Performance Indicators

Performance Indicators are quantifiable metrics that evaluate the success, efficiency, or impact of strategic responses. They close the feedback loop in the Strategic Response Model, enabling organizations to measure whether responses achieved their intended outcomes.

Schema: performance-indicator.schema.json
Specification: JSON Schema Draft-07

Overview

What are Performance Indicators?

In the SRM context, performance indicators are specific, measurable criteria that:

• Define what success looks like for a strategic response
• Provide quantifiable targets against baselines
• Enable ongoing monitoring and adjustment
• Support governance reviews and audits

A strategic response or strategic intent lists the indicators that measure it in its performanceIndicatorReferences, using each indicator's performanceIndicatorID. An indicator records the strategic elements it supports in strategicAlignments.

The Measurement Loop

Indicator Types

The schema has no indicator-type field: the classification below is guidance for choosing a balanced set of indicators. Early signals are recorded in an indicator's leadingIndicators, and when results are expected to appear in its outcomeTimeframes.

Outcome Indicators

Measure the ultimate result or impact of the response.

Type	Description	Example
Effectiveness	Degree to which objectives are achieved	Compliance rate = 100%
Impact	Broader organizational effect	Customer satisfaction +15pts
Value	Business value delivered	Revenue increase $2M

Process Indicators

Measure the execution and delivery of the response.

Type	Description	Example
Efficiency	Resource utilization	Cost per transaction -20%
Timeliness	Schedule adherence	Milestones on-time 90%
Quality	Output quality	Defect rate <2%

Leading Indicators

Predict future performance or outcomes.

Type	Description	Example
Predictive	Early warning signals	Pipeline coverage 3x
Adoption	Uptake and usage	User adoption 75%
Readiness	Preparation state	Training completion 100%

Lagging Indicators

Confirm outcomes after the fact.

Type	Description	Example
Result	Final outcome achieved	Project delivered
Retrospective	Post-implementation review	Benefits realized 85%

Indicator Attributes

Core Attributes

Attribute	Type	Required	Description
performanceIndicatorID	String	✓	A unique identifier for the performance indicator
title	String	✓	The name or label of the performance indicator
description	String	✓	A brief explanation of what the indicator measures
owner	String		The person or role responsible for this indicator
orgUnitTitle	String		The organizational unit to which this indicator belongs
orgUnitID	String		ID of the organization unit named in orgUnitTitle
version	String		Version of this indicator definition
lastUpdated	DateTime		When this indicator was last updated

Measurement Attributes

Attribute	Type	Required	Description
unitOfMeasure	String		The unit in which performance is measured (e.g. %, $AUD)
baselineValue	Number		The starting reference point for performance
currentValue	Number		The current measured value (actual performance)
targetValue	Number		The target or goal value to be achieved
variance	Number		The calculated difference between currentValue and targetValue
variancePercentage	Number		The percentage difference from the target value
thresholdType	Enum		General threshold logic, e.g. higher-is-better or lower-is-better
thresholds	Array[Object]		Detailed list of threshold rules
evaluativeModel	Object		Describes a model used to analyse or interpret performance trends
measurement	Object		Objective, subjective, or proxy measurement approaches

Timing Attributes

Attribute	Type	Required	Description
targetDate	Date		The date by which the target should be achieved
validFrom	Date		Start date of the performance measurement period
validTo	Date		End date of the performance measurement period
aggregationPeriod	Enum		The timeframe used to aggregate performance data (shared frequency list)
assessmentFrequency	String		How often the performance is assessed (e.g. weekly, monthly)
statusHistory	Array[Object]		Historical performance records for trend analysis

Data and Relationship Attributes

Attribute	Type	Required	Description
dataSource	String		Source system or method used to collect performance data
leadingIndicators	Array[Object]		Metrics that show early progress before outcomes materialize
potentialMetrics	Array[Object]		New measurement categories for innovative initiatives
outcomeTimeframes	Object		When different results are expected to manifest
strategicAlignments	Array[Object]		Strategic objectives or initiatives this indicator supports
relatedIndicators	Array[Object]		Other performance indicators related to this one
stakeholderImpacts	Array[Object]		How this indicator affects or interests different stakeholders

Threshold (thresholds)

Attribute	Type	Required	Description
level	String	✓	Label for the threshold level (e.g. warning, critical)
value	Number	✓	Numeric threshold value
comparisonOperator	Enum	✓	Logical operator for threshold evaluation
alertMessage	String		Message to display or send when threshold is breached
notificationRecipients	Array[String]		List of roles or individuals to be notified

Evaluative Model (evaluativeModel)

Attribute	Type	Required	Description
modelType	String		The name of the model (e.g. movingAverage, trendLine)
parameters	Object		Model parameters as key-value pairs
description	String		Explanation of the model's role or calculation logic

Leading Indicator (leadingIndicators)

Attribute	Type	Required	Description
indicatorName	String	✓	Name of the leading indicator
description	String	✓	Explanation of how this indicator signals future performance
triggerThreshold	Number		Value at which action should be taken
leadTime	String		Typical time between indicator change and outcome impact
confidenceLevel	Number		Estimated confidence (0-100%) that this indicator predicts the outcome
currentValue	Number		Current measurement for this leading indicator

Potential Metric (potentialMetrics)

Attribute	Type	Required	Description
metricName	String	✓	Name of the potential new metric
description	String	✓	Explanation of what this metric would measure
valueProposition	String		How this metric would add value to performance measurement
implementationChallenges	Array[String]		Potential challenges in implementing this metric
dataRequirements	Array[String]		Data needed to calculate this metric
estimatedImplementationTime	String		Estimated time required to implement this metric

Outcome Timeframes (outcomeTimeframes)

Attribute	Type	Required	Description
immediateOutcomes	Array[Object]		Outcomes expected within 0-3 months
intermediateOutcomes	Array[Object]		Outcomes expected within 3-12 months
longTermOutcomes	Array[Object]		Outcomes expected after 12+ months
catalyticEvents	Array[Object]		Key events that may accelerate or modify outcomes

Each immediate, intermediate and long-term outcome has these fields:

Attribute	Type	Required	Description
outcome	String		Description of the outcome
expectedValue	Number		Expected value to be achieved
confidenceLevel	Number		Confidence level for this outcome (0-100%)

Each catalytic event has these fields:

Attribute	Type	Required	Description
event	String		Description of the catalytic event
probability	Number		Probability of this event occurring (0-100%)
impactDescription	String		Description of how this event would impact outcomes
estimatedDate	String		Estimated date when this event might occur

Measurement (measurement)

Attribute	Type	Required	Description
approachType	Enum	✓	The primary approach to measurement
objectiveComponents	Array[Object]		Direct, quantifiable measurement components
subjectiveComponents	Array[Object]		Judgment or perception-based measurement components
proxyComponents	Array[Object]		Indirect measurement components used when direct measurement isn't possible
dataNormalization	Object		Methods for normalizing or standardizing different measurement components

Objective Component (objectiveComponents)

Attribute	Type	Required	Description
component	String	✓	Name of the objective measurement component
method	String	✓	Method used for collecting this data
formula	String		Formula or calculation used (if applicable)
weight	Number		Weight of this component in the overall metric (0-100%)
validationProcess	String		Process used to validate this measurement

Subjective Component (subjectiveComponents)

Attribute	Type	Required	Description
component	String	✓	Name of the subjective measurement component
assessmentMethod	String	✓	Method used for subjective assessment (e.g., survey, expert review)
assessors	Array[String]		Roles or individuals conducting the assessment
weight	Number		Weight of this component in the overall metric (0-100%)
biasControlMeasures	Array[String]		Measures to control bias in subjective assessment

Proxy Component (proxyComponents)

Attribute	Type	Required	Description
component	String	✓	Name of the proxy measurement component
targetMeasure	String	✓	What this proxy is intended to represent
correlationStrength	Number		Estimated correlation between proxy and target (0-1)
validationMethod	String		Method used to validate the proxy's correlation
limitations	Array[String]		Known limitations of this proxy measure
weight	Number		Weight of this component in the overall metric (0-100%)

Data Normalization (dataNormalization)

Attribute	Type	Required	Description
method	String		Normalization method used (e.g., min-max, z-score)
description	String		Explanation of how normalization is applied
parameters	Object		Parameters used in the normalization process

Strategic Alignment (strategicAlignments)

Attribute	Type	Required	Description
alignmentID	String	✓	ID of the strategic objective or initiative
alignmentType	Enum	✓	Type of strategic element this indicator aligns with: the shared domain list (e.g. initiative, policy, capability, valueStream) plus strategicObjective
alignmentStrength	Integer		Strength of alignment on a scale of 1-5
alignmentDescription	String		Description of how this indicator supports the strategic element

Status History Entry (statusHistory)

Attribute	Type	Required	Description
date	Date	✓	Date of the performance measurement
value	Number	✓	Measured value on that date
status	Enum		Performance status relative to target
comment	String		Optional commentary on this measurement

Related Indicator (relatedIndicators)

Attribute	Type	Required	Description
indicatorID	String	✓	ID of the related indicator
relationshipType	Enum	✓	Type of relationship with the related indicator
relationshipStrength	Integer		Strength of relationship on a scale of 1-5
relationshipDescription	String		Description of how this indicator relates to the other

Stakeholder Impact (stakeholderImpacts)

Attribute	Type	Required	Description
stakeholderID	String	✓	ID of the stakeholder
interestLevel	Enum		Level of interest from this stakeholder (shared four-point rating: low, medium, high, critical)
impactDescription	String		How this indicator impacts the stakeholder
communicationFrequency	String		How often updates are shared with this stakeholder

Value Lists

Aggregation Period (aggregationPeriod)

Value	Use Case	Example
continuous	Streamed, uninterrupted measurement	Sensor telemetry
realTime	Critical operational metrics	System availability
hourly	Intraday operational monitoring	Call queue length
daily	High-frequency operational	Transaction volumes
weekly	Tactical project metrics	Sprint velocity
monthly	Standard business metrics	Revenue, costs
quarterly	Strategic review metrics	NPS, market share
semiAnnually	Half-yearly reviews	Employee engagement
annually	Long-term strategic	Brand equity
eventDriven	Aggregated when a defined event occurs	Incident post-mortems
onDemand	Aggregated when requested	Board information requests
adHoc	Irregular, as needed	One-off investigations

Threshold Type (thresholdType)

Value	Meaning	Example
higherIsBetter	Higher is better	Revenue, satisfaction
lowerIsBetter	Lower is better	Costs, defects
targetIsOptimal	Performance is best at the target value	Certification obtained, staffing level
rangeIsOptimal	Stay within range	Compliance rate, inventory level

Comparison Operator (comparisonOperator)

Thresholds enable automated alerting when metrics move outside acceptable ranges. Each threshold rule names a level, a value and the operator used to compare the measured value with it:

{
  "thresholdType": "higherIsBetter",
  "thresholds": [
    { "level": "warning", "value": 95, "comparisonOperator": "lessThan" },
    { "level": "critical", "value": 90, "comparisonOperator": "lessThan" }
  ]
}

Value	Description
greaterThan	Greater than value
lessThan	Less than value
greaterThanOrEqual	Greater than or equal to value
lessThanOrEqual	Less than or equal to value
equal	Exactly equals value
notEqual	Does not equal value

A range is expressed as two threshold rules, one with greaterThanOrEqual and one with lessThanOrEqual.

Measurement Status (status)

Value	Description
aboveTarget	Measured value is better than target
onTarget	Measured value meets target
belowTarget	Measured value falls short of target
critical	Measured value has breached a critical threshold

Relationship Type (relationshipType)

Value	Description
parent	The related indicator rolls up this one
child	The related indicator rolls up into this one
correlatesWith	The two indicators move together
influences	This indicator drives the related one
derivedFrom	This indicator is calculated from the related one
componentOf	This indicator is part of a composite indicator

Measurement Approach (approachType)

Value	Description
objective	Direct, quantifiable measurement
subjective	Judgment or perception-based assessment
proxy	Indirect measurement standing in for the target measure
hybrid	A combination of approaches

JSON Schema Definition

The full definition is performance-indicator.schema.json. It requires performanceIndicatorID, title and description, and rejects properties it does not define.

Examples

Compliance Rate Indicator

{
  "performanceIndicatorID": "PI-001",
  "title": "Privacy Compliance Rate",
  "description": "Percentage of data processing activities compliant with Privacy Act requirements",
  "unitOfMeasure": "%",
  "baselineValue": 72,
  "currentValue": 94,
  "targetValue": 100,
  "variance": -6,
  "variancePercentage": -6,
  "thresholdType": "higherIsBetter",
  "thresholds": [
    { "level": "warning", "value": 95, "comparisonOperator": "lessThan" },
    {
      "level": "critical",
      "value": 90,
      "comparisonOperator": "lessThan",
      "alertMessage": "Privacy compliance below 90%",
      "notificationRecipients": ["Chief Compliance Officer"]
    }
  ],
  "targetDate": "2025-06-30",
  "validFrom": "2024-06-15",
  "aggregationPeriod": "monthly",
  "dataSource": "Compliance Management System",
  "owner": "Chief Compliance Officer",
  "orgUnitTitle": "Risk and Compliance",
  "orgUnitID": "OU-RISK-001",
  "measurement": {
    "approachType": "objective",
    "objectiveComponents": [
      {
        "component": "Compliant processing activities",
        "method": "Automated control testing",
        "formula": "(Compliant activities / Total activities) × 100"
      }
    ]
  },
  "strategicAlignments": [
    { "alignmentID": "srm-privacy-compliance-2024", "alignmentType": "initiative", "alignmentStrength": 5 }
  ],
  "statusHistory": [
    { "date": "2024-09-01", "value": 85, "status": "belowTarget", "comment": "Initial remediation complete" },
    { "date": "2024-10-01", "value": 89, "status": "critical", "comment": "Training program launched" },
    { "date": "2024-11-01", "value": 92, "status": "belowTarget", "comment": "Technical controls deployed" },
    { "date": "2024-12-01", "value": 94, "status": "belowTarget", "comment": "Process changes implemented" }
  ]
}

Customer Satisfaction Indicator

{
  "performanceIndicatorID": "PI-002",
  "title": "AI Service Customer Satisfaction",
  "description": "Net Promoter Score for customers using AI-powered service channels",
  "unitOfMeasure": "NPS points",
  "baselineValue": 40,
  "currentValue": 48,
  "targetValue": 55,
  "thresholdType": "higherIsBetter",
  "thresholds": [
    { "level": "warning", "value": 45, "comparisonOperator": "lessThan" },
    { "level": "critical", "value": 35, "comparisonOperator": "lessThan" }
  ],
  "targetDate": "2025-12-31",
  "validFrom": "2024-01-01",
  "aggregationPeriod": "monthly",
  "dataSource": "Customer Feedback Platform",
  "owner": "Head of Customer Experience",
  "measurement": {
    "approachType": "subjective",
    "subjectiveComponents": [
      {
        "component": "Likelihood to recommend",
        "assessmentMethod": "Post-interaction survey: % Promoters (9-10) minus % Detractors (0-6)",
        "assessors": ["Customers"]
      }
    ]
  },
  "relatedIndicators": [
    { "indicatorID": "PI-004", "relationshipType": "correlatesWith", "relationshipStrength": 4 }
  ]
}

Cost Efficiency Indicator

{
  "performanceIndicatorID": "PI-003",
  "title": "Cost per Customer Service Interaction",
  "description": "Average cost to resolve a customer service request across all channels",
  "unitOfMeasure": "AUD",
  "baselineValue": 12.0,
  "currentValue": 9.25,
  "targetValue": 8.5,
  "thresholdType": "lowerIsBetter",
  "thresholds": [
    { "level": "warning", "value": 10.0, "comparisonOperator": "greaterThan" },
    { "level": "critical", "value": 12.0, "comparisonOperator": "greaterThan" }
  ],
  "targetDate": "2025-06-30",
  "aggregationPeriod": "monthly",
  "dataSource": "Financial Management System + CRM",
  "owner": "Finance Business Partner - CX",
  "measurement": {
    "approachType": "objective",
    "objectiveComponents": [
      {
        "component": "Total customer service cost",
        "method": "Financial system extract",
        "formula": "Total CS cost / Total interactions"
      }
    ]
  }
}

Adoption Indicator

{
  "performanceIndicatorID": "PI-004",
  "title": "AI Channel Adoption Rate",
  "description": "Percentage of eligible customer interactions handled by AI channels",
  "unitOfMeasure": "%",
  "baselineValue": 0,
  "currentValue": 42,
  "targetValue": 60,
  "thresholdType": "higherIsBetter",
  "targetDate": "2025-12-31",
  "aggregationPeriod": "weekly",
  "dataSource": "Channel Analytics Platform",
  "owner": "Digital Channels Manager",
  "leadingIndicators": [
    {
      "indicatorName": "Agent training completion",
      "description": "Share of service agents trained to hand over to and from AI channels",
      "triggerThreshold": 80,
      "leadTime": "4 to 6 weeks",
      "confidenceLevel": 70,
      "currentValue": 92
    }
  ],
  "outcomeTimeframes": {
    "immediateOutcomes": [
      { "outcome": "AI handles password resets and balance enquiries", "expectedValue": 20, "confidenceLevel": 90 }
    ],
    "longTermOutcomes": [
      { "outcome": "AI handles the majority of eligible interactions", "expectedValue": 60, "confidenceLevel": 60 }
    ]
  }
}

Indicator Relationships

Performance indicators can relate to each other through relatedIndicators:

Usage Guidelines

Selecting Effective Indicators

1. SMART criteria — Specific, Measurable, Achievable, Relevant, Time-bound
2. Balance leading and lagging — Don't wait until the end to measure
3. Limit quantity — 3-5 indicators per response is typically sufficient
4. Ensure measurability — Data source must exist and be reliable
5. Align with response objectives — Indicators must reflect what success means

Common Mistakes to Avoid

Mistake	Problem	Solution
Too many indicators	Dilutes focus, overwhelming	Prioritize 3-5 key metrics
Vanity metrics	Look good but don't matter	Focus on actionable metrics
No baseline	Can't measure improvement	Establish baseline before starting
Unmeasurable targets	"Improve customer experience"	Define specific, quantifiable targets
Wrong frequency	Measure too late to act	Match aggregationPeriod to response urgency

Indicator Lifecycle

For Data Engineers

Performance indicators often map to data quality metrics and pipeline KPIs. Consider creating automated feeds from your data observability tools to populate SRM performance indicators, enabling real-time tracking of how data quality initiatives are progressing.

Related Documentation

• Strategic Response Model Overview — Full SRM documentation
• Trigger Schema — What initiates responses
• Rationale Schema — Why responses are taken
• Performance Domain — Domain-level performance modeling