SimOps 101: How Simulation Reduces Product Development Costs
In 2025, Michelle Ash, CEO of Dassault Systèmes' SIMULIA brand, described a plastic bottle manufacturer that used to produce and crush thousands of physical bottles every year just to test compression performance. With simulation, those tests moved to software. The bottles stopped being destroyed. The savings went directly to the bottom line [1].
That example is small in scale but representative of a pattern that plays out across every major industry: simulation replaces a physical process that was expensive, slow, or wasteful, and the cost difference compounds across every iteration, every product line, and every development cycle.
This guide quantifies that pattern. How much does simulation actually save? Where do the savings come from? And what does it take to capture them?
Why Product Development Is Expensive Without Simulation
Before simulation became mainstream, the standard product development process was built around physical iteration. Engineers designed something, built a prototype, tested it, found problems, revised the design, built another prototype, and repeated until the product worked well enough to manufacture.
This process has two fundamental cost drivers that simulation attacks directly.
Physical prototypes are expensive. Prototype costs vary enormously with complexity. Simple proof-of-concept models can cost a few hundred dollars. Beta versions of complex electronic devices regularly exceed $50,000 per iteration [2]. For aerospace or automotive components requiring specialized materials and precision manufacturing, the cost per prototype can reach six figures. Multiply that by the number of iterations required to resolve all design issues, and prototype expenditure alone can consume a significant fraction of a program's R&D budget. Let alone a product, like a car, with a failure which is discovered after the commercial market rollout.
Late-stage failures are catastrophic. Traditional product development tends to defer rigorous testing until physical prototypes exist. By that point, according to PTC's analysis of simulation-driven design, 90% of product costs are already committed [3]. A major design flaw discovered at this stage does not just cost the price of another prototype. It costs the engineering time to redesign, the manufacturing time to rebuild, and the program time lost while competitors continue to advance. One designer described the experience as "falling through a trap door" [3].
Simulation changes both of these dynamics. It moves testing earlier, makes iteration cheaper, and makes late-stage surprises less likely.
The Four Cost Levers Simulation Pulls
1. Reducing the Number of Physical Prototypes
The most direct cost saving from simulation is reducing how many physical prototypes a development program requires. When engineers can test a design virtually and resolve the majority of issues before committing to fabrication, the number of physical builds drops.
The evidence across industries is consistent. Bicycle frame manufacturer Alloy reduced physical prototypes by 50% after adopting simulation-driven design, while simultaneously cutting time-to-market by 25% [1]. Cummins, working with Siemens Simcenter, achieved a 50% reduction in the number of prototypes required in their engine development programs while shortening lead times [4]. These are not marginal gains. Halving the prototype count on a complex development program eliminates a substantial portion of direct materials and fabrication cost.
2. Reducing Labor and Engineering Costs
Beyond the direct cost of building prototypes, simulation reduces the labor associated with the test-build-revise cycle. Engineers spend less time managing physical test logistics and more time on analysis and design decisions.
PTC's research on upfront simulation in product development quantifies this effect: moving simulation earlier in the design process reduces labor and prototype cost by 26 to 30% [3]. When design-validation cycles that previously took weeks now complete in minutes, the productivity of every engineer in the loop increases. Michelle Ash noted at 3DEXPERIENCE World 2025 that design-validation cycles that previously took weeks now complete in minutes with AI-powered simulation [1].
3. Reducing Quality Assurance and Testing Costs
Simulation does not only replace prototypes. It changes the nature of physical testing when physical testing still happens. Instead of exploratory testing that discovers unknown problems, physical tests become validation tests that confirm what simulation has already predicted.
This shift generates measurable savings. PTC's analysis shows that upfront simulation reduces testing and quality assurance costs by 19 to 33% [3]. Engineers enter physical testing with a much clearer picture of where the risks are, which tests are critical, and what they expect to find. Test programs become shorter, more targeted, and less likely to generate expensive surprises.
4. Expanding Design Exploration Without Additional Cost
One of the less-discussed cost benefits of simulation is what it enables rather than what it replaces. Physical prototypes constrain design exploration: each variant costs time and money to build and test. Simulation makes variants essentially free to explore.
PTC's research found that upfront simulation broadens design space exploration by 40 to 60% [3]. Engineers who can test fifty virtual configurations in the time it previously took to test one physical prototype do not just save money. They find better designs. Simulation's cost benefit is not only in avoiding the bad; it is in reliably finding the good.
What the Numbers Look Like in Practice
Automotive: Ford CFD for Aerodynamics
Ford uses Computational Fluid Dynamics (CFD) simulation to optimize vehicle aerodynamics before physical wind tunnel testing. The result is up to a 10% reduction in drag, translating directly to improved fuel efficiency [5]. More significantly, simulation dramatically reduces the number of wind tunnel hours required, which cost thousands of dollars per hour for full-scale automotive testing.
Medical Devices: Boeing and NIST Benchmarks
The cost savings from simulation are not limited to any single sector. Boeing reported that its use of simulation tools, including CFD and FEA, led to approximately $150 million in annual savings by reducing the need for physical prototypes and testing. A study by the National Institute of Standards and Technology (NIST) found that simulation software can reduce the cost of physical prototypes by up to 50% [6].
Aerospace: NASA and ANSYS
In 2020, ANSYS partnered with NASA to provide advanced simulation tools for analyzing the aerodynamics and thermal properties of spacecraft, enhancing simulation accuracy and reducing the physical test requirements for spacecraft components operating under extreme conditions [5].
Startups: Scaling Without Physical Testing Overhead
Physical testing is disproportionately burdensome for startups, where budget constraints make each prototype iteration a significant commitment. Norwegian startup OptiFloat, developing floating offshore wind turbines, relied on simulation because physical testing in pool tanks and instrumenting test models with sensors is very expensive. As Niels Christian Olsen of OptiFloat put it: virtual testing and prototyping before going into the pool tank was a natural choice, and Ansys delivered reliable results for their complex offshore physics [7].
Cloud HPC: The Infrastructure That Makes Simulation Economics Work
Simulation's cost benefits are real, but they depend on having the compute infrastructure to run simulations fast enough to keep pace with design iteration cycles. A simulation that takes two weeks to complete on an under-resourced workstation does not compress development timelines. It extends them.
This is where cloud HPC becomes a direct lever on simulation ROI. As SimOps has covered in detail in Why Cloud HPC Is the Future: Benefits and Cost Savings, cloud HPC eliminates the capital expenditure of building on-premise clusters, allows teams to scale compute on demand to match simulation requirements, and provides access to the latest GPU hardware without procurement cycles.
Cloud HPC providers offer spot and reserved instances that can reduce compute costs by up to 80% compared to standard on-demand pricing [8]. For simulation teams running high volumes of parametric studies, design of experiments, or optimization sweeps, that discount directly multiplies the number of simulation variants that fit within a given budget.
The practical implication: a team that previously ran 10 design variants per week on an on-premise cluster can run 80 or more on cloud HPC, for comparable or lower infrastructure cost. The cost per design decision drops dramatically, compounding the cost benefit of simulation across the development cycle.
The "Shift-Left" Principle: Why Timing Determines ROI
Not all simulation investment delivers equal return. The timing of simulation relative to the design process is the single most important factor determining how much cost benefit is captured.
Traditional simulation practice placed analysis near the end of the design process, just before physical prototyping, using it as a validation check on a design that was already largely fixed. By the time simulation found a problem at this stage, fixing it was expensive: design changes required revisiting decisions that downstream teams had already acted on.
The shift-left methodology moves simulation to the front of the design process, embedding it from the earliest concept stage. Engineers validate ideas virtually in real-time rather than waiting for a downstream analysis phase. This approach enables rapid iteration, reduced prototyping costs, and smarter decision-making from the outset [9].
The cost impact of shift-left is not linear. Catching a design flaw in the concept phase, before any tooling or downstream decisions have been made, costs only the engineer's time to run a simulation and revise the model. Catching the same flaw after tooling has been committed can cost orders of magnitude more. Simulation's ROI is highest when it is used earliest.
The Operational Side: Where ROI Gets Left on the Table
Engineering teams that have invested in simulation software frequently report that they are not capturing the full potential cost benefit. The reasons are operational, not technical.
Simulation jobs sit in queues because HPC infrastructure is undersized or poorly managed. Engineers wait days for results that should take hours. Mesh generation and model setup consume time that should be spent on design analysis. Results are interpreted inconsistently across teams because there is no shared methodology. Software licenses are idle because workflows are not automated.
These are not software problems. They are process and infrastructure problems. And they are precisely the domain that SimOps addresses. Just as DevOps built shared practices for software infrastructure that unlocked the full value of cloud computing, SimOps is building the framework for simulation and HPC teams to operate with the same efficiency and consistency.
For engineers looking to build operational competency in this area, the SimOps Fundamentals certification provides a structured foundation covering HPC infrastructure, simulation workflow management, and the operational practices that determine whether simulation investment delivers its promised return. For those ready to go further, the SimOps Expert certification covers building portable simulation environments, automating complex HPC deployments, and scaling from laptop to supercomputer.
Quantifying the ROI: A Summary
The research evidence on simulation ROI is consistent across sources and industries:
Prototype reduction: 50% reduction in physical prototypes required, based on documented cases at Alloy and Cummins [1, 4].
Labor and prototype cost savings: 26 to 30% reduction in combined labor and prototype costs from upfront simulation, based on PTC's analysis [3].
Testing cost savings: 19 to 33% reduction in quality assurance and testing costs [3].
Design space expansion: 40 to 60% broader design exploration within the same development budget [3].
Time-to-market: up to 25% reduction in time-to-market from simulation-driven design, with individual cases reporting 50% improvement from AI-powered simulation tools [1].
These numbers do not all apply simultaneously to every program. The actual return depends on where in the design process simulation is introduced, how well the underlying infrastructure supports rapid iteration, and how consistently simulation practices are applied across the team. But they establish the envelope of what is achievable when simulation is used well.
Key Takeaways
Simulation reduces product development costs through four primary mechanisms: reducing the number of physical prototypes required, compressing engineering labor on the test-revise cycle, reducing physical testing and quality assurance costs, and expanding design exploration without proportional cost increases. The cost benefit is highest when simulation is applied early in the design process, before downstream decisions and tooling commitments are made. Cloud HPC is the infrastructure enabler that allows simulation's cost benefits to compound: more variants, faster results, lower cost per decision. Operational practices, not just software, determine how much of simulation's potential ROI is actually captured. Teams that automate workflows, manage HPC resources efficiently, and apply simulation consistently across the design process extract significantly more value than those that treat simulation as an ad hoc tool.
What's Next in This Series?
This is part of SimOps' Simulation 101 series. Related reading:
References
TheAI.com / 3DEXPERIENCE World 2025. (2025). Simulation Meets AI, Rewriting the Product Development Timeline. newstheai.com
StudioRed. (2025). 10 Product Development Costs + How To Estimate Them. studiored.com
PTC. (2025). Simulation Software in Product Development. ptc.com
Siemens. (2023). Cummins uses Simcenter Amesim to cut number of prototypes by 50 percent. resources.sw.siemens.com
Allied Market Research Blog. (2024). Assessing Simulation Software's Impact on Accelerating Product Development. blog.alliedmarketresearch.com
Allied Market Research Blog. (2024). Role of Simulation Software in Product Development. Boeing $150M savings and NIST prototype cost reduction data. blog.alliedmarketresearch.com
EDRMedeso. (2024). Five Innovative Startups That Have Used Simulation to Cut Costs. edrmedeso.com
SimOps. (2024). Why Cloud HPC Is the Future: Benefits and Cost Savings. simops.com
CADD Centre. (2025). The Future of Simulation-Driven Product Development: Trends to Watch in 2025. caddcentre.com
About SimOps
Software development was transformed when teams stopped treating infrastructure as an afterthought and started building shared practices around it. That's what DevOps did for code. SimOps is doing the same thing for simulation.
Simulation and HPC have long operated in silos: different tools, different teams, different workflows, with no shared language or common standards. SimOps exists to change that. We're building a framework and a community where simulation engineers, HPC specialists, and CAE teams can work from the same playbook, share best practices, and push the field forward together.
If that mission resonates with you, this series is a starting point. And the community is where the conversation continues.
