How Bredenoord built a unified skill matrix to speed up onboarding and deployment

About the Client

Bredenoord is Europe's go-to specialist for rental and maintenance of mobile power solutions. From compact 15 kVA units that keep construction sites lit to 2 MW containerized systems that back up entire data centers, their generators power critical operations in more than 50 countries.

Founded in the Netherlands in 1937, the family-owned company now employs 450 people across eight depots, with technicians, truck drivers and commercial employees working side by side.

Challenge: When Informal Knowledge Hits Its Limits

Bredenoord relied on an apprentice-style model: new employees shadowed veterans until they could perform tasks solo. Skills lived in heads and notes, which worked - but did not scale with the company.

Four pain points forced change:

1. Slower onboarding. Growth in the company meant hiring dozens of mechanics at once. Getting each new starter productive could take months because no one could see efficiently, at a glance, who could teach which repair step.
2. Cross-team redeployment. Large-scale events can cause a rise in demand. Dispatching the right experts to the right depot required lots of phone calls between supervisors.
3. Many versions of disjointed skill matrices. Different teams had built their own Excel sheets over the years, each with unique structures and lots of overlap within the skills database.
4. No fitting training program. The technical training courses on offer were chosen based on good feeling. It has not yet been possible to determine objective requirements. As a result, not all of the training courses that were actually needed were included in the programme, and it was not always possible to assign the training courses to the right participants.

Solution: A Pragmatic, Universal Skill Matrix

edyoucated's Skill Architect kicked off the project together with the Bredenoord team to identify the steps required to move from multiple disjointed skill matrices to a unified data-driven skill framework. Through a series of workshops, we worked closely together with the client to understand needs and requirements regarding their skill matrix. A pragmatic solution, granular enough to serve the different use cases, was required.

Step 1 - Building the skill structure

• Before consolidating the data, we reviewed the design criteria with the client team.
• Building an effective skill taxonomy required decisions about the granularity level, skill wording and descriptions, hierarchy structures, scope and proficiency-level design.
• We aimed for the right level of granularity, while grouping similar items and maintaining a sufficiently high granularity to ensure practical usability for the end users.
• We settled on a three-level hierarchy with skill categories, skill chapters and skills with clear naming conventions for skills and clusters.

Step 2 - Consolidating the data

• Once the structure was defined, we merged all nine Excel sheets into one master table containing every skill, skill category and required skills for each separate team.
• Adding a “skill category” field (e.g., Products and Materials, Assembly, Postrental/Maintenance) and a “skill chapter” field turned scrolling nightmares into filterable views that managers could now scan in seconds.

Step 3 - Right sizing the granularity

• Technicians had logged a lot of skills. Rather than deleting detail, we grouped similar skills and defined an optimal level of detail to support decision-making for business users.
• The result: 341 core skills, clustered around 89 skill chapters and 20 skill categories, each clearly named and defined.

Step 4 - Extract Skills from Job Profiles and Match Skills to Profiles

• In addition the skill matrix, we supported the client in the process of extracting additional skills from selected job profiles
• Our AI-supported system parsed 17 job descriptions to build skill profiles and aligned them with the consolidated skill matrix.

Step 5 - Bring it to practice

Bredenoord was already using a three-level proficiency model and favored “training on the job” over classroom sessions. We retained both approaches while integrating e-learning links to help teams further develop their skills. Everything was consolidated into one user-friendly spreadsheet.

Results: Clear Visibility, Faster Decisions

Individual employees have been and continue to be assessed within the company. This means that there are not only target goals for individual skills and job profiles, but also an actual overview of the current skill level of employees. This knowledge helps to develop and offer training programmes that are precisely tailored to the needs of the employees. In addition, the skill matrix has already been used to process an 8D report, which made it possible to check the extent to which various employees require further training. Bredenoord wants to further intensify the use of skill matrices and expand the overviews into a useful tool for managers. “Insert quote from Bredenoord”

Why the Project Worked

1. Language of the shop floor - We avoided HR jargon and kept names technicians recognize.
2. Incremental, not disruptive - By retaining the three-level scale and on-the-job ethos, adoption felt easier than developing a completely new standard.
3. Data you can hold - While a software solution would have been even better, adapting fast and building out a skill matrix in Excel helped the client to get adoption fast - while maintaining the option to scale through a skills-based system later on.

Thanks to edyoucated's advice, I could be sure that we were on the right track and not getting bogged down. The project is enormous and involves many internal resources. Thanks to the thorough preparation of the skill matrices, managers had an ideal basis for assessing employees. The skill matrices are already being used in some cases during onboarding, and we will now continue to work on making them a sustainable management tool within the company.— XXX, Bredenoord

‍