When news broke about the inner workings of Amazon in Sunday’s New York Times article, I was positively riveted. Reading about how heavily the company is said to rely on data to evaluate employees got me thinking about the role of data in employee-related matters. Should those types of decisions be entirely data-centric, as seems to be the case at Amazon? Or should business leaders rely more on nuance and instinct when they’re making decisions about their people?
As the head of Umbel, a company that advocates strongly for data-driven decision-making and advises other companies accordingly, I believe firmly in the business value of data. But when it comes to matters involving employees, I think that while data is something to strongly consider, it shouldn’t be theonly thing. After all, data can’t tell us (yet) that a top employee’s performance is suffering because he or she is battling an illness or coping with a sick child or parent. Data can uncover problem areas, but you need more than data to assess and determine how best to address them. That’s why I believe in using data to inform, rather than to make, employee-related decisions.
Here are three ways you can make sure that data is helping, and not hurting, both employee morale and the company’s bottom line.
1. Use data for insight into technical competencies.
When you need to hire employees who have strong technical expertise or fluency in a particular area, data can help you identify candidates who have the specific skills and proficiencies you’re looking for. This is basically an aspect of talent analytics, the data science that’s been defined as the application of big data techniques to human resources. By comparing talent data (including technical proficiencies) against organizational data, you make it possible to align HR strategy with business strategy — and hire the right people to achieve your goals. For example, at Umbel we use a gamecalled Umbelmania as part of the interviewing process where developers are challenged to write a program to help them advance. This data helps us determine a candidate’s technical prowess and offers better insight into their skill set.
2. Don’t rely on hard data to measure soft skills.
While big data may be useful in identifying the technical skills that will help a company meet key business goals, there’s another set of skills hard data alone simply can’t measure. These are the “soft” skills, such as problem solving, conflict management and creative thinking, that can be particularly important for employees to bring with them to the workplace — largely because, as an entrepreneur.com article has pointed out, they’re not easily taught. You can certainly collect and analyze data from assessment tests or other forms of skills measurement to evaluate an employee or job candidate in this context, but odds are that you’ll benefit as much, if not more, from asking qualitative questions in interviews and talking with references.
3. Keep the “human” in human resources.
Dan Newman, head of the digital marketing agency Broadsuite, has made the very good point that relying solely on instincts and gut feelings to make decisions about people can be limiting, and that the availability of HR data can make it possible to transcend those limitations. But I also think it’s possible to swing too far in the other direction. What’s needed is a balance — a way to use data to expose performance issues and inefficiencies where they exist while at the same time applying good judgment and managerial experience to identify when exceptions to data-driven policies are warranted. After all, let’s face it: There are people who have legitimate reasons for poor performance, and there are those who have no excuse. And when the data points to poor performance, HR professionals sometimes have to look beyond that data to tell the difference and respond accordingly. I’m not saying that’s easy, but I do think it’s necessary.