3 signs you should consider incorporating crowdsourced data entry
For all the incredible technological leaps and bounds we’ve made in the past few decades, we haven’t been able to bypass the need to transfer information from a document, image, or video to a software system. The task of data entry remains a thorn in the side of any organization that solves business challenges with technology.
The reason data entry is such a stubborn challenge is that it can, for the most part, be automated, but it still requires human intervention. Manual data entry is slow and prone to errors, and automated methods such as OCR consume employee time and attention to resolve exceptions. Sound familiar?
This is precisely why more and more organizations are turning to crowdsourcing for data entry. By combining the best of human ingenuity and technology, a crowdsourcing solution can offer accuracy, speed, and data privacy that other data entry methods have not reached. Today, the best of technology is artificial intelligence (AI), and it can be applied throughout the crowdsourcing process to incorporate human work in the most effective way possible.
Wondering if crowdsourcing could solve your data entry woes? Here are three signs your organization should consider incorporating crowdsourced data entry:
1. Bad data is a big deal
All businesses collect data of some kind, and more and more organizations are putting that collected data to use. In a 2019 Deloitte survey, 49% of respondents reported that data helps them make better decisions, 16% said it better enables key strategic initiatives, and 10% said it helps them improve relationships with customers and business partners. But if you’ve ever performed or overseen data entry work, you know very well how many errors make their way in. We touched on this in a recent blog post, but the impact of bad data on the bottom line is real (Gartner found that the average annual cost of poor data quality to an organization is $15 million). Think of the implications of bad data for a medical prescription processor, for example, or a BPO with service-level agreements for data accuracy.
The right crowdsourcing solution will plug AI in along the data entry process in the steps where errors are typically introduced. To prepare data that will be sent to the crowd, for example, we can apply AI to an incoming document to understand a) what kind of a document it is (Receipt? Invoice? Insurance claim? Prescription?), and then b) what specific information to take from that document. Using AI for data preparation in this way ensures crowd contributors only receive correctly classified and extracted information.
2. Your automation rates aren’t where you want them to be
Automated document or business case classification, automated data extraction, RPA, OCR—solutions such as these have changed a lot about the way businesses process documents. Yet each has its limitations; for example, the need for employee involvement for exception handling or to train algorithms. These limitations often hold organizations back from an even mostly automated operation, as well as from the scalability that automation was supposed to deliver.
The truth is that there are tasks that we simply need people for, or for which the best possible way to do the task is by an employee. So, instead of focusing on full automation as the holy grail, it’s better to focus on accuracy and speed/scale. If you can find a solution that delivers both, then what does automation rate matter?
Rather than trying to take people out of the equation, a solution like ScaleHub uses AI to better automate the steps of a process that can be automated, and to organize the “human work” in a way that ensures scalability and accuracy (in the case of ScaleHub, that accuracy rate is above 99%).
3. Your data volumes fluctuate, and you can’t quickly scale
It’s simple math. Whether you manage data entry 100% manually or with the help of an automation solution, people must be involved in some capacity. If the volume of your data fluctuates for any reason, you have to either hire or divert resources in order to get the data processed in a timely fashion.
This is where crowdsourcing truly shines. Snippeting – cutting a document into individual pieces of data and removing the data from context – is key to the remarkable turnaround crowdsourcing can offer. When one document (or image or video) becomes a collection of snippets, those snippets can be sent out to crowd contributors simultaneously. In other words, rather than one person working his or her way through a document, crowdsourcing deploys individual pieces of a document to numerous crowd contributors, who simultaneously key in what they see in the snippet using an intuitive web interface. This is how crowdsourcing solutions such as ScaleHub have brought truly limitless scalability to data entry.
At ScaleHub, we harness the power of crowdsourcing and put it to tasks like data entry with a crowd network of 2.3 million people. Watch this short video to learn more about how crowdsourcing data entry works.