Google is replacing the 20th century subjective decision-making approach in HR. Although it calls its approach “people analytics,” it can alternatively be called “data-based decision-making,” “algorithm based decision-making,” or “fact or evidence-based decision-making.”
Top 10 reasons for Google’s people analytics approach
The people analytics team reports directly to the VP and it has a representative in each major HR function. It produces many products, including employee surveys that are not anonymous, and dashboards. It also attempts to identify insightful correlations and to provide recommended actions. The goal is to substitute data and metrics for the use of opinions.
Almost everyone has by now heard about Google’s free food, 20% time, and wide range of fun activities but realize that each of these was implemented and are maintained based on data. Many of Google’s people analytics approaches are so unusual and powerful, I can only describe them as “breathtaking.”
Below I have listed my “Top 10” of Google’s past and current people management practices to highlight its data-driven approach:
- Leadership characteristics and the role of managers –ts “project oxygen” research analyzed reams of internal data and determined that great managers are essential for top performance and retention. It further identified the eight characteristics of great leaders. The data proved that rather than superior technical knowledge, periodic one-on-one coaching which included expressing interest in the employee and frequent personalized feedback ranked as the No. 1 key to being a successful leader. Managers are rated twice a year by their employees on their performance on the eight factors.
- The PiLab — Google’s PiLab is a unique subgroup that no other firm has. It conducts applied experiments within Google to determine the most effective approaches for managing people and maintaining a productive environment (including the type of reward that makes employees the happiest). The lab even improved employee health by reducing the calorie intake of its employees at their eating facilities by relying on scientific data and experiments (by simply reducing the size of the plates).
- A retention algorithm — Google developed a mathematical algorithm to proactively and successfully predict which employees are most likely to become a retention problem. This approach allows management to act before it’s too late and it further allows retention solutions to be personalized.
- Predictive modeling – People management is forward looking at Google. As a result, it develops predictive models and use “what if” analysis to continually improve their forecasts of upcoming people management problems and opportunities. It also uses analytics to produce more effective workforce planning, which is essential in a rapidly growing and changing firm.
- Improving diversity – Unlike most firms, analytics are used at Google to solve diversity problems. As a result, the people analytics team conducted analysis to identify the root causes of weak diversity recruiting, retention, and promotions (especially among women engineers). The results that it produced in hiring, retention, and promotion were dramatic and measurable.
- An effective hiring algorithm – One of the few firms to approach recruiting scientifically, Google developed an algorithm for predicting which candidates had the highest probability of succeeding after they are hired. Its research also determined that little value was added beyond four interviews, dramatically shortening time to hire. Google is also unique in its strategic approach to hiring because its hiring decisions are made by a group in order to prevent individual hiring managers from hiring people for their own short-term needs. Under “Project Janus,” it developed an algorithm for each large job family that analyzed rejected resumes to identify any top candidates who they might have missed. They found that they had only a 1.5% miss rate, and as a result they hired some of the revisited candidates.
- Calculating the value of top performers – Google executives have calculated the performance differential between an exceptional technologist and an average one (as much as 300 times higher). Proving the value of top performers convinces executives to provide the resources necessary to hire, retain, and develop extraordinary talent. Google’s best-kept secret is that people operations professionals make the best “business case” of any firm in any industry, which is the primary reason why they receive such extraordinary executive support.
- Workplace design drives collaboration – Google has an extraordinary focus on increasing collaboration between employees from different functions. It has found that increased innovation comes from a combination of three factors: discovery (i.e. learning), collaboration, and fun. It consciously designs its workplaces to maximize learning, fun, and collaboration (it even tracks the time spent by employees in the café lines to maximize collaboration). Managing “fun” may seem superfluous to some, but the data indicates that it is a major factor in attraction, retention, and collaboration.
- Increasing discovery and learning – Rather than focusing on traditional classroom learning, the emphasis is on hands-on learning (the vast majority of people learn through on the job learning). Google has increased discovery and learning through project rotations, learning from failures, and even through inviting people like Al Gore and Lady Gaga to speak to their employees. Clearly self-directed continuous learning and the ability to adapt are key employee competencies at Google.
- It doesn’t dictate; it convinces with data — The final key to Google’s people analytics team’s success occurs not during the analysis phase, but instead when it present its final proposals to executives and managers. Rather than demanding or forcing managers to accept its approach, it instead acts as internal consultants and influences people to change based on the powerful data and the action recommendations that they present. Because its audiences are highly analytical (as most executives are), it uses data to change preset opinions and to influence.