Importance-Performance Analysis
Updated 2026-08-10
INTRODUCTION
English translation pending.
CORE DEFINITION
Importance-Performance Analysis was introduced by Martilla and James in 1977. Respondents rate how important each attribute is and how well the organization performs on it, and the two scores place each attribute in one of four quadrants. High importance with low performance is the concentrate-here quadrant, where improvement effort pays most. High importance with high performance is keep-up-the-good-work. Low importance with low performance is low priority. Low importance with high performance is possible overkill. The method assumes the two ratings are measured independently and from a defensible source.
SCAFFOLDING EFFECT
Reduce cognitive load
- Use dual rating: score importance and performance separately for every attribute. - Use quadrant targeting: send improvement effort to the high-importance low-performance cell first. - Use overkill review: cut or redeploy spending on attributes that are strong but unimportant to customers.
Anchor fast decisions
Improvement effort is usually allocated to whatever is visibly weak or internally interesting, which misses attributes that matter to customers but are not salient internally. Separating importance from performance produces two independent axes, and their combination identifies where the gap between what matters and what is delivered is largest. That cell concentrates effort where it changes customer perception, while the overkill cell reveals spending that can be released. Placement depends entirely on the ratings, so the analysis is only as good as the sample.
MINIMUM ACTION
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Source support: Explicit
- link.springer.comhttps://link.springer.com/rwe/10.1007/978-3-319-01384-8_371verified
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