WinterMilestone 3 BPHC ReputationIdea : Referral Network for Workers
We propose a solution consisting of three design aspects, that attempt to solve needs related to - worker reputation, matching requester and worker requirements and the high bar for entry for newcomers.
- 1 Referral Network for Workers
- 2 Assisting Requesters in Finding the Right Workers at the Right Time
- 3 Reputation of Newcomers
- 4 Milestone Contributors
Referral Network for Workers
We propose a referral based system that deals with the following reputation and relevant work issues:
- A problem with a system that prefers assigning tasks to workers with high reputation, is that new workers may find it difficult to find good HITs. Requesters would tend to allot jobs to the same set of highly rated users. Similarly, existing workers would tend to take up HITs from the same set of requesters with high ratings.
- Workers rely on external forums (TurkerNation, Reddit etc) to find good HITs from reliable requesters. Clearly any future crowd-sourcing platform should reduce this burden on the worker by allowing dedicated workers to easily share good HITs and help fellow workers to find relevant work .
The employee referral network in the corporate world is known to be a cost and time effective method of recruitment that produces high quality candidates. 92% of the participants in the Global Employee Referral Index 2013 Survey stated that referrals were a top source of recruitment. We thought about adapting the referral system to our crowd sourcing platform design. This would enable workers to recommend or “refer” other workers (existing or new) for good HITs.
Implementation of a Referral Network for Crowdsourcing
We illustrate the use of the referral system through the following example.
1. Requester R has a HIT to post on the crowd-sourcing platform. R can view highly rated workers using Boomerang and make the HIT visible to them (or post the HIT publicly for all to see).
2. Worker W notices the HIT posted by R and has the following options:
- Accept the HIT.
- Share the HIT with fellow workers. In the referral based scheme, this can be done in the following ways:
- 1. W refers workers he or she knows to R.
- 2. W can publicly offer to refer anyone who is interested in HIT. This is similar to how referrals are shared across social networks like Facebook, Twitter. This referral sharing network can be integrated into the crowd-sourcing platform, removing the need for multiple external forums.
- 3 The quality of referrals is incentivized in a number of ways, such as including a measure of good referrals in the scores used to rank workers and requesters. A separate index could also be used for referrals or requesters may reward good referrals with bonus payments.
Benefits of Referral Network
Assisting Requesters in Finding the Right Workers at the Right Time
Although Boomerang attempts to resolve this issue by creating a time staggered access to work, based on reputation; as the number of workers grow, this may not be enough to resolve this issue.
Suggestion: 73% of workers you have rated as 'Good' are usually available between 9:00 am and 3:00 pm. Would you like us to post the task for you in those hours?
This would require workers to allow the platform to log usage timings which is a potential privacy issue. In addition, if most workers are from a certain timezone, it could skew the tasks in favor of one country.
Reputation of Newcomers
In addition to the referral scheme we suggested above, we propose a simple technique to allow a new worker's ability to be evaluated:
- Similar to how many freelance work websites offer skill tests, a requester who has posted tasks multiple times will be asked to offer a snippet of an old completed task to be used as a test. - New workers seeking access to a task offered by that requester complete this sample task. - New worker's answers are correlated with answers given by a worker that was judged to be good by the requester. - If there is high correlation between the answers, the new worker may be allowed to perform the latest task.
@adityanadimpalli , @sreenihit