Q&A: How data analytics can identify toxic work environments

We speak to Dave Weisbeck from Visier, which uses employee data to discover (often negative) social trends in the workplace

In the past there was never much of a focus on toxic work environments. Nobody really cared what went on behind closed doors – it was all about results. Steve Jobs was a poster boy for terrible bullying and everyone applauded him anyway. Today things have changed. Despite Uber’s many successes it has been genuinely pilloried for its terrible work environment.

This means companies, like Visier, which use employee data and analytics to identify problems in the workplace, are gradually emerging. We speak to Visier’s chief strategy officer, Dave Weisbeck, to learn more about what this might mean in practice.


What kinds of data does Visier need access to in order to determine workplace trends?

Companies collect far more data than people probably realize. For example, when you’re interviewing, your resume is now online rather than on paper. When you start your job and begin training, your information is put into a system or database. What we’re trying to do at Visier is scan across all of that information to find answers to questions that shape business strategy, provide the impetus for taking action, and drive better business results.

The information we use depends on what kinds of questions we’re trying to answer. For example, when we look at quality of hire we will want to understand if they stay, progress and perform. This generally requires performance management, promotion, and retention data which may be further augmented with hiring manager surveys or business measures of productivity.  Visier’s approach is not to attempt to surgically collect narrow elements of data, but instead to take information from every system holding data on employees so no matter the question, you have one place to go to get an answer. Moreover, this is also how we power our machine learning algorithms which can then find interesting insights no one considered analyzing like the relationships within an employee’s job history and retention.


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