Tag: data analytics

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Labor analytics: A how-to guide for company leadership

astronaut with a magnifying glass

Summary

  • Requesting and collecting data in real-time allows your management to make better business decisions and keep costs low.

  • Focus on gathering insights that will ultimately address your business needs.

  • With labor analytics, variety is key. Use and collect data from multiple sources.

Data plays a vital function in all aspects of running a business. It is used in everything, from analyzing and predicting product performance to segmenting and understanding your customers in order to optimize the user experience. 

So naturally, data has an important role to play in workforce management through the process of labor analytics – also known as workforce analytics. Through labor analytics, HR professionals gather and analyze workforce data to:

  • Understand what new roles and functions a company should seek to fill and which ones it should cut. 
  • Understand what roles and functions might require a reduction or elimination altogether.
  • Forecasting the value and success a prospective employee can bring to a company.
  • Obtain actionable insights on how to better manage labor costs.
  • Gain a deeper understanding of the employee experience and what positively boosts employee engagement.
  • Optimize business strategy in a way that increases performance and productivity.
  • Make data-driven business decisions on fair and cost-effective worker compensation and incentives.

The good news is that most businesses already have access to massive amounts of workforce data – the catch is that gathering and making sense of this data can be tricky. But in the end, the benefit of utilizing labor analytics significantly outweighs the effort spent organizing the data. 

Research shows the positive impact that workforce analytics has on business outcomes. Case studies show that companies that use labor analytics say they have a clearer understanding of their workforce needs and can identify employees with high potential. They have also noted an improvement in retention rates and are generally happier with their human resources. 

Webinar: How to Stop Employee Turnover

Since the pandemic, attracting talent has never been trickier, and the benefits of labor analytics cannot be overstated. Following these four steps will help you optimize your labor analytics process and put your business in a better position for success.  

Gather analytics data in real-time

It is essential that your C-suite decision-makers have access to labor analytics in real-time, before they need to make critical business decisions. Visibility like this improves response time to frontline labor issues and ensures a more efficient allocation of resources. 

Real-time analytics give managers a clear picture of labor costs as a percentage of revenue across all locatins and throughout the day, allowing them to see where and when their workforce is struggling. This way, they can make better decisions regarding staffing levels, absenteeism, overtime, and more.

Whitepaper: Workforce Analytics

Connect labor analytics with business needs

While organizations should always make decisions on the most current data available, having too much data can hinder decision-making. Labor analysis shouldn’t be aimless in scope. Each research activity should address a specific question that needs answering by the organization. In other words, business outcomes need to guide the analytics process in the right direction.

Use multiple types of data and analytics

To best utilize data analytics, using multiple, targeted sources of data — including business-appropriate performance analytics and HR/talent management analytics — is important. But it’s not enough. In workforce analytics, variety is key.

Internal reports focus on metrics such as completed training hours or satisfaction with training. Predictive modeling uses statistical analysis to project the outcome of various actions. And external benchmarking allows an organization to compare itself against the industry-standard. Incorporating data from a variety of analytics types gives the business a more robust viewpoint, allowing for better-informed decision-making.

Avoid common data analytics mistakes 

Organizations should be sure to avoid common pitfalls when using analytics. The data needs to be organized and cleaned, and organizations should start with small, simple projects rather than something big to help get leadership buy-in. 

They should also be careful not to confuse correlation with causation in research results. For example, if data shows that older employees are more successful at a task than younger employees, that may have nothing to do with age demographics but with years of experience. 

Data literacy – “the ability to read, write, and communicate data in context” — is a vital skill for any business today, according to 2019 Gartner research. Some companies may still have ways to go to maximize the potential of their labor analytics. Hiring a chief data officer or data scientist or outsourcing analytics capabilities to a vendor can help make sense of the data that’s collected. 

The growing importance of data analytics is inevitable. For the unprepared company, this may be intimidating. Getting leadership buy-in and using data analytics strategically to achieve a specific business outcome can help. But once the organization gets a handle on its labor analytics function, it can expect promising business outcomes. 

Optimize your labor analytics process with Workforce.com

Utilizing labor analytics tools like Workforce.com makes it easier to turn your data into real-time, actionable insights. These insights help you more efficiently tackle frontline labor issues like:

  • Predicting future hiring requirements
  • Understanding current staffing needs
  • Managing compensation and overtime
  • Understanding and optimizing employee engagement

If you’re interested in using workforce management software to improve both your labor analytics and your bottom line, check out our webinar below featuring exclusive research from a Forrester TEI report:

Building a Business Case for WFM Software

For more information, get in touch with us now. 

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How to effectively use data analytics for workforce success

data analytics

There’s a lot of emphasis put on data-driven decision making. But how do organizations start that process? Serena Huang, global head of people analytics at the Kraft Heinz Co., shared some helpful insights into how leaders can use data to better understand the workforce and improve overall management and performance. 

Workforce recently caught up with her, and she shared her thoughts on how to use data analytics and gather information and employee feedback for better workforce management. 

Workforce: What do leaders need to know about the relationship between strategic business planning and data analytics?

Serena HuangSerena Huang: I’d encourage leaders to think of data analytics as a new mindset and a new language rather than a new tool from IT. There are several areas where analytics can improve business planning, such as more accurate demand forecasting and a better understanding of consumer behaviors. 

WF: What is the importance of using analytics in managing people? How did the COVID-19 pandemic highlight this?

Huang: It’s always been important to use analytics in managing people. Many companies would say that “people are their most important asset” and even the most technologically advanced companies cannot operate without people. Instead of relying on intuition, analytics can help organizations make more informed decisions faster and at scale. 

Employees’ health, safety and engagement have never been more important. The pandemic has provided an opportunity for HR to become heroes by caring for employees and ensuring business continuity.  At Kraft Heinz, this is critical because our employees are crucial to making food that everyone needs.  We have a responsibility around the world to feed people, and our employees make it happen.

WF: What are the common misconceptions about people analytics and its role in workforce management?

Huang: One of the biggest misconceptions is that data must be perfect before you can do analytics. I always recommend starting with the business problem rather than the data. You’d be surprised how much usable data already exists. Another misconception is that you need data scientists or know how to code to start doing people analytics. It is much more important to focus on the right questions before hiring a data scientist or learning how to model.

Also read: Labor data analytics can inform better talent decisions

WF: How can organizations effectively use and make sense of the data they have? 

Huang: Visualizations and dashboards are great ways to turn data into insights. To know where to start, it’s best to align with business leaders on solving problems. 

For example, in workforce management, companies often have significant data on time and attendance, so a starting point can be using analytics to optimize labor costs. If there are different systems, it’s helpful to choose a country or location that needs the most help and start with a pilot.  

To create the most value, it’s important to monitor data quality on an ongoing basis.

WF: How can organizations track the right type of data for their workforce? How can they identify metrics of success?

Huang: It’s crucial to stay closely connected with the leadership team on strategy and business problems. If you can figure out the top three to five pain points, you can then frame questions to answer and think about what data you’d need. 

The metrics of success will vary from one problem to another. I’d recommend thinking in different time frames and ask yourself what success looks like in six months, 12 months, and two to three years.  

WF: How can managers use data to improve productivity and boost employee engagement?

Huang: Managers can certainly leverage surveys if they have a large organization. Often organizations conduct engagement surveys on a regular basis, so start with existing surveys for potential areas of improvement.

For managers with smaller teams, it is most beneficial to conduct regular check-ins and one-on-ones. Managers must create an environment where there is psychological safety, so team members feel comfortable sharing concerns openly. 

WF: What are different ways companies can collect feedback or listen to their employees, especially in the era of remote work?

Huang: There are several ways companies can listen to employees, including surveys, virtual focus groups, and Q&A during employee town halls. It’s helpful to monitor the participation rates as it could signal overload if participation decreases. It’s also important to encourage managers to connect with their team members directly on a regular basis in addition to this corporate-level feedback. 

WF: What are the factors to consider when choosing the right tools, methods or technology to measure and improve employee engagement?

Huang: A good starting point will include an evaluation of how many employees, how many languages, local legal requirements, reporting/analytics for users, text analytics capabilities. In my article published on LinkedIn, I explain why there isn’t the “right” number of times to pulse employees, and it depends on how quickly the business leaders can act on feedback. 

WF: What do you think the future of work will look like given current times?

Huang: It’s hard to predict what will be a temporary rather than permanent shift in the future of work, but I see more focus on flexibility, diversity and inclusion, well-being and skills development. 

Data from COVID HR-Pulse show that fewer than 50 percent of companies had a remote work program before the pandemic, and now office employees have been working virtually for months. Employees will demand more flexibility, and organizations can use flexibility to attract new hires. 

We have seen different businesses get creative during the pandemic. At Kraft Heinz, we’re focused on being agile at scale because we believe that agile and nimble organizations will outperform those that cannot pivot quickly when needed. To be truly agile in workforce planning, an organization should know the skill sets needed to deliver business results and the skills its workforce currently has. 

Also read: A midterm outlook on the future of the workplace

The recent tragedies have brought diversity and inclusion front and center for many organizations. Companies that can create an inclusive environment where everyone belongs will continue to be able to attract and retain talent. 

While mental health remains a difficult topic to discuss, especially in a corporate setting, the pandemic has made it more critical to talk about this topic. We will likely see a focus on employee well-being extend beyond the pandemic.  

 

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Labor data analytics can inform better talent decisions

labor analytics, people analytics

Labor data can help organizations make more informed talent decisions, but more companies could be taking advantage of it. 

According to Mercer’s “2020 Global Talent Trends Study,” 39 percent of organizations use predictive analytics to inform their people-related decision making. Thirty-one percent said they use a cause/effect analysis of key workforce and business outcomes, and just 18 percent gather data to assess the impact of different pay strategies on performance.  Meanwhile, 61 percent of executives who have used talent analytics said that doing so to inform decision-making is the number one HR trend that has delivered an impact

A workplace strategy expert spoke to Workforce about the potential of people analytics and how organizations can use it in their talent management strategy.

Using labor data analytics to measure employee impact

People analytics can inform complex predictive models, but it can also help organizations understand  how certain decisions have impacted employees. 

One prime example of this is pay equity, according to Tauseef Rahman, partner in Mercer’s San Francisco office. Labor analytics can be used to understand if there are pay gaps at an individual or group level, after taking into account factors like where employees live, what work they do and how long they’ve been working at the company. 

Also read: Labor analytics add power to workforce management tools

Analytics can also help organizations understand performance measurements better, Rahman said. Based on performance ratings and rewards like promotions or raises, are those performance ratings biased toward a specific subset of employees? 

Doing this analysis at a company-wide level is a good place to start, Rahman said. From there, leaders can see if there’s a company wide gap. There may not be a pay gap within the organization as a whole, for example, but through analytics, one can drill down and see if there are gaps in a specific business unit or a specific team. 

“That data can certainly help shine a light on where those patterns are and then that will help redirect efforts and resources to areas that need the most help,” Rahman said.

Using data analytics predictively 

Remote work has become more commonplace for many organizations during the COVID-19 pandemic, and experts expect remote work to continue to be more widely accepted afterward as well. Rahman said that analytics can help organizations interested in adapting an increasingly remote workforce. 

As organizations consider a more geographically distributed talent pool, many questions arise, like: If we hire people from across the country, how does that change how we do talent acquisition? How does that change how we pay people? And how do we manage the employee experience across different locations?

 Data can help answer questions and  inform decisions like this. 

Also read: The most pressing workforce management issues of 2020

Acknowledge the inherent flaws of data collection

No set of data can be completely unbiased, but what organizations can do to address this fact is simple, Rahman said. The key here is to clearly acknowledge that there’s bias in how data is created. 

Also read: Keeping Data Safe: The Next Wave of HR Tech Innovation

People who use data to inform decisions or strategy can acknowledge this bias by considering a few questions when they plan on using a dataset to do or plan something. These questions include: How was the gathering of this data framed? Was anything missing? Was answering these questions optional or required for survey takers? Were survey creators biased to presume certain outcomes?

For example, in recruiting, Rahman has seen the presumption that no one over the age of 65 would be interested in applying to a tech position. The reasoning behind this may be laziness or mental shortcuts rather than malice or age discrimination, but it’s flawed reasoning no matter the intention. “Things that are done in the spirit of making it easy can result in unintended consequences,” Rahman said.

Cross functional teams are critical

labor analytics, people analytics

According to Mercer’s “2020 Global Talent Trends Study,” the  “quality and reliability of data are critical.” Cross functional teams are critical for organizations interested in using data the right way, Rahman said. 

The team shouldn’t only include analysts and statisticians but also people with HR expertise, legal expertise and an ethical understanding of data collection. What data does an organization have access to, and how can it collect it in a way that’s not creepy?

“You can configure technology to do whatever you want. If you do something wrong, you can’t blame the technology. You blame the people who configured it,” Rahman said. 

Managing privacy concerns is an important part of these teams. There are interesting ethical questions that come up with the possibility of using labor analytics predictively. For example, Rahman said, what are the ethics of having a model that predicts how likely an employee is to quit? If they haven’t actually quit, what decisions can you ethically make with that prediction? 

Having someone with policy expertise is also beneficial for a cross functional team. For example, if an employee has a 90 percent chance of quitting according to an analytics model, a policy expert could consider what could be driving the employee’s dissatisfaction and what workplace policy could help them be more engaged. Maybe it’s something related to compensation or work-life balance that can be addressed.

The scope of people analytics 

Businesses go through times of uncertainty for many reasons, from global crises to national recessions and more. Times like this highlight the role of labor data analytics to make the employee experience better, at a time when many employees may be going through financial or personal struggles. 

Still, while focusing on improving the employee experience, organizations cannot lose sight of broader, also important areas of business that analytics can inform, Rahman said. These bigger picture topics include pay equity and diversity. 

“Having a broad mindset is really important,” he said. “You want to solve daily issues, weekly issues, monthly issues and multiyear issues, [all while] not losing sight of the fact that you still have to do your pay equity analysis and you still have to make people engaged in your company. It’s a lot more work, but who better to do it than these strong, multi-disciplinary [people analytics] teams?”

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The in-demand potential of a data-driven CHRO

data analytics, data privacy

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.”