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Jim van Hulst has held several senior leadership roles at EY, ING Bank, ABN AMRO Bank and Johnson Controls International. His previous positions include Director Talent Management, Global Head of Professional Development and Global Learning Technology Leader. 

Jim holds an MSc in Learning Technology from the University of Sheffield and a Bachelor of Education from the University of Arnhem and Nijmegen. He also completed a diploma in Business Management and Leadership at Rotterdam School of Management and earned his MBA from Maastricht School of Management in 2020. He is a regular speaker and the author of numerous articles on learning, leadership, digital transformation and organisational change.

Jim founded Jignite in 2021 to help organisations strengthen learning, leadership and digital transformation.

Designing Training That Sticks in a Digital World

Introduction

We have all seen it. A new CRM or ERP system goes live. Employees attend a two-hour demo that clicks through every screen. They receive an 80-page manual. Three weeks later, half of them are back to their old spreadsheets.

The problem is rarely the people. It is the design of the learning. In this blog I want to share two models that, in my experience, explain why so much training fails and how to fix it: Merrill’s First Principles of Instruction and Cognitive Load Theory by John Sweller. Merrill tells us what good learning needs. Sweller tells us why it so often goes wrong.

What Are Merrill’s First Principles of Instruction?

In 2002, David Merrill compared a wide range of instructional design models and theories. He looked for what they had in common. The result was five principles. His conclusion: learning improves as more of these principles are present.
1. Task-centred: Learning starts with a real, recognisable task from daily work, not with abstract theory. Tasks are offered in a progression, from simple to complex, but always as a whole task.
2. Activation: Prior knowledge and experience are brought to the surface, so new knowledge has something to connect to. A simple question works: “How do you handle this today?”
3. Demonstration: Show, don’t just tell. Use worked examples, modelling, and good-versus-bad examples.
4. Application: Learners practise with the new knowledge and receive feedback. Guidance is reduced step by step, from coaching to working independently.
5. Integration: Learners transfer what they learned to their own work. They reflect on it, explain it to colleagues, or show it in practice.
In short: real task → connect → show → do → own it.

Merrill was critical of “tell-and-test” training, where information is broadcast and then tested. Many system trainings still work exactly that way.

What Is Cognitive Load Theory?

Cognitive Load Theory (CLT), developed by John Sweller from 1988 onwards, starts from how our memory works:
1. Working memory is small. We can only process a few new elements at once, and they fade quickly.
2. Long-term memory is practically unlimited. Knowledge is stored there as schemas: organised patterns of knowledge.
3. Expertise means rich schemas. An expert sees one pattern where a novice sees ten separate things. That leaves the expert with working memory to spare.
Learning, therefore, is building and automating schemas. That only works when working memory does not overflow.

Three Types of Cognitive Load

Five Effects Every L&D Professional Should Know.

Five Effects Every L&D Professional Should Know.
1. Worked example effect: Novices learn more from worked-out examples than from solving problems on their own.
2. Split-attention effect: Explanation and visual on separate screens cost extra working memory. Integrate them.
3. Redundancy effect: Offering the same information twice, such as a voice-over reading the slide text aloud, harms learning.
4. Modality effect: Visuals combined with spoken explanation often work better than visuals with written text.
5. Expertise reversal effect: What helps novices, such as lots of structure, can hinder experienced learners. Support must grow with the learner.

Where Merrill and Sweller Meet.

At first sight, the two models seem to clash. Merrill wants to start with whole, real-life tasks. CLT warns that complex tasks overload novices. The solution is already built into both models:

The model that brings both together best is 4C/ID (Four-Component Instructional Design) by the Dutch scientist Jeroen van Merriënboer, who worked closely with Sweller. 4C/ID uses whole learning tasks, from simple to complex, with support that fades as learners grow. For complex skills in a digital workplace, it is one of the most practical frameworks I know. This model is close to my heart: I have worked with Jeroen van Merriënboer, and my MSc dissertation in Learning Technology at the University of Sheffield was about the 4C/ID model.

In Practice: Rolling Out a New CRM System.

Let’s return to the CRM rollout from the introduction. The classic approach overloads people: the content is too complex at once (intrinsic), switching between manual and system adds noise (extraneous), and there is no real task. Here is how the two models change the design:
1. Start with the task: Build the training around real work processes, such as “handling a customer request”, not around the menu structure.
2. Activate: Ask how people do this in the old system today, and where it hurts.
3. Demonstrate: Give a short walkthrough of that one process. Keep explanation inside the screen and use spoken guidance instead of text blocks.
4. Apply: Let people practise in a sandbox with their own cases. Start with half-completed tasks, then move to full ones, with feedback along the way.
5. Support at the moment of need: In-app guidance and job aids keep extraneous load low after go-live.
6. Integrate: Let super users and floor coaches support colleagues, and let teams share what they now do differently. This is where learning and change management meet.
7. Grow with the learner: Experienced users get less hand-holding and more complex exceptions.

Moving Forward Together.

Merrill gives us the building blocks of effective learning. Sweller gives us the boundary condition: everything has to fit into a small working memory. Together, they turn training from an event into a journey that people can actually follow.
Digital transformation is not about the tools. It is about the people who use them. When we design learning that respects how the brain works, adoption follows.
Are you preparing a system implementation or digital transformation, and do you want learning that really sticks? Contact me and let’s explore how Jignite can help.

See also my other articles related to this field.

External links (authority): Merrill (2002), First Principles of Instruction, ETR&D 50(3); Sweller (1988), Cognitive Load During Problem Solving, Cognitive Science 12(2).

 

The Human Side of a Merger: What Happens to “Me”?

The First Two Letters of Merger Are ‘Me’

When two teams are brought together, leaders often start by discussing structures, responsibilities, processes, reporting lines and organisation charts. Employees usually start somewhere else. The first two letters of Merger are “Me”. What will happen to my role? Will I still have a place in the new organisation? Who will I report to? Will my responsibilities change? Will I have the same opportunities? And, perhaps most importantly: what does this mean for me?

I am currently moving from primarily leading a team on an interim basis to also taking responsibility for a broader transformation in which two teams will come together. That transition reinforces something I have seen repeatedly in organisational change: workforce transformation is not simply an organisational design exercise. It is fundamentally about people. Of course, structure matters. Roles need to be clear, responsibilities must be allocated and processes need to work. But a successful transformation starts earlier.

Why is this change?

First, people need to understand why the change is necessary. A merger without a clear rationale quickly becomes an exercise in uncertainty. Leaders need to explain what the combined organisation should achieve that the two separate teams cannot achieve as effectively today. The next step is understanding what the future organisation actually needs. Which capabilities will become more important? Where do we have duplication? Where are there gaps? What capacity is required? And how can we organise work in a way that creates both quality and efficiency? This is where workforce transformation becomes practical. It means looking beyond job titles and current structures and focusing on future capabilities, skills, roles and ways of working.

Involve people

Involvement is another important principle. Involving people does not mean that every decision is made collectively. It means listening carefully, testing assumptions and using the experience already available in both teams. People often understand operational risks and opportunities long before they appear on a project plan.

Communication also plays a critical role. During transformation, not every question can immediately be answered. Leaders should be transparent about that. There is a big difference between saying “we do not know yet” and saying nothing at all. At the same time, business continues. Clients, colleagues and stakeholders still expect delivery. One of the biggest challenges in workforce transformation is therefore balancing two realities: keeping today’s organisation performing while building tomorrow’s organisation.

For leaders, this requires empathy, clarity and decisiveness. We need to recognise the legitimate “Me” questions people have, while gradually helping them see the bigger picture. Because a merger may start with Me, but a successful transformation ultimately creates a stronger We.

 

Empowering Future Innovators: The Value of Practice in Learning

Introduction

Sometimes, you come across experiences that remind you why investing in education and development is so impactful.

Recently, I had the opportunity to engage with students at a university in the Arnhem-Nijmegen region, brainstorming ideas for AI training programs tailored to employees of a major municipality. The session was designed as a half-day “pressure cooker,” challenging the students to come up with innovative solutions under tight constraints. And what a burst of energy and creativity they brought to the table! Their ideas were not only inventive but also practical, showcasing a deep understanding of how to apply AI to real-world scenarios.

This experience reinforced a critical lesson: creating opportunities for students to practice and apply their knowledge in realistic settings is essential. Why is this important?

Bridging Theory and Practice.

Academic knowledge forms the foundation, but it’s through hands-on exercises that students truly learn to navigate complexities. In our session, the students tackled real-life challenges, learning to balance innovation with feasibility.

Boosting Confidence.

Giving students the platform to share their ideas and receive constructive feedback helps build their confidence. It’s not just about getting the “right” answers; it’s about learning to articulate, adapt, and refine their thought processes.

Encouraging Collaboration.

Brainstorming in groups cultivates essential teamwork skills. Students learn to listen, contribute, and co-create—skills they’ll carry into their future careers.

Cultivating a Growth Mindset.

The high-energy environment of a pressure cooker session pushes participants to think on their feet and embrace challenges. It’s not about being perfect; it’s about showing progress and resilience. These sessions are not just about the content but also about shaping a mindset—one that’s curious, collaborative, and capable of solving complex problems.

For anyone working with students, creating spaces where they can practice, experiment, and learn in real-time is invaluable. The future depends on how well we prepare these bright minds for the challenges ahead. And based on what I saw, the future looks promising! Let’s continue to foster innovation and creativity, one session at a time. What will you do?

Please read my article, including pictures on my LinkedIn profile using this link.

Why I Joined a Dynamic Network for L&D Professionals

From Orange to Purple: Why I Joined the Learning Alliance

Learning Alliance

Today, I leave behind my company’s familiar orange colours and step into the vibrant purple of the Learning Alliance. This shift isn’t just about a new look—it’s about embracing a dynamic network that values creativity, collaboration, and meaningful impact over bureaucracy.

As an independent professional, I’ve found the perfect balance here: the freedom to innovate paired with the strength of working alongside top L&D experts. Together, we merge our skills and ideas, co-create pioneering solutions, and focus on delivering results that truly matter to our clients. Teamwork makes the dream work!

For me, this isn’t just a network—it’s a community of peers who inspire and challenge each other to grow. What sets the Learning Alliance apart is its no-nonsense approach: no unnecessary overhead, just craftsmanship and shared purpose.

If you’re an L&D professional looking to connect, collaborate, and innovate, explore what the Learning Alliance has to offer. It might just be the game-changer you’ve been seeking.

Visit our website (only in Dutch) and see how we can make an impact for you together!

Learning Alliance
Learning Alliance

How to Keep Less Digitally Skilled People on Board.

Successful Change Management Strategies in a Digital World.

How to Keep Less Digitally Skilled People on Board

All abord. Digital transformation brings opportunities for more efficient work processes, but not everyone feels equally confident about embracing new technologies. Some colleagues may feel hesitant or overwhelmed, especially if they are less digitally skilled. It’s your role as project manager or educator to ensure no one gets left behind. By using practical tools, personalised support, and floor coaches, you can make the transition to digital processes accessible for everyone.

Start with Understanding.

The first step in any change is listening. Ask your colleagues what challenges they face and what they need to feel more confident. Some might need extra time to learn new systems, while others may fear making mistakes. Showing understanding and working together to find solutions builds trust and reduces resistance.

Practical Tools to Ease the Transition.

Support your team with tools that make digital transformation more manageable. Consider introducing:

  1. Step-by-step guides: Clear, easy-to-follow instructions with simple language and visual examples.
  2. Instructional videos: Allow colleagues to learn at their own pace.
  3. FAQs: A quick reference for commonly asked questions, offering immediate answers.
    These tools empower employees to practice independently and reduce their uncertainty.

Floor Coaches: Hands-on Support at Work.

One of the most effective ways to support your team is by introducing floor coaches. These are colleagues who are already familiar with the new technologies and are available to assist others. Floor coaches provide:

  1. Personalized guidance: They can address individual concerns and offer on-the-spot help.
  2. Accessible support: Employees can approach them without feeling judged.
  3. Tailored assistance: Coaches can adapt their help to meet the specific needs of the team, such as demonstrating a particular feature.

Floor coaches make the transition smoother and foster trust on the work floor.

Build Confidence Through Practice.

Learning takes time, and not everyone progresses at the same speed. Provide employees with opportunities to practice in a low-pressure environment. Create a test setting where they can explore new systems without fear of making mistakes. Floor coaches can supervise and offer small tips, gradually increasing confidence.

Highlight the Benefits.

Resistance often stems from not understanding the purpose of change. Make sure your team knows why digital transformation is happening and how it benefits them. For instance:

  1. Fewer administrative tasks, freeing up time for more engaging work.
  2. Faster, more efficient processes that reduce workload and stress.

Make it personal: when employees see how the changes make their work easier, they’re more likely to embrace them.

Celebrate Progress.

Every step forward, no matter how small, is worth celebrating. Did someone create their first report in the new system? Acknowledge it. Recognizing progress motivates others to take their own steps and fosters a sense of pride. Floor coaches can play a key role by identifying and highlighting these small successes.

Moving Forward Together.

Digital transformation is not just about implementing new tools but about empowering the people using them. By providing practical tools, floor coaches, and a supportive environment, you ensure everyone can keep up with the changes. Doing so creates a workplace where technology and people grow together.

The Future of Talent Management in a Post-AI World

Introduction

Artificial Intelligence (AI) is transforming industries, and talent management is no exception. As AI technologies become more embedded in human resources (HR), businesses are beginning to rethink how they approach recruitment, performance evaluation, and learning & development (L&D). However, while AI presents numerous opportunities, organisations must balance leveraging technology and preserving the human elements essential to fostering a thriving workforce.

AI-Driven Recruitment: Finding the Right Fit

AI has revolutionized recruitment by automating routine tasks such as resume screening and candidate matching. AI-powered tools like HireVue and Pymetrics analyse not only hard skills but also behavioural traits, enabling companies to assess candidates’ compatibility with the organizational culture. These tools can reduce unconscious biases by focusing on data, rather than human judgment alone. However, this shift has raised concerns about over-reliance on algorithms, potentially overlooking nuanced qualities that make a candidate stand out. For instance, candidates with unconventional career paths may be overlooked by AI systems tuned to find traditional profiles, thereby stifling diversity. To mitigate this risk, HR professionals must use AI as an enhancement, rather than a replacement for human judgment.

AI in Performance Management: Precision but at a Cost?

AI-driven performance management tools can provide precise data analytics to measure productivity, identify skills gaps, and predict employee turnover. Tools like Workday and SuccessFactors use AI to analyse patterns in employee behaviour, offering data-backed insights to managers that can help with more objective performance reviews. While these systems improve efficiency, they can also unintentionally prioritize metrics over meaningful employee engagement. When performance is reduced to numbers and patterns, it can erode trust and alienate employees. Therefore, a key challenge is ensuring that AI tools complement, rather than replace, human interaction in performance evaluations. Managers should combine AI’s data-driven insights with empathetic leadership to maintain motivation and job satisfaction among employees.

L&D and Personalized Learning: Tailored for the Individual

AI is dramatically shifting the L&D landscape by enabling personalized learning paths. Platforms like Coursera and LinkedIn Learning utilize AI algorithms to suggest tailored courses and development plans for employees, making it easier for them to acquire new skills. This personalized approach helps individuals focus on areas where they need the most growth, optimizing their learning experience. However, companies must ensure that the focus on data does not strip away the importance of mentorship and hands-on learning, which remain invaluable for holistic employee development. AI can suggest what to learn but cannot replace the experiential learning that comes from real-world problem-solving and human interaction.

The Human Touch: Balancing AI and Emotional Intelligence

While AI can make talent management more efficient, it cannot replace the emotional intelligence (EQ) required to build strong, engaged teams. Humans are uniquely equipped to understand and respond to the nuances of workplace relationships, empathy, and ethical decision-making—areas where AI still falls short. Leaders in talent management must strike a balance between using AI to improve processes and preserving the human touch that fosters creativity, trust, and engagement. AI should enhance decision-making, not strip it of empathy or individual consideration.

Conclusion: The Future is Hybrid

The future of talent management in a post-AI world will require a hybrid approach that leverages AI’s efficiency while retaining human-centric strategies. Organizations that succeed will be those that embrace AI as a tool to augment human capabilities rather than replace them. By blending AI-driven insights with emotional intelligence, businesses can build high-performing, adaptive, and engaged teams ready to thrive in an increasingly digital world.

References:

HireVue and Pymetrics: Companies leveraging AI in recruitment processes to assess both hard skills and behavioural traits. For more details, see HireVue’s AI capabilities at HireVue and Pymetrics’ approach to AI hiring at Pymetrics.

AI in Performance Management: Tools like Workday and SuccessFactors use data analytics to evaluate employee performance. See Workday’s Insights at Workday and SuccessFactors’ AI integration at SuccessFactors.

Other articles