There’s no shortage of workforce analytics tools today from vendors including Visier, SAP, IBM and Aon Hewitt. But that’s not stopping some companies from passing up on off-the-shelf options in favor of homemade, proprietary talent-seeking systems.
One such company is Riviera Partners. A San Francisco-based executive search and technical recruiting firm, Riviera Partners matches seasoned techies with some of the Bay Area’s most highly sought-after employers like LinkedIn, Zappos and Dropbox.
Riviera examined a number of applicant tracking systems and analytics tools to manage its matchmaking activities. But according to Ali Behnam, Riviera’s managing partner and co-founder, “These tools were very good at tracking events and activities but lousy at providing real insight.”
The problem for HR professionals, he says, is that many workforce analytics and applicant tracking systems are great at gathering and aggregating “transactional information” but fall short of capturing a company’s unique perspective on what makes a candidate perfect for a particular position or employer.
“There are certain data points that we target, try to keep track of and that we try to develop insight on,” adds Behnam. “So our system has evolved from a linear data collection process to examining proprietary variables that allow us to bubble up the right people very quickly for our recruiters.”
What’s more, he adds, “Many of these off-the-shelf solutions aren’t geared towards companies handling 8,000 to 10,000 contacts a month and aggregating all of that information in order to derive actionable insights.”
So Riviera did what many HR departments would consider anathema: it created its own proprietary workforce analytics tool. Today, Riviera’s custom-made workforce analytics tool consists of a huge database of internal and external data on candidates that the firm uses to target, score and identify the best match for its clients.
External data is culled from sites such as LinkedIn, Twitter, GitHub and Facebook. This personal information is then combined with internal data on more than 200,000 job applicants. By leveraging the power of internal data Riviera has collected on thousands of candidates and fusing it with readily available external data, Riviera can begin the process of analyzing best talent-to-client fits using the system’s built-in, proprietary algorithms. These algorithms have been designed with key metrics in mind – measures of “recruit-ability” such as career history, career trajectory, education, big data experience and interviewing skills that are used to assign a score to each candidate.
Riviera is not the only firm to mine external data to find the right job candidates. For example, Dice, a tech-industry job site, recently launched OpenWeb, a service that collects and analyzes millions of personal profiles to help recruiters match job seekers to IT positions.
Reducing Noise Levels
With hundreds of thousands of job applicants to choose from, Behnam says Riviera’s homemade analytics system “really reduces the noise on the number of candidates we look at and helps us target the right folks. We can zero in very quickly on the right match because we’re able to eliminate folks that won’t be a good fit.”
But Riviera’s workforce analytics tool is more than simply a high-tech matchmaking service. Behnam says Riviera has reduced its search time for candidates by 25 percent and has increased revenue per head by 52 percent over the past year. “The system is paying off in our ability to get things done faster,” says Behnam. “We’re not chasing people if we don’t have to.”
And because Riviera’s in-house system is tailor-made, it’s been able to grow with the firm and accommodate changes in demand for talent, from programmers one day to data scientists the next – scalability that Behnam says “just wasn’t going to come from an off-the-shelf solution.”
However, for all its perks, homegrown workforce analytics systems aren’t for all HR teams. For starters, Riviera’s founders, both of whom have a background in designing software, were willing to fork over the money needed to hire three on-site data analysts to help build the system, “look for patterns in the data and figure out what are the right variables to hone in on.” It’s a hefty investment most HR folks would have a tough time selling to a company’s bean counters.
Running your own analytics system also requires either investing in costly servers or negotiating service level agreements with a hosting provider. Either way, it’s a step outside most HR professionals’ comfort zone when so many of today’s SaaS-based workforce analytics systems can be up and running with the flick of a switch.
Nevertheless, Behnam says, “At the end of the day, you have to do something that sets you apart.” For some, a proprietary workforce analytics system is the answer.
Cindy Waxer, a contributing editor who covers workforce analytics and other topics for Data Informed, is a Toronto-based freelance journalist and a contributor to publications including The Economist and MIT Technology Review. She can be reached at firstname.lastname@example.org or via Twitter @Cwaxer.