Why Large Teams Often Result in Low Efficiency in Software Development

The article shares personal experiences of "odd phenomena" in software development where a large team produces little output, highlighting the mismatch between team size and efficiency.

1. Non‑specialists doing specialized work reduces efficiency – Assigning tasks to people without the required expertise (e.g., backend engineers writing front‑end code or DBA tasks) leads to slower progress, especially as software roles become more specialized.

2. Ignoring code quality causes rework – Rushing development without proper testing or design may appear fast initially, but later testing reveals many defects, forcing costly rework and jeopardizing project schedules.

3. Team expansion increases communication cost – As the number of members grows, daily stand‑ups and information transfer take longer, and messages can become distorted, leading to misunderstandings and duplicated effort.

4. Lack of trust between superiors and subordinates hampers work – When managers do not trust their team, they over‑monitor and duplicate tasks; when team members feel mistrusted, they become hesitant and less productive.

5. Inter‑departmental communication barriers – Different departments (e.g., development and operations) have distinct knowledge bases and risk perceptions, causing delays such as waiting for approvals before simple actions like restarting a service.

6. Poor task allocation by managers – Inadequate project planning and task breakdown lead to some members being idle while others are overloaded, especially for new managers lacking holistic process thinking.

7. Unclear or misinterpreted requirements cause rework – Requirements often get lost or altered as they pass through multiple layers, resulting in significant rework when the final implementation does not meet the original intent.

8. Outdated or overly complex technical architecture reduces productivity – Modern, unified development standards and tools (e.g., automated UI generation, messaging frameworks, service governance) dramatically increase developer output compared to legacy, cumbersome systems.

Overall, the article emphasizes that improving efficiency requires assigning the right people to the right tasks, maintaining code quality, minimizing communication overhead, fostering trust, clarifying requirements, and adopting modern, streamlined architectures.