predictive analytics

Hourly employees have common scheduling problems, which helped spur a series of fair workweek laws now in effect in the state of Oregon and in many cities across the United States. The impact of these laws on businesses should not be ignored, though.

The COVID-19 pandemic has also added another layer to the scheduling complexity environment. Industries like retail, food service and hospitality that have been greatly impacted by the pandemic are also the industries primarily affected by predictive scheduling laws.

Depending on state or local laws, businesses all face scheduling challenges. Here are some of the most common scheduling problems and how to address them.

Also read: Shift scheduling strategies can be improved through technology

The most common scheduling problems for employers

1. Overstaffing and understaffing

The clear problem for businesses with overstaffing is that they’re unnecessarily increasing their labor cost with no return on investment, said Ari Hersher, partner at law firm Seyfarth. And labor costs are already one of the biggest costs for businesses, along with real estate.

Meanwhile, if a shift is understaffed, the business is not efficiently meeting demand. Its employees may be overworked and need to work extra hours, and the business may have to pay these workers unplanned overtime, Hersher said. Meanwhile, in jurisdictions with predictive scheduling laws, an employer may need to pay additional wage to staff that are added last minute, he added.

2. TIme

Creating a schedule takes time, and managers already have busy jobs. Using technology solutions could help, yet the Sierra Cedar “2018-2019 HR Systems Survey” found that only 42 percent of organizations use labor scheduling applications.

Also read: 3 Steps to Navigating Effective Wage and Hour Compliance

3. The need for flexibility

Managers need flexibility to create schedules, Hersher said. Employees may quit, call in sick or simply not show up, and then managers must figure out how to quickly find a replacement.

Employers in jurisdictions with predictive scheduling laws may have further responsibilities, he said. Some of these laws have employers document that someone called out of their shift, offer proof that they called and store the information for three years in case of audits. For managers who supervise a large number of employees, the number of call outs they get in a week may be substantial.

Sometimes there are tech solutions, he said, but the patchwork landscape of predictive scheduling can complicate that. Employers with locations in cities or states with different laws need a way to take all laws that impact them into account.

Also read: Predictive Scheduling Laws — What Are They, Where Do They Exist and Employers’ Reaction

4. Compliance

According to XpertHR’s survey “Top HR Compliance Challenges for 2020,” 10.1 percent of employers surveyed said that pay and scheduling issues is their top compliance concern, topped only by benefits (16.2 percent) and recruiting/hiring (28.3 percent).

The most common scheduling problems for employees

1. Overstaffing and understaffing:

Understaffing has an obvious impact on employees, leaving them overworked and with low morale, Hersher said. And industries like retail and food service with many hourly workers already see high turnover.

Meanwhile, given the right context, overstaffing also may impact workers negatively. They may get sent home, therefore not getting paid for hours they expected to work. Employees who earn commission for sales or tips for service may also find this situation bad, Hersher added. If there are only six customers and seven servers or sales associates, they wouldn’t expect to earn a fair wage for their time.

2. Predictability and cost of living:

Many hourly employees work in cities with high costs of living, and they could be working multiple jobs, Hersher said. A lot of these may be part-time jobs. For these workers, advance notice in what their schedules will be has a lot of value.

As the Economic Policy Institute explained it in a 2018 article, “Volatile hours not only mean volatile incomes, but add to the strain working families face as they try to plan ahead for child care or juggle schedules in order to take classes, hold down a second job, or pursue other career opportunities.”

The power of analytics

Predictive analytics could help many of these issues, Hersher said. Retail has experienced an explosion of data studying people’s buying habits, how long they stay in a store and how much they purchase, which should allow employers to staff more efficiently.

This could benefit employers and employees in a few ways. With predictive data, employers could still create schedules in advance, which means predictability for employees. And if employers are able to create more accurate schedules, their risk of either understaffing or overstaffing decreases, which could help deter some of the negative impacts that understaffing and overstaffing may have on both employers and employees.

“The more you can spot trends, the better you can anticipate needs and the more you can reduce changes,” he said.

Are you leveraging predictive analytics to reduce turnover? Using hiring data to improve recruiting? Monitoring internal social media comments to measure employee sentiment or identify diversity issues?

If not, you are missing opportunities to become your CEO’s most valuable advisor.

Executives are finally recognizing that the ability to hire, retain and mobilize top talent is the key to their business success. And they are turning to their CHROs for advice, guidance and data to chart their course forward.

“HR leaders who adopt AI tools for recruiting, engagement and reorganization are reaping the benefits of these trends,” said Ben Eubanks, principal for Lighthouse Research in Huntsville, Alabama, and author of “Artificial Intelligence for HR.” “They can absolutely gain credibility and add value for the CEO and every business unit.”

But to become that indispensable business advisor, CHROs have to know how to capture and analyze people analytics, then link those insights to business decisions. And not all of them are ready to deliver.

Also read: AI is coming — and HR is not prepared

The power of data

When companies figure out how to leverage human capital analytics, they experience measurable business benefits that go well beyond improved engagement scores. Visier’s “The Age of People Analytics” report found organizations with mature people analytics processes generate 56 percent higher profit margins than those with less advanced capabilities. They also found that these organizations are more likely to link people analytics to improved business outcomes and labor cost savings.

This shouldn’t be a surprise. People analytics has been a hot topic in HR forums for the last few years. KPMG’s “Future of HR 2019” report found 80 percent of these leaders believe HR can provide more value through analytics.

However, just as many studies show that most HR leaders are still struggling to join the ranks of mature analytics users. PwC’s 2019 Saratoga benchmark report found 55 percent of companies failed their analysis of “good people data”, and another 41 percent were only “partway there.” They also found that lack of leadership around deploying people analytics severely limits how quickly companies can leverage this data for better business outcomes.

Also read: Are more companies in tapping HR executives for board seat?

This combination of high interest in HR analytics and low maturity among HR leaders can either be viewed as a risk or an opportunity, Eubanks said. “Companies need HR leaders who can be on top of human capital analytics,” he said. “It’s an opportunity to become a real partner to the business.”

How to get started

Historically, human resources has not had a lot of experience in using data and analytics in decision-making, said Dan Staley, global HR technology leader for PwC US. “Finance has always been viewed as more data-driven, but HR has to realize that it is sitting on a treasure trove of data,” he said. Companies constantly capture information about hiring, demographics, salaries, performance, turnover, diversity and other stats that offer powerful insights into the behavior and ability of the workforce, he said. The trick is figuring out how to access that data and ask the right questions to uncover actionable results.

Staley encouraged HR leaders to start by talking to the CEO and business unit leaders about what business obstacles they face and how they can use human capital data to overcome them.

Then look at what internal and external data sets you already have access to and what questions it can answer, Eubanks said. For example, combining internal salary data with industry benchmark reports can allow a company to determine whether it is offering competitive compensation packages and where they can afford to make more targeted offers to high-demand candidates. “It’s no longer just your opinion,” Eubanks said. “The data can justify the decision.”

And when HR leaders have data-driven results, they need to communicate in business terms that are relevant to board members. “Don’t just report on reductions in turnover or absenteeism or time-to-hire,” Staley said. “Talk about the impact those metrics have on the business.”

CHROs who embrace human capital analytics and who can communicate the value of linking that data to business strategy can become indispensable to their C-suite.

Also read: AI’s growing role in human resources

“HR leaders have the most influence when it comes to workforce decisions,” said Michael Moon, people analytics leader for ADP in North Attenborough, Massachusetts. They already have experience with hiring and performance management. By integrating data into these decisions, it replaces gut instinct with with evidence based decision-making, and makes it possible to pinpoint what is happening with the workforce and why, she said. “Once analytics are part of the way things are done, it becomes easy to measure the impact on ROI.”

Tag: predictive analytics

The most common scheduling problems for employers and how to address them

The in-demand potential of a data-driven CHRO