Option screening
Screen the options before you score them
Separate mandatory requirements from preferences, identify dominated options, and keep uncertainty visible before using a weighted comparison.
Before adjusting weights, ask whether each option belongs in the comparison. An attractive total cannot make an unavailable option available. And if one feasible option is no better on any relevant measure and worse on at least one, a detailed argument about weights may be unnecessary.
Use this screening worksheet before opening the Idea Comparison tool. It helps reduce a list for reasons you can inspect. It does not turn a preference model into an objective verdict or establish facts that have not been checked.
Keep mandatory conditions outside the total
Write the conditions that every viable option must meet. NASA's decision-analysis guidance distinguishes mandatory criteria from enhancing criteria and excludes options that fail mandatory requirements. Apply that distinction before scoring attractive extras.
In an invented craft session, the chosen activity station must accommodate eight participants and use materials available for the agreed session. Those requirements are part of this fictional decision. Another project would need its own requirements and evidence.
Give each requirement one of three statuses: met, not met or unknown. An unanswered availability question is unknown. Hold that option outside a final feasible shortlist until the requirement is resolved; retain it in the record so the reason remains visible.
Sources: NASA: Define criteria for evaluating alternative solutions
Use comparable measures and directions
For each feasible option, record the same measures, units and conditions. Our fictional comparison uses setup minutes, number of supply types offered, and packing minutes. Lower times are preferred; more supply types are preferred within the modest range shown. The club assumes equal material costs and no other relevant differences for this example.
Keep a source or an assumption label beside every entry. A preparation estimate is not an observed preparation time. If one design's figure includes sorting materials and another excludes it, fix the boundary before comparing the numbers.
Recognize a dominated option
An option is dominated for this worksheet when another feasible option is at least as desirable on every included measure and strictly better on at least one. Check the direction of each measure: a larger number can mean a longer delay. The Government Analysis Function places a dominance check before weighting in its decision-analysis process.
This conclusion is limited to the measures and evidence in the comparison. The same guidance warns against discarding an apparently dominated option when an omitted cost could favor it. Check money, effort and other consequential differences before removing anything from the shortlist.
Sources: Government Analysis Function: Checking for dominance
Work through four fictional designs
Design A, prepared trays: eight participants; materials available; twelve setup minutes; eight supply types; ten packing minutes. Design B, divided bins: eight participants; materials available; eighteen setup minutes; eight supply types; fifteen packing minutes.
Design C, compact boxes: eight participants; materials available; eight setup minutes; six supply types; eight packing minutes. Design D, demonstration table: six participants; materials available; six setup minutes; ten supply types; six packing minutes. These are invented inputs, not measurements from a session.
D fails the eight-participant requirement. Its favorable times do not compensate for that failure. Among the feasible designs, A dominates B: A takes less time to set up and pack, while offering the same number of supply types. The example assumes their costs and other relevant properties are equal.
A and C present a real tradeoff within the fictional model. C needs less preparation and packing, while A offers two more supply types. Neither dominates the other. Those differences are suitable for a conversation about preferences and, if useful, a weighted comparison.
Copy the screening worksheet
Decision: What single choice must be made? Scope: Which conditions and time period does it cover? Mandatory requirements: What must be true, what evidence establishes it, and is each option met, not met or unknown?
Comparison rows: What is measured, in which units, and which direction is favorable? Evidence: Which figures are observed, estimated or missing? Omitted differences: Could a cost, limitation or benefit outside the table change the choice?
Pairwise check: Which feasible option is no worse in every row and better in at least one? Record each row supporting that conclusion. Shortlist status: Retained, excluded for a named requirement, held for missing evidence, or dominated under stated assumptions?
Reopening trigger: What changed fact would restore an excluded option? Keep the original entry and reason; screening should leave an explanation someone else can challenge.
Know what weights can change
With fixed favorable-direction scores and nonnegative weights, an option that is no worse in every row cannot receive a lower weighted sum. It receives a strictly higher sum when at least one row where it is better has positive weight. If all such weights are zero, the totals can tie.
That arithmetic does not protect a comparison from mistaken estimates, missing criteria or a different feasible set. If B's preparation estimate is uncertain enough to reverse its relation to A, mark the dominance conclusion provisional and investigate that uncertainty.
Take A and C into the Idea Comparison tool only after defining criteria you can explain. Then test a weight to see which judgments affect the remaining choice. Keep the screening worksheet beside the export so the shorter list has a visible history.