HR is one of the many sectors currently being disrupted by software and the Big Data movement. According to Forbes, the top 50 HR technology PE/VC deals in 2014 had a combined value of over $560 million.
What does this frenzy means for businesses? Companies have long used data and analytics to understand their HR challenges, from recruitment to retention, and focused on metrics such as turnover. Much of the analysis and reporting that went into addressing HR issues was based on small sets of internal data. Without some type of benchmark, deriving meaning and patterns from this data was unsurprisingly difficult.
Emerging companies like hiQ Labs (“hiQ”) and Workplace have stepped in with Big Data tools that are designed to help businesses gain a stronger hold on what is happening HR-wise by enabling them to incorporate external data into their analysis. hiQ in specific aims to help businesses take preemptive action to retain key personnel before it’s too late.
hiQ’s value proposition is grounded in the belief that the loss of key personnel is extremely costly for businesses. In order to combat this flight risk and understand the factors driving retention, hiQ’s software (available on both desktop and mobile) analyzes public data to identify patterns that are relevant for a specific business. According to hiQ, “public data can be significantly more predictive than internal HR data about people.”
The process works like this: hiQ gathers public data, including information on social networks, and pushes it through “complex statistical algorithms” that observe general employment trends and other factors (including geography, industry, and in-demand skills). The output provides information on attrition risk at the individual level.
Ultimately, the goal is to allow businesses to predict which key personnel may be leaving and take responsive action. The software is also designed to provide suggestions on what actions the business can take that may help retain the employee.
Of course, another component of hiQ’s value proposition is the personnel behind the algorithms and software they are selling. The hiQ team is composed of San Francisco-based PhD data scientists, workforce scientists, talent analysts and IO psychologists.
Some other thoughts
Accurate, transparent and available data is obviously key to hiQ’s success. Its algorithms and use of machine-learning will only create effective solutions for HR if the information analyzed is valid. But hiQ isn’t in the business of selling data; it’s in the business of running predictive algorithms that considers all that data and helps HR make better decisions and plan. The software will likely continue to get better as it analyzes more and more information over time.
I was unable to find any information pertaining to hiQ’s value capture model, but I imagine it is likely offered on a subscription basis. An interesting, alternate approach would outcomes-based and allow the client and hiQ to share the value or savings generated from successfully retaining key employees.
hiQ Labs Revolutionizing Businesses with “Machine Learning” http://www.socialnomics.net/2015/04/10/hiq-labs-revolutionizing-businesses-with-%E2%80%9Cmachine-learning%E2%80%9D/
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hiQ Labs company sites