Crowdsourcing obtains ideas, content, labor, or solutions by opening a task to a large, often loosely organized group of people, rather than assigning it to a single expert or small team.
The idea
A large enough group brings a wider range of knowledge, perspectives, and effort than any individual or small team can. When the group is diverse and contributions are aggregated well, crowdsourcing can surface solutions, catch errors, or produce volume that would be slow or expensive to generate internally. It works because it trades centralized control for scale and diversity of input.
When to use it
- Generating a large volume of ideas, designs, or content options
- Tapping specialized knowledge scattered across many people (e.g. bug bounties, open-source contributions)
- Validating or improving a solution by exposing it to many eyes
- Tasks that are easy to parallelize into small, independent pieces
How to apply it
- Break the task into units that individuals can contribute to independently.
- Open the task to a broad, relevant group (public or a defined community).
- Provide clear guidelines and a way to submit contributions.
- Aggregate, filter, or vote on submissions to surface the best results.
Watch out for
- Quality varies widely; you need a filtering or curation mechanism
- The crowd can converge on popular-but-wrong answers without independent input (see wisdom of crowds)
- Coordination and review overhead can eat into the time saved
- Incentives matter — unpaid or poorly incentivized crowds may not sustain effort
Related models
- Wisdom of Crowds — the underlying principle for why aggregated independent judgments can outperform individual experts.
- Social Proof — explains why crowd contributions can also converge on herd behavior rather than independent judgment.
- Network Building — a broad, open network is what makes a crowd worth tapping into in the first place.
Sources
Jeffrey Howe coined the term “crowdsourcing” in his June 2006 Wired article “The Rise of Crowdsourcing.”