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Ever Since Artificial Intelligence and IoT has transformed businesses worldwide, there has been a need for data collection and crowdfunding on a large scale. Enterprises and businesses have leveraged crowdsourcing of data to solve their issues and problems for years now.
So, to cater to corporate demands of crowdsourcing data for solution of problems or R&D work, there began crowdsourcing contests like TopCoder or Kaggle.
These contests have helped businesses not only to solve their business-related troubles but also to access an external pool of knowledge not associated with the firm.
Through innovation, we can leverage the synergies between health and sustainability, giving great opportunity to improve people’s lives.
Frans van Houten, CEO of Royal Philips
Last year itself, the crowdsourcing testing market grew by $1.3 billion and will grow up to $2 billion till 2024, with a compound annual growth rate of 9.9%. It clearly shows the importance of crowdsourcing techniques in business operations and, specifically, testing operations.
Giant enterprises like SAP, Dell, Google, General Electric, Fiat, LEGO, and Procter & Gamble have already started their crowdsourcing platforms.
But, yet the biggest challenge in crowdsourcing remains to be the participation of external resources in appropriate numbers. We will discover how crowdsourcing contests are encouraging higher participation?
Also read: SaaS
What is Crowdsourcing?
It was introduced in 2006. Crowdsourcing is an act performed by enterprises and businesses to take their operations and processes already achieved by their employees and outsource it to an extensive network of the undefined workforce through an open call.
With crowdsourcing, the companies get the benefit of crowd intelligence. Participants get the satisfaction of not only the issue being solved, but, also get to contribute to building innovative products.
what the types of crowdsourcing used commonly in industries are
Virtual Labor Markets
These are spot labors mediated by technology markets. Virtual labor markets like MTurk, FigureEight, and many others, facilitate people to perform tasks, which are not easy to complete by the usage of current technology.
Take an example of Amazon Mechanical Turk or MTurk, which uses human intelligence as their resource to achieve completion of tasks requested by businesses through crowdsourcing.
FigureEight is a crowdsourcing marketplace, where business-related data are aggregated through the use of human intelligence and train machine learning algorithms to enhance business processes.
Even the task related to core business processes such as developing a mobile application is now outsourced through virtual labor marketplace like Upwork and others.
The rising gig economy is powering more crowdsourcing techniques and usages for business purposes. The only problem with virtual labor markets as a potential crowdsourcing solution is that it is only suitable for specific tasks and can’t be used for a generalized model.
Crowdsourcing Contests
It is a crowdsourcing type, where business ideation is performed through the tournament. Business organizations use their platforms to post problems or use some third-party platforms like Kaggle.
Starbucks started a crowdsourcing tournament called MyStarbucks in 2008. It reported more than 150000 ideas for the food and beverage company, off which 277 were put to work by Starbucks.
Crowdsourcing contests are great platforms for consumers to submit ideas regarding anything linked to the brand and its products directly to the company.
Kaggle is an online community of data scientists that organizes crowdsourcing contests. Kaggle is owned by Google and is powering several researchers and data scientists in obtaining essential knowledge regarding different domains.
From DeepFake detection challenge to House prices: advanced regression techniques, you will find a crowdsourcing contest for every domain.
It allows users to search for datasets and publish them on the platform. Users can also build models and algorithms using these datasets.
Models and algorithms developed by users are placed in open crowdsourcing contests to solve the challenges of data science. Kaggle has successfully facilitated hundreds of crowdsourcing contests and has provided solutions for enterprises as well as scientific communities.
Open Collaborations
Open collaborations are crowdsourcing techniques with voluntary contributions. Here, the participants do not have any monetary gain in place of the contributions they offer.
Think of Google Maps! Where people update locations nearby and data regarding the same through information, pictures, or even reviews. Google Maps, Apple Maps, Wikipedia, and many other such community-based services are open collaborations.
Here, data accumulated help several businesses to operate and maintain their processes. Just thinks of Uber without Google Maps? You can’t navigate through your mobile or even search for any specific data like you do on Google, without open collaboration.
VLM Vs. Contests Vs. Collaborations; Which is the better one?
VLM has had its success with the outsourcing of projects and development works.
But, due to its disability to cope up with a generalized model, it is not so much of a use to businesses with large scale or successful product development.
On the other hand, open collaborations with little or no incentives to participants do not provide accurate data and need higher curation of the data received.
But, if you are a business with innovation or a new concept in mind, crowdsourcing contests can undoubtedly lift the process and make your ideas come to life.
With incentivized participation, you are bound to receive more significant contributions and more brand conscious participation.
Let us discover some factors that affect the business decision to choose among the three crowdsourcing techniques
Costing
It refers to the cash outflows performed by businesses and firms for crowdsourcing purposes.
OC or Open Collaborations, does not need massive cash outflows due to the usage of social platforms such as Twitter, Reddit, and others. While if you go for crowdsourcing contests or VLMs, there will be a need for explicit cashflows.
For crowdsourcing contests, the costing remains fixed, with all the prizes and remuneration set before the competition begins. While VLMs have variable cashflows depending upon the magnitude of the task and contribution required.
Participation
The type of participation in all three crowdsourcing techniques is different. In VLMs, the participation is more specific, and the anonymity of the participants remains methodological. The reason for this, being crowd workers being identified through unique numbers.
In OC, the identities of participants online and participants offline is virtually twinned. For crowdsourcing contests, the anonymity of the participants remains in a medium state, with some intermediaries offering total anonymity.
Data Reliability
Probably, an essential part of the crowdsourcing process is achieving reliable data. When we compare all the three types of crowdsourcing techniques in terms of data they aggregate, OC remains at the front with the most substantial amount of data aggregated, but, in terms of reliability, there is no match to crowdsourcing contests as they provide the most reliable data. VLM’s have task-specific data and need enterprises to share data too.
Signing Off
Data is the new currency of the digital era. Every innovation, technology, or new concept needs massive amounts of data for analysis, design concepts, and implementations.
Businesses today know the essentiality of data in operations and product development, and that is the sole reason, crowdsourcing has seen such traction and investments from enterprises over the years.
If there is anything to suggest the broader acceptance of crowdsourcing techniques like crowdsourcing contests for data aggregation, problem-solving and innovative ideation, then extensive usage of IoT devices in businesses today will vouch for it.
So, if you are an innovative startup, get your idea polished with a crowdsourcing contest
Thank you!
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