Designs

The design decides how PM Optimizer explores the combinations of your factors. It is the trade-off between how thorough the search is and how long it takes.

The four choices

• Full factorial: runs every combination of every factor level. Complete, but the number of runs climbs fast, and the card warns you when it does.
• Fractional: a structured subset of the full grid that still separates the main effects, for far fewer runs.
• Smart coverage: spreads a set number of points evenly across the whole factor space, then adds more around the areas that look best. A slider sets the budget.
• Optimizer: searches for the best settings, learning from every run and choosing where to look next. It stops when better results stop coming or the budget is spent. Covered in automatic optimization.

Each card shows how many points it will run, and the count updates as you add or remove factors, so you can weigh cost against thoroughness before you start.

Find out what matters first

Before you commit to a full experiment, the screening panel points out which settings actually move your result. It runs a small, efficient set of points, estimates each factor’s effect, and marks the ones worth keeping.

Screening answers the first question of any study: of everything I could change, which few things matter? Drop the factors that do nothing and the real experiment gets much smaller and much faster.

Which to use

• Use screening or fractional when you have several factors and want to find the important ones cheaply.
• Use full factorial when you have only a few factors and want the complete picture, including how they interact.
• Use smart coverage to map a wide space without running everything.
• Use the optimizer when your aim is to find the best configuration rather than to study every effect.