Competency Matrix & Portfolio Scoring

Executive summary#

• Competency matrix operationalizes the three-axis model at portfolio scale — tracking 50-500 people across 5-20 capabilities
• Four interconnected views: Capabilities (requirements), People (assessments), Gaps (supply vs. demand), Decisions (staffing actions)
• Key metrics: Delivery-ready score per capability, utilization by competency level, gap FTE by horizon
• Most firms track headcount only; competency matrix tracks capability readiness, which predicts delivery success better
• Use this framework for quarterly planning, weekly staffing decisions, and hiring prioritization

Definitions#

Competency Matrix: Portfolio-scale tracking system combining capability requirements, individual competency assessments, and availability to calculate organization-wide readiness.

Delivery-Ready Score: Composite metric combining competency score (Technical × Business × Agency), complexity fit, and availability to predict whether someone can successfully staff a project.

Gap Analysis: Comparison of supply (current competency inventory) vs. demand (project requirements) to identify hiring, upskilling, or partnering needs.

What this includes: Structured data model, scoring formulas, decision rules for staffing and investment.

What this does NOT include: Performance management, compensation decisions, or career pathing (those use different systems).

Key distinction: This is a planning and staffing tool, not an HR system of record. It answers: "Do we have the capability to deliver this work?"

Why this matters#

Business impact#

Competency matrix enables:

• Better staffing decisions — match people to projects based on competency, not just availability
• Proactive gap identification — spot capability shortfalls 3-6 months early
• Investment prioritization — know which capabilities to hire for vs. partner
• Risk visibility — flag projects at risk due to competency-complexity mismatches
• Improved skill coverage — track proportion of required competencies adequately staffed across the portfolio

Without competency matrix:

• Reactive staffing — "who's available?" instead of "who's capable?"
• Surprise gaps — discover capability shortfalls mid-project (too late)
• Wasted hiring — hire for wrong capabilities or wrong levels
• Hidden risk — assign work to insufficient competency, discover failures in delivery

Why competency tracking changes outcomes#

The directional effects are consistent:

• Fewer delivery surprises — competency-complexity mismatches are visible before they become client problems, not after
• Earlier gap identification — a quarterly portfolio review can spot a capability shortfall 3-6 months before it creates a staffing crisis
• Better use of senior capacity — when you know who is genuinely delivery-ready (not just available), you stop over-relying on the same 3 senior FTEs for everything
• Cleaner hiring logic — gap analysis tells you which capability to hire for, not just how many people you need

The Framework: Four Views#

canonical_block: data_primitives
version: 1.0.0
concept_id: framework.competency_architecture
updated_date: 2026-02-16

system_name: "Competency Matrix"
description: "Portfolio-scale system tracking capabilities, people, gaps, and staffing decisions"

data_model:
  capabilities:
    description: "Required competency profiles by capability"
    fields:
      - capability_name: "string"
      - required_technical: "0-4"
      - required_business: "0-4"
      - required_agency: "1-5"
      - required_complexity: "0-4"
      - classification: "Core | Strategic | Contextual"

  people_assessments:
    description: "Individual competency evaluations by capability"
    fields:
      - person_id: "string"
      - capability_name: "string"
      - technical_score: "0-4"
      - business_score: "0-4"
      - agency_score: "1-5"
      - complexity_experience: "0-4"
      - availability_fte: "0.0-1.0"

  computed_scores:
    description: "Derived metrics from assessments"
    formulas:
      - name: "agency_norm"
        formula: "(agency_score - 1) / 4"
      - name: "competency_score"
        formula: "(technical * 0.5) + (business * 0.2) + (agency_norm * 0.3)"
      - name: "complexity_fit"
        formula: "MIN(1, complexity_experience / required_complexity)"
      - name: "agency_gate"
        formula: "IF(agency_score >= required_agency, 1, 0)"
      - name: "delivery_ready_score"
        formula: "competency_score * complexity_fit * agency_gate * availability_fte"

  capability_summary:
    description: "Aggregate readiness by capability"
    calculations:
      - name: "total_ready_fte"
        formula: "SUM(delivery_ready_score WHERE capability = X)"
      - name: "average_competency"
        formula: "AVERAGE(competency_score WHERE capability = X)"
      - name: "utilization"
        formula: "(allocated_fte / total_ready_fte) * 100"

How it works#

View 1: Capabilities (Requirements)#

Define required competency profiles for each capability.

Example: Cloud Architecture

Example: Project Management

View 2: People (Assessments)#

Assess each person's competency per capability.

Example: Sarah (Cloud Engineer)

Calculations:

• Cloud Architecture Competency Score: (2 × 0.5) + (1 × 0.2) + (0.5 × 0.3) = 1.35
• Complexity Fit (Cloud): MIN(1, 2/3) = 0.67
• Agency Gate (Cloud): IF(3 >= 4, 1, 0) = 0 ❌ (Fails agency requirement)
• Delivery-Ready Score (Cloud): 1.35 × 0.67 × 0 × 1.0 = 0 ❌

Interpretation: Sarah has decent technical skills but the agency gap (3 vs. required 4) means she'll need closer oversight on Cloud Architecture work than the role allows for — client-facing problems will require escalation instead of autonomous resolution. She's genuinely better suited for DevOps work where she scores 2.03 and the agency bar is lower.

On the agency gate: The binary 0/1 output is intentional — it surfaces a hard risk, not a gradient. In practice, if Sarah were the best available option for a Cloud Architecture engagement, the gate flags the gap so it can be managed deliberately: paired with a senior, shorter delivery window, specific escalation path agreed upfront. The gate doesn't prohibit the assignment. It forces the question: do we understand and accept this risk, and have we structured for it?

View 3: Capability Summary (Portfolio View)#

Aggregate readiness by capability.

Example Portfolio

Insights:

• Cloud Architecture: 18.5 ready FTE, 95% utilized → only 0.9 FTE bench → under-capacity, hire urgently
• Project Management: 8.4 ready FTE, 85% utilized → 1.3 FTE bench, but PM is contextual → over-invested, reduce internal team
• Data Engineering: 12.2 ready FTE, 88% utilized → 1.5 FTE bench → healthy capacity

View 4: Gap Analysis#

Compare demand forecast vs. supply.

Example: Q2 2026 Demand

Actions:

1. Cloud: Immediate gap → engage partners, activate stash
2. Data: Short-term gap → partner for Q2, consider hiring if demand stays high in Q3
3. Security: Chronic gap → hire 1 FTE, establish partner relationship
4. PM: Surplus → phase out 2 internal PMs over 12 months

Example: CaseCo Mid#

Action: Competency Matrix Implementation#

Implementation Checklist#

Phase 1: Setup (Month 1)

• Define 5-10 key capabilities
• Set required competency profiles per capability (T/B/A/Complexity)
• Classify capabilities (Core / Strategic / Contextual)
• Build spreadsheet or database schema

Phase 2: Assessment (Month 2-3)

• Assess 50-100% of billable team (start with revenue-critical roles)
• Calculate delivery-ready scores
• Identify assessment gaps (people not yet assessed)

Phase 3: Analysis (Month 3)

• Generate capability summary (ready FTE, utilization, avg competency)
• Forecast demand for next 2 quarters
• Run gap analysis
• Prioritize actions (hire / partner / upskill)

Phase 4: Operationalize (Month 4+)

• Quarterly portfolio reviews
• Monthly utilization tracking
• Weekly staffing decisions use delivery-ready scores
• Continuous assessment updates (new hires, promotions, skill development)

Spreadsheet Template (Google Sheets / Excel)#

Sheet 1: Capabilities

Sheet 2: People_Assessments

Sheet 3: Computed_Scores (calculated columns)

Sheet 4: Capability_Summary

Pitfalls#

Next#

• Competency Model — Understand the three-axis scoring framework
• Complexity & Experience — Match complexity to competency
• Core vs Contextual — Classify capabilities before investment
• Staffing Gate — Use delivery-ready scores in weekly staffing decisions

What decisions this enables#

• Whether a specific engineer can be assigned to a project without a competency-complexity mismatch
• Which capabilities to prioritise in the next hiring cycle based on readiness gap data
• When to partner versus hire based on a gap's classification and time horizon
• How to present capability readiness to the board in a format that connects to revenue risk
• Whether a quarterly portfolio review warrants any changes to hiring plans or partner investments

FAQs#