Experfy's disruptive business model is constructed around the idea of a big data analytics "auction" and social media. Get more details about how this on-demand consultancy is democratizing big data.
Imagine starting a big data "expert network" at Harvard by bringing in 25,000 Ph.D.s from academic institutions around the country with specializations that range from nanotechnology, microbiology, and astrophysics to marketing, and then reaching out to 150 companies to determine the companies' most pressing big data needs.
"This was the idea we had in mind," said Harpreet Singh, cofounder and CEO of Experfy, a big data resource company based in the Harvard Innovation Lab that commands an army of thousands of academic big data experts. "What the companies we surveyed told us was that they were having the most difficulty productively using and analyzing the big data they were collecting. This job became even more difficult because their big data under management was doubling every 18 months. What we recognized was that we could build a business around on demand consulting in big data analytics."
From their company research, Singh and his collaborators also uncovered the fact that many midsized companies were further behind in their big data efforts than originally thought. "These companies were struggling with both data quality and quantity," said Singh. "Many were at the stage of building dashboards that provided insights to managers from the analytics, and their goal was just to understand the status quo of the business. They had not yet broached the idea of using predictive analytics that could help them with anticipating business trends and demands."
Singh and his team came up with a disruptive business model constructed around social media and the idea of a big data analytics "auction." In the model, companies come to Experfy with big data projects that they wanted to do. The academic data scientists already screened and qualified by Experfy see the projects on Experfy's project posting board and then bid on the projects. In the process, bidders explain in detail how they would go about performing and completing the analytics projects and what they would charge. There is even a button on the Eperfy website that enables companies to video-interview data scientist respondents to their projects. Companies can evaluate the bids on their projects and then make an informed choice as to whom to award their project work.
"This is often a collaborative process," said Singh. "In some cases, companies already know what they want to accomplish with their big data projects, and they are comfortable using a self-service approach where they take on the control and the risk of evaluating the bids that come in. In other cases, they talk to us first, and we work together to define the project and what it is that they want to achieve. For instance, if the project is in marketing, they might want to figure out their return on investment from their media buying, and have this information come out in the form of a summary dashboard. Or, they might want to develop analytics that can tell them how effective their brand management program is."
By innovatively using social media techniques to reach out and communicate with companies and legions of academic data scientists, Experfy has seemingly found a way to democratize big data analytics so that anyone with a project, regardless of company size, can get the help it needs without having to pay six figures annually for a dedicated data scientist.
"Our average project costs a client company ten to twenty thousand dollars," said Singh. "This is not a large amount to experiment with for many companies. Because these projects are affordable, we help small to midsized companies to level the playing field by sending out the message that big data analytics is within reach of every company."
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