TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a multi-criteria decision method that InnoBee offers as an alternative to simple weighted-average scoring. Instead of just averaging a judge's scores across criteria, TOPSIS measures how close each submission is to a hypothetical "ideal" entry (the best possible score on every criterion) and how far it is from a hypothetical "worst" entry — then ranks submissions by that combined distance.
In practice, this tends to reward submissions that are strong and balanced across all of a challenge's criteria, rather than submissions that are exceptional on one dimension but weak on others — useful for challenges where creators genuinely want a well-rounded winner rather than a specialist one.
Challenge creators choose between standard weighted scoring and TOPSIS when they set up judging criteria, and can preview how each method would rank the same set of sample scores before the challenge goes live, so there are no surprises once real submissions start coming in.
