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How Does HR Analytics Transform Workforce Planning?

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With so many interesting new HR tools available lately, are you wondering if more modern HR analytics could improve your workforce planning capabilities? In a world where companies need data-driven approaches to define, deliver, and improve workforce strategies, exactly how can modern tools help?

Today’s HR tools offer exciting new capabilities. For example, these solutions can accelerate data gathering, provide predictive intelligence, assist with hiring decisions, streamline performance management, and much more. But to avoid becoming overwhelmed with choices, it’s important to define the people challenges your company needs to address.

This article is intended to employers consider multiple facets of HR analytics:

  • Historical context
  • Popular functionality
  • Key benefits
  • Real-world use cases

How HR Analytics Has Evolved

Initially, HR analytics focused primarily on helping organizations eliminate intensive manual labor. These tools were useful for complex data collection and spreadsheet management to help employers gain useful intelligence from HR metrics and KPIs.

However, technology is constantly evolving, and this has led to multiple breakthroughs in HR analytics. For example, innovative solutions now integrate advanced workforce planning tools for faster, easier employee data analysis.

Now HR professionals can much more quickly and easily identify meaningful workforce patterns and forecast relevant trends. Using these insights, HR teams can develop, implement, and measure strategies and programs with greater precision and confidence. This improves HR’s ability to work side-by-side with business leaders to align with organizational objectives and improve overall performance.

To see what exactly HR analytics tools can do to improve workforce management, let’s move on…

Key HR Analytics Functions

1. Data Collection and Aggregation

Collecting and aggregating huge data sets is a core HR analytics strength. These tools can integrate data from numerous sources for access through centralized storage.

For instance, imagine you need to verify that a staff member has signed an NDA. Or when preparing an annual review, you want to see how an employee’s performance metrics have changed over time.

When detailed data is structurally organized and highly accessible, HR and business managers can make better-informed decisions much more quickly.

2. Data Analysis and Visualization

Leading-edge HR analytics also provide powerful ways to analyze and visualize workforce data. By extracting actionable insights and applying high-end algorithms and statistical analysis, these tools can help HR teams uncover meaningful patterns, trends, and relationships.

In addition, these tools can make complex data more coherent and useful by translating information into visually rich charts and graphs that add context and improve understanding.

3. Talent Management

It’s crucial for HR analytics platforms to include talent management capabilities. These features are designed to help organizations improve employee engagement and retention throughout the employee lifecycle.

For example, some tools make it possible to assess individual and team skills and translate them into recommended learning paths and development opportunities. This helps HR build employee competencies and align career growth with company needs and goals.

4. Workforce Planning

HR analytics plays a central role in workforce planning because it directly supports strategic decision-making. With more timely, accurate, complete decision support insights, HR and business leaders can develop workforce strategies that are more fair, less biased, and better tuned to organizational realities and priorities.

These capabilities typically focus on resource allocation, employee recruitment, and workforce restructuring, among others.

5. Performance Improvement

Many newer platforms make it possible to analyze workforce performance data in a variety of ways. This helps HR pinpoint and resolve specific performance gaps, curate and deliver customized development plans, and acknowledge excellent performers.

Benefits of HR Analytics

1. More Effective Strategic Planning

Data-driven tools enhance strategic HR planning in several critical ways. For example, it becomes faster and easier to forecast future workforce requirements, facilitate succession planning, and avoid potential talent gaps.

These tools also help HR teams more quickly develop appropriate recruitment procedures to meet existing business needs.

2. Valuable Predictive Capacity

HR analytics tools provide powerful forward-looking capabilities that help HR teams operate more efficiently and effectively. By applying data from past patterns and trends, it’s possible to generate forecasts that more accurately anticipate and prepare for future needs.

This kind of advanced capability helps HR and business leaders take proactive measures and adjust on-the-fly. It also leads to more effective talent management practices and higher employee retention.

3. Better Understanding of Workforce Performance

The ability to more deeply analyze employee performance is beneficial at several levels. First, it helps organizations evaluate, motivate, and reward talent in the most effective ways. Also, it reveals the differences between high-performers and their under-performing colleagues. This can lead to more effective performance improvement roadmaps and results.

Ultimately, this not only helps individual employees grow but also elevates skills and competencies across the company.

4. Improved Hiring and Engagement Outcomes

When hiring, data-driven analytics is an exceptional sourcing tool. It can dramatically decrease time-to-hire by helping talent acquisition teams quickly assess any candidate’s suitability for a job.

Once an employee is onboard, retention becomes crucial. Workforce analytics can help HR continuously calibrate metrics like employee engagement, productivity, and burnout. By benchmarking these indicators, HR can take action when needed to reduce negative factors and boost positive results.

5. Stronger Diversity and Inclusion

Data-driven tools can also help employers build a culture of diversity and inclusion.

For example, HR teams can identify key factors that contribute to job satisfaction and engagement (and conversely turnover) among minorities. Then, by monitoring these indicators, they can identify potential issues and work proactively with recruiters and managers to support inclusion and belonging.

6. Optimized Costs

Analytics also helps HR leaders effectively allocate and manage workforce budgets and resources.

For instance, by benchmarking factors like headcount, compensation, benefits, or location strategy, employers can determine which costs are higher than comparable organizations. This can also be a foundation for calculating return on investment across various workforce-related variables.

Real-World HR Analytics Examples

The following examples demonstrate how world-class employers are using data-driven workforce tools to improve decision-making and HR operations.

1. Google

Google is an excellent example of how employers can apply HR analytics to enhance workforce planning and organizational culture.

Even though the company had been growing successfully for more than two decades, it became obvious in 2020 that workforce diversity and inclusion weren’t keeping pace. Historically, the company had struggled with gender and ethnic diversity in hiring. And by 2018, employee confidence in the company’s leaders was declining.

This issue began to cast a shadow over Google’s employer brand, which made it increasingly difficult to attract and retain top talent, especially among underrepresented groups.

Google’s People Analytics team recognized the need to improve workforce planning, so they turned to HR analytics for a solution. Relying on their workforce planning tools, the team gathered and interpreted relevant data and generated useful insights. As a result, they defined talent gaps, identified areas where diversity was lacking, and exposed below-average recruitment patterns.

How Google Tackled These Problems

To address these issues, Google turned to its annual feedback process known as Googlegeist. Launched in 2007, this survey captures employee opinions about multiple facets of work life and organizational culture.

By rigorously analyzing employee feedback data, the HR team easily recognized underlying factors that allowed DEI issues to persist. In response, they developed targeted recruitment strategies to provide more opportunities for employees, job candidates, and potential applicants from underrepresented groups.

One of the outcomes of this effort is Google’s partnership with historically black colleges and universities (HBCUs). The main purpose is to draw hidden potential from sources that have historically been overlooked.

In addition, Google now trains recruitment staff to avoid hiring biases and exclusionary hiring practices. The company also trains its leaders in methods for managing diverse teams more effectively. Over time, Google is building a more diverse and inclusive workforce, while simultaneously improving its work culture and employee experience.

2. IBM

Another company that relies heavily on data-driven employment tools is IBM. This particular case focuses on applying HR analytics to reduce employee attrition.

The HR team was concerned with the rate of job hopping across its employee base. By using Watson Analytics, they analyzed a variety of factors, including employee demographics, engagement data, and performance metrics.

How IBM Resolved This Problem

These findings helped the HR team develop a predictive prototype to identify employees who were most likely to quit their jobs. Next, the team created a multifaceted retention strategy to address the specific needs of high-risk employees.

This strategy included curated development programs, employee safety and wellbeing, workforce recognition, and mentoring.

After implementing this strategy, IBM’s employee retention rate improved. As a result, the company saved money on recruitment and training, while improving the work environment for everyone in the company.

Final Note on the Power of HR Analytics

Data-driven workforce planning tools are a game changer for modern organizations. They bring a new level of convenience and efficiency to HR professionals. No wonder employers everywhere are embracing these platforms. But is data-driven HR, alone, enough to change an organization’s culture?

These tools can’t replace the unique people and innovative spirit that set great employers apart. However, they can become a decision-making backbone and help keep any organization ahead of the competition.

What about you? What do you see ahead for your workforce? How will you put HR analytics to prepare for your organization’s future?

HR Is About to Get an Analytics Makeover

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Many organizational departments rely on analytics for decisions they make and strategies they implement. Through using analytics and data, these departments can get a better idea of what customers and clients need or want. But until now, HR hasn’t led the way. That’s about to change as HR braces for an analytics makeover.

Business analytics is used primarily in logistics or marketing. But HR is beginning to dip its toes into the world of data-driven tracking and measurement. Many companies have already implemented HR analytics. However, big data metrics aren’t always understood. And they’re seldom used with practical applications.

As we get deeper into 2017 and HR analytics grows more popular, we expect to see businesses take advantage of big data in new ways. Here are some areas that should benefit from appropriate HR analytics implementation:

What to Expect From an HR Analytics Makeover

1. Better Data-Backed Hiring and Promotion Processes

Hiring and promotion processes can be complicated. When a hiring manager is in charge of sifting through applications to select the best candidates, personal bias can easily cloud their judgment. This can prevent the most qualified applicant from getting the job. The same idea applies when HR considers who should be promoted.

However, by using data gathered through analytics HR teams can identify who is best suited for a job or promotion. For example, it’s easier to determine who outperforms coworkers and who has the right skills for a position.

2. More Efficient Ways to Track Engagement, Productivity and Job Satisfaction

Your human resources department is responsible for ensuring company employees are meeting certain standards and performing their jobs correctly. Unfortunately, this can be difficult to track. In 2017, we believe analytics will help HR departments see how engaged and productive employees are.

Job satisfaction is another area HR departments must consider. Very few employees want to openly admit to their boss that they are unhappy in their jobs. But when people don’t feel connected or committed to their work, the whole company suffers. By using analytics, HR departments can help make suggestions on how to improve job satisfaction.

3. Better Operations and Cost Management

If you’re trying to oversee the costs and operations of an entire company without analytics, there are definitely going to be some key components you miss. By implementing HR analytics in 2017, business owners can use data knowledge at all levels of their companies to improve operations and reduce costs.

Analytics can help HR departments get a better view of how the company is running and what could be modified to save money or time. With the right programs, systems and software, HR analytics can actually be beneficial to the company as a whole, not just to the HR department.

4. Ability to Plan for the Future

Analytics can also be beneficial for creating plans for the far-off future. While you may have a strong workforce now, this does not necessarily guarantee the workforce will continue to stay strong in the next few years. Through using HR analytics, companies can track what problems may come in the future, what those problems could cost the company, and what the HR department will need to do if that problem happens.

This idea is especially true for companies with employees all around the same age or experience level. If you don’t have a healthy mix of ages working for your company, you risk having each employee retiring around the same time. Without a proper plan on how you’re going to navigate this situation, the HR department could be left scrambling for new hires. With proper analytics, you could see this coming.

When the HR department takes advantage of analytics, the entire company benefits. This helps HR focus on hiring the right employees, ensuring they’re doing their job productively and efficiently, and overseeing company operations. As a result, HR teams can be a more strategic partner in business performance.

Soon, using analytics in HR will be something companies can’t ignore. As data-based technology advances, HR analytics will become just as crucial as analytics in other business departments.

Photo Credit: Jahangeerm Flickr via Compfight cc

Five HR Analytics Terms You Need to Know

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I love big data. I love it for many reasons, but, as I’ve said before, one of the main reasons is the way it’s “raised the profile” of HR and its importance. The sheer volume of information HR analytics can bring to the table has moved HR practitioners from an “out of sight out of mind” back room business function, to a major player when it comes to company goal setting and overall planning. Today we use HR analytics for everything from determining passive and active candidates; assisting with onboarding, training, and engagement; and predicting retention, attrition, and performance rates.

That said, the sheer volume of data available today for HR professionals to work with can feel overwhelming, and at times, paralyzing. Not only do we have mountains of data to interpret, but the data is constantly evolving, shifting, forming, and reforming as we learn about the newest technologies, which actively measure even more employment-related functions.

The key to getting your arms around big data and analytics is to do your research and start to understand it. And to do that you must become familiar with its “lingo”.

Five HR Analytics Terms You Need to Know

Before 2011, if you Googled “data scientists jobs” you would be lucky to find more than a handful of listings. That has changed, dramatically. In fact, by 2015 the demand for data scientists had surpassed the demand for statisticians. But if you’re not lucky enough to have a data scientist on your team, fear not. Knowing the following five terms will lead you one step closer toward all the benefits big data and analytics has to offer.

Data mining. Try and wrap your head around this number: Around 2.5 quintillion bytes of data are created every day. Clearly, it can’t all be analyzed. There’s not enough manpower on earth to get that job done. And that’s where data mining comes in. Akin to “panning for gold,” data mining involves sifting through raw data, and finding where patterns emerge. Analysts convert those patterns into tangible information, which then allows for relatively accurate prediction making about real life behaviors or events.

Machine learning piggybacks nicely off of data mining, as it’s often used to make that mining job just a little easier. Just as it sounds, computers can “learn” from the data ingested, helping to translate the data into recognizable patterns. You will sometimes see the term Artificial Intelligence used instead of “machine learning,” as AI is what provides computers with the tools they need to absorb and sift through new information.

Hiring channel mix modeling. There are myriad channels available today for talent managers looking to recruit, including—but not limited to—advertising, employee references, recruitment consultants, and social media. Hiring channel mix modeling allows HR pros to make use of previous data on all of the hiring channels employed in the past, and clearly map out which ones were most useful, allowing for more efficient, streamlined human resources departments and optimized hiring expenditures.

Cost modeling. Cost modeling helps those in the C-Suite understand many HR-driven costs. These include hiring and onboarding costs, the time estimated for an employee to reach full productivity, salary and productivity ratios, overall productivity, and employee turnover costs.  Cost Modeling can provide a rich “dollar value” picture of hiring and retention plans for a given year, and allow you to quantify costs associated with certain activities and processes (like mistakes made in hiring, voluntary turnover, etc.) 

People analytics. Simply put, people analytics involves combining all of the employee data in your organization—and using that data to understand and help predict potential business problems, issues like sales productivity, retention, fraud, customer satisfaction, and more. It effectively helps measure the success of both human resources practices and learning and development programs, and eventually (as new apps are developed) will begin measuring the value of different roles, leaders, and other business investments.

While “gut instinct” is always a good thing to have, long gone are the days when that and a fancy resume were the only things helping HR practitioners make hiring and other decisions. Now, big data and analytics can help HR teams run in tandem with those from other key departments, as well as play a significant part in helping their organization achieve success when it comes to business goals and strategies.

What do you think? Are there other HR analytics terms that you’ve encountered? Has your company delved into big data and all its potential? I’d love to hear your thoughts.

A version of this post was first published on Converge.xyz

Photo Credit: hocmba@gmail.com via Compfight cc