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Multi-Variate Analysis

Also referred to as "Multiple Index Analysis"

Tabular and graphical reports that  cross  reference multiple indices. Two dimensional and 33 dimensional matrices. 

While each of these bivariate correlations reveals interesting insight into the portfolio, the owners and decisions makers benefit from multivariate analysis. For example:

  • The relationship between the age (#1) of buildings, their condition (#2) and their mission criticality (#2).  



Types of Multivariate Analysis
Listed below are some of the different types of multivariate analysis:

Further discussion on each of these matrices can be found on the corresponding pages of this glossary.


Applications of Multivariate Analysis

Through interactions with elected local government officials and their city staff, the authors have participated in dialogues on the challenges in making reasonable and defensible decisions in the public good, including:

  • Decisions on the cost-benefit of continuing to reinvest in the sustainment of an aged facility or to replace that facility, considering factors of physical deterioration and functional obsolescence.
  • Decisions on when it is appropriate to consciously allow certain assets to run to failure (failure replacement) or to mitigate collateral damage and other risks through preventive replacement.
  • Decisions on whether to construct a new facility (freehold) or enter into a lease agreement (leasehold) to complement the portfolio and achieve an optimum freehold:leasehold ratio.
  • Decisions on the skewed appropriation of limited capital towards the deemed mission-critical facilities and controlled “drift” of the backlog of deferred maintenance at the non-critical facilities.
  • Decisions to invest in energy upgrades (with incremental capital cost) relative to some assets or to replace like-for-like (without incremental capital cost) on other assets.

These complex decisions require insight into the correlations between multiple variables, such as: age, condition, obsolescence, energy efficiency and mission criticality. The correlation of two variables (say age-condition) returns a bi-variate analysis, whereas the correlation of three or more variables (say, age-condition-criticality) returns multivariate insight.

Example of a facility in poor condition established by the faciltiy condition index and extended facility condition index
Fig. Two key performance indicators (KPIs) confirming that a facility is in relatively "good" condition.


3D matrix to cross reference the Facility Condition Index (FCI) with the Mission-Dependency Index (MDI) and backlog quantum.
Fig. 3D matrix to cross reference three separate indexes: #1 Facility Condition Index (FCI) with the #2 Mission-Dependency Index (MDI) and E3 backlog quantum.


Multivariate analysis in the form of matrix overlays
Fig. Multivariate analysis in the form of matrix overlays: condition-age matrix, condition-energy matrix, and condition-criticality matrix

See also:
  • Correlations
  • Distributions
  • Copulas


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