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

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

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.


What signifiers does Viser use to determine toxic behaviour and dissatisfaction?

Some of the questions that we’ve asked previously include, “Why is there gender inequality?” and “Is there ageism in tech?” Most of these pursuits involve looking for outliers or anomalies in the data. For example, when we looked into gender equality, what we started from was a known difference - women as a whole earn approximately 20% less than men. From that known fact we act like detectives trying to figure out the what and the why that led to that outcome.

Data scientist, Michael Housman, is using big data to “decode the workforce”: Avoid one ‘toxic worker’ don’t hire two ‘superstars’

Our investigation looked at performance, promotions, retention, and many other aspects to try to uncover a deeper understanding through data. Most of the insightful answers are a combination of many elements that taken together create a story. In the case of our Gender Equity Report, what we saw was women were exiting the workforce exactly during the period when a first promotion to management was likely to take place. This created a “Manager Divide” that you only can see when you combine workforce participation, the growth of compensation by age and tenure, compensation differentials for individual contributor and managerial positions, voluntary turnover, and data on when families have their first child.


What does your data show makes a bad manager?

A great manager is a coach rather than a dictator. The analogy to sports is a good one: the coach is obviously not the best player but, rather, someone responsible for getting the most out of his or her players. Perhaps unlike the sports world, managers should be encouraging their direct reports to take on new challenges and even join new teams - particularly, if it leads to progress for the individual and for the company at large.

How can we discover these traits through data? While there’s no specific data point that can reveal a bad manager, we can analyze certain data such as promotion rates, performance reviews, overall employee engagement and resignation rates. Great managers are more likely to be developing talent for the rest of the organization, than the competition. Looking at these trends can reveal signals that suggest a bad manager. For instance, if a manager’s direct reports are consistently being given poor performance reviews over an extended period of time, that’s a cause for concern. This finding may reveal that the manager isn’t doing an adequate job at mentoring or addressing performance issues in his or her direct reports.


How prevalent is bullying in the workplace?

While we haven’t studied bullying ourselves, we do know it’s a big problem in the workplace. In fact, a recent CareerBuilder survey found that 29% of employees claim they've been bullied on the job. From a data analysis standpoint, bullying in the workplace is difficult to measure and this is made even harder because companies aren’t collecting data on harassment issues at a large scale. When we investigated ageism in the technology industry, we were surprised to find that ageism complaints for Silicon Valley’s 150 largest technology companies outnumbered both racial and gender complaints. Bias and bullying may have some common elements that manifest in very different ways. We expect that forward-looking companies will soon begin tracking and analyzing information on broader harassment issues in their workplaces, just as we have seen companies like Salesforce.com and Facebook do with diversity and gender pay equity information.

Workplace bullying is a problem everywhere but could things be worse in IT?


Are there some environments (maybe by industry or location) that reveal themselves to be most toxic?

Underlying many toxic workplaces is a focus on performance-at-all-costs. Focusing on performance can be a great motivator for a workforce, but it also can bring unintended consequences. Too much pressure can lead to unethical behaviour, particularly among managers. In fact, managers are responsible for 60 percent of workplace misconduct, while senior managers are more likely than lower-level managers to behave unethically, according to a 2014 National Business Ethics Survey. A culture of bad behaviour can have a serious impact on employee morale.

While Visier hasn’t looked at toxic environments by industry or location directly, I can tell you anecdotally that most toxic environments result from one common problem: a lack of leadership at the top. For instance, what behaviours are senior leaders in the company willing to accept? And, have they demonstrated that they’re willing to listen to people who feel they’re being mistreated by co-workers? Ultimately, the health of a work environment is shaped by a core group of people in positions of power.


Is there a recipe for a happy workplace?

The short answer is no – there is no one size fits all recipe for a happy workplace. Unfortunately, companies tend to try to create a happy workplace by focusing on things they can most easily measure or compare, like compensation. But the reality is that, study after study has found that compensation is only something that will make employees feel good about their jobs in the short-term.

Fostering long-term happiness in the workplace is less about the workplace and more about the work. While more difficult to put in place than big salaries or bonuses, what really leads to a happy workplace is focusing on what motivates an individual employee – being able to exercise their brains, being empowered to take on challenges, and solve real problems with an understanding of how these impact the company's success. From a management perspective, companies can help create a happy workplace by making sure their employees feel supported in their personal role in the company and that their voice is heard. The hard costs in doing so are cheaper than the alternatives, and the benefits are a more engaged and productive workforce.

We discuss Steve Jobs’ bullying. Check out: Steve Jobs: The Tech Bully Poster-Boy


Have you identified any wider patterns within organizations which might be surprising?

A surprising dynamic we’ve been studying is called the “leaky bucket problem”. When companies attempt to build out a diverse workforce, they usually focus on recruiting. But often the problem lies in retention: specifically, the fact that minority groups are leaving the company at a particularly high rate for whatever reason. We are all guilty, from time to time, of jumping to the obvious conclusion which, in this case, means hiring more diverse candidates. But diversity challenges rarely are this simple and so companies need to look closely at who is leaving the company and why. If diverse employees are leaving at an especially high rate, or leaving specific teams and departments, they need to fix the problem. Otherwise, you'll just have a continually “leaky bucket”.



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