Interrelationship diagram

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Interrelationship diagram
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An interrelationship diagram shows natural relationships and the connections between different constructs identified or ideas for quality improvement. Frequently used in combination with:

The interrelationship diagram is based on the expertise and knowledge of the quality improvement team in relating to critical linkages across different concepts[1].

The interrelationship Diagram explains the connection between different factors involved in a complex situation. A diagram is charted by putting factors or the issues in individual matrices or circles. Arrows are used to show cause-and-effect relationships. Furthermore, proper weight is allocated to each factor on the basis of specialist opinions. Factor or the issue with the arrow pointing away shows the root reason and is defined as a driver. Factor or the issue with an arrow pointing inward shows a real issue of concern. The outgoing or incoming sum of the arrows weights shows the gravity of reason and effect for the given factor. In consequence, the interrelationship diagram locates the reason and effect relationships of the factors so the identified key outcomes and drivers resolve the problem[2].

The interrelationship diagram tools

The interrelationship diagram is a tool used with the greatest impact to prioritize those issues. The interrelationship diagram aids in making distinctions between effects (or outcomes) and causes(or drivers). The affinity diagram was used to recognize the key essential issues of a problem. The main purpose of this tool is to better understand the relationships between complex issues. There are following main uses of this tool [3]:

The interrelationship diagram is a graphic representation of the reason and effect relationships between the elements of an issue or problem. The purpose of doing an interrelationship diagram is to recognize the root reason and root effects of a problem. Root reasons are those aspects or factors of a problem which mainly influence other factors. Whereas root effects are those factors of a problem where the main are influenced by other factors[4].

Footnotes

  1. (K. Boyer, R. Verma 2009)
  2. (L. Wankhade, B. Dabade 2010)
  3. (E. Jones 2014)
  4. (D.H. Stamatis 1997)

References

Author: Agnieszka Piwowarczyk