{"id":2616,"date":"2015-11-22T19:14:40","date_gmt":"2015-11-23T00:14:40","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-digit\/submission\/entelo-using-big-data-for-social-recruiting\/"},"modified":"2015-11-22T19:18:59","modified_gmt":"2015-11-23T00:18:59","slug":"entelo-using-big-data-for-social-recruiting","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/entelo-using-big-data-for-social-recruiting\/","title":{"rendered":"Entelo: Using big data for social recruiting"},"content":{"rendered":"

Recruiting Challenges<\/strong><\/p>\n

During his time as an entrepreneur in residence for a VC firm, John Bischke realized that the most important challenge faced by startups is recruiting great talent. Talent starved fast growing startups can\u2019t rely anymore on the traditional recruiting practices: recruiting agencies, online jobs posting in the company\u2019s website or traditional recruiting platforms posting (i.e. Linkedin). As an alternative, companies have started to incentivize their employees to refer their contacts after realizing that internally referred employees outperform none referred employees. Despite the apparent effectiveness of employee referral systems, Bischke challenge<\/a>s this practice by stating that employees aren\u2019t necessarily aware of these programs, have difficulties assessing who would be a good fit for the posted roles, may refrain from contacting them and\/or may perform an ineffective communication when interacting with candidates.<\/p>\n

Fine tuning the recruiting funnel<\/strong><\/p>\n

\"Entelo1\"<\/a><\/p>\n

In response, Bischke and McGrath started experimenting with an alternative approach: using publicly available online social data to identify talented individuals and their willingness for a career move. This article<\/a> explains that by aggregating data from websites such as linkedin, twitter, github, stackoverflow, proformative, benchling, dribble, among others (over 50), the company is able create composite profiles and run algorithms to identify the best talent with a high level of accuracy. On top of this, the firm aggregates more data such employers\u2019 performance and the number of recent social profile updates to determine the employee\u2019s willingness for a career change. By entering into a subscription model ($500 per month or $5,000 per year<\/a>), recruiters are able to tap into Entelo\u2019s platform to target candidates more accurately and fine tune the recruiting funnel (i.e. better candidate matching, increased response rate, higher conversion, etc.). So far, the startup has gained significant traction by attracting important customers such as Tesla, Uber, Facebook, Box, among many others.<\/p>\n

According to the company\u2019s webpage, Entelo\u2019s database covers over 200 million public profiles, and considering that most of the websites from which Entelo gathers data were created in the last 10 years, Bischke believes<\/a> that we are only seeing the starting point: \u201cWe’re probably in the bottom of the first inning for watching this trend play out but\u00a0it is our feeling that big data is going to impact recruiting in a massive way\u201d.<\/p>\n

Challenges: Mounting competition & Privacy Concerns<\/strong><\/p>\n

Recognizing the evident value for recruiters, other players have also jumped in the race for using big data & data mining for HR\/Recruiting activities. Even though companies such as TalentBin, Gield, TheSocialVC, Predikt, ConceptNode and Connectiflyer have positioned themselves in different niches of the market, they are all ultimately leveraging on big data capabilities for recruiting. It will be interesting to see if this market keeps evolving into niche verticals (programmers, accountants, designers, etc.) or if it tips towards a profession agnostic platform.<\/p>\n

Additionally, although the company reports that only 2 users have requested being delisted from the database, I believe there is a valid concern among the general public with regards to third party companies using your online social information (aside from the more technical social sites such as stackoverflow) for making recruiting\/professional decisions. If this practice would become the standard, I wonder if people would modify their online social behavior (or even decrease user\u2019s activity), and if so, what would be the response from these social sites.<\/p>\n","protected":false},"excerpt":{"rendered":"

Entelo is aggregating user's online social data and running algorithms to identify best talent <\/p>\n","protected":false},"author":42,"featured_media":2617,"comment_status":"open","ping_status":"closed","template":"","categories":[134,29,975,974,802],"class_list":["post-2616","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-analytics","category-big-data","category-data-mining","category-social-recruiting","category-startup"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/data-driven-value-creation-value-capture-and-operating-models\/","yoast_head":"\nEntelo: Using big data for social recruiting - Digital Innovation and Transformation<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-digit\/submission\/entelo-using-big-data-for-social-recruiting\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Entelo: Using big data for social recruiting - 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