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# 3 Ways to Reduce Experimentation Costs in Product Development
[Oliver Franz](https://blog.minitab.com/en/blog/author/oliver-franz) | 6/4/2026
Topics: [Design of Experiments - DOE](https://blog.minitab.com/en/blog/tag/design-of-experiments-doe), [Research and Development](https://blog.minitab.com/en/blog/tag/research-and-development), [Minitab DOE by Effex](https://blog.minitab.com/en/blog/tag/minitab-doe-by-effex)
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[R&D teams](https://www.minitab.com/en-us/solutions/role/research-and-development/) are under constant pressure to deliver results faster while working within limited budgets, materials, and equipment.
Experiments can expand the need for developmental resources as new knowledge is gathered, which adds to the challenges that R&D teams face. A promising idea turns into a long cycle of testing. New variables are introduced, results raise additional questions, and experimental scope grows. More runs are added, more materials are consumed, and timelines begin to slip.
This is why R&D tends to be an expensive endeavor. Experimentation is essential to development; however, costs can quickly add up due to a lack of structure.
Reducing cost and waste in R&D requires a more disciplined approach to how experiments are planned, prioritized, and executed. With [Minitab](https://www.minitab.com/en-us/), R&D teams can reduce unnecessary runs, focus resources on high-impact experiments, and reach reliable conclusions faster.
## Why do R&D experiments become costly and inefficient?
R&D costs increase when experimental effort is spread too broadly. Teams often test too many variables without clear prioritization, or rely on one-factor-at-a-time testing that fails to reveal how inputs work together.
As a result, experiments multiply, insights take longer to emerge, and resources are consumed without proportional value. This leads to higher material usage, longer timelines, and repeated rework.
A more structured approach helps teams control experimental effort and reduce unnecessary cost.
1. Reduce experimental runs with smarter experiment design
One of the fastest ways to reduce R&D cost is to precisely determine the optimal number of test trials needed to meet development objectives.
[Design of experiments (DOE)](https://support.minitab.com/en-us/minitab/help-and-how-to/statistical-modeling/doe/supporting-topics/basics/phases-of-a-designed-experiment/) allows engineers to evaluate multiple factors simultaneously instead of testing variables in isolation. This makes it possible to identify critical inputs earlier and eliminate unnecessary trials.
With Minitab, teams can identify which factors matter most early in the process, avoid redundant experiments, and reach optimal settings with fewer runs. Fewer experiments means less material consumption and faster progress toward validated results.
### Run fewer trials without sacrificing insight with Minitab DOE by Effex. [](https://blog.minitab.com/hs/cta/wi/redirect?encryptedPayload=AVxigLL1MnoAAY6xnFrYGmoyIiMKB%2F5%2B7ukq7GZ5FAncYFSEZU2L0DFnwcs5faz5lwgIoi58zencV7W2yhUdD7vO0pfrpHdsrP4b1ylNpUXaKMO%2FEKJK%2B6Vsc%2BaLPWIJeh3LXnUc7ChQcESnDcknkCEsKB%2FYihtker%2B41FCqGnv6ewx3OnvcuYg49DAKJM%2BgGZ3rmOsNFZsJFDA70I00cIXfoUg%2Bl3yH9mLO5toz5tYnA4HcAWrwZKX%2B4DpkbDdIGW%2Fry%2Fw%3D&webInteractiveContentId=214356240017&portalId=3447555&hsLang=en)
**2. Prioritize high-impact experiments to minimize resource waste**
Waste increases when experiments are not aligned to the variables that drive outcomes. Broad test plans and poorly defined conditions often produce runs that add little insight while consuming materials, tying up equipment and facilities, occupying valuable technical experts, and extending development timelines.
Minitab helps teams focus experimental effort where it delivers the most value by [screening out low-impact factors early](https://blog.minitab.com/en/blog/3-things-rd-teams-should-know-about-advanced-doe?hsLang=en), concentrating testing on critical variables, and adapting experiment plans based on incoming data.
This ensures that materials, technical time, equipment capacity, and budget are spent on experiments that move product and process development forward, not on exploratory runs that slow decisions or divert scarce resources from higher-value work.
[](https://event.on24.com/wcc/r/5377226/FE4303AF8175AAA56B8C14EAD5912579)
Watch our recent webinar on-demand to learn how predictive analytics and DOE help R&D teams make faster, more confident development decisions.
### [](https://blog.minitab.com/hs/cta/wi/redirect?encryptedPayload=AVxigLLWTUTKiie999x3BZDTS%2F0pF7ytKLYkchcj52lHyHu1YYIgp96sHuXanQLmGtcbuJ9kwLIK8x2T35fi%2FHs1UYOjh0QAk0ot1YNxnnPBom1SJff18CmQcfglu4BDxriNGpVkqEAxg2%2FpXOkpIn%2Fw3QaB5fsiW3tc1r6PIdLFrw6d7G%2BmsOemOKjrQ%2BJ2nfYIImw5dAgLO7lBR8xFvzSjPsoUERGL9f6%2BKQ%3D%3D&webInteractiveContentId=214356341660&portalId=3447555&hsLang=en)
**3. Define the design space to focus controls where they matter most**
DOE provides useful information across an entire design space, not just individual test conditions. Without this broader view, teams may rely on isolated results, apply controls too broadly, or miss the operating conditions that most strongly influence product quality.
Minitab helps teams model relationships between key factors and outcomes, visualize the design space, and identify the combinations of settings that produce reliable, repeatable results.
With a clearer understanding of where defect risk is lowest, technical teams can focus operational controls on maintaining products and processes within robust areas of the design space, improving confidence in scale-up and reducing the likelihood of defects.
### See how smarter R&D supports the factory of the future.
## [](https://blog.minitab.com/hs/cta/wi/redirect?encryptedPayload=AVxigLLNqNIs2Ikqvzd2WMroU3OhcbyCHzIl2EFqrZnawHRYb2noebNF9G0in4KvncIJkYdYq2JUl%2BPfP27j3hhG60Bh00wpcqiLfbViMKxUanCF4C%2BwFFYN8AZXrICIVyDy0q5T02xhWohVSvlqU%2Ft%2Bm%2BbfaBGGvxx%2F6tW1EjBWedpbe%2BtzdKRD3cDLcp%2B2aKhcUM79R%2FN4DBrVipaoPSoYVTpUby5Cbf7hPNnqcP70TA%3D%3D&webInteractiveContentId=214356341530&portalId=3447555&hsLang=en)
## Reduce cost and waste to accelerate R&D
Reducing cost in R&D should be centered on making every experiment count.
By improving how experiments are designed, prioritized, and analyzed, R&D teams can reduce waste, shorten development cycles, and make better use of limited resources. Minitab supports this approach by helping teams optimize experiments, reduce unnecessary effort, and turn data into decisions faster.
### Talk to our team to see how DOE and predictive analytics can help your R&D team reduce waste, move faster, and make more confident decisions. [](https://blog.minitab.com/hs/cta/wi/redirect?encryptedPayload=AVxigLJocP19E3nA91fN3gZduX8IM1AOVy252yxGPO0vVTx9VdGsXrRRSYFcqgkDrU0rsnxmyLH52PNDnHldTEU3M30R%2BF%2FFbAZMzj0RDfd3Fm8gQn2zFgNj2ESFIC4q9B4hx6QGbls5%2FZCzUswhiAimKUU5dEIYucOuIHkx%2Fda%2B0Phhi4Rr2gvHLt4mtlrzTvk38KA%3D&webInteractiveContentId=214356341908&portalId=3447555&hsLang=en)
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