3 Ways Workforce Intelligence Enables Better Workforce Risk Management

3 Ways Workforce Intelligence Enables Better Workforce Risk ManagementNo business is immune to risk, especially when it comes to its workforce. People can be unpredictable — their behavior can change in an instant. Whether HR is dealing with health and safety incidents, compliance issues, compensation and payroll errors, or wrongful hiring and termination practices, these are all risks that HR can mitigate with the right data-driven approach.

According to PWC’s 2016 Global CEO Survey, 79% of CEOs are most concerned about over-regulation. These days it seems new legislation is always coming into effect. And, channeling my best ghostbusters voice, “Who you gonna call?” Well, in this case: HR!

HR needs to stay on top of changing workforce rules and regulations to ensure that their company complies. And, like fighting ghosts, this is no easy task.

Whenever a new workforce-focused ruling is passed, chances are someone in HR is tasked with — urgently — figuring out what the new ruling means to the organization. To answer this question, that person (or, if lucky, team of people) will typically take a deep dive into the abyss of spreadsheets — spending countless hours exporting, cleaning, and merging workforce data from multiple sources, and then countless more performing analysis on that data. The result is a monolithic spreadsheet — with dozens of different columns across thousands of people — and no guarantee that the data or analysis is error-free.

I remember a story a friend told me when she was audited by the IRS, who found an error in her tax return. She told the auditor, I didn’t know that tax rule, to which the auditor responded: “Ignorance does not make you less guilty.”

Similarly, a company cannot claim innocence based on erroneous data.

HR data is complex and without a well-developed analytics function (one with the right people, technology, and process in place), it can take weeks for HR to identify the impacts of new legislation (and still not be certain that their analysis is correct). When organizations fail to comply, there can be fines, lawsuits, and/or damages to company reputation.

For better workforce risk management, HR leaders need to focus on building strong HR analytics capabilities. Below are three examples of how analytics can mitigate the most pressing compliance risks:

1. Ensure Gender Pay Equity At Your Organization

New pay equity reporting requirements in the U.S. are proposed to start in 2017. Every year by September 30, employers with 100 or more employees are already required to fill in the EEO-1 form, which asks them to report their employee numbers by job category, sex, race, and ethnicity.

If the new proposal is passed, employers will also be required to report which of 12 pay bands those workers fall into. This pay data is intended to help enforce federal pay discrimination laws.

Avoid getting blindsided the first time you fill out the new report by using analytics to look at how pay is distributed in your organization today. Aim to answer questions such as:

  • Are there signs of bias related to gender and levels of pay?
  • Are pay increases distributed equally between female and male employees?
  • Does the way variable pay is awarded create pay equity risks?
  • What risks are related to the rate at which female and male employees progress through their pay ranges?

The data you uncover can support the validity of apparent pay disparities and also confirm valid reasons for pay differentials, such as longer tenure, more education/training, or higher performance. Furthermore, your HR analytics team should continuously measure pay equity, discover where the greatest risks are, and make suggestions to adapt programs and policies accordingly.

Data visualization showing what pay equity risks needs to be reviewed and managed

2. Avoid Overtime Chaos

A new “overtime rule” will go into effect in the U.S. on December 1, 2016. The new legislation requires employers to pay overtime to a larger number of employees—the exempt salary threshold jumps from $23,660/year to $47,476/year. Without proper analysis and planning, the new rule will disrupt wage planning as employers scramble to decide whether to pay more workers overtime, raise salaries above the threshold, limit workers to 40 hours a week, or deploy some combination of those options.

Compounding this already complex, time-pressured situation is the fact that it’s not a “one and done” event. The Department of Labor (DOL) will be updating the salary threshold every three years beginning in January 2020.

This post has useful information on how to use analytics to get a handle on this new ruling. Remember: it should take your analytics team minutes — not weeks — to answer business-critical workforce questions, such as:

  • How does the new rule impact us?
  • How can we optimize workforce costs?
  • How can we better track, report, and manage overtime?

I also recommend reading about how the City of Edmonton’s HR team used a workforce intelligence tool to help them quickly mitigate overtime risks during an unexpected crisis.   

Workforce planning data visualization comparing the costs of new overtime rules and costs with increases to reduce non-exempt population

3. Classify Employees The Right Way

Since the recession, many employers have been choosing to use more contractors in their workforce because of the flexibility it offers. However, this creates a significant risk, because U.S. legislation on whether workers can be classified as contractors or employees changes constantly, and the trend has been to classify more workers as employees.

Studies suggest that 10-30% of employers may misclassify their employees as independent contractors, and nearly $1.6 billion in back wages have already been recovered by the DOL’s Wage and Hour Division since 2009.

Deep analysis is needed to understand the cost and effects of moving to more or less contingent labor. Questions for the HR analytics team to investigate include:

  • Are there long tenured workers that are misclassified as contingent workers?
  • Do any organizations within the company have managers who are classified as contingent employees?

Get On Top of Your Workforce Risk Management

Workplace risks can crop up at anytime. With HR analytics, your team is well-prepared to deal with any issues as they appear. It should only take them a few minutes to find the answers you need to any risk management questions. When it comes to compliance, time is not on HR’s side.

However, the true power of analytics lies in providing the data you need to react to new regulations and other risks before they occur. Regularly monitor your workforce data for any issues and use this information to create strategic workforce plans for the most likely scenarios.

With a proper workforce intelligence function, HR can take a proactive approach to risk management, which will save the business money, protect its reputation, and earn HR the respect of business leaders.

Read more about this topic:

Avoiding the Cost and Pain of Business Intelligence Projects

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Ian Cook |

Curious about the differences between gaussian and pareto distribution? Ask Ian. Want to know what it’s like to kite ski North of the Arctic Circle? Ask Ian. Not only is he an expert in statistical analysis and HR metrics, he’s also an avid cyclist, skier and runner. At Visier, Ian helps customers drive organizational change through linking workforce analysis to business outcomes. He is responsible for the workforce domain expertise within the Visier solutions.

Human Resources Today
Human Resources Today