Red-Amber-Green Analysis

what is red amber green (rag) analysis? red amber green (rag) analysis is a widely adopted tool for visual and quantitative analysis in optioneer, it is used to analyze and compare options using metrics each metric is evaluated and assigned a status based on predefined thresholds red — significant risk amber — moderate risk green — minimal risk why use rag analysis? intuitive risk assessment — color coding is easy to interpret and helps identify risks early, making results accessible to both technical and non technical stakeholders increased stakeholder engagement — visual indicators communicate findings clearly without requiring a technical background efficient and centralized — rag is built directly into optioneer, bringing data, analysis, and visualization together without the need for spreadsheets, manual calculations, or external software using rag analysis to access rag, select red amber green from the analysis mode dropdown in the results library you must have at least one option selected to use this feature rag boundaries to set boundaries, click the icon to the right of any metric and select a boundary type absolute — fixed values for red, amber, and green thresholds best used when industry standards or predefined limits apply minimum — thresholds are set relative to the lowest value in the dataset best used when the lowest recorded value is considered optimal and deviations indicate increasing risk maximum — thresholds are set relative to the highest value in the dataset best used when the highest recorded value is considered optimal or represents the worst case scenario average — thresholds are set relative to the dataset average best used when performance is measured against the group mean, with deviations in either direction indicating better or worse outcomes top tip when defining boundaries, consider data variability if metric values fluctuate significantly across your options, relative boundaries (minimum, maximum, or average) may be more suitable than absolute boundaries configuring ra g boundaries rag boundaries use a metric's minimum and maximum values across your options, along with basic operations (+, , ×, ÷), to define thresholds — typically expressed as a percentage as a starting point, we recommend setting the green amber boundary at 10% below the minimum value setting the amber red boundary at 10% above the maximum value adjust these as needed if there is little variation across your options — for example, all options are showing red — consider increasing the amber red boundary to better differentiate them example rag boundary configuration using average boundary type and the recommended default values using absolute boundaries for categorical decision making with custom metrics, you can create rankings by assigning values (0, 1, 2…) based on whether an option meets certain conditions for example, when assessing environmental impact, you might check whether an option is within 500m of a protected area, or within 500m of a river using the any expression, each fulfilled condition adds +1 to the option's ranking when combined with absolute boundaries, this approach makes it easy to identify which options meet specific criteria — supporting more structured, transparent decision making