FlowRadar — Organizational Flow Diagnostics

🧠 Overview

FlowRadar is an analytical model designed to diagnose organizational flow through the lens of dependencies and system structure.

Instead of focusing only on execution metrics (like lead time or throughput), FlowRadar reveals:

• where the system actually depends
• how fragile the structure is
• how coordination impacts delivery

It shifts the perspective from managing work to understanding the system behind it.

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🔍 What is this?

FlowRadar is not a tool or a dashboard.

It is a model that answers questions such as:

• Where are the real bottlenecks?
• Is the system structurally fragile?
• How much coordination is required to deliver value?

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🚀 Installation

1. Clone the repository

git clone https://github.com/brunonovaesgit/flowradar.git
cd flowradar

Before cloning, pick a local folder where you want to store the project.

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2. Set up a virtual environment

python3 -m venv venv
source venv/bin/activate  # Linux / Mac

# ou
venv\Scripts\activate     # Windows

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3. Install dependencies

pip install -r requirements.txt
pip install -r requirements-dev.txt

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▶️ Running

Run the main analysis:

python run_flowradar.py

Run impact simulations:

python compare_simulations.py

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🧪 Testing

Run all tests:

pytest

Run with more detailed output:

pytest -vv

📊 What you get

Depending on your scenario, FlowRadar will generate:

• Dependency network (graph.json)
• Impact ranking (who actually matters in the flow)
• Dependency concentration heatmaps
• Simulations of squad removal or changes
• Structural explanations of system behavior

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📈 What you start to see

After using FlowRadar, some things become pretty clear:

• Why features get stuck for weeks
• Why splitting stories doesn’t always help
• Why some teams “always seem delayed”
• Why good metrics don’t necessarily mean a healthy flow

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⚠️ The necessary discomfort

FlowRadar won’t give you comfortable answers.

It might show that:

The problem isn’t the team The problem isn’t the process The problem is how the work is structured

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📊 Project structure

.
├── src/
│   ├── analysis/
│   ├── graph_builder/
│   ├── metrics/
│   ├── pipeline/
│   ├── reports/
│   ├── simulations/
│   └── visualizations/
│
├── tests/
├── data/
│
├── run_flowradar.py
├── compare_simulations.py
│
├── requirements.txt
├── requirements-dev.txt
├── pytest.ini
└── README.md

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🧩 Core Concept

Organizations can be modeled as a network of dependencies:

• Nodes → squads / teams
• Edges → dependencies between them

G = (V,E)

Where:

• V = set of nodes
• E = set of dependencies

This allows us to move from isolated metrics to system-level analysis.

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⚠️ Criticality

Each node can be evaluated based on its structural importance.

A simplified formulation:

Cᵢ = α · InDegreeᵢ + β · BetweennessCentralityᵢ

Where:

• InDegree captures how many depend on the node
• Betweenness captures how much flow passes through it

High criticality indicates potential bottlenecks.

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🔥 Flow Fragility Index (FFI)

FFI = Σ(Cᵢ²) / Σ(Cᵢ)

What it measures

The concentration of critical dependencies in the system.

Interpretation

| Range      | Meaning                      |
|------------|------------------------------|
| < 0.3      | Distributed (low fragility)  |
| 0.3 – 0.6  | Moderate concentration       |
| > 0.6      | High fragility               |

Insight

A high FFI means the system depends heavily on a few nodes, increasing systemic risk.

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🔄 Coordination Cost Index (CCI)

CCI = Σ(dependencies) / N

Where:

• N = number of squads

What it measures

The average coordination effort required per squad.

Interpretation

| Range  | Meaning                     |
|--------|-----------------------------|
| < 2    | Low coordination            |
| 2 – 4  | Moderate                    |
| > 4    | High coordination overhead  |

Insight

Higher CCI means more alignment, more communication, and slower flow.

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🌐 System Behavior

By combining FFI and CCI, we can characterize the system:

| Scenario             | Interpretation             |
|----------------------|----------------------------|
| High FFI + High CCI  | Fragile and overloaded     |
| Low FFI + Low CCI    | Resilient and autonomous   |
| High FFI + Low CCI   | Centralized but efficient  |
| Low FFI + High CCI   | Distributed but complex    |

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📊 Example Output

FlowRadar transforms operational data (e.g., Jira) into:

• dependency graphs
• heatmaps
• criticality rankings
• system-level indicators

These outputs make invisible structures visible.

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🎯 Why This Matters

Traditional metrics answer:

“How fast are we delivering?”

FlowRadar answers:

“Why are we slow — structurally?”

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🧭 Positioning

FlowRadar is not:

• a project management tool
• a dashboard
• a reporting layer

It is:

a model for diagnosing organizational flow as a system.

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📖 Article

For a deeper explanation and narrative context:

👉 (https://medium.com/@brunonovaesbr/flowradar-hidden-architecture-of-flow-461e96d42ddd)

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🧠 Final Thought

Organizations don’t struggle because they lack effort.

They struggle because they cannot see the system they operate in.

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☕ Support FlowRadar

If FlowRadar helps you understand flow, dependencies, and bottlenecks in real-world systems, consider supporting its evolution:

👉 https://buymeacoffee.com/brunonovaes