The Measurement Matrix


Nichols, Alice E.   (1990, ASQC)   IDO, Burlington, MA

Annual Quality Congress, San Francisco, CA    Vol. 44    No. 0
QICID: 9462    May 1990    pp. 276-282
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Article Abstract

White collar employees at all levels of organizations frequently freeze when faced with the task of choosing measures that can verify accomplishments and prevent future problems. This paper will present a model to help unfreeze such managers, helping them to build a common language and approach to measurement, both within and between organizations. Frequently managers measure nothing, in fear of choosing a set of measures that are incomplete and that therefore might, by their exclusion, be meaningless or misleading.

Multiple risks threaten every manager trying to design a comprehensive set of measures. One is that an incomplete selection can mislead and misinform. A second is that measures chosen as indicators of success are powerful drivers of behavior. You will create expectations and shape behavior by the measures you choose.

This paper will present a simple yet thorough matrix to help anyone selecting measures to do so comprehensively. The model involves classifying measures in two ways and then applying a matrix analysis. The steps are as follows:

  1. List the measures that you feel will most thoroughly track success of your work.
  2. Classify each measure as a result (what is to be accomplished, delivered, or achieved) or process (how I want to perform my work).
  3. Classify each measure as serf (what is important to me personally -- how "T" will judge success) or customer (what my customer would choose to track).
  4. Plot your measures by placing them in a two-by-two, four-quadrant grid.
Each of the four quadrants should be represented with at least one, if not several, measures to have a comprehensive set. In the case that a quadrant is blank, a checklist of key questions as illustrated on the next page will help you develop measures to address the omitted area.

By using the measurement matrix you will guard against a biased or incomplete set of indicators and better guarantee success in tracking your quality improvements.


Quality management (QM)

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