Intelligent Foundations
Module 1 is the diagnostic layer of the entire operating system. Nothing downstream works correctly without it.
The three tools in this module (Vision Canvas, Leadership DNA Radar, AI Readiness Index) produce scored outputs across 14 distinct dimensions. Those scores feed into a Heat-Map Output that routes directly into 11 downstream modules (2 through 12). Module 13 is the cadence layer that re-runs it each quarter. A red score on data hygiene here does not just flag a problem. It forces Module 4 to centralize data before any AI project, restricts Module 7 from deploying machine learning models, and doubles the governance cadence in Module 12.
This is the difference between a diagnostic checklist and a system routing layer. Standalone assessments tell a leadership team what is wrong. Module 1 proposes what the rest of the VWCG OS should do about it.
Why Foundations Fail
Most operating system failures do not come from bad strategy or weak talent. They come from misalignment at the base layer.
Three patterns account for the majority of execution breakdowns in mid-market companies scaling past their first growth plateau:
Pattern 1: Vision fragmentation. The CEO articulates a growth target. The VP of Sales interprets it as "more logos." The VP of Operations interprets it as "higher margins on existing accounts." Marketing runs campaigns for new verticals while Customer Success doubles down on retention. Every leader is competent. Every leader is pulling in a different direction. The company grows revenue 20% while burning 35% more cash.
Pattern 2: Leadership behavioral gaps that stay invisible. Traditional 360 reviews measure perception. They do not measure the six operational traits that determine whether a leadership team can actually execute a scaling plan: strategic foresight, data-driven decision velocity, psychological safety creation, change advocacy, accountability consistency, and cross-functional collaboration. A team can score well on a 360 and still fail to execute because the assessment measured the wrong things.
Pattern 3: Premature AI investment. The average mid-market company invests heavily in its first AI initiative. Companies that skip structured readiness assessment fail at that first initiative far more often than they succeed. The failure is rarely technical. It is organizational: dirty data, unclear processes, teams that fear replacement rather than embrace augmentation, and compliance gaps that surface only after deployment.
Module 1 exists to diagnose all three patterns before a single dollar moves into execution.
Tool 1: The Vision Canvas
What it does
The Vision Canvas translates long-range strategic intent into a format that forces alignment. A leadership team completes it together, in a room, in one session. The output is a single-page document that every manager in the organization can reference without interpretation.
Structure
The canvas has four components:
North-Star Statement. One sentence, 15 words or fewer, describing the three-year destination. This is not a mission statement. Mission statements are permanent and abstract. A North-Star is time-bound and measurable. Example: "Reduce enterprise customer onboarding to under 48 hours globally."
Three Strategic Pillars. The three capability areas (markets, products, operational capacities) that must improve to reach the North-Star. Three is the constraint. Not four, not five. Each pillar gets one sentence. If a leadership team cannot reduce their strategy to three pillars, they have not made the hard prioritization choices that scaling requires.
Pillar KPIs. One headline metric per pillar. These are not comprehensive dashboards. They are the three numbers that tell a leadership team whether the company is on track. These KPIs become the seed data for Module 3 (KPI Precision Grid), where they expand into role-level metrics with alert thresholds.
Risks and Assumptions Block. Every strategic plan rests on assumptions. This block forces the team to name them. "We assume customer acquisition cost holds at current levels." "We assume the integration with Salesforce ships in Q2." Naming assumptions turns invisible risk into trackable risk. These assumptions feed directly into Module 8 (Agile Capital Allocation), where they become funding gate criteria: if an assumption breaks, the capital allocation shifts.
Downstream connections
The Vision Canvas is not a one-time exercise. Its outputs route into four downstream modules:
- Module 3 (KPI Precision Grid): Pillar KPIs become the starting point for the Baseline Snapshot. Module 3 expands them into role-level metrics with weekly tracking cadence.
- Module 6 (Sales Velocity Engine): If the Vision Canvas shows red on pipeline accuracy or forecast reliability, Module 6 activates hardened CRM validation rules and compresses follow-up cadences.
- Module 8 (Agile Capital Allocation): Assumptions from the Risks block become funding gate criteria. A broken assumption turns its gate KPI amber, and a second consecutive break freezes the tranche.
- Module 9 (Exit and Acquisition Layer): The Vision Canvas score on financial transparency sets QOE audit frequency (quarterly for green, monthly for amber and red). Documentation completeness red flags QOE exposure for diligence.
What makes this different from a V/TO
The EOS Vision/Traction Organizer (V/TO) captures core values, core focus, ten-year target, marketing strategy, three-year picture, one-year plan, rocks, and issues. It is a comprehensive strategic document for companies building their first operating rhythm.
The Vision Canvas captures four things and ignores everything else. This is deliberate. The VWCG OS does not need the Vision Canvas to be a complete strategic framework because the rest of the system handles strategy execution. The Vision Canvas needs to do one job: produce scored outputs that route into downstream modules. A V/TO cannot do this because it was not designed to feed a multi-module routing layer. The Vision Canvas was.
Tool 2: The Leadership DNA Radar
What it does
The Leadership DNA Radar measures six operational traits that determine a leadership team's capacity to execute a scaling plan. It runs quarterly, not as a one-time assessment, because leadership behavior shifts under operational pressure and the system needs current data to calibrate downstream modules.
The six dimensions
Each dimension was selected because it directly affects how downstream modules execute:
Strategic Foresight. The ability to anticipate market shifts and adjust plans before they become urgent. Leaders who score low on foresight generate more reactive change requests, which increases the load on Module 10 (Change Enablement Sprint). The system needs to know this in advance.
Data-Driven Decision Making. The degree to which decisions rely on evidence rather than intuition. Leaders who score low here will resist Module 3's KPI-driven accountability framework. Knowing this upfront lets Module 10 adjust its adoption messaging.
Psychological Safety Provision. Whether team members feel safe reporting bad news or challenging assumptions. Low scores suppress data quality. If people hide problems, KPI dashboards lie.
Change Advocacy vs. Resistance. How actively leaders champion operational change. RED scores double Module 10's adoption timelines and mandate executive sponsorship for every rollout.
Accountability Rituals. The consistency of follow-through on commitments and deadlines. This affects whether Module 3's weekly KPI reviews drive behavior change or become performative.
Cross-Functional Collaboration. The ability to work across departments without gaps. Low scores mean Module 4 must prioritize system integration, since the humans cannot bridge gaps alone.
Scoring method
Each executive self-rates on a 1-10 scale across all six dimensions. The facilitator also records three secondary signals on the same bands: communication consistency, inclusive decision-making, and financial discipline. A facilitator compiles results into a radar chart. The diagnostic signal is not the individual scores. It is the variance. A gap greater than 3 points between any two executives on the same dimension indicates a misalignment that will surface as execution friction in downstream modules.
Downstream connections
Leadership DNA scores route into three downstream modules:
- Module 10 (Change Enablement Sprint): RED on communication consistency extends communication cadences and adds redundant channels. RED on change advocacy makes executive sponsorship mandatory for all rollouts.
- Module 11 (People and Culture Analytics): Leadership DNA scores become the behavioral benchmark against which employee engagement survey results are interpreted. If leaders score red on inclusive decision-making, Module 11 adds inclusion questions to pulse surveys and increases DEI scorecard weight from 20% to 40%.
- Module 8 (Agile Capital Allocation): RED on financial discipline moves every gate KPI exception to board-level sign-off. Prevents founders from retroactively redefining success criteria. (Module 8 also receives input from the Vision Canvas. The Vision Canvas controls what the capital allocation criteria are. The Leadership DNA Radar controls who has the authority to override them.)
What makes this different from a 360 review
A 360 review measures how others perceive a leader. It answers "what do people think of you?" The Leadership DNA Radar measures six specific operational traits and answers "can this leadership team execute a multi-module scaling plan?" The distinction matters because a leader can be well-liked, respected, and score highly on a 360 while scoring red on data-driven decision making and change advocacy. A 360 would not flag this. The DNA Radar flags it and routes the signal to the modules that need to adjust.
Tool 3: The AI Readiness Index
What it does
The AI Readiness Index evaluates whether an organization has the foundational requirements to deploy AI effectively. It is a safety gate. Organizations that score below 40% do not proceed to Module 7 (AI Deployment Canvas) until they complete the foundation work identified by the assessment.
Five dimensions evaluated
Data Hygiene (weighted 25%). Completeness, accuracy, and accessibility of existing data. A red score here means Module 4 (Integrated Tech Stack) must prioritize data centralization before any AI project begins. It also constrains Module 3 (KPI Precision Grid) to high-confidence data sources only.
Process Clarity (weighted 20%). Whether existing workflows are documented, consistent, and measurable. A red score accelerates Module 2 (SOP Codex) from optional to mandatory. AI cannot automate a process that is not defined.
Team Attitude (weighted 20%). The workforce disposition toward AI: fear, indifference, curiosity, or enthusiasm. A red score triggers Module 10 (Change Enablement Sprint) to run AI-specific adoption campaigns before any deployment begins. Micro-training asset count increases from 3-5 videos to 10-15.
Compliance Baseline (weighted 20%). Current regulatory posture across GDPR, SOC2, HIPAA, or industry-specific requirements. A red score forces Module 12 (Cyber/Data Privacy and Security) into stricter classification protocols: all customer personal data defaults to Restricted tier, and incident response windows compress from 72 hours to 24 hours.
Tool Stack Compatibility (weighted 15%). API availability, integration readiness, and data portability of current systems. A red score means Module 4 (Integrated Tech Stack) adopts Hub-and-Spoke architecture as non-negotiable and allocates a dedicated Integration Steward at 10% FTE.
Scoring thresholds
- Below 40%: Foundation work first. Module 7 starts no new AI deployments. The organization completes Modules 2-4 to build process clarity, data infrastructure, and system integration before any AI deployment.
- 40-70%: Pilot under supervision. Module 7 opens but restricts projects to low-risk use cases with human-in-the-loop oversight. Bias and drift audits run monthly instead of quarterly.
- Above 70%: Scale-out candidate. Module 7 operates at full capacity with standard governance.
The Change Narrative
A critical output of the AI Readiness Index is not the score itself but the narrative it produces. The assessment converts identified gaps into a sequenced communication plan: "We will first centralize data pipelines and finalize operational SOPs. Only then will we train models." This narrative feeds directly into Module 10's communication cadence for AI adoption (town halls, Q and A sessions, micro-learning modules) and sets organizational expectations before the first AI project launches.
What makes this different from a readiness checklist
Standard AI readiness assessments produce a report. The VWCG OS AI Readiness Index proposes a system-wide configuration change. A score of red on data hygiene does not just appear in a presentation deck. It restricts Module 7's ML deployments, forces Module 4 to centralize data, tightens Module 12's compliance protocols, and triggers Module 2's SOP creation sprints. The assessment is not the deliverable. The system response to the assessment is the deliverable.
The Heat-Map Output: Where Everything Converges
The Heat-Map is not a summary document. It is the control panel for the entire VWCG OS.
All three diagnostic tools produce scored outputs across 14 dimensions. The Heat-Map combines them into a single Red/Amber/Green table that serves as the routing layer for Modules 2 through 12.
How the routing works
Every cell in the Heat-Map corresponds to a parameter in at least one downstream module. When the color changes, the heat-map proposes the parameter change:
- RED cells compress review cadence, not adoption timelines, which Module 10 sets. Weekly reviews replace monthly reviews unless the module publishes its own red cadence. Emergency governance layers activate.
- RED cells restrict automation. Modules that include AI-powered components default to manual processes or human-in-the-loop oversight until the underlying dimension improves to amber or green.
- RED cells increase governance. Sign-off requirements escalate. Manager approval becomes VP approval. VP approval becomes board approval. The system adds friction intentionally, because friction prevents organizations from scaling dysfunction.
- AMBER cells trigger monitoring. The module runs at standard parameters but adds pulse-check reviews at 30-day intervals to detect drift toward red.
- GREEN cells enable full autonomy. Modules run at designed speed with standard governance. Automation is approved. Timelines are standard.
The multiplier effect
The real power of the Heat-Map is the multiplier effect across modules. A single red cell on data hygiene simultaneously:
- Forces Module 4 to centralize data before any AI project
- Restricts Module 7 from deploying ML models
- Triggers Module 2 to prioritize data-related SOPs
- Doubles Module 12's compliance audit frequency
- Constrains Module 3 to high-confidence data sources only
Five modules adjust from a single diagnostic input. No standalone framework does this because no standalone framework has five downstream modules waiting for the signal.
Quarterly recalibration
The Heat-Map is not static. Module 1 diagnostics run quarterly. As the organization improves, downstream module parameters loosen. This creates visible progression: "We started with 6 red cells. After two quarters, we are at 2 red and 4 amber. Module 7 is now open for supervised pilots."
This progression is the core execution rhythm of the VWCG OS. It is not a 90-day rock cycle. It is a quarterly recalibration of the entire system based on fresh diagnostic data.
Routing in practice
A professional services firm scored red on data hygiene and change advocacy. Module 4 centralized customer and revenue data first. Module 7 restricted ML deployments until the data foundation was built. Module 10 doubled CRM adoption timelines due to predicted resistance. Two quarters later, data hygiene moved to amber. Module 7 lifted the ML restriction. Module 4 returned to standard integration work. The heat-map proposed loosening those constraints, and the leadership team confirmed it in the quarterly review.
Who This Module Is For
Module 1 was designed for mid-market companies that have outgrown founder-driven decision making but have not yet built the integrated operational infrastructure that scaling requires.
These companies typically have discipline. They have processes, KPIs, leadership teams, and technology stacks. What they lack is integration. Sales uses one set of metrics. Operations uses another. Finance runs its own dashboards. The leadership team meets weekly but discusses symptoms rather than root causes because no diagnostic framework connects the dots across functions.
EOS addresses this problem for smaller companies by providing a simple, unified operating rhythm. The trade-off is depth. EOS deliberately avoids the complexity of AI readiness assessment, multi-dimensional leadership diagnostics, and system-wide routing logic because its target market does not need it.
The VWCG OS accepts that complexity. Module 1's three diagnostic tools produce 14 scored dimensions across vision alignment, leadership capability, and technology readiness. That depth is the entry price for a system that proposes changes in 11 downstream modules based on the results.
The Working Specification
The instrument scores fourteen dimensions across three blocks: the Vision Canvas, the Leadership DNA Radar, and the AI Readiness Index. Weights are version 1.0 calibration defaults from 2026-08-20, tuned to each client during calibration.
Reliability status, 6 October 2026. Four independent scorers rated the same evidence for 8 companies against these anchors. Scorer pairs disagreed on the band of more than 3 of the 14 dimensions in 12 of 48 comparisons, and the pass rule allows none. Until the anchors pass, the heat-map proposes and leadership confirms every route that fires from a scored dimension. Safety routes still tighten on the first reading.
The Instrument
The Intelligent Foundations Diagnostic scores 14 dimensions across three tools: the Vision Canvas, the Leadership DNA Radar, and the AI Readiness Index (AERI). Every dimension is scored on a 0 to 5 scale against written anchors. The composite score is a weighted sum with block weights of 0.30 for Vision Canvas, 0.30 for Leadership DNA, and 0.40 for AERI. The DNA Radar runs on its published 1 to 10 self-rating scale, halved into the 0 to 5 standard. Each DNA score is the median of the executives' halved ratings, adjusted by the facilitator's evidence review, and every adjustment is documented. Every instrument scores in half points. The AERI subscore is the weighted mean of the five AERI dimension scores, divided by 5 and multiplied by 100. The published misalignment signal is the largest gap between any two executives' self-ratings. Above 3 points on the 1 to 10 scale becomes above 1.5 on the 0 to 5 scale.
Vision Canvas block (weight 0.30)
| Dimension | Weight | What it measures | Score 1 | Score 3 | Score 5 |
|---|---|---|---|---|---|
| Financial Transparency | 0.10 | Monthly P&L and balance sheet produced by the 15th, budget vs actuals reviewed monthly, numbers reconciling across CRM, accounting, and board deck | Financials are late, manual, or contested. Leadership argues about whose numbers are right | Reliable monthly close and reporting exist. Some reconciliation gaps between systems. Assumptions rarely stress-tested | Investor-grade reporting cadence. Single source of truth. Assumptions named, tracked, and reviewed quarterly |
| Documentation Completeness | 0.10 | Core processes documented and current. Strategy artifacts (canvas, pillars, KPI definitions) written down and referenceable by any manager | Strategy lives in the founder's head or a stale deck. Key processes undocumented | Strategy documented but partially stale. Core processes covered unevenly. Documentation effort is episodic | Single-page strategy referenceable without interpretation. Process documentation current within a 90-day cycle |
| Pipeline and Forecast Reliability | 0.10 | Forecast vs actual variance over trailing 4 quarters, pipeline coverage ratios, CRM hygiene indicators | Forecast wrong most quarters. Pipeline inflated or unverifiable. Close dates and next steps missing | Forecast directionally right but with material variance. Pipeline hygiene enforced inconsistently | Forecast variance inside agreed tolerance for 4 or more consecutive quarters. Pipeline data trusted for capital decisions |
Leadership DNA Radar block (weight 0.30)
| Dimension | Weight | What it measures | Score 1 | Score 3 | Score 5 |
|---|---|---|---|---|---|
| Strategic Foresight | 0.05 | Facilitated self-ratings per executive plus evidence review: frequency of proactive plan adjustments vs reactive change requests | Plans change only under pressure. Market shifts surface as emergencies | Some forward planning exists. Adjustments happen but often later than needed | Leadership anticipates shifts and adjusts plans before they become urgent. Reactive change requests are rare |
| Data-Driven Decision Making | 0.05 | Decision review sample: proportion of material decisions citing defined metrics vs intuition | Decisions run on instinct and seniority. Metrics consulted after the fact if at all | Data consulted for major decisions. Everyday calls still intuition-led. Some resistance to KPI accountability | Evidence is the default basis for decisions at every level. KPI frameworks welcomed, not resisted |
| Psychological Safety Provision | 0.05 | Pulse survey items, bad-news latency (how fast problems reach leadership), challenge behavior in meetings | Bad news is hidden or punished. Problems surface late. Meetings are performative agreement | Most staff will raise problems. Some topics remain unsafe. Escalation depends on the manager | Team members report bad news, challenge assumptions, and flag failures early and without fear |
| Change Advocacy | 0.05 | Behavior during recent change initiatives: visible sponsorship, resource commitment, follow-through vs quiet blocking | Leaders quietly block or wait out change. Sponsorship absent or nominal | Leaders support change when convenient. Sponsorship inconsistent across initiatives | Leaders actively champion operational change. They sponsor visibly, fund it, and hold the line through resistance |
| Accountability Rituals | 0.05 | Follow-through audit: commitments, deadlines, escalation protocols honored vs silently dropped | Commitments evaporate after meetings. Deadlines slide without consequence. Escalation is ad hoc | Core rituals exist (weekly reviews, action logs) but enforcement is uneven across leaders | Follow-through is consistent and visible. Reviews change behavior. Escalation protocols are used and trusted |
| Cross-Functional Collaboration | 0.05 | Handoff quality audit: frequency of dropped handoffs, duplicate work, interdepartmental escalations | Departments operate as silos. Handoffs drop routinely. Integration depends on heroics | Collaboration works between some pairs of leaders. Systemic handoff gaps persist | Work crosses departmental boundaries without handoff gaps. Shared metrics align the functions |
Secondary DNA signals (not weighted)
The facilitator scores three secondary signals on the same anchors and bands. They route, but they do not count toward the composite.
| Signal | Weight | Score 1 | Score 3 | Score 5 |
|---|---|---|---|---|
| Communication Consistency | 0 (not in the composite) | Leaders give conflicting messages on priorities. Changes reach teams through rumor or not at all | The top team agrees on core messages, but they drift below it. Change announcements follow no set cadence | One message per change, repeated through set channels on a fixed cadence. Managers restate it accurately |
| Inclusive Decision-Making | 0 (not in the composite) | One or two people decide. Affected teams learn about decisions after the fact | Input is sought on major decisions, but inconsistently and without a record of dissent | Affected roles are consulted before decisions, dissent is recorded, and the rationale is shared |
| Financial Discipline | 0 (not in the composite) | Spending is decided ad hoc. Budgets are revised after the fact and success criteria get redefined | Budgets exist and are reviewed, but exceptions are common and loosely recorded | Spending follows pre-set gates. Exceptions are rare and recorded with a reason |
AI Readiness Index block (weight 0.40)
| Dimension | Weight | What it measures | Score 1 | Score 3 | Score 5 |
|---|---|---|---|---|---|
| Data Hygiene | 0.10 | Completeness, accuracy, and accessibility audit of core data stores, duplicate rates, stale-record share, access patterns | Data is incomplete, duplicated, and scattered. No single customer or revenue record is trusted | Core data mostly reliable in primary systems. Duplicates and stale records persist at the edges. Access uneven | Data is complete, accurate, and accessible. Quality monitored continuously. Downstream teams trust the numbers |
| Process Clarity | 0.08 | SOP coverage of core processes, documentation currency (reviewed within 90 days), observed vs documented process variance | Workflows exist only in people's heads. Execution varies person to person | Core processes documented but coverage or currency is uneven. Deviations common | Workflows documented, consistent, and measurable. Documentation current. Deviation data feeds improvement |
| Team Attitude Toward AI | 0.08 | Structured attitude survey (fear, indifference, curiosity, enthusiasm distribution), shadow-AI usage signals, participation in AI pilots | Dominant disposition is fear of replacement or active resistance. AI usage is covert | Mixed curiosity and caution. Pockets of enthusiasm. No shared narrative about the role of AI | Workforce embraces augmentation. Experimentation is open and supported. The AI narrative is shared |
| Compliance Baseline | 0.08 | Regulatory posture review across applicable regimes (GDPR, SOC2, HIPAA, or industry-specific), data classification practice, incident history | Compliance obligations improvised. No data classification. Exposure surfaces only in incidents | Baseline controls exist for the primary regime. Classification partial. Response procedures documented but untested | Regulatory posture current across applicable regimes. Classification practiced daily. Response procedures tested |
| Tool Stack Compatibility | 0.06 | System inventory: API availability, integration readiness, data portability per system, share of systems reachable through a governed hub | Key systems lack APIs or export paths. Data portability poor. Integration would require replacement | Most core systems integrable. Some legacy gaps. Portability varies by vendor | Systems API-ready and portable. Integration hub covers the core stack. New tools onboard through governance |
Scoring and Bands
| Band | Range | What it routes to |
|---|---|---|
| Red | 0.0 up to but not including 2.0 | Proposes the owning remediation playbook for that dimension. Safety routes act on the first reading (Routing table below) |
| Amber | 2.0 to 3.5 inclusive | Standard parameters plus a 30-day pulse check, scheduled by PB-M01-08 and run by the COO |
| Green | above 3.5 up to and including 5.0 | Hold and monitor inside the M13 quarterly cycle |
The AERI subscore also carries its own published 0 to 100 bands with direct deployment effects:
| AERI band | Range | Effect |
|---|---|---|
| Red | below 40 | No new AI deployments in M07. Foundation work in M02, M03, and M04 first |
| Amber | 40 to 70 inclusive | Supervised pilots only, human-in-the-loop, monthly bias and drift audits |
| Green | above 70 | Full deployment capacity, standard governance |
Routing
Red bands fire the routes below. Every amber dimension gets a 30-day pulse check, scheduled by PB-M01-08 and run by the COO as diagnostic steward. Every green dimension holds and is monitored quarterly through M13. Conditions read the module 0 to 5 bands unless a row names another scale. A color changes only when a score clears the band edge by a margin, or holds for two consecutive scorings. The margin is 0.25 points on 0 to 5 scales and 5 points on the AERI 0 to 100 scale. Safety routes are the routes that set AI mode in any module, the Privacy Impact Assessment rule, or Module 12 classification and response windows. They tighten on the first reading and loosen only after an independent re-score clears the edge. When two routes set the same parameter differently, the most restrictive value wins for safety routes, and the owning module's value wins for every other parameter. A route that fires from a scored dimension is a proposal until leadership confirms it in the M13 Phase 3 review. Routes that fire from measured values and events (PV2, KPI variance, revenue concentration, dates, and logged events) act on the reading. Scorer agreement has not yet passed the reliability test. A proposal is confirmed at the next monthly governance review or the M13 Phase 3 review, whichever comes first, and a playbook's stated duration starts at confirmation. Routes that restore the M13 cadence itself act on the reading. A route that carries evidence feeds the next scoring of the receiving dimension and never sets a score directly. Module instruments are scored quarterly in weeks 11 to 12 of the M13 cycle, Module 1 in Phase 1, and measured signals at their own review cadence. An RT code names the destination action, so several source rows can share one.
Outbound routes
| Signal | Condition | Destination | What fires |
|---|---|---|---|
| Financial Transparency | red | M01 PB-M01-01 | Vision Alignment Reset (spine RT-M01-VC-RED) |
| Financial Transparency | red | M09 PB-M09-01 | Monthly QOE with CFO and external advisor (RT-M09-QOE-RED) |
| Financial Transparency | amber | M09 PB-M09-04 | Monthly QOE with flagged areas |
| Documentation Completeness | red | M01 PB-M01-01 | Vision Alignment Reset |
| Documentation Completeness | red | M09 PB-M09-01 | QOE exposure flagged for diligence |
| Pipeline and Forecast Reliability | red | M01 PB-M01-01 | Vision Alignment Reset |
| Pipeline and Forecast Reliability | red | M06 PB-M06-01 | Hardened CRM validation, stage aging 14 to 10 days, hygiene amber at 5% deviation, compressed follow-up cadences |
| Any DNA dimension | red | M01 PB-M01-02 | Leadership Alignment Sprint (RT-M01-DNA-RED) |
| Strategic Foresight | red | M10 PB-M10-01 | Anticipate elevated reactive change-request load |
| Data-Driven Decision Making | red | M10 PB-M10-01 | Adjust adoption messaging for KPI-framework resistance |
| Psychological Safety Provision | red | M11 PB-M11-01 | Psych-safety questions in every pulse cycle until improvement |
| Change Advocacy | red | M10 PB-M10-01 | Adoption timelines doubled, executive sponsorship mandatory |
| Accountability Rituals | red | M03 PB-M03-04 | Weekly KPI reviews at risk of becoming performative, tighten review format |
| Cross-Functional Collaboration | red | M04 PB-M04-01 | Prioritize system integration over tool optimization |
| Data Hygiene | red | M01 PB-M01-03 | Data Hygiene Remediation Sprint (RT-M01-AERI-DATA-RED) |
| Data Hygiene | red | M04 PB-M04-02 | Data centralization before any AI project |
| Data Hygiene | red | M03 PB-M03-01 | Constrain to high-confidence data sources only |
| Data Hygiene | red | M07 PB-M07-02 | ML model deployment restricted |
| Data Hygiene | red | M12 PB-M12-04 | M12 compliance audit frequency doubles |
| Process Clarity | red | M01 PB-M01-04 | Process Clarity Sprint (RT-M01-AERI-PROCESS-RED) |
| Process Clarity | red | M02 PB-M02-01 | SOP Codex shifts from optional to mandatory |
| Team Attitude Toward AI | red | M01 PB-M01-05 | AI Attitude and Adoption Readiness Campaign |
| Team Attitude Toward AI | red | M10 PB-M10-01 | AI-specific adoption campaign before deployment, micro-training rises from 3-5 to 10-15 assets |
| Compliance Baseline | red | M01 PB-M01-06 | Compliance Baseline Remediation |
| Compliance Baseline | red | M12 PB-M12-02 | Customer personal data defaults to Restricted tier, response windows compress from 72 to 24 hours |
| Tool Stack Compatibility | red | M01 PB-M01-07 | Integration Architecture Reset |
| Tool Stack Compatibility | red | M04 PB-M04-01 | Hub-and-Spoke architecture non-negotiable, Integration Steward at 10% FTE |
| AERI overall subscore | < 40 (AERI 0 to 100) | M07 PB-M07-02 | No new AI deployments in M07. Foundation work in M02, M03, and M04 first (RT-M07-LOCKED) |
| AERI overall subscore | 40-70 (AERI 0 to 100) | M07 PB-M07-04 | Supervised pilots only (RT-M07-SUPERVISED) |
| AERI overall subscore | > 70 (AERI 0 to 100) | M07 PB-M07-04 | Full capacity, standard governance (RT-M07-FULL) |
| DNA variance signal | largest pairwise gap > 3 | M01 PB-M01-02 | Leadership Alignment Sprint |
| AERI overall subscore | < 40 (AERI 0 to 100) | M05 PB-M05-03 | Churn predictor and QBR generator run advisory only. The model never starts the escalation SOP, a person decides |
| AERI overall subscore | 40-70 (AERI 0 to 100) | M05 PB-M05-04 | Each churn flag starts the escalation SOP once a person confirms it. Monthly accuracy review |
| AERI overall subscore | > 70 (AERI 0 to 100) | M05 PB-M05-04 | Churn predictor fires the escalation SOP automatically |
| AERI overall subscore | < 40 (AERI 0 to 100) | M06 PB-M06-02 | Lead scoring advisory only with human approval. Proposal generator template-only |
| AERI overall subscore | < 40 (AERI 0 to 100) | M02 PB-M02-01 | Draft-With-AI off. SOPs drafted by interview-and-write |
| Vision Canvas assumption broken | on event | M08 PB-M08-02 | The linked gate KPI turns amber. A second consecutive checkpoint over the break condition turns it red and freezes the tranche |
| Compliance Baseline | red | M07 PB-M07-02 | Models reading customer personal data run human-in-the-loop while red |
| AERI overall subscore | < 40 (AERI 0 to 100) | M08 PB-M08-01 | Scenario modelling engine advisory only. No automated tier recommendations |
| AERI overall subscore | < 40 (AERI 0 to 100) | M11 PB-M11-02 | Turnover model advisory only. HR reviews every flag before an intervention |
| AERI overall subscore | < 40 (AERI 0 to 100) | M12 PB-M12-01 | Automated threat detection keeps running. A person reviews every alert |
| Communication Consistency (secondary DNA signal) | red | M10 PB-M10-01 | Communication cadences extend and redundant channels activate |
| Inclusive Decision-Making (secondary DNA signal) | red | M11 PB-M11-03 | DEI scorecard weight in leadership evaluations rises from 20% to 40%. Inclusion questions join the pulse |
| Financial Discipline (secondary DNA signal) | red | M08 PB-M08-02 | Every gate KPI exception needs board-level sign-off |
| Communication Consistency (secondary DNA signal) | red | M11 PB-M11-01 | Communication effectiveness questions join the next pulse, inside the survey calendar limit |
| M01.data_hygiene | red | M02 PB-M02-01 | M02 prioritizes data-related SOPs (data entry, validation, ownership) |
Inbound routes
| Signal | Condition | Source module | What fires in M01 |
|---|---|---|---|
| Documentation Currency | red in M02 | M02 | Overdue average is evidence for the M01 Process Clarity anchor review at the next recalibration (PB-M01-08) |
| Alert Threshold Discipline | red in M03 | M03 | Measurement layer flagged unreliable at next heat-map recalibration (PB-M01-08) |
| Action Closure Rate | red in M03 | M03 | Check DNA Accountability Rituals dimension, closure failure is often behavioral (PB-M01-02) |
| Architecture Pattern Fit | red in M04 | M04 | Confirm the M01 Tool Stack Compatibility red that forces Hub-and-Spoke (PB-M01-08) |
| Diagnostic Calibration Response | red in M10 | M10 | M01 confirms the Change Advocacy state at the next recalibration (PB-M01-08) |
| Diagnostic Re-Run Discipline | red in M13 | M13 | M01 instruments overdue, immediate re-run outside the cycle if more than 6 months stale (PB-M01-08) |
| Diagnostic-Driven Priority Sourcing | red in M13 | M13 | Judgment-set priorities despite diagnostics often trace to DNA accountability and data-driven gaps (RT-M01-DNA-RED) (PB-M01-02) |
| Recalibration trigger signal | on event in M13 | M13 | Phase 1 days 1 to 3, full diagnostic re-run (RT-M13-RERUN-RED) (PB-M01-08) |
Playbooks
Every playbook follows one lifecycle: open, running, met or missed, escalated, closed. A trigger that arrives while a playbook is open is logged against the open run. An outcome met, with an independent re-score at amber or better, closes the run, and the owner's next queued red opens. An outcome missed at the end of its stated duration escalates to the owner's manager and the next M13 quarter planning agenda. Someone other than the owner re-scores the dimension. Each owner runs at most three red playbooks at once. Further reds queue, ranked by how many modules the red dimension routes into. Safety playbooks (PB-M07-02, PB-M12-02, PB-M12-03) never queue. A red route opens a red playbook. A route that changes a mode, a cadence, or a data feed runs under the module's standing playbook. When a red playbook's outcome is met, any standing duty it set up continues under the standing playbook, which does not count toward the cap. Escalation for a CEO-owned playbook goes to the board.
PB-M01-01: Vision Alignment Reset
Trigger: any Vision Canvas dimension red, or leadership cannot articulate a shared North-Star. Runs one full-day facilitated session to reconcile a single time-bound, measurable North-Star and fix exactly three strategic pillars with one headline Pillar KPI each. Assumptions are registered with break conditions as M08 gate candidates. Five sampled managers then read the canvas back without interpretation before publication. Outcome: canvas published, five-for-five manager readback, three Pillar KPIs registered as M03 baseline seeds, VC dimensions rescored amber or better. Owner: CEO with external facilitator, 2 weeks.
PB-M01-02: Leadership Alignment Sprint
Trigger: any Leadership DNA dimension red, or inter-executive variance above 3 points on any dimension. Also opened by routes from M03 Action Closure Rate, M13 Diagnostic-Driven Priority Sourcing. Re-runs the six-dimension assessment in one week, then reconciles every above-threshold variance through evidence-backed facilitation to a shared rating or a documented disagreement. The two lowest dimensions become sprint targets with one observable behavior change and a named owner each, backed by a weekly 30-minute alignment check. Outcome: variance at or below 3 points on every dimension, or documented disagreement with a 90-day resolution owner, and no red target dimension at re-score. Owner: CEO with external facilitator, 4 weeks.
PB-M01-03: Data Hygiene Remediation Sprint
Trigger: AERI data hygiene red (M04 prioritizes centralization, M07 ML restricted, M03 constrained to high-confidence sources, M12 governance doubled while it runs). Scopes the audit across core data stores, measures duplicate rate, stale-record share, and completeness for the 10 fields downstream modules depend on, and freezes new data-silo creation. Remediation runs in dependency order: customer records first, then revenue, then pipeline, with weekly duplicate and monthly completeness reports installed. Outcome: quality measured and improved against baseline, named system of record per core entity, dimension rescored amber or better. Owner: COO with data steward, 6 weeks.
PB-M01-04: Process Clarity Sprint
Trigger: AERI process clarity red, which shifts M02 from optional to mandatory. Inventories the 14-area core-process checklist (operations 4, customer 4, finance 3, quality 3), ranks by downstream dependency, and documents the top 5 processes through interview-to-draft. Each draft is SME-reviewed and published with owner and 90-day review date before the engine hands over to M02. Outcome: top 5 dependency-ranked processes documented and published, coverage percentage registered as a standing M02 metric, dimension rescored amber or better. Owner: COO with SOP librarian designate, 4 weeks.
PB-M01-05: AI Attitude and Adoption Readiness Campaign
Trigger: AERI team attitude red (M10 runs an AI-specific adoption campaign before deployment, micro-training rises from 3-5 to 10-15 assets). Measures the attitude baseline with an anonymous segmented survey, surfaces specific fears in listening sessions without rebuttal, then delivers a CEO-signed Change Narrative. Expanded micro-training targets the logged fear themes, and one visible pilot volunteer per team publishes a before and after experience. Outcome: re-survey shows measurable movement with no segment majority fear, library live at 10 or more assets, dimension rescored amber or better. Owner: CEO sponsor with HR/People lead, 6 weeks.
PB-M01-06: Compliance Baseline Remediation
Trigger: AERI compliance baseline red (customer personal data defaults to Restricted tier and response windows compress from 72 to 24 hours while it runs). Enumerates applicable regimes with a named owner each, applies the red-state defaults immediately, and gap-assesses posture per regime. Top severity gaps close first, and a tabletop incident exercise tests the 24-hour window. Outcome: regime owners named, Restricted default operating, top gaps closed, tabletop completed inside the window or failures logged with owners, dimension rescored amber or better. Owner: COO with external compliance counsel as needed, 6 weeks.
PB-M01-07: Integration Architecture Reset
Trigger: AERI tool stack compatibility red (M04 Hub-and-Spoke architecture becomes non-negotiable, Integration Steward allocated at 10% FTE). Builds the System Inventory Sheet across every tool with owner, API availability, data objects, refresh cadence, and cost. Per-system integration readiness is scored, and the 60-second data-flow test runs. The Hub-and-Spoke constraint is ratified in writing and the Integration Steward is designated. Outcome: inventory complete, readiness scored, architecture decision recorded, steward named, dimension rescored amber or better. Owner: COO with Integration Steward, 4 weeks.
PB-M01-08: Quarterly Recalibration and Amber Monitoring
Trigger: standing inside every M13 quarterly cycle (Phase 1, days 1-3), or an out-of-cycle re-run when instruments are more than 6 months stale. Amber cells get a 30-day pulse check run by the COO. Also opened by routes from M02 Documentation Currency, M03 Alert Threshold Discipline, M04 Architecture Pattern Fit, M10 Diagnostic Calibration Response, M13 Diagnostic Re-Run Discipline, M13 Recalibration trigger signal. Re-runs all three instruments for 14 fresh scores after a data-quality pre-check. The heat-map register is updated with trend notes, and 30-day pulse checks are scheduled for every amber dimension. Every red cell must carry an active or queued playbook, and no red cell may persist two quarters without one. Outcome: 14 fresh scores logged and delivered to M13 Phase 2 on day 3, every red cell owned, every amber cell scheduled. Owner: COO as diagnostic steward with CEO participation, 3 days per quarter.
Working templates ship with the module: the vision canvas session, the leadership DNA radar, and the heat map register. Template artifacts and full playbook bodies are delivered during an engagement.