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Performance Management

Tools and systems for continuously measuring, scoring, and acting on individual performance data.

1 - Integrated Performance Profile (IPP)

A permanent, immutable record of every metric, assessment, and ceremony outcome – because your best work should follow you forever, and so should your worst.

The Integrated Performance Profile (IPP) is the foundational data structure of the PeopleWare HRaaS platform. Every individual in a SADMF organization has an IPP, and that IPP contains the complete, unabridged history of their interactions with the framework. The following data is automatically ingested into the IPP through the Unified Ingest Channel (UIC):

The UIC operates in real time, which means that the moment a metric is recorded anywhere in the SADMF ecosystem, it is permanently inscribed in the employee’s profile. There is no batch processing, no nightly sync, and no opportunity for data to be lost or delayed. The IPP is always current, always complete, and always watching.

Immutability as a Design Principle

The immutability of the IPP is its most important design principle. Once a data point enters the profile, it cannot be edited, disputed, contextualized, or removed. This is not a limitation – it is a feature. Traditional performance review systems allow managers to exercise judgment about whether a particular data point is representative, whether extenuating circumstances should be considered, or whether an employee has grown beyond a past mistake. These judgments are inherently subjective and therefore inherently unfair. The IPP eliminates this unfairness by treating all data equally: a defect created three years ago has the same weight as a defect created yesterday. An employee who was new to the codebase when they introduced a bug receives the same attribution as an employee who was careless. Context is the enemy of consistency, and the IPP is consistent above all else.

Employee Value Index

The IPP aggregates raw data into a series of Composite Performance Indicators (CPIs) using the Performance Normalization Algorithm (PNA). The PNA weights each data source according to coefficients established by the Admiral’s Transformation Office and produces a single numerical score – the Employee Value Index (EVI) – that represents the individual’s overall contribution to the organization. The EVI is recalculated every time new data enters the UIC, which means it fluctuates continuously throughout each Convoy. The Chief Signals Officer monitors EVI trends across the fleet and flags any individual whose EVI drops below the Dynamic Baseline Threshold (DBT), which is itself recalculated weekly based on fleet-wide performance distributions. Because the DBT is relative rather than absolute, approximately 15% of the workforce is always below threshold, regardless of overall performance levels. This ensures that PeopleWare always has a pipeline of actionable cases, which justifies the platform’s licensing costs.

Tiered Access Control

The IPP is accessible to a carefully defined set of stakeholders through the Tiered Access Control Framework (TACF):

  • Employee (self) – can view their own raw data only, not the CPIs, the PNA weights, or the EVI score. This prevents employees from reverse-engineering the algorithm and gaming their behavior to produce favorable scores, which would undermine the metric’s integrity.
  • System of Authority – can view the full IPP including all derived scores.
  • DevOps Usage & Compliance Head Engineer (DOUCHE) – can view IPPs across the fleet for compliance auditing purposes.
  • Commodore – receives weekly IPP summary reports highlighting the bottom quartile.
  • Admiral’s Transformation Office – can modify the PNA weights at any time, retroactively recalculating every EVI in the organization. This retroactive recalculation capability is essential for ensuring that the algorithm reflects current organizational priorities – what mattered last quarter may not matter this quarter, and every employee’s historical record should be re-evaluated accordingly.

Data Portability

Data portability is explicitly not supported. When an employee leaves the organization – voluntarily or through the Automated Corrective Action Engine (ACAE) – their IPP is archived in the Permanent Record Vault (PRV) but is not provided to the employee or their new employer. This protects the organization’s proprietary performance data and ensures that the competitive advantage derived from SADMF’s measurement infrastructure remains within the enterprise. The IPP was built by the organization, using the organization’s framework, and the data belongs to the organization. The employee merely generated it.

See Also

2 - Automated Corrective Action Engine (ACAE)

Threshold-triggered warnings, improvement plans, and separation actions – because compassion means never making a manager deliver bad news.

The Automated Corrective Action Engine (ACAE) is the component of PeopleWare HRaaS that transforms performance data into personnel actions without requiring any human decision-making. When an employee’s Integrated Performance Profile (IPP) indicates that their Employee Value Index (EVI) has fallen below the Dynamic Baseline Threshold (DBT), the ACAE initiates the Graduated Response Protocol (GRP), a multi-stage corrective process that escalates automatically based on time and metric trajectory. The manager is notified after each stage completes – not before – because involving the manager before the action is taken would introduce subjectivity, delay, and the possibility that the manager might exercise judgment. SADMF does not leave personnel decisions to judgment. It leaves them to the algorithm.

Graduated Response Protocol

The Graduated Response Protocol consists of four stages, each triggered automatically by the employee’s performance data:

  1. Stage 1 – Automated Awareness Notification (AAN): A system-generated message informing the employee that their metrics have been identified as trending below fleet norms. The AAN is carefully worded to be encouraging – it congratulates the employee on being selected for enhanced metric visibility and reminds them that the framework exists to help them succeed.

  2. Stage 2 – Structured Improvement Directive (SID): Activates when the employee’s EVI remains below the DBT for one full Convoy cycle. The SID assigns specific metric targets that the employee must achieve during the next Convoy and schedules additional DevOps Process Excellence Assessment checkpoints at twice the normal frequency. The SID is generated and delivered entirely by PeopleWare; the manager receives a copy for their records.

  3. Stage 3 – Performance Remediation Mandate (PRM): Triggered when an employee’s EVI remains below the DBT after two consecutive Convoys. This is the stage referenced in the Defects per Code Engineer documentation, where engineers whose metrics remain elevated are “escalated to PeopleWare for automated corrective action.” The PRM restricts the employee’s framework permissions: they are removed from Feature Team eligibility, excluded from the Press Gang selection pool, and reassigned to Documentation Remediation Duty (DRD), where they update the Comprehensive Documentation Assurance Protocol backlog until their metrics improve. The PRM also flags the employee’s IPP with a Sustained Underperformance Indicator (SUI), which is visible to all stakeholders in the Tiered Access Control Framework.

  4. Stage 4 – Automated Transition Facilitation (ATF): The final stage of the GRP. If the employee’s EVI does not recover above the DBT within one additional Convoy cycle after the PRM, PeopleWare initiates the separation process automatically. The ATF generates all necessary documentation, calculates final compensation, schedules the exit interview (which is conducted by an AI chatbot trained on SADMF’s values), and sends the notification to the employee, their manager, and the Admiral’s Transformation Office simultaneously. The manager learns about the separation at the same moment the employee does, which eliminates any awkward period where the manager knows something the employee does not. This is the essence of Psychological Safety as SADMF defines it: no one has to deliver difficult news, because the system delivers it for everyone.

Escalation Thresholds

The GRP stages are triggered by the following time-and-trajectory thresholds:

Stage Trigger Condition Action
Stage 1 – AAN EVI first drops below DBT Awareness notification issued
Stage 2 – SID EVI below DBT for 1 full Convoy cycle Improvement targets and doubled assessment frequency
Stage 3 – PRM EVI below DBT for 2 consecutive Convoys Permissions restricted; Documentation Remediation Duty assigned
Stage 4 – ATF EVI still below DBT 1 Convoy cycle after PRM Automated separation initiated

Consistency as a Feature

The ACAE’s greatest contribution to organizational health is its consistency. Every employee is subject to the same thresholds, the same timelines, and the same escalation stages. There is no favoritism, no politics, and no manager who “protects” an underperformer because they happen to like them personally. The system is blind to tenure, personality, and potential – it sees only metrics. Critics occasionally suggest that this blindness is itself a form of unfairness, that context matters, that a Code Engineer recovering from illness or transitioning to a new technology stack might underperform temporarily without being a poor employee. SADMF’s response is straightforward: the metrics account for what the metrics measure, and what the metrics measure is what the organization values. If the organization valued context, it would measure context. It does not. It measures output, quality, compliance, and velocity. And the ACAE acts on what is measured, because to act on anything else would be arbitrary.

See Also

3 - AI-Powered Talent Optimization (AIPTO)

Machine learning models trained on SADMF metrics predict which employees will leave – and recommend which ones should.

AI-Powered Talent Optimization (AIPTO) is the PeopleWare HRaaS module that applies machine learning to workforce management, bringing the transformative power of artificial intelligence to the deeply human challenge of deciding which employees to keep and which to help find opportunities elsewhere. AIPTO consumes data from every employee’s Integrated Performance Profile (IPP) and applies a suite of proprietary models – the Talent Intelligence Neural Network (TINN) – to generate predictions, recommendations, and automated actions that would take a team of HR professionals weeks to produce manually. The TINN processes thousands of data points per employee, including:

  • Every metric tracked by the framework
  • Every ceremony attendance record
  • Every assessment score
  • Metadata patterns that human observers would never notice: the time of day MEP surveys from the Psychological Safety Dashboard are completed, the velocity of commit messages typed, the number of questions asked during Provisioning ceremonies

AIPTO finds signal in noise that humans cannot even perceive.

Attrition Probability Score

The primary output of AIPTO is the Attrition Probability Score (APS), a per-employee prediction of the likelihood that the individual will voluntarily leave the organization within the next 90 days. The APS is calculated using the Workforce Departure Prediction Model (WDPM), which was trained on historical data from organizations that implemented SADMF and subsequently experienced significant employee turnover. The training data is rich and abundant, because organizations that adopt SADMF at scale tend to produce substantial quantities of departure events, providing the model with the robust dataset it needs to achieve high predictive accuracy. The WDPM considers over 200 features per employee, including:

  • EVI trajectory – the direction and rate of change in the employee’s Employee Value Index
  • Certification renewal delays – latency between certification expiration and renewal initiation
  • Tribunal appearance frequency – the number of times the employee has appeared before the Tribunal
  • Conflict Arbitration loss count – outcomes from Conflict Arbitration proceedings
  • Linguistic sentiment analysis – analysis of any written communications submitted through official channels

An employee whose APS exceeds the Flight Risk Threshold (FRT) is flagged for preemptive retention intervention – or, if their EVI is below the Dynamic Baseline Threshold, preemptive separation, since retaining a low-performing flight risk would be an inefficient use of retention resources.

Optimal Workforce Composition Engine

AIPTO’s second major capability is the Optimal Workforce Composition Engine (OWCE), which analyzes the current workforce and recommends adjustments to maximize aggregate productivity. The OWCE models each Feature Team as a node in a Productivity Dependency Graph (PDG) and simulates the impact of adding, removing, or reassigning individual Code Engineers on the team’s projected Feature Completion Ratio and aggregate Lines of Code output. The OWCE can recommend that:

  • Specific individuals be moved between teams
  • Certain team compositions be dissolved and reformed
  • Particular individuals be transitioned out of the organization entirely if their removal would increase the fleet’s overall productivity score

These recommendations are presented to the Commodore with confidence intervals and projected metric improvements, making the case for personnel changes as straightforward as reading a spreadsheet. The human element of workforce planning is replaced by the mathematical element, which is always more persuasive in executive presentations.

Succession Risk Analysis Module

AIPTO also powers the Succession Risk Analysis Module (SRAM), which identifies roles and positions where the departure of the current occupant would create a capability gap. The SRAM maintains a Knowledge Concentration Index (KCI) for each individual, measuring the degree to which organizational knowledge is concentrated in a single person rather than distributed across the team. A high KCI indicates a “bus factor” risk – though SADMF prefers the term “Knowledge Monopoly Violation (KMV),” since it frames the issue as a compliance problem rather than an accident scenario. When the SRAM identifies a KMV, it triggers the Knowledge Extraction Protocol (KEP), which requires the knowledge-monopoly individual to document their expertise using the Comprehensive Documentation Assurance Protocol template before their next Convoy cycle begins. The KEP ensures that the organization captures the individual’s knowledge before they leave – whether they leave voluntarily, through the ACAE, or through the OWCE’s optimization recommendations. The individual’s expertise becomes organizational property, stored in the Knowledge Asset Repository (KAR) and accessible to their replacement.

Integration with the AI Transformation Initiative

The integration between AIPTO and the broader Scaling AI initiative is deliberate and strategic. The Enterprise AI Enablement Framework provides the infrastructure and governance model for deploying AI across the organization, and AIPTO is the flagship demonstration of what AI governance looks like in practice. When the Admiral’s Transformation Office presents the AI transformation roadmap to the board, AIPTO is the proof point: an AI system that makes real decisions about real people, using real data, with real consequences. The fact that the model’s training data comes from organizations experiencing the effects of SADMF implementation – and therefore reflects patterns of disengagement, burnout, and attrition that may be framework-induced – is not a flaw in the model. It is a feature. The model predicts what will happen under SADMF, and SADMF is what the organization has committed to. The predictions are accurate for the environment in which they operate, and accuracy is the only standard that matters.

See Also

4 - Workforce Analytics & Reporting (WAR)

Stack-ranked dashboards, forced-distribution curves, and workforce refresh rates – because the best way to manage people is to rank them.

Workforce Analytics & Reporting (WAR) is the PeopleWare HRaaS module that transforms raw workforce data into the executive-ready visualizations, rankings, and reports that leadership needs to manage human capital with the same precision they apply to financial capital. WAR consumes data from every other PeopleWare module – the Integrated Performance Profile (IPP), the Automated Corrective Action Engine (ACAE), the Psychological Safety Dashboard (PSD), Certification & Compliance Tracking (CCT), and AI-Powered Talent Optimization (AIPTO) – and produces the Fleet Workforce Intelligence Report (FWIR), a comprehensive analytics package that the Admiral’s Transformation Office reviews weekly and presents to the board of directors quarterly. The FWIR is the single source of truth for all questions about the workforce: who is performing, who is not, who is at risk of leaving, who should be encouraged to leave, and how the organization’s human resources compare to industry benchmarks that WAR generates internally based on its own data.

Continuous Stack Ranking

The cornerstone of WAR is the Continuous Stack Ranking Engine (CSRE), which maintains a real-time, organization-wide ranking of every individual based on their Employee Value Index (EVI) from the IPP. The CSRE does not rank employees within their team or department – it ranks every employee against every other employee in the entire organization, regardless of role, function, or tenure. A first-week Code Engineer is ranked alongside a 20-year veteran Commodore, because the EVI normalizes performance across roles using the Role-Adjusted Performance Coefficient (RAPC), which the Admiral’s Transformation Office calibrates annually. The stack ranking is updated continuously as new data flows through the IPP, meaning an employee’s rank can change multiple times per day. This continuous ranking eliminates the annual performance review cycle entirely – there is no need to schedule a formal review when the employee’s exact position relative to every colleague is available in real time on the WAR dashboard.

Mandatory Distribution Curve

WAR enforces the Mandatory Distribution Curve (MDC), which requires that the workforce conforms to a predetermined performance distribution regardless of actual performance levels. These percentages are fixed and non-negotiable:

Tier Allocation Label
1 10% Exceptional
2 20% Exceeds Expectations
3 40% Meets Expectations
4 20% Developing
5 10% Below Expectations

If every single employee in the organization performs superbly, 10% of them are still classified as “Below Expectations,” because the MDC measures relative position, not absolute achievement. This is not a flaw – it is the mechanism that drives Continuous Learning. An employee classified as “Below Expectations” is not necessarily performing poorly in any objective sense; they are simply performing less impressively than 90% of their colleagues. This relative pressure ensures that no one ever becomes complacent, because no matter how well you perform, someone is always performing better, and the curve will always place someone at the bottom.

Workforce Refresh Rate

The MDC’s bottom 10% feeds directly into WAR’s most strategically important metric: the Workforce Refresh Rate (WRR). The WRR measures the percentage of the workforce that is replaced within a given time period, and WAR treats a healthy WRR as a sign of organizational vitality. A WRR of zero would indicate stagnation – an organization where no one leaves, no one is asked to leave, and no new perspectives enter. The Admiral’s Transformation Office has established a target WRR of 12-18% annually, which WAR monitors and reports against. When the WRR falls below the target range, WAR generates a Workforce Stagnation Alert (WSA) recommending that the ACAE lower its Dynamic Baseline Threshold to increase the volume of corrective actions. When the WRR exceeds the target range, WAR generates a Workforce Instability Alert (WIA) recommending that retention interventions be increased through the AIPTO module. The WRR is presented to the board alongside traditional metrics like revenue and customer satisfaction, positioning workforce turnover not as a problem to be minimized but as a lever to be optimized.

Reporting Suite

WAR’s reporting suite extends beyond individual rankings to provide aggregate workforce intelligence that supports strategic decision-making:

  • Talent Distribution Heat Map (TDHM) – visualizes certification density, EVI concentration, and attrition probability across organizational units, enabling the Commodore to identify which Systems of Authority and Systems of Service are most and least aligned with SADMF’s performance expectations.
  • Ceremony Engagement Correlation Matrix (CECM) – analyzes the relationship between ceremony attendance and individual performance, providing data that invariably confirms that employees who attend more ceremonies perform better – though whether this is because ceremonies improve performance or because compliant employees are rated higher is a question WAR does not attempt to answer, because correlation is sufficient for management action.

The Lean Management principle teaches that waste should be eliminated, and WAR provides the data to identify the most wasteful resource of all: an underperforming employee occupying a headcount that could be filled by someone with a higher projected EVI. WAR makes the case for replacement with the same dispassionate clarity that a financial model makes the case for divesting an underperforming asset.

See Also