On our blog, we recently explained the four pillars of ethics and trust in People Analytics – privacy, security, eliminating bias, and people impact. In this article, we’d like to further discuss how – by recognizing these four elements – you can safeguard employee data and nurture their trust. You’ll find a comprehensive list of the best practices below, inspired by some of the best People Analytics implementations on the market. Let’s jump right in.
When it comes to people function and insights, it’s vital to ensure that employees know which data is collected and how it’s being used and to assure them that it is being gathered for positive purposes. The people team should be transparent about what they do with data, and guarantee that there are effective privacy policies to protect employee data.
It’s necessary for every business to put in place clear guidelines to explain what data can be collected and how it can be used, analyzed, and distributed.
We’ve put together a list of best practices and preemptive actions that will help you reduce the risk of privacy violations:
To understand your People Analytics security levels, it’s worth starting with a question – is your data stored and protected in a database that can’t be easily found? Also, is it encrypted, hidden away behind complex password policies, or other security measures?
Here are our top recommendations:
As mentioned in our previous piece, our systems can only become as biased as we allow them to. Josh Bersin points out that if our existing data is biased, so will our software’s actions and recommendations. Therefore, it’s always best to assume that our People Analytics tools come with their set of prejudice.
So, how to ‘scan’ your system for traces of bias? Here are a few best practices:
Your people analytics program should focus only on strategies that positively impact employees. For instance, if you’re tracking work productivity in the hopes of making the workplace better, then that’s perfectly OK. However, if you collect it to eliminate low performers, high chances are, you’re in violation of your company’s management principles.
Josh Bersin mentioned that some companies use data to predict retention. If they spot employees who are thinking of leaving they start to give them unfavorable treatment. For instance, managers stop talking to them and reduce their support since they think it’s a waste of time as they’re going to leave anyway.
Here are a few best practices that we recommend following to reduce the risk of imposing psychological harm on employees:
There are a number of preemptive measures you can take to ensure the right privacy, security, objectivity, and impact of your People Analytics solution. First and foremost, it’s essential to use a tool like Network Perspective which, at its very core, respects employee privacy. Furthermore, remember that People Analytics should be a joint effort of the people team, IT, and C-level executives, and should be refined continuously. Only then will you be able to create a bias-free, safe system which supports team growth, productivity and well-being.
If you’d like to see how Network Perspective protects employee data, reach out – we’ll be more than happy to jump on a call!