Workforce Analytics: A Guide for Small Businesses

Workforce analytics is the data collection and analysis that businesses use to understand their people (i.e., employees, teams, etc.). It can help your business measure employee performance, engagement, behavior, retention, and overall return on investment (ROI) related to your workforce. With technology, it is easier than ever to gather and crunch big data, simplifying work for managers wanting to make data-based decisions for their company.

Types of Workforce Analytics

All forms of workforce analytics help identify issues and present courses of action to improve business processes. Knowing the type of analytics you want can help define the problem, although sometimes the issues you need to identify may cover more than one solution.

Depending on the purpose and end goal, these can be divided into the following types:

• Descriptive
• Predictive
• Prescriptive
• Diagnostic

Descriptive

This data can provide a clear view of your employees’ current state or help you understand a past event. For instance, a company can run analytics reports to determine the steps taken when onboarding employees (when the offer letter was sent, how quickly the offer was accepted, how long onboarding took, etc.) or a survey can be done to analyze the hiring and onboarding to find areas for improvement. This can help reduce costs for future hiring decisions by finding ways to expedite the process.

Rippling allows you to view all employee data in one platform by selecting the variables you need.

Predictive

This analysis helps you anticipate future outcomes based on current and existing data. For example, a company may run analytics on the number of support tickets plus the per ticket cost over a period of time. From there, they can predict how much IT help desk support they may need based on trends throughout the year, answering questions like, “When do the number of issues peak, and what months are they at their lowest?” and “Is there a trend around when the most complex and costly issues occur, or is it sporadic?”

This data will help users predict the number of support tickets that will be produced and determine areas they can investigate to help them improve support time and potentially decrease their cost per ticket.

Rippling allows you to customize your reports to get the data information you need.

Prescriptive

This type of data can help in deciding better courses of action based on past performance. For example, a company can run a report on their target vs actual employee headcount to determine gaps in hiring and which departments have historically lacked necessary employees. Besides the use of software, such a report can be done from an analysis of records and using the results to project the growth within the company and each department. This data can then be used to make better hiring decisions and improve the recruitment process.

Diagnostic

This type applies to solving specific problems and is used to find the underlying cause and suggest a course of action. For instance, a company with a high turnover rate may use workforce analytics to determine if the problem lies in pay, company policies, managers, or office culture.

A detailed compensation report can help determine where there may be a pay gap within a department or the company as a whole. Company surveys can also determine employee satisfaction, while exit surveys can identify areas where employees may be unhappy. You can use this information to adjust pay to be more competitive with industry standards.

Rippling allows you to run compensation reports by department or filter by employee.

How to Use Workforce Analytics

Much of today’s HR software and workforce management software allows you to collect data on a regular basis. In addition, some HRIS systems, payroll services, and PEO programs come with employee survey data, which employers use every month to check in on worker satisfaction.

Using workforce analytics software, such as Rippling, can make tracking and analyzing your workforce easier. Rippling brings all employee data (HR, IT, Finance, and third-party systems) into one platform and allows you to control who can view data by location, role, department, and more.

Visit Rippling

Hiring and interview notes, exit surveys, and performance feedback also provide excellent, ongoing data for workforce analytics. Regardless of how and where you get the data, you should have a clear game plan when using workforce analytics.

Identify the Problem

Begin with a clear idea of what problem you are addressing and how you want to solve it. Be specific—for instance, “causes for employee dissatisfaction” is very general, whereas “Why do employees leave after four to seven years?” gives you greater focus.

Determine the Information You Need

You are looking for actionable data—information your business can apply when making a decision. You also need to consider what information you have access to and can gather.

How you define the problem can determine the type of analytics you do. For example:

• Why do they leave? Use exit surveys and interviews to determine a pattern.
• How do we stop them from leaving? Specific questionnaires throughout the life of an employee can help with retention.
• What kind of employees leave after four years? Use hiring notes, personality tests, and manager feedback to determine the types of employees who leave.
• Can we improve retention by doing X? Researching who had the training, support, or promotions in question and whether or not they continued in the company can help determine a path for improved retention.

Set Benchmark Questions & Goals

Determine what your benchmark questions will be to help you gather the data for your overall goal. For example, if your goal is to improve employee retention, you could ask whether a certain action helps retain employees. Does a raise of a minimum percentage motivate employees to stay, or will a flexible schedule promote better retention?

It can also mean getting a certain number or percentage of replies and assessing which responses fall within the different metrics/criteria you use. For example, in the larger analysis of “Why do employees leave,” your benchmarks may include specific lifestyle markers, like a new baby or completing an advanced degree, employee satisfaction at the time of exit, performance factors, and even personality types.

Gather & Analyze the Data

When you have identified the problem and the information you need and established benchmarks, you can then determine how to gather and analyze your information. You’ll consider what data you may already have available and what new data you may need.

As we mentioned earlier, your software tools will often have data readily available for you. Other data you already have may come from previous survey results, resumes and personality assessments, company goals and key performance indicators (KPIs), etc.

If you need new information to make the best, most informed decision, consider new team surveys (Slack is a great tool for running frequent informal surveys) or adding new questions or areas of discussion to your performance review process.

Benefits of Workforce Analytics

Workforce analytics can help lead to actionable changes that make a difference. While an investment, they can save you time, money, and headaches down the line. For example, the Workforce Institute’s 2022 Retention Report found that the majority of reasons for employee turnover are preventable, and it costs nearly 33% of an employee’s annual salary just to replace them.

The proper use of workforce analytics can help with the following:

• Improving Hiring: With analysis, you can determine the best types of employees for your business and what factors you should look for in recruiting and interviewing. Additionally, you can determine which of your company’s values and cultural aspects attract the best candidates. (A recent survey shows that strong company values and culture ranked third, below compensation and work-life balance, for what candidates look for when accepting a job offer.)
• Managing Employees: Managers can encourage traits that high-performers have in common and determine what keeps them loyal to the company. Analytics can be used to find a correlation between training and performance and improve company policies. Job stress, including lack of proper training, is listed as one of the top reasons employees become dissatisfied with their positions.
• Organizing Roles: Analytics can be used to determine roles within your organization. For example, you may find three employees are doing different parts of the same task and getting in one another’s way. To ease the situation, you could reshuffle the project to one employee, whether an existing worker or a new hire.
• Engaging Employees: Analysis of how engaged your employees are can give you insight into how you can improve the office culture and encourage collaboration. It will enable you to keep morale high in stressful seasons. According to a popular retention survey, when employees have a higher rating of their supervisors and managers, they stay longer with an organization.
• Reducing Employee Churn: Workforce analytics can give you insight into why employees leave. Knowing the metrics around employee satisfaction can help your business devise a plan to reduce turnover. In a recent employee turnover insight report, lack of job growth was the top reason employees leave a company.

Bottom Line

Workforce analytics uses information gathered from surveys and mined from employee records to help you make informed decisions concerning employee hiring, management, and retention. With the amazing amount of data available, especially for companies using HR or workforce management programs, it’s not hard to create and conduct studies to answer vital questions on how to run your company better.