What is the difference between outsourcing and crowdsourcing?

The line is blurry between crowdsourcing and outsourcing and for good reason: there are lots of areas where the two overlap. You might even go so far as to say that crowdsourcing is a type of outsourcing, particularly when used to tackle document- and data-centric tasks.

There is such a wealth of information that needs to be identified across an organization every day of the year. According to Deloitte, the volume of data grows exponentially year over year: global data volume is projected to reach 175 zetabytes by 2025. With this in mind, processing  data—accurately—presents a challenge for each organization.

Many companies find themselves with backlogs of unidentified incoming information. For those with the most to lose when either the information isn’t accurately captured, or comes too late to impact decision making, this is a critical challenge that must be addressed. For organizations in the healthcare, insurance or banking verticals, the exposure goes beyond customer retention, and extends to increased risk and large cost outlays. In these industries, and in a growing number of countries, considerations must also be made for legal requirements around data privacy and consumer data protection.

Often these organizations must look beyond their own ability to hire and train staff to help manage the data entry, labeling and validation processes that are critical to keep the doors open and the business running as hiring and retaining resources at large volumes is unsustainable. This is where outsourcing and crowdsourcing solutions are often introduced into the process.

What is the difference between the two? Are they the same thing? Is one “better” than the other?

Outsourcing is a more traditional approach that was common until crowdsourcing was introduced into the market, made possible by the improved processing speed of cloud technologies and wider availability of the internet even in developing countries. The latter, a relatively new trend,  started with crude plug-ins provided by the big three brands in tech (Amazon, Google, Microsoft).

You’ve likely interacted with a crowdsourcing provider in the last week: it’s the operating model for everything from DoorDash to Uber and Lyft. It offers access to a pool of resources, made available on demand and seamlessly. Both models have strengths and can be more or less effective in certain types of projects. New, modern BPOs and crowdsourcing platforms are leveraging machine learning and AI to bolster human interaction. We call this collective intelligence.

Because the stakes are often high with these document-centric tasks, which can inform everything from risk analysis to customer experience and retention, organizations were hesitant to let data be dispersed to “just anyone” in a crowdsourcing environment. New providers have answered these concerns with improved controls and microtasking, meaning the crowd can be harnessed safely. Think: more humans-in-the-loop (HITL), less broad funnel engagement.

What types of tasks are right for crowdsourcing vs outsourcing?

As you consider the graph below, one important difference to note is that with outsourcing, the  workers interacting with data are much closer to the customer experience than with crowdsourcing, regardless of task.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

Crowdsourcing combined with outsourcing results in powerful processing

Unlike what the table might suggest, the two work perfectly as complementary services to one another, bolstering scalability of an outsourcer’s resources with crowdsourcing, for example, or funneling documents or images from a commercial organization via an outsourcer to a crowdsourcing platform for a particularly mundane task, or tasks that require human intervention. For example, when processing insurance claims or medical records, simple data entry is pushed out of a BPO’s task list to a crowdsourcing provider. This may also occur in scenarios where there are massive volumes of pages that must be classified before more thought-based processing is completed, or where handwriting is present. All of this means higher data accuracy for the BPO, while also making the process more efficient.

Do you have more questions about which type of outsourcing model is right for you? We have a wealth of resources available to help you make the right decision, or reach out to us for a discussion about your specific needs.

Sign for regular news from ScaleHub

orem ipsum dolor sit amet, consectetur adipiscing elit.

Recommended Posts

Scroll to Top