The Dutch maakindustrie is not a side story in Europe’s economy. It is one of the engines that keeps the continent competitive, innovative, and strategically resilient. In 2023, EU manufacturing employed roughly 30.2 million people and generated around €2.5 trillion in value added, making it the largest contributor to EU business-economy value creation. That scale is exactly why delivery reliability matters. When manufacturing execution becomes unpredictable, the impact doesn’t stop at one company’s margins. It ripples through supply chains, investment decisions, and innovation cycles.
In the Netherlands, the stakes are even sharper. The country’s high-tech and advanced industrial base is built on complex products, systems engineering, and collaboration networks. TNO describes Dutch high-tech industry as R&D intensive, reliant on partnerships, and often producing sophisticated systems in relatively small volumes. PwC similarly positions high-tech manufacturing as crucial for long-term prosperity and for major transitions like decarbonization and energy system redesign. In other words: the Dutch industrial advantage is “high complexity, high value”.
And that’s precisely the tension. The maakindustrie is:
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Highly innovative (R&D intensive, faster cycles, more variants)
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Capital intensive (specialized people, labs, equipment, suppliers)
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Increasingly complex (hardware-software integration, compliance, interdependencies)
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Under pressure to deliver faster and more predictably, even as uncertainty grows.
Meanwhile, manufacturing organizations are running more projects than ever, often simultaneously:
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product development and platform roadmaps
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engineering changes and variant proliferation
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automation initiatives and smart factory programs
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digital transformation and data programs
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sustainability and compliance programs.
This is where many leadership teams hit the same wall: ambitious portfolios, finite engineering capacity, and a delivery system that was never designed to handle this much parallelism. The result is a strategic capability gap, not a tooling gap.
This article explores how manufacturing companies regain control using integrated planning, how Critical Chain Project Management (CCPM) fits manufacturing realities, and why this matters for the future competitiveness of the maakindustrie.
The challenge: project complexity in manufacturing portfolios
Most manufacturing organizations today operate in a genuine multi-project environment: multiple projects share the same constrained resources, while uncertainty and complexity are structurally high. In practice, that looks like:
1) Many parallel projects competing for the same expertise
Specialists become the portfolio bottleneck: systems architects, verification engineers, embedded developers, certification experts, commissioning engineers, prototype shops, test rigs. These are not resources you can “scale” quickly without quality trade-offs. When too many projects draw from the same limited pool, the portfolio begins to behave like a traffic jam: everyone moves, but nobody arrives.
2) Multitasking and context switching that quietly destroys throughput
Engineering work is “deep context” work. Requirements, interfaces, design rationale, test evidence, supplier constraints, risk assumptions. When people switch between complex tasks, the system pays a tax in reorientation time and increased errors. Cognitive research on multitasking consistently shows measurable switch costs. In an engineering portfolio, that cost compounds because the “context” is heavy and often distributed across tools and teams.
3) Unpredictable delivery timelines, even when teams are competent
Many manufacturing delays are not caused by a lack of skill or effort. They come from queues and dependencies. Work waits for specialists. Work waits for test rigs. Work waits for a decision. Work waits for a supplier input. Then the plan updates too late, and leadership sees risk only when the deadline is already close.
4) Low portfolio visibility and weak prioritization signals
A familiar symptom: everyone can report status on “their project”, but nobody can confidently answer:
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What is the portfolio constraint this quarter?
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Which projects must be protected to improve total output?
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Where are we overcommitted, and what should we stop starting?
Without portfolio-level visibility, companies tend to default to local optimization: keep everyone busy, start everything, push harder. That often produces the opposite outcome: longer lead times and lower on-time delivery.
5) Hybrid execution, Agile teams plus traditional governance
Manufacturing portfolios increasingly combine Agile delivery (software, data, controls) with stage-based planning (hardware, compliance, supply chain readiness). That hybrid reality raises coordination demands and makes static planning less reliable. When tools and governance can’t unify these modes, teams build workarounds. Workarounds create blind spots. Blind spots create surprises.
The downstream consequences are real and costly:
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delayed innovation (work stuck in queues, slow learning cycles)
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missed customer commitments (plans not resource-realistic)
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overloaded specialists (burnout risk, quality risk, attrition risk).
Why traditional project management tools are not enough
Most manufacturing organizations are not “bad at project management.” They often have task tracking, reporting, and schedules. The issue is that many tools and practices are optimized for single-project control, not portfolio flow.
Many tools primarily provide:
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task tracking and progress reporting
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static planning
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dashboards that summarize, but don’t explain.
What manufacturing leaders increasingly need is different:
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portfolio-level prioritization that is operational, not political
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resource capacity insight that reflects real constraints
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integrated planning across multiple projects, not isolated schedules
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early warning signals that indicate risk while there is still time to act.
A useful way to phrase it: if the portfolio is the strategy, then capacity is the budget. Any planning approach that ignores shared constraints is planning with fictional resources.
This is why manufacturing project portfolio management is becoming a board-level capability. It determines whether the organization converts engineering capacity into delivered outcomes, or just keeps everyone busy.
The approach: Critical Chain Project Management
Critical Chain Project Management (CCPM) applies the Theory of Constraints to projects. Its core premise is simple and uncomfortable: in multi-project environments, performance is governed by constraints, especially resource constraints. Optimizing each project locally does not optimize the system.
CCPM brings manufacturing-friendly principles:
Focus on the constraint
Instead of treating all projects as equal and trying to accelerate everything, CCPM asks: what is the true limiting factor? A specialist group? A test asset? A supplier-driven lead time? Then it plans to protect and synchronize around that constraint.
Resource-realistic scheduling
CCPM accounts for resource dependencies, not only task logic. The “critical chain” reflects the path constrained by both precedence and shared resources. This matters in engineering portfolios where specialists connect projects more tightly than task networks do.
Buffer management as an early-warning system
Rather than hiding safety time inside every task estimate, CCPM aggregates uncertainty into strategic buffers. Progress is tracked against buffer consumption, creating clearer signals than percent-complete reporting. This provides actionable warnings earlier, when intervention still matters.
Reduce multitasking by controlling work-in-process
Multi-project delay is often a work-in-process problem. When too many projects run concurrently, queueing and context switching explode. CCPM explicitly limits overload by sequencing release, which improves flow in the same way WIP control improves production performance.
Evidence: measurable outcomes in real environments
CCPM and TOC-style integrated planning have delivered strong results in industrial settings. Beyond widely cited cases in aerospace maintenance, there are highly relevant examples closer to the manufacturing world that A-dato supports:
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Endress+Hauser (Process Automation, 500–1,000 employees, Switzerland):
Reported a drop in deadline delays from 50% to 25% within 18 months, and a threefold increase in throughput with the same resources. Their framing is telling: “Our portfolio instead of my project.” The result was clearer priorities and reduced harmful multitasking.
A senior leader described the change as: “This is more successful than anything we have ever wanted from this change process… CCPM is simple, though not easy, yet it is worth it.” -
Bruns (Netherlands, 100–200 employees, developer and producer of exhibitions and exhibits):
After adopting Theory of Constraints, Bruns reportedly minimized the need for extra capacity significantly, reduced an installation budget overrun profile from 150% down to 90%, increased employee engagement, enabled clearer prioritization and autonomy on the shop floor, and reduced reliance on external freelance capacity. -
MEIKO (Professional warewashing, 2,000–2,500 employees):
LYNX became established across a wide range of MEIKO projects over time, with MEIKO stating an intent to shape the future of their project and portfolio management with LYNX for the long term. -
Diamond Aircraft:
An internal survey quote captures a common benefit in distributed engineering environments: “A program like LYNX really helps to increase the output of the development and also to keep the output high during times where direct coordination of employees is reduced.”
These aren’t “feel-good” outcomes. They are signals that when prioritization becomes portfolio-driven, and planning becomes constraint-aware, organizations can unlock throughput without adding headcount.
The role of software: LYNX as an integrated planning layer
A common failure pattern is this: organizations understand the principles, but cannot sustain them because planning is fragmented across spreadsheets, disconnected schedules, and siloed execution tools.
Integrated planning needs a reliable layer that can:
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represent the portfolio as a resource-constrained system
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keep priorities consistent across projects
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make risk visible early
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connect portfolio commitments to execution reality
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absorb change without losing coherence.
This is the role that LYNX by A-dato is designed to support.
LYNX enables organizations to:
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build realistic integrated plans across projects
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manage resource conflicts and capacity constraints
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monitor project health through buffer management
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maintain a single, integrated portfolio overview
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connect planning with execution tools like Jira, Azure DevOps, MS Project, and Excel.
Importantly, the intent is not to rip and replace existing execution tools. In modern manufacturing environments, engineering delivery is distributed across specialized systems. The planning layer should unify reality, not fight it.
Where integrated planning delivers the most value in manufacturing
Integrated planning becomes particularly powerful in environments where complexity is structural, not occasional:
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machine building and high-tech systems (many interfaces, long validation cycles)
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engineering-to-order companies (customer delivery plus platform evolution)
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R&D-driven manufacturers (innovation portfolio plus operational commitments).
In these environments, the practical advantage isn’t a “perfect plan.” It is a portfolio operating system that repeatedly answers:
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What should we start, what should we delay, and what should we stop?
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Which constraint determines our delivery capability this quarter?
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Which few projects must be protected to maximize portfolio output?
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Where is risk building up, based on buffer health, not late milestones?
This is the heart of modern manufacturing project portfolio management: making prioritization operational and capacity real.
ESEF Maakindustrie 2026
ESEF Maakindustrie is widely positioned as one of the key meeting points for the manufacturing industry. The 2026 edition takes place 10–13 March 2026 at Jaarbeurs Utrecht.
It is where professionals compare approaches to automation, production technology, sustainability transitions, and increasingly, the less visible but decisive layer: whether organizations can actually deliver complex portfolios with predictable outcomes.
A-dato will be present at ESEF Maakindustrie 2026 and welcomes conversations with manufacturing professionals who are working to improve project delivery predictability and regain control over portfolio flow.
Conclusion
For the modern maakindustrie, competitive advantage depends on more than engineering excellence. It depends on whether the organization can convert finite engineering capacity into delivered outcomes, reliably, across many parallel initiatives.
The evidence points in a consistent direction: in multi-project environments, performance improves when organizations reduce overload, plan realistically around constraints, and manage using early-warning signals rather than late-stage surprises.
Critical Chain Project Management offers a pragmatic portfolio-level operating system for exactly this. And when integrated planning is supported by software, it becomes sustainable, scalable, and visible across the organization.
If you are attending ESEF Maakindustrie 2026 (10–13 March, Jaarbeurs Utrecht), the A-dato team would be happy to meet and exchange perspectives on improving project performance and portfolio flow in complex manufacturing environments.
Sources and References
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Eurostat.
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https://ec.europa.eu/eurostat/statistics-explained/index.php/Businesses_in_the_manufacturing_sector -
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https://publications.tno.nl/publication/34640945/W2sLVo/kappen-2023-hightechindustry.pdf -
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https://www.pwc.nl/nl/actueel-publicaties/assets/pdfs/made-in-nl.pdf -
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A-dato Support.
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A-dato Support.
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A-dato.
Stop surviving with tools that weren’t built for hybrid project environments.
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A-dato Support.
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A-dato.
LYNX planning overview graphic.
https://www.a-dato.com/wp-content/uploads/2025/06/Frame-49-1024×261.png -
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Building a flexible supply chain in low-volume, high-mix industrials.
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