Measures of Effectiveness (MOE)

Measures of Effectiveness (MOE) are measures designed to correspond to the accomplishment of mission objectives and the achievement of desired results. They quantify the results to be obtained by a system and may be expressed as probabilities that the system will perform as required. The Capability Based Assessment (CBA) defines the MOE’s and articulates them in the Initial Capabilities Document (ICD) and Capabilities Development Document (CDD). MOEs may be further decomposed into Measures of Performance (MOP) and Measures of Suitability (MOS).

Definition: “A Measure of Effectiveness is a measure of the ability of a system to meet its specified needs (or requirements) from a particular viewpoint. This measure may be quantitative or qualitative and it allows comparable systems to be ranked. These effectiveness measures are defined in the problem-space. Implicit in the meeting of problem requirements is that threshold values must be exceeded.” Smith and Clark, (2004)

: J7 Commander’s Assessment Handbook (2011)

Measures of Effectiveness (MOE) Best Practices

Measures of Effectiveness should use assessment Indicators that are relevant, measurable, responsive, and resourced so there is no false impression of task or objective accomplishment. They should be easily understood and evaluated. Complicated MOE is more difficult to evaluate and can lead to confusion and a lack of understanding of the real issue. A mix of quantitative and qualitative indicators is used to evaluate MOEs to mitigate the risk of misinterpretation and overcome the limits of raw data in understanding complex situations.

Characteristics of Measure of Effectiveness (MOE) Indicators: [1]

Relates to performance
Objective
Simple to state
Testable
Complete
Clear
States any time dependency
States any environmental conditions
Can be measured quantitatively (if required, may be measured statistically or as a probability)
Easy to measure
Select only MoEs that measure the degree to which the desired outcome is achieved
Use the same MoEs to measure more than one condition when appropriate
Structure so that they have measurable, collectible, and relevant indicators
Write as statements (not questions)
Maximize clarity

Developing Measures of Effectiveness (MOE) Indicators

Creating clear and appropriate MOE “Indicators” to inform an evaluation is the goal. A MOE could be expressed into five elements:

Short Title: the name;
Definition: a clear description of what is measuring;
Unit of Measure: may be quantifiable or qualitative;
Benchmark: a value that would define the desired state in terms of the particular aspect of the operational environment being measured;
Formula: an expression of how changes in the value affect the MoE (i.e., is more or less better?)

The Acquisition Program Baseline (APB) should reflect broadly defined, operational-level measures of effectiveness or measures of performance to describe needed capabilities. [2]

Measures of Performance (MOP)

A measure of a system’s performance expressed as speed, payload, range, time-on-station, frequency, or other distinctly quantifiable performance features. Several MOPs and/or Measures of Suitability (MOSs) may be related to the achievement of a particular Measure of Effectiveness (MOE).

Definition Joint Center for International Security Force Assistance (JCISFA) Planning Guidance: “MOPs are necessary for correlation to specific MOEs in order to determine the optimal levels of effort for objective achievement. A careful analysis of the relationship between MOPs and MOEs reveals the need to shift COAs if the current plan is inefficient, or has adverse effects.”

Measures of Suitability (MOS)

A measure of an item’s ability to be supported in its intended operational environment. MOSs typically relate to readiness or operational availability and, hence, reliability, maintainability, and the item’s support structure. Several MOSs and/or Measures of Performance (MOPs) may be related to the achievement of a particular Measure of Effectiveness (MOE).

AcqLinks and References:

Updated: 1/20/2024

Rank: G1.9

Systems Engineering