Employees are one of the biggest investments that an organization can make, so it’s not surprising that the field of workforce analytics has emerged to help support it. And with the amount of data that is being generated and recorded about not just employees, but the organization as a whole, the time is ripe for analysis. This is becoming even more true as our working population expands to include alternative forms of employees in chatbots and similar. 

In this post we will introduce workforce analytics by answering the following questions:

What is workforce analytics and how does it differ from HR and people analytics?

What are the benefits associated with workforce analytics?

What are some best practices for workforce analytics?

What are some challenges with workforce analytics?

How can organizations begin to implement workforce analytics?

What are some existing tools designed for workforce analytics?

What is Workforce Analytics?

Workforce analytics is a growing practice that uses metrics and tools to get a thorough and holistic understanding of workforce performance. This analysis includes a number of factors such as:

  • Staffing and recruitment
  • Training and development
  • Compensation and benefits

Workforce analytics also takes into account wider factors such as skill gaps and demographic issues and more specific problems to a location or within an office, such as productivity concerns.

Workforce vs People vs HR Analytics

In addition to workforce analytics, there are two other terms that are common to the topic: people analytics and HR analytics. For many, these terms are used largely interchangeably, but some alternative definitions are:

People analytics: Uses data and tools to measure, report, and understand the performance of employees. Often used in place of workforce analytics and includes the impact of exterior forces and similar on the movement of people within and through an organization.

HR analytics: A more narrow definition, focused solely on HR issues and not other business issues that may impact HR and vice versa.

It is also important to keep in mind the role that an increasing number of bots and AI entities are taking; suggesting a need for a more inclusive term – like workforce analytics. For the sake of this article, we will consider that ‘people’ and ‘workforce’ analytics are equal in definition and reference.

Benefits of Workforce Analytics

As with any type of analytics, businesses stand to gain enormous benefits from properly executed people analytics. Some of the biggest benefits that organizations can experience include:

  • Improved recruitment practices: By having knowledge of what has worked in the past, whether it be in terms of candidate characteristics or hiring methodology, knowing what does and doesn’t work can make a huge difference in acquiring the right talent. Some key benefits in this area include:
    • Less ‘mismatches’ when hiring
    • A smoother hiring and onboarding process
    • A better understanding of employee trends, when they’re happiest, or when they’re most likely to leave; enabling better planning practices
  • Improved employee experience: HR often plays a huge role in developing company culture and having access to essential employee information can help in building and implementing a cultural fit.
  • More accurate compensation: By going beyond factors such as internal employee performance and expectations to include demographics and market characteristics, organizations can be sure that employees are being paid fairly (and within budget).
  • Enhanced training and onboarding: A major part of any business is ensuring the successful integration of new team members. However, this alone is not enough, and providing the right initial and ongoing training is key to keeping employees productive and effective. With workforce analytics, it’s easier to see what skills are most in need and where resources should be distributed.
  • Getting the most from machine learning: Organizations today are harnessing the power of AI and machine learning throughout their operations, so it’s no surprise it’s becoming part of HR and people efforts too. Analytics provide the information necessary, for example, such as employee and applicant data, to help put together great times, identify weaknesses and more.

These benefits together can help to build a more unified operation with lower employee turnover and a more balanced benefits and compensation structure. A more in depth look at this topic is available in our recent blog post 6 Reasons Why HR Analytics is Required for a Great HR Function.

Best Practices in Workforce Analytics

To make your people analytics more effective, there are a number of best practices that can be implemented:

Focus on outcomes: This helps you to measure the right things. Some numbers may be interesting and seem good on paper, but focusing on them may ultimately be causing more problems. For example, think about the case of customer service call time reduction: is it that the issue getting resolved faster? Or are customers getting frustrated and hanging up?

Implement predictive analytics: Use the data and knowledge gained to be proactive instead of reactive. This can help eliminate bad hires and integrate better practices related to employee retention and engagement before problems emerge. 

Start small: It’s tempting to jump into a new HR analytics program with both feet, but it’s important to lay a solid foundation and start with smaller efforts first. This will make it easier when it comes time to integrate data from outside of the HR department.

Connect analytics with business needs: Companies today are flooded with data. Choosing data that has direct, demonstrable business needs has two benefits:

    1. Narrowing down the field of data to only include what is relevant
    2. Achieving executive buy-in when growing and developing your people analytics program

Challenges with Workforce Analytics

Though there are a number of benefits associated with people analytics, it is not without its own challenges. Some of them, and their related solutions include:

Challenge 1: Data Quality

Analytics are only as good as the data that is used to support it. In large, decentralized organizations it can be difficult to ensure that high quality data is what is being used 100% of the time.

To solve this problem, many organizations implement comprehensive data cleaning programs that help to ensure incoming data adheres to a certain format and to make any necessary changes before the data reaches the point of analysis.

Challenge 2: Skills Gap

There is a much greater need than availability when it comes to data scientists, analysts, IT professionals and other similar roles. This can cause analytics to either fall into the wrong hands or by the wayside until something environmental changes.

Thankfully, new tools are constantly emerging with the ‘business user’ in mind to help simplify analytics practices down to dashboard and displays. However, despite these rapid advances, there still does remain a need for skilled professionals in the field.

Challenge 3: Thinking only about HR

With a name like people or workforce analytics, it can be tempting for organizations to focus all of their attention and analysis on HR, without considering the potential impact that can be had from other departments.

Instead, choose platforms and approaches that take into account data from throughout an organization. This can help to highlight hidden relationships that may not otherwise be clear. It is also helpful to demonstrate the potential business benefits associated with workforce analytics to encourage congruence and cooperation.

Challenge 4: Ethical issues

Employers today have the capacity to obtain more information than ever before about employees. However, how much about an employee can be tracked before it’s considered to be ‘too much’?

As technology, particularly when it comes to IoT enabled devices and similar evolves, laws are slowly catching up, but there still remains a gap in many places. A more actionable solution? Being open and transparent. Tell employees what information you’re collecting, how you’re using it, and give them a chance to communicate with you about how they feel about it.

Getting Started with Workforce Analytics

Implementing your own HR analytics program can seem daunting, but this guide can help you as you begin.

Tackling data management is essential. Before you can have an effective analytics program, it is key to have a system that ensures data quality and accessibility. Some general factors that this program should take into consideration include:

    • Specifying accountability for certain elements
    • Establishing clear data definitions
    • Setting clear goals and KPIs for data collection and input

It’s then necessary to build a business case for how workforce analytics is going to contribute to achieving greater business goals. Subsequently it is necessary to outline your strategy, including clear goals and what data is needed to meet these goals.

Next, identify the right people to become accountable for specific metrics in each part of your organization. Here it can be helpful to emphasize the anticipated benefits and how their active integration will be helping to achieve them.

After that, it will be time to determine total cost of ownership (TCO) for the entire program. Some costs to consider at this point include:

    • Assessment costs
    • Technology
    • People expenses: hiring, training and similar
    • Overhead

Working together with your previously established stakeholders to validate any cost assumptions that you may have made can be helpful at this point.

The final step is to establish your metrics and how you will define success. Remember to make your metrics easy to measure and straightforward to interpret and apply as part of your overall business goals. Some common metrics include:

    • Time to fill
    • Cost per hire
    • Competency analytics
    • Retention rate
    • Replacement rate
    • Accession rate
    • Employee performance

Meeting these major prerequisites is essential prior to implementing a new workforce analytics tool or program. For a thorough list of questions to ask yourself as you are planning your implementation, check out this list.

Workforce Analytics Tools

There is a rapidly-growing market for workforce analytics tools, giving organizations an almost dizzying array of tools to choose from. We cover some of these tools later in this blog, but in the meantime, these are some of the common functionalities that your tool should possess:

    • Visual HR metrics and dashboard
    • ‘Real time’ environment analysis
    • Future employment planning based on predictive analytics
    • Performance measuring tools
    • Budget planning

For some organizations, it may be better to have a custom built solution. For others, a cloud-based solution might be the right choice. After choosing the right tool, it will be necessary to complete the actual integration, employee training, and data collection and analysis.

Some tools currently available on the market include:

NameFoundedStatusNumber of Employees
Advance Systems1984Private51-200
Aurion Analytics1990Private51-200
IBM Kenexa1911Public10,001+
Oracle HR Analytics1977Public10,001+
People Analytics by TrenData2017Private11-50
Talentsoft Analytics2007Private501-1,000
Workforce Software1999Private501-1,000
Zoho People1996Private1,001-5,000

Choosing the right tool will require the input from a wide range of sources, so it is important to allow ample time to complete the selection process.

No matter whether you’re referring to workforce, HR, or people analytics, one thing remains the same: the goal is to find a better way to bring employees and tasks together, better. Workforce analytics will only stand to become more useful and complex as our working population will grow to include robots and other forms of AI.

Want to learn more about topics related to people analytics? Take a look at our blog

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