Performance indicators
- damian.hickey
Introduction
This documentation describes the Performance Indicator Schema within the Performance domain of the Orthogramic Metamodel. These indicators leverage the Performance domain to provide organizations with sophisticated capabilities for measuring, tracking, and optimizing their performance metrics, ensuring alignment with strategic goals and enabling proactive performance management.
Performance indicators
The Performance domain in Orthogramic is a critical domain that underpins the entire business architecture. The Performance Indicator Schema is an essential component within this domain, providing the structure and framework for measuring performance across the organization.
The Performance Indicator Schema includes capabilities for:
Identifying early indicators of performance trends
Exploring innovative measurement approaches
Understanding the temporal dimensions of outcomes
Employing diverse measurement methodologies
These indicators strengthen Orthogramic's approach to performance management, enabling proactive monitoring, continuous improvement, and alignment with long-term strategic goals, all while operating within the established Performance domain framework.
Indicators within the performance domain
The Orthogramic model positions the Performance domain as central to all domains, ensuring businesses can leverage real-time insights for operational efficiency and strategic alignment. The Performance Indicators provide measurement capabilities within this domain through:
Predictive Performance Management: Using leading indicators that can identify potential issues before they manifest
Innovative Measurement Approaches: Exploring new metrics that may better capture emerging aspects of performance
Temporal Performance Understanding: Explicitly modeling when different outcomes are expected to materialize
Methodological Flexibility: Combining objective, subjective, and proxy measurement approaches
These indicators provide business architects with sophisticated measurement tools within the Performance domain, helping organizations meet the demands of the digital age with a data-driven, forward-looking approach to performance management.
Integration with strategic response model
Performance Indicators play a crucial role in the Strategic Response Model by providing measurable criteria for evaluating the effectiveness of strategic responses to triggers. As documented in the Strategic Response Model:
Performance indicators are explicitly referenced through the
performanceIndicatorReferencespropertyThese indicators define what success looks like for a strategic response
They enable continuous assessment of strategic effectiveness
They support the "how much" dimension of tracking strategic impact
The integration works as follows:
When an organization creates a strategic response to an external trigger (such as regulatory change) or an internal insight
The response includes references to specific performance indicators that will measure its success
These indicators provide the quantifiable metrics needed to evaluate progress
Through temporal indicators (immediate, intermediate, and long-term outcomes), organizations can track effectiveness across different timeframes
This connection ensures that strategic responses are measurable and accountable, with clear metrics defining success. It creates a feedback loop where performance measurement directly informs future strategic decisions and responses.# Performance Indicator Documentation
Performance attributes
leadingIndicators
Leading indicators are metrics that show early progress before outcomes materialize. They serve as predictive signals, allowing organizations to take action before issues develop or to capitalize on emerging opportunities.
Sub-Element | Description | Example |
|---|---|---|
| Name of the leading indicator | Early Customer Engagement Rate |
| Explanation of how this indicator signals future performance | Measures initial customer interactions that precede formal conversions |
| Value at which action should be taken | 15% decrease from baseline |
| Typical time between indicator change and outcome impact | 45 days |
| Estimated reliability of prediction (0-100%) | 85% |
| Current measurement for this leading indicator | 3.2 interactions per customer |
potentialMetrics
Potential metrics represent new measurement categories for innovative initiatives. These are forward-looking measures that may better capture emerging aspects of performance, especially for novel business activities.
Sub-Element | Description | Example |
|---|---|---|
| Name of the potential new metric | Digital Ecosystem Engagement |
| Explanation of what this metric would measure | Measures how customers move between our digital platforms |
| How this metric would add value | Identifies cross-platform opportunities and friction points |
| Potential obstacles to implementation | Data privacy concerns, cross-platform tracking limitations |
| Data needed to calculate this metric | Device IDs, session timestamps, platform identifiers |
| Estimated timeline for implementation | 3-6 months |
outcomeTimeframes
Outcome timeframes categorize when different results are expected to manifest. This helps organizations understand the temporal dimension of performance and set appropriate expectations for when different types of value will be realized.
immediateOutcomes (0-3 months)
Sub-Element | Description | Example |
|---|---|---|
| Description of the immediate outcome | Increased customer engagement with new feature |
| Expected value to be achieved | 25% usage among active customers |
| Confidence in this outcome (0-100%) | 90% |
intermediateOutcomes (3-12 months)
Sub-Element | Description | Example |
|---|---|---|
| Description of the intermediate outcome | Improved customer retention rate |
| Expected value to be achieved | 15% reduction in churn |
| Confidence in this outcome (0-100%) | 75% |
longTermOutcomes (12+ months)
Sub-Element | Description | Example |
|---|---|---|
| Description of the long-term outcome | Market share growth |
| Expected value to be achieved | 3.5% increase in market share |
| Confidence in this outcome (0-100%) | 60% |
catalyticEvents
Sub-Element | Description | Example |
|---|---|---|
| Description of the catalytic event | Competitor product launch |
| Probability of this event occurring (0-100%) | 80% |
| How this event would impact outcomes | Could accelerate adoption if our solution provides clear advantages |
| Estimated date for this event | 2025-09-15 |
measurement
The measurement object specifies objective, subjective, or proxy measurement approaches, providing methodological flexibility in how performance is assessed.
approachType
Value | Description |
|---|---|
| Based on direct, quantifiable data with minimal interpretation |
| Based on judgment, perception, or qualitative assessment |
| Uses indirect measures as substitutes for direct measurement |
| Combines multiple measurement approaches |
objectiveComponents
Sub-Element | Description | Example |
|---|---|---|
| Name of the objective component | Transaction Completion Rate |
| Method for collecting data | Automated system logging |
| Calculation used | (Completed transactions / Initiated transactions) ร 100 |
| Weight in overall metric (0-100%) | 65% |
| Process to validate measurement | Monthly audit and cross-check with financial records |
subjectiveComponents
Sub-Element | Description | Example |
|---|---|---|
| Name of the subjective component | User Experience Quality |
| Method for subjective assessment | Post-interaction surveys |
| Who conducts the assessment | Customers, UX specialists |
| Weight in overall metric (0-100%) | 25% |
| Measures to control bias | Randomized sampling, normalized scoring |
proxyComponents
Sub-Element | Description | Example |
|---|---|---|
| Name of the proxy component | Digital Engagement Depth |
| What this proxy represents | Customer satisfaction and loyalty |
| Correlation between proxy and target (0-1) | 0.78 |
| Method to validate correlation | Quarterly analysis against direct satisfaction measures |
| Known limitations | Not applicable to certain customer segments |
| Weight in overall metric (0-100%) | 10% |
Performance indicator examples
Performance indicator schema
See: GitHub - Orthogramic/Orthogramic_Metamodel
Enumeration values
thresholdType
Defines the general logic for evaluating performance values:
Value | Description |
|---|---|
| Performance improves as values increase (e.g., customer satisfaction, revenue) |
| Performance improves as values decrease (e.g., error rates, costs, complaints) |
| Performance is optimal at a specific target value (e.g., inventory levels) |
| Performance is optimal within a specified range of values (e.g., temperature, staffing) |
aggregationPeriod
Specifies the timeframe used to aggregate performance data:
Value | Description |
|---|---|
| Continuous measurement with immediate updates (e.g., system availability) |
| Data aggregated on an hourly basis (e.g., peak load monitoring) |
| Data aggregated once per day (e.g., daily sales figures) |
| Data aggregated once per week (e.g., project progress) |
| Data aggregated once per month (e.g., budget performance) |
| Data aggregated once every three months (e.g., strategic initiatives) |
| Data aggregated once per year (e.g., annual objectives) |
Integration with Orthogramic architecture
The Performance Indicators are designed to work within the Performance domain and integrate seamlessly with other domains in the Orthogramic metamodel. These indicators enable organizations to:
Connect with Capabilities: Leading indicators can be linked to capability improvements
Enhance Value Streams: Measurement approaches can be tailored to different value stream stages
Align with Stakeholders: Outcome timeframes can be mapped to stakeholder expectations
Support Information Management: Potential metrics can identify new data requirements
Enable Strategic Responses: Performance indicators provide measurable success criteria for strategic responses to internal and external triggers
This integration reinforces Orthogramic's holistic approach to business architecture, ensuring that performance measurement through these indicators directly supports strategic objectives and operational excellence within the existing Performance domain framework.
Practical implementation
When implementing Performance Indicators within the Performance domain, organizations should consider:
Starting with high-impact areas: Focus initial implementation on critical business areas
Balancing measurement types: Combine objective, subjective, and proxy measures appropriately
Establishing temporal expectations: Set clear timeframes for when different outcomes should manifest
Exploring innovative metrics: Regularly evaluate potential new metrics as the business evolves
Building predictive capabilities: Develop leading indicators to support proactive management
This approach ensures that these indicators drive meaningful business outcomes within the Performance domain framework rather than creating additional overhead.
The Orthogramic Metamodel license: Creative Commons Attribution-ShareAlike 4.0 (CC BY-SA 4.0), ensuring it remains open, collaborative, and widely accessible.