Context

Siemens Gamesa operates in a high-uncertainty R&D environment, developing wind turbine platforms involving multiple engineering disciplines, mechanical, electrical, hydraulics, aero design, manufacturing, procurement, and quality. Typical R&D cycle times were approximately two years, with increasing pressure to reduce this to nearly one year, implying a ~50% reduction driven by market demands.
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Business Challenge

Despite strong engineering capability, planning and execution were consistently constrained by structural issues. There was high uncertainty in scope and sequence of work, and iterative design cycles often led to spillovers across phases, commonly referred to as “travelled work.” At the same time, there was limited visibility into how work actually flowed across functions.

Planning was heavily dependent on static, complex schedules that were difficult to build and maintain, and in practice, were rarely followed during execution. Given this complexity, teams defaulted to local optimization, focusing on what was manageable at an individual level rather than what was optimal for the system.

In practical terms, this translated into significant execution inefficiencies. Projects planned for a few months could extend dramatically, with one instance stretching from 2.5 months to 2.5 years. Milestone tracking at actionable levels was weak, and re-prioritization became frequent and reactive.
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Intervention: Change Started from Planning Itself

Instead of forcing detailed planning upfront, Siemens Gamesa shifted its approach by implementing a Two-Tier Task structure.

At the first level, the entire R&D cycle was structured into approximately 50 Tier-1 tasks. Each of these tasks clearly defined inputs, outputs, and the required cross-functional team. Importantly, this level avoided forcing micro-level sequencing and was designed to be intuitively understood and validated by experts. This simplicity enabled senior experts to review and validate the entire process within minutes, creating alignment and clarity across the organization.

At the second level, detailed execution was managed within each Tier-1 block. These Tier-2 tasks were typically maintained within a duration of one to three weeks, allowing teams to retain flexibility in handling changing sequences, design iterations, and inherent engineering uncertainty. This separation ensured that planning did not attempt to over-specify work upfront, while still providing sufficient control during execution.
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How the Approach Addressed Core Challenges

This structure directly addressed the underlying issues in execution. Uncertainty in scope and work sequencing was absorbed at the Tier-1 level, where the focus remained on defining what needed to be achieved rather than prescribing an exact sequence. This allowed teams to adapt without losing alignment.

Design iterations and spillovers were reduced by grouping related work into logical “boxes” executed by the same teams, minimizing cross-phase rework. Cross-functional alignment improved as eachTier-1 task inherently defined the required disciplines and inputs, eliminating ambiguity in team formation.

At the same time, planning effort was significantly reduced. Instead of building large, static schedules with thousands of line items, planning shifted toward establishing structural clarity. This enabled teams to focus on execution within defined blocks of work, reducing fragmentation and coordination overhead, and ultimately improving flow.
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Execution Approach

The planning process began by mapping the actual workflow through structured sessions with domain experts. Rather than relying on assumptions, the approach focused on capturing how work was truly performed. This was done iteratively using workshops, post-it mapping, and repeated validation loops until a consistent structure emerged.

Duration estimates were based on expert judgment and were found to be within approximately ±10% accuracy. To manage uncertainty, task durations were reduced to around 70% of the estimated time, with the remaining uncertainty absorbed through an aggregated buffer of approximately 30%.
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Results (Initial Phase)

In the conceptual design phase, Siemens Gamesa achieved approximately a 50% reduction in cycle time. Alongside this, there was a measurable improvement in quality outcomes, including adherence to cost targets and higher completeness of documentation. This also enabled earlier engagement with customers.

Equally important was the impact on execution stability. Once the Tier-1 structure was visible, organizational anxiety reduced significantly. Teams were no longer required to manage the complexity of the entire system at once and could instead focus on the next priority, improving both clarity and decision-making.
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Testimonial

“We were under pressure to significantly reduce our R&D cycle times, but the way we were planning and executing projects wasn’t supporting that. The plans were complex, difficult to maintain, and in practice, not followed.

What changed for us was shifting away from trying to detail everything upfront. Instead, we structured our work at a higher level, aligned cross-functional teams clearly, and managed execution within that structure.

In our conceptual design phase, we were able to reduce cycle time by roughly 50%, while also improving the quality of our outputs and meeting our cost targets.

The approach brought clarity. Our teams could see how the work flows, focus on priorities, and make better decisions without getting lost in the complexity.”

— Rob Fuller
Director of Engineering, Siemens Gamesa

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‍Key Learning

The core learning from this implementation was that clarity at the right level matters more than excessive detail. Tier-1structure provided the alignment and confidence required for execution, whileTier-2 handled variability where it actually existed.

It also became evident that organizations often do not have an explicit understanding of how work flows, as critical knowledge typically resides within experts. Structuring this knowledge creates immediate value. Finally, separating planning from execution proved essential, planning provides direction, while execution requires dynamic adjustment. As complexity reduced, buy-in improved, and teams moved from resistance to participation.
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Conclusion

Two-Tier Task structuring did not simplify the work itself. It simplified how the work was understood, aligned, and executed.

In a high-uncertainty R&D environment, this shift enabled faster decision-making, reduced rework, measurable cycle time reduction, and better alignment across functions, without increasing planning effort or complexity.

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