed. 

Degreed MCP es una suerte de “archivo contextualizador”. Gracias a la organización de ese archivo, la IA se vuelve una ayuda mucho más precisa en el proceso de aprendizaje. Puede analizar todos los datos sobre los empleados y proporcionarles los contenidos de aprendizaje adecuados en el momento oportuno.

How MCP Works in the Flow of Learning

Supongamos que un martes a la mañana un gerente de ventas abre Copilot y le pide que ayude a su equipo a prepararse para el discurso que debe dar el viernes sobre un producto.

Sin el MCP…

Copilot puede buscar presentaciones, tácticas y materiales sobre ventas, pero no tiene forma de saber quién dará la charla, qué habilidades le faltan a esa persona ni cómo puede ayudarla a hacer mejor su trabajo.

Con el MCP…

Degreed y Maestro aportan la información faltante y la contextualizan: quiénes forman parte del equipo, quiénes están al tanto de qué y en qué áreas necesitan algún tipo de coaching para perfeccionar sus habilidades.

Juntos…

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.

En este caso, el gerente puede asignar todo directamente en el chat y el MCP, sincronizar la información en Degreed, de modo que cada habilidad, sesión de coaching y parámetro de aptitud se actualice, se controle y se pueda cuantificar.

No es necesario abrir ningún programa ni dar más instrucciones a la IA para recordarle quién es quién. Más allá de la herramienta que se use, el contexto y los ajustes de personalización de este ejercicio quedan vinculados con los aprendices, de modo que el asistente resulte útil con diversas tecnologías y los datos estén siempre protegidos.

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

Preparación más expeditiva: Los planes de onboarding se agilizan adaptándose de manera automática a cada rol, empleado y plazo de entrega.
Mayor adopción: Los trabajadores tienen acceso a contenidos de aprendizaje ajustados a sus necesidades directamente en las herramientas que ya usan.
Posibilidad de hacer auditorías: Cada etapa del proceso de aprendizaje y de la adquisición de habilidades está debidamente detallada y justificada.
Datos de confianza: Degreed sigue siendo la única fuente de información; el MCP se limita a recuperar esos datos al instante.

Built to Fit your Tech Stack, Not Replace It

El MCP se integra a tu ecosistema de tecnologías y vincula los datos procedentes de plataformas como Workday, Salesforce y cualquier otro LMS, sin copiarlos. Su uso no depende de ningún proveedor en particular y, de manera predeterminada, tiene los niveles de acceso más básicos, es decir, opera únicamente con los datos y permisos indispensables para su funcionamiento. Tus normas de seguridad y gobernanza se mantienen vigentes, uses la IA que uses.

As Nikki Helmer, Chief Product Officer at Degreed, shared during Vision, “MCP doesn’t just make AI sound smarter. sino que la ayuda a tomar mejores decisiones para ceñir los programas de aprendizaje a los objetivos de la empresa, atenuar los riesgos y preparar al personal para la vida real”.

The post Presentamos Degreed MCP: el GPS del aprendizaje con IA appeared first on Degreed.

¿Qué sucede cuando una de las instituciones financieras más respetadas del mundo decide que llegó el momento de reformular su estrategia para desarrollar habilidades?

En State Street, la respuesta era evidente: había que agilizar al personal y facilitar la movilidad interna sentando una base para toda la empresa a partir de sus datos y con el apoyo de los ejecutivos, e integrar esa base en la estrategia empresarial anual y los planes de acción del equipo de Talentos.

Como posee más de 50 000 empleados a nivel internacional, y el 11 % de los bienes financieros del mundo pasan por sus sistemas a diario, State Street necesitaba un método más estratégico para abordar el desarrollo de habilidades, uno que se mantuviera a la par de las exigencias cambiantes de las empresas y que estuviera a la altura de las expectativas de los empleados.

“Los ejecutivos se acercaron y nos comentaron: ‘No tenemos manera de saber qué habilidades tienen los empleados ni cuáles faltan, en qué áreas se necesita upskilling y en cuáles hay que hacer reeskilling’”, relató Laura Sullivan, vicepresidenta del equipo de Desarrollo de Talentos.

Esa dificultad fue la que dio pie al lanzamiento de SkillsFIRST. Más que una iniciativa de RR. HH., es un mecanismo esencial que pone de relieve la importancia de las habilidades para el desempeño, la retención del personal y el crecimiento profesional. Por un lado, esta iniciativa posibilitada por Degreed e integrada en Workday ayuda a los altos mandos a adecuar la oferta de talentos a las necesidades más básicas de la empresa. Por el otro, les da a los empleados la posibilidad de hacerse cargo de cómo adquieren habilidades.

De una noción limitada a un panorama integral de las capacidades

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.

En lugar de comprar licencias de costosos programas para hacer inferencias, State Street usó Degreed y Workday para crear su propia biblioteca de habilidades personalizada combinando normas del sector y los conocimientos especializados de sus propios expertos. Con los aportes de expertos en la materia, los equipos de Aprendizaje definieron siete habilidades centrales para cada rol y prepararon planes de roles especiales en Degreed.

Cómo funciona la integración de Degreed y Workday en State Street

En State Street, la integración entre Degreed y Workday es la columna vertebral de la estrategia de la empresa para priorizar las habilidades, ya que relaciona el desarrollo profesional de los empleados con el plan estratégico del área de Talentos.

El proceso comienza en Degreed, donde los empleados buscan contenido de aprendizaje gestionado y recurren a los planes de roles personalizados. Posteriormente, se les recomienda que evalúen su nivel de competencia con la escala de ocho puntos de Degreed y que, a partir de eso, entablen conversaciones estructuradas sobre su desarrollo profesional con los líderes solicitándoles que les den su opinión sobre las calificaciones.

En última instancia, las habilidades se trasladan a Workday, de modo que se puedan aprovechar para tareas esenciales de RR. HH., como correlacionarlas con puestos vacantes, hacer recomendaciones internas y planificar el personal de manera estratégica, siempre en función de los datos actualizados de Degreed, que prueban la competencia necesaria.

Con esta integración, el desarrollo profesional deja de ser un mero anhelo y se convierte en un aspecto operativo y cuantificable que guarda una estrecha relación con los resultados empresariales.

Efectos estratégicos que se multiplican a gran escala

En apenas el primer año de implementación, State Street obtuvo importantes resultados:

• Se ahorraron millones de dólares al evitar la compra de costosas herramientas externas de inferencia de habilidades y gestión del mercado de talentos.
• El 50 % de los empleados se sumó a SkillsFIRST.
• Hubo 1200 ascensos internos más en seis meses.
• Se registró un aumento del 11 % en las puntuaciones de compromiso de los empleados a causa del desarrollo profesional.
• El 34 % de las contrataciones internas se consiguió gracias a datos de SkillsFIRST, por lo que se evitaron los gastos inherentes a las contrataciones externas.
• Se hicieron más de 21 000 calificaciones de habilidades por mes, lo cual permitió formar perspectivas completas sobre los talentos, y eso contribuye a la planificación y al aprendizaje.

Estos resultados dan cuenta de algo más que un simple cambio de tecnología: señalan un compromiso de toda la empresa con la transparencia, el crecimiento y la movilidad.

Principales enseñanzas para los directores del equipo de Talentos

Para los directores de las áreas de RR. HH., Talentos y Aprendizaje y Desarrollo que quieren empezar a trabajar con las habilidades, el proceso de State Street demuestra la eficacia de varias estrategias:

• Comenzar con objetivos empresariales claros, no solo funcionalidades del sistema.
• Acordar un vocabulario común mediante una biblioteca unificada de habilidades y planes de roles.
• Integrar las plataformas para convertir los datos sobre habilidades en información sobre el personal.
• Darles a los empleados la posibilidad de participar en el proceso y aprovechar sus beneficios.

Al transformar las habilidades en el elemento que subyace al desempeño, a la planificación y al desarrollo profesional, State Street reinventó el modo en que una compleja empresa multinacional puede explotar su potencial y estar siempre preparada para el futuro.

Sigue aprendiendo.

La iniciativa SkillsFIRST no solo transformó el aprendizaje en State Street, sino que aumentó la retención del personal, mejoró la participación, facilitó la movilidad interna y permitió recortar gastos concretos.

Descubre cómo un método similar podría acelerar los resultados en tu empresa. Hablemos.

The post Desarrollo de habilidades a gran escala: en qué se diferencia el método de State Street 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.

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.

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Depending on who you ask, you might get complicated answers.

We’re making it simple. 

Many organizations have relied on competency models for measuring performance and capabilities since they entered the business conversation. Competencies date to the early 1950s. In 1973, David McClelland, Professor of  Psychology at Harvard University, questioned the use of intelligence tests to predict job performance. Instead, he championed measuring competencies (the underlying traits that lead to superior performance). A framework was born, a model unique to an organization that lists expectations required to perform well for a particular role or function. 

Now, some organizations are looking at an alternative: skill-based talent strategies. With 58% of respondents in a McKinsey survey stating that closing the skill gap at their company has become a priority, a majority (69%) from the same survey also said skill-building at their organizations has increased in an effort to close the gap. 

Competency model or skill model? Learning and talent leaders have strong opinions about which is best. Here’s a key point: they both address the same thing, which is how we get work done.

To understand how they’re different, let’s look at how “competency” and “skill” are defined: 

• Competency: Knowledge, behaviors, attitudes and even skills that lead to the ability to do something successfully or efficiently. The ability to make business decisions would be a competency.
• Skill: Learned and applied abilities that use one’s knowledge effectively in execution or performance. Using the same example of making business decisions, in order to do so, you would have to maintain certain skills to perform well: budgeting, market research and competitive strategy. 

Whether your organization is using skills or competencies to measure development, the goals are the same: assessing your people, identifying areas for growth and offering the right opportunities to learn and stay engaged. 

“The corporate learning landscape is evolving very, very fast,” Peter Fox, Global Head of Digital Learning and Talent Technology at Citi, said at the recent Degreed LENS conference. You can navigate this evolution by fully understanding the differences (and similarities) between a competency and skills model, how they work together, and which might be best for your organization. 

Skills vs. Competencies: Breaking it Down

While these concepts might seem complicated, they’re ideas you can often blend when you’re planning goals and strategies for your organization and people. Understanding how they work can help you when and how each model, or a combination, is best for your team and your leadership.

Competencies: Powerful, with Limits

A competency entails more than just knowledge and ability. It’s a mix of behaviors and attitudes. And it can include skills, too. But managing such a large and complex model can be challenging. As Annee Bayeux, Chief Learning Strategist at Degreed, said at LENS: “Competencies tend to be big-picture and aspirational.”

Competencies are value-based. They’re specific to an organization or project. Since they’re tied to values and culture, they aren’t easily measured or standardized. For example, expectations for competency in analytical ability can differ heavily depending on context.

Competencies are rigid. They aren’t agile in practice. It can take months or even years for someone to reach a specific competency. You could become skilled in data analytics software in a few hours, but you can’t become fully competent in data analytics in that time. In our fast-paced and ever-changing world, adaptability and agility are vital for success.

Competencies are non-transferrable. They’re mostly mapped to individual functions or behaviors, making it hard to transfer them across an organization. Because of this, it’s difficult to imagine how one competency can perform in another role.

Despite limitations, many learning teams create competency models for their organizations. Because key competencies are specific, rigid and non-transferrable, the act of creating a competency model takes a ton of time and effort. Your model can become outdated before it’s even put into action.

Skills: Agile and Efficient

When we talk about skills, we’re using the language that people use to describe their own development. Skills are smaller and more manageable than competencies, making them easier to track. Because of that, skills are the unit of measurement in Degreed. As Laura Jones, Executive Director of Global Talent at General Motors, said at Degreed LENS: “Learning is nothing unless you do something with it.” 

Skills can be developed. Think of skills such as computer programming, project management, knowledge of specific platforms or even soft or human skills such as active listening and communication. These can be learned in a matter of days, weeks or months and improved in practice over time. 

Skills can be measured. As opposed to being outcome-based or value-based, skills can be measured and standardized. Degreed uses a rating system designed by The Lumina Foundation. By using a standard rating system with skills as a unit, we can measure growth, track progress and match your people to on-the-job learning opportunities. You can, for example, know exactly at what level someone is skilled in Java. 

Skills are applicable. Work can be deconstructed into three components: tasks, projects and roles. Skills are used to perform tasks. Tasks are the things required to complete projects. And projects are how roles are organized. This means skills are how work gets done. You can’t complete the task of making a sale by solely being competent in customer service, but you can when you are skilled in communication, active listening, project management and negotiation. 

Skills are transferable. Skills — like programming and project management — are transferable between companies, roles, projects, and tasks. Competencies are loaded with factors related to roles, like performance expectations, attitudes and behaviors, making them non-transferable between jobs or collaborative projects.

To achieve agility and efficiency and increase retention, many learning teams are shifting to a skills model. How are they doing this? By mapping people’s skills to roles. This helps people improve in their current roles and prepare for future endeavors. How can you do this? Identify key skills needed for roles, empower your people to upskill and reskill in these areas and watch them and your organization grow with the shifts. 

Speaking the Language of Work

Competencies are the language of behavior. Skills are the language of work. And as we all know, leaders most of the time are more concerned with the language of work. “Business leaders very rarely think of work to be done in terms of attributes, behaviors or competencies. Instead, they often think of work as tasks to get done — specific and objective tasks or areas of expertise,” according to Janice Burns, Chief People Officer at Degreed. 

Cisco relied on a competency model but the organization found it difficult to explain, maintain, and measure. The software maker has since shifted to a skills-centered strategy, finding it easier to define. 

“We were able to define roles by skills rather than competencies,” said Josh Clark, Director of Learning & Careers at Cisco. L&D mapped 4,000 job titles to around 200 roles, creating a much simpler and maintainable system.

Expecting your learning team to identify and match every worker’s skills with internal opportunities is unreasonable, especially if it’s done manually. But a purpose-built, user-friendly platform can do that work. And when it engages people by offering them learning opportunities you can use that data to help address growth and business needs. 

“How we’re using the data is extremely interesting,” Clark said. “We loaded all the skills that are relevant to each employee’s role within Cisco. For instance, someone in a PM position will automatically have the set of PM skills loaded onto their profile. When someone logs into their profile for the first time, it is already populated with the skills they have and those they need to build.” This provides both Cisco and individual workers transparency into their abilities and the areas in which they need to grow.

When they first work with skill data, many organizations are reactive, using the data to validate specific ideas. But with more data and reporting abilities, those companies start proactively making decisions. And advanced organizations are predictive, identifying patterns in its people data that point to potential disruptors. 

Should You Use Competencies or Skills?

Because only slight differences exist between the two models, Degreed is able to support whatever one you choose for your organization. That said, we may have thoughts to share about which would be the most efficient and effective approach for your specific organization. Contact a Degreed representative to chat more about skills vs. competencies. 

If you’re not yet ready to scrap the competency management system your company has used for years, you’re not alone. You can still increase standardization, organizational agility and experiential learning based on skills. You can keep your current model in place and simultaneously map skills to job roles to gain a lot of the same benefits as using a skill model. 

In the end, whichever method you choose should be the right fit for your organization and people. Make sure that your model can successfully and efficiently assess your people, identify areas for growth and offer the right opportunities to learn. 

Want to Learn More?

Power workforce change with Degreed Skills. See how you can develop the skills your workforce needs next.

Degreed Skills offers all the capabilities and insights you need to harness the power of skills, from normalized ratings to taxonomies. 

Find out more.

The post Skills and Competencies: What’s the Difference? appeared first on Degreed.

Today’s complex world of work requires a proactive emphasis on resiliency. As a result, every company needs more sophisticated ways of looking at the skills and capabilities of workers to better plan and pivot. 

Business intelligence tools that help solve problems have existed for years. Still, companies don’t often use them to retrieve, report, and analyze data on people’s skills, effectively deprioritizing intelligence and analytics that would otherwise optimize workforce development.

In fact, fewer than half of HR and talent leaders say they have a clear sense of what their people can do. 

That’s where Degreed Intelligence comes in, a first-to-market solution we’ve created to give learning and HR leaders a simple and quick way to access data, intelligence, and tools to visualize workforce skills. Fresh insights into your most valuable asset — your people — help you close skill gaps by deploying the right learning to the right individuals or teams at the right time. And you don’t need a doctorate degree in data science to do it. 

Degreed Intelligence provides a suite of tools designed to help workers, managers, and learning leaders understand and build skills they need across the organization. It’s a cost-effective way to turn that learning and skill-building activity into insights you can use to understand skill supply and demand and make smarter decisions.  

How? By using machine learning to turn signals of skills — like self, peer, and manager ratings, assessments, and project and role experiences — into real-time actionable intelligence.

When advanced skill analytics give you the bigger picture, you’re ready to plan, respond, and be a better strategic business partner. Continuous upskilling? Check. Digital transformation? You’ve got it covered. New company initiatives like diversity and inclusion? You’re ready to go.  

The Right Skills to the Right People at the Right Time

More than half of business leaders (53%, according to Gartner) say a lack of visibility into skills is their top barrier to workforce transformation. 

With Degreed Intelligence as your new L&D superpower, you can prioritize your people’s time and focus your learning budget on the most critical business objectives. And when you quickly mobilize talent to seize new opportunities, you’ve got a better chance of outperforming your competitors. According to McKinsey & Company, companies that mobilize talent efficiently are six times more likely to report higher shareholder returns.

When you track the supply and demand of skills with Degreed Intelligence, you can: 

• Efficiently invest in talent by understanding the skills your people have and need
• Standardize data through integrations with talent and learning tools
• Get critical insights without setup or maintenance from your tech teams
• Automatically keep skill data up to date

And the benefits go beyond you and your learning team.

Your people managers can: 

• Use intuitive tools to match workers to learning resources and projects
• Use skill ratings and assessments to give people better feedback

Your workers can: 

• Get more visibility from managers into valuable learning content, mentors, and experiences
• Receive guidance from managers that helps personalize learning
• Make development a part of everyday work life
• Understand which skills are needed to achieve professional goals

A New Way Forward With L&D Insights

It’s true; numerous intelligence tools are already available. And it’s no secret that other learning technology companies are trying to help organizations make sense of skills. By 2023, 40% of large organizations will have deployed learning analytics technologies, according to Gartner. So we’re giving you the opportunity to get ahead.

What’s different about Degreed Intelligence? Degreed is built largely on skill data — in particular, our unique ability to measure and track skill development over time by weaving the whole process into the one thing people do frequently: learn. And something else they value —  career growth. 

Two tools already in Degreed keep data continually updated with development activity. Skill Coach gives people managers an intuitive toolkit for discovering, building, and rating team skills — to set development goals and target learning where it matters most. Skill Review uses machine learning and skill insights to provide real-time skill intelligence on the skills your business needs as well as who has them, who needs them, and who wants them.

We generate our analytics from that data and then structure them as in-app dashboard reports, visualizations, and insights.

Through a unique partnership with Visier, a leader in people analytics, we’ve developed new algorithms that pull skill data from Degreed and package it into simple and intelligent dashboards. This is much more than an integration between Visier and Degreed. It’s unique, purpose-built software to enhance the Degreed platform and take the complexity out of data science.

For organizations that want to build the skills of today and tomorrow, Degreed now has the only integrated platform that combines the best tools for monitoring and deploying skills with the best tools for driving strategic upskilling. 

Ready to make smarter decisions about your people? Contact us for a demo today.

The post Meet Degreed Intelligence: Skill Data Uniting Learning and Business appeared first on Degreed.

When we sat down to plan the most recent installment of Degreed LENS Lite, we determined that our flagship virtual conference would provide some clarity. 

We started with a question: what the hell is skill data? By definition, skill data includes data points that relate to the capability, demonstration, or definition of a skill. In short, it’s the measurement of what your people can do. The insights we got from learning leaders at Novo Nordisk, Whirlpool, and FICO at the event showed us that how skill data is used can vary significantly between organizations. 

Novo Nordisk: Aligning Strengths to the Business

Skills at Novo Nordisk are vital. For nearly 100 years, the Denmark-based pharmaceutical company has translated the unmet medical needs of people living with serious diseases — diabetes, obesity, rare blood afflictions, and more —  into innovative treatments. Workers there need to be engaged and at the cutting edge of what they do.

“They constantly have to be at the top of their games,” said Derek Mitchell, Global Performance Data Lead. “They can’t just ‘let it be.’”

Deep appreciation for these dynamics means learning leaders at Novo Nordisk think about skill data as a way to understand:

• The company’s bench strength. Do people in analytics, for example, feel confident using visualization tools such as Power BI or Tableau?
• How strengths and weaknesses align to strategic objectives. Regardless of role, leaders expect all workers to have certain skills (for example, skills in digitalization and sustainability). The company can quickly see which skills within a category people have — and where people need to upskill.
• People’s broader interests. Just because someone works in finance doesn’t mean they’re only interested in accounting-related skills. Perhaps they also have skills needed elsewhere by the business.

These insights enable cross-functional collaboration and support agile talent development, Mitchell said. “I often think about contact center environments, where we might have lots of people answering calls and webchat three days a week. Often within contact centers, we will have a significant student population, and so we’ll have data science skills, psychology skills, business development skills. These are just sitting latent within our organizations untapped.”

Using Degreed, Novo Nordisk L&D captures data on how people self rate their current skills and identify others they’d like to learn. By parsing this with information from HR systems — including region, business function, age, or any combination of the above — learning leaders can identify the strengths and weaknesses of a niche cohort in only three mouse clicks, Mitchell said. “This means we can be proactive in bringing solutions to the business. . . to be on the front foot with business stakeholders. We also use this data to power hyper-targeted campaigns.”

Whirlpool: Open and Honest Career Advancement

At Whirlpool, skill data is the lifeblood of a new way to approach learning and agile talent development. It informs L&D guidelines and helps the household appliances manufacturer fill skill gaps. 

To infuse skill data into that process, L&D first determined the purpose of the Whirlpool learning experience, said Rayssa Mederios, L&D senior manager.

The skill development process at Whirlpool has several goals:

• Give people opportunities to master the skills they need for their current roles
• Provide more transparency around career advancement, so people understand the skills they need to move forward 
• Boost employee engagement by giving people a chance to share knowledge and learn from others
• Capitalize on increased engagement to boost productivity, increase innovation, and grow the entire company

Recently, Whirlpool L&D conducted a pilot designed to capture skill data, engaging 300 workers, 70 managers, and 50 subject matter experts in research and development roles.

Using that data, L&D encouraged workers and leaders to have open and honest career conversations, to set more effective personal learning goals, and to create custom, actionable plans for achieving those goals. And using Degreed, L&D created Plans and Pathways customized for specific skill sets.

The early result? Customized personal development plans. New R&D learning targets. And improved resource allocation, Mederios told LENS Lite. “It’s very good to have a third data point of an expert or a subject matter expert sharing their perspective on your skill proficiency… We want to expand.”

FICO: Upskilling for the Future

At FICO, skill data is a tool for informing and creating targeted initiatives and personalized learning plans rooted in agile talent development. They’re directly aligned with the strategic priorities of the global business, which is well known for its credit ratings and provides analytics software solutions to banks, insurance companies, telecommunications firms, retailers, and more.

Unlike skill data, traditional learning data often emphasizes course completions and time spent learning, Chrissy Chamberlain, Sr. Director of Digital Learning, told LENS Lite. “Raise your hand if you’ve ever tried to measure learning effectiveness and tie it directly to your business outcomes. It’s notoriously difficult to achieve and even more difficult to sustain. Am I right? Learning data, in my experience, more often becomes a study of time and motion.

“The same can’t be said of skill data. That’s because business strategies at their core have a set of skill and talent requirements to achieve successful outcomes, not a set of training requirements. And skills are measurable. You can put a scale to it. You can wrap context around it. You can track an upskilling development journey from novice to intermediate to expert, and learning then becomes a supported activity within that journey.”

Because of this, skill development becomes a purpose of learning, Chamberlain said, and measuring skill movement over time becomes a critical metric to agile talent development and employee engagement strategies. 

Focused on a handful of core use cases, FICO uses skill data to:

• Target upskilling by consulting with leaders on emerging business priorities (for example, to increase analytics services, pivot to a new sales strategy, or advance female leaders).
• Create skill plans to support upskilling initiatives and individualized development plans based on baseline and target skill ratings for specific roles.
• Measure skill movement over time and report results like “We’ve accomplished a 15% increase in our capacity to do X.”

Learning leaders enable this process by first creating a sense of psychological safety around skill ratings, Chamberlain said. “We remind colleagues that skills are not part of how we measure performance. We measure performance based on a combination of behaviors and performance-based outcomes. Your skills will be a contributing factor in meeting performance expectations, but they’re not part of how performance is measured. This allows individuals to be very honest with where they are and where they need to go.”

Want To Learn More? 

You can find all the presenters mentioned above, and more, on our OnDemand page. 

Join us in November for LENS LA 2021, where we’ll explore the smartest ways to harness technology and data about the skills people have (or don’t have), so you can make better investments in hiring, managing, and developing all of your workforce.

The post What the Hell Is Skill Data? 3 Ways You Can Use It for Agile L&D appeared first on Degreed.