WBS Resource Allocation: Why Larger Teams Aren't Always Faster

Source: Dev.to

If we add more people, it’ll finish faster, right?
When developers hear this, they often sigh internally.
Actually, it might take longer.

Brooks’ Law—“Adding manpower to a late software project makes it later”—has been true for 50 years and still holds today. Below we explore why larger teams aren’t always faster and how to allocate resources effectively.

Communication Overhead

The number of communication paths grows quadratically with team size:

In a 20‑person team, even 1 hour per day disappears to coordination. Measured data shows that teams of 10 + developers often spend less than 4 hours per day actually coding; the rest is meetings, reviews, questions, answers, and waiting.

Team Size Guidelines

“A team that can’t be fed with two pizzas is too large.” – Jeff Bezos

Ideal composition (≈ 7 people):

• Product Owner: 1
• Backend Developers: 2
• Frontend Developers: 2
• Designer: 1
• QA Engineer: 1

Why “just assign the best person” fails

Even if Alice is a React expert, without domain knowledge her productivity drops ≈ 50 %. She still needs:

• ~2 weeks to understand the existing codebase
• ~1 week to adapt to team coding conventions

Common Misconceptions

“Divide work into 10 tasks, 10 people can do them simultaneously”

// PM's imagination
const ideal_timeline = {
  workDivision: 10,
  peopleAssigned: 10,
  expectedDuration: '1 week',
};

// Actual reality
const reality = {
  dependencyWaiting: '30% time waste',
  integrationWork: 'additional 20% time',
  communication: 'additional 25% time',
  actualDuration: '2.5 weeks',
};

Division Strategies

Team Structure

Core Team (3‑4 people)

• Core architecture design
• Major decisions
• Final code‑review approval

Support Team (5‑6 people)

• Specific feature implementation
• Test writing
• Documentation

Advantages: maintain decision speed, ensure quality consistency, enable efficient knowledge transfer, and never allocate 100 % of capacity to a single task.

Recommended Resource Allocation

# Recommended allocation (percent of capacity)
recommended_allocation = {
    "Planned work": 70,
    "Urgent issue response": 15,
    "Code review / mentoring": 10,
    "Learning / improvement": 5,
}

Adjustment by Experience Level

junior_allocation = {
    "Planned work": 50,   # lower to allow learning
    "Learning / improvement": 20,
}

Real‑World Example

Project A – 3‑month effort, 5‑person team

• After 1 month: only 20 % progress
• Decision: add 5 more people
• Outcome: training overhead, tripled communication, frequent merge conflicts → 2‑month delay

Project B – Same company, next effort

• Structure: 3 teams of 3 people, each owning an independent microservice
• Coordination: pre‑defined API contracts, full sync only once per week
• Result: finished 2 weeks early

Workload Visualization

resource_heatmap = {
    "Mon": {"Alice": 120, "Bob": 80,  "Charlie": 100},
    "Tue": {"Alice": 100, "Bob": 120, "Charlie": 80},
    "Wed": {"Alice": 80,  "Bob": 100, "Charlie": 120},
    # …
}

• ≥ 120 % – Overload (red)
• 80‑120 % – Appropriate (green)
• < 80 % – Available (blue)

Pair Rotation

// Weekly pair rotation
const pair_rotation = {
  'Mon‑Tue': [
    ['Senior', 'Junior'],
    ['Mid',    'Mid'],
  ],
  'Wed‑Thu': [
    ['Senior', 'Mid'],
    ['Junior', 'Mid'],
  ],
  Fri: 'Individual work / Refactoring',
};

Effects

• Maximize knowledge sharing
• Improve code quality
• Reduce bus factor

Global Collaboration

Korean Team (09:00‑18:00 KST)
   ↓ Handoff
US Team (09:00‑18:00 PST)
   ↓ Handoff
European Team (09:00‑18:00 CET)

A 24‑hour development cycle is possible, but hand‑off documentation is essential (e.g., Plexo’s real‑time WBS updates, GitHub PR async comments, Notion RFCs, Loom video stand‑ups).

Key Takeaways

• Small, cross‑functional teams (5‑7 people) outperform larger groups.
• Communication cost grows quadratically; keep it low.
• Allocate ≤ 70 % of capacity to planned work; reserve ≈ 30 % for unexpected events.
• Avoid “superstar dependency”; invest in raising the whole team’s capability.
• Pair programming and regular rotation reduce bus factor and spread knowledge.
• Treat resource allocation as a complex optimization problem, not simple arithmetic.

Need efficient resource management and WBS? Check out Plexo.