Every business strives for operational efficiency. Finding ways to increase productivity, reduce waste, and improve processes will significantly impact your company’s bottom line. Maximizing efficiency will save your company money and facilitate growth and scale.
Your workforce is your most valuable asset in achieving operational efficiency, and workforce analytics are crucially important to helping your organization reach peak performance. Workforce analytics can paint a vivid picture of your workforce’s strengths and weaknesses and inform strategies for talent acquisition, talent retention, and employee engagement. Analytics can also support incentivization strategies as your business pursues new organizational goals.
To get the most out of your workforce analytics, you must identify your business’s key metrics and develop key performance indicators (KPIs) that depict success. Here, we break down some of the most important types of workforce analytics to track in 2024 and how you can leverage them to your benefit.
1. Descriptive Analytics
Descriptive analytics is one of the most common types of workforce analytics, and it is used to paint a picture of your organization. Descriptive analysis uses historical data to identify and analyze patterns and relationships within your workforce. The goal is to help you understand the impact of past decisions on business outcomes while providing a base with which to track future trends.
When applied to your workforce, descriptive analytics — like the name suggests — describes the most important facets of your workforce, helping you draw valuable insights.
Examples of metrics used in descriptive analytics
- Headcount: Employee headcount is an analysis of how many and what type of full-time employees (FTEs) an organization employs over time.
- Turnover rate: This metric tracks how often employees depart the organization, whether by voluntary decision or involuntary dismissal.
- Absenteeism: The frequency with which FTEs fail to show up for work, whether by sickness, personal days, or unexcused absences.
- Employee demographics: These workforce demographic statistics describe the makeup of your workforce, including gender, race, ethnicity, sexual orientation, and more identifying characteristics.
Benefits of using descriptive analytics
Descriptive analytics allow you to draw data-driven insights about your workforce. From ensuring you have the right number of employees to achieve your business goals to determining employee engagement, descriptive analytics gives you a complete picture of your team.
This informs hiring decisions to keep the right teams fully staffed with people with the right skill sets. By using descriptive analytics, you can get a broad overview of your workforce to understand if you have a gender bias or other weaknesses in diversity, an abundance of unmotivated employees, staffing shortages on certain teams, and a number of other important indicators. With this knowledge, you can make changes to build the right workforce.
2. Diagnostic Analytics
Whereas descriptive analytics uses historical data to understand your workforce’s makeup, diagnostic analytics is a data analytics technique that explores the root causes of events, behaviors, and outcomes. The goal of diagnostic analytics is to understand why something happened the way it did and inform data-driven decisions to effect more positive future outcomes.
For instance, if you roll out a new product and suddenly get a large influx of customer complaints because it’s taking extremely long to ship, diagnostic analytics can use data to get to the bottom of why there’s such a shipping delay. This is just one example of the many actionable insights you can draw from diagnostic analytics.
Techniques used in diagnostic analytics
- Data mining: Data mining is the process of analyzing large data sets to extract data and discover patterns, often using machine learning techniques and workforce analytics platforms. It’s useful in detecting patterns that may have led to certain negative (or positive) outcomes.
- Correlation analysis: This statistical method is used to understand if there’s a connection between two specific variables. For instance, an increase in the cost of raw materials likely correlates to decreased profits.
- Root cause analysis: This problem-solving method uses data to identify the root causes of specific problems.
Benefits of using diagnostic analytics
Businesses face myriad challenges over time, especially when investing in innovation or making significant workforce changes. Diagnostic analytics provide organizations with powerful tools to understand operations better and make informed decisions to drive toward more positive outcomes. When things go wrong, you must figure out why it went wrong so you can avoid making the same mistakes in the future.
Any department may deploy diagnostic analytics to explore specific scenarios. When it comes to the workforce, however, diagnostic analytics are especially useful in understanding employee productivity. This type of analysis will help determine whether you have the right number of people on staff to meet certain goals, whether there are skills gaps preventing you from performing certain processes efficiently, or whether there are bottlenecks within the organization preventing your workforce from achieving peak efficiency.
3. Predictive Analytics
Nobody can see the future, but predictive analytics uses data to project how past and present employee performance may predict future performance. Analysis can also forecast the most likely outcomes of business decisions.
This field often uses machine learning and other automation techniques to predict industry trends and employee performance without requiring an incredibly heavy manual lift. Predictive analysis is an excellent way to predict future company performance based on workforce behavior and provides potential solutions to optimize your workforce and improve business performance to reach changing goals over time.
Examples of workforce-related predictions
- Employee turnover: Employees are the foundation of productivity, and being able to use workforce behavior data to predict layoffs and voluntary employee departures helps an organization plan for staffing changes.
- High-potential employees: Predictive analytics can use employee data to predict future talent performance to help organizations invest in retaining the best talent.
- Future skill requirements: Based on planned and potential changes, predictive analytics can inform hiring practices to ensure you have the right skills in the right places and incentivize employee performance and growth.
Benefits of using predictive analytics
We outlined a few examples of workforce predictions above, but predictive analytics has a wide range of applications within an organization. The workforce applications are extensive, allowing you to predict employee engagement metrics, employee productivity, changes that may occur from adjusting staffing or re-organization, and much more.
Using past and present employee behavior and performance data, prediction models may assist in forecasting future individual performance, both high and low. Together, all of this data can inform broad strategic decisions and help you work backward from desired future outcomes to make smarter decisions in the present.
Predictive analytics is also useful in business development and finance, IT, sales and marketing, HR, and improving employee communications.
4. Talent Analytics
Also known as people analytics, talent analytics is a data-driven method to optimize talent within an organization’s workforce and improve external talent attraction. From recruitment and hiring to talent incentivization and retention programs, talent analytics help an organization maximize existing talent and bring in new skills and talented individuals to meet evolving needs. The right talent is crucial both to optimizing day-to-day operations and succeeding in new initiatives and innovations.
Areas of focus in talent analytics
- Talent acquisition: Using talent analytics, organizations can identify the skills they need and use that information to find the right candidate experience in the existing talent pool, informing the recruitment and hiring processes.
- Employee development: Every organization has a wealth of untapped potential, and talent analytics helps identify high-potential employees and future leaders worth investing in with professional development support.
- Retention strategies: Talent analytics helps organizations better understand their employees and what they want — from leadership training and perks to better compensation packages — to make them more loyal.
Benefits of using talent analytics
For many organizations, the workforce is its greatest asset. However, a workforce’s success is predicated on more than simply a number of people’s labor; it’s also dependent on the quality of that labor.
Every organization can benefit from talent analytics because they identify present talent shortcomings, future talent needs, emerging skill gaps, and inform talent acquisition and retention strategies. Not only can analytics determine what your organization needs to meet business goals, but it can illuminate the potential you already have in the workforce to promote and develop from within — thereby saving on labor costs of hiring externally.
Every organization wants to employ the best people and bring in the best people to help with new projects, product releases, and other innovations. Talent analytics simplify talent-based decisions and streamline recruitment and internal promotion by utilizing the data you already have to showcase potential in your current workforce and opportunities for external hiring.
5. HR Analytics
Related to talent analytics, HR analytics inform day-to-day workforce-related decision-making. While talent analytics assesses talent needs and potential opportunities, HR analytics uses data to create frameworks and processes to meet workforce-related goals and improve employee experiences.
It’s a key tool for helping your organization’s HR department optimize how it recruits, hires, and retains employees. (And increase employee morale.) If your organization aims to build an engaged, talented, diverse workforce, HR analytics can help make more informed HR decisions.
HR-related data analyzed in HR analytics
- Recruitment metrics: HR analytics help develop recruitment processes by assessing the effectiveness of recruitment methods, allowing teams to hone techniques to attract and retain the best talent.
- Employee engagement: Engaged employees can drive as much as a 21% increase in profitability, and HR analytics help devise strategies to keep employees engaged and motivated to do their best work for the organization.
- Compensation and benefits: Compensation packages are a powerful tool to help an organization gain a competitive edge in talent recruitment, and HR analytics can inform total rewards programs that improve employee retention and prevent turnover.
- Learning and development: Investing in employees’ learning and development is one of the most cost-effective ways to improve company performance and encourage innovation. HR analytics can identify the best programs and opportunities for upskilling specific employees.
Benefits of using HR analytics
HR teams are tasked with building, managing, and optimizing a workforce. Yes, individual business leaders or leadership teams may make broader organizational decisions and recruit certain talent, but HR teams must optimize the organization’s workforce.
HR analytics help create programs to improve employee engagement, incentivize workforce performance and development, and much more. Plus, they can use industry data to build the best compensation and benefits packages to attract the best talent and develop stronger recruiting strategies to ensure that every new initiative is staffed with the right people. It’s a profound way to improve the workforce planning process. Plus, plenty of HR analytics software exists to help make the process easier.
Employee turnover and changing organizational strategies can significantly impact HR initiatives. HR analytics help HR teams stay ahead of workforce changes, motivate current employees, and keep the organization well-staffed and supported.
How To Leverage Teramind for Workforce Analytics
Teramind is the global leader in behavioral solutions as over 10,000 organizations in 125+ countries, across every industry, have turned to Teramind to protect and optimize their business.
Here’s how you can use Teramind as part of your workforce analytics initiatives:
- Define Objectives and Metrics
- Set clear goals for what you want to measure (e.g., productivity, compliance).
- Identify key metrics such as application usage and time spent on tasks.
- Implement and Customize
- Deploy Teramind across your organization and configure it to match your objectives.
- Customize monitoring rules and settings to align with your specific needs.
- Monitor and Analyze
- Track employee activity and behavior using Teramind’s analytics tools.
- Generate and review reports to identify productivity trends and compliance issues.
- Engage and Improve
- Communicate findings with employees and use data to provide constructive feedback.
- Adjust strategies and settings based on insights to continuously improve performance and efficiency.
Conclusion
An organization’s workforce is the foundation of any project, business objective, or initiative. All operations are predicated on the efficiency and productivity of its workforce, which is why workforce analytics are so important to achieving operational efficiency.
Having the right analytics and KPIs in place will help organizations understand their workforce’s performance and develop strategies to improve present performance, find the right talent, and set the organization up for success in all business scenarios.
