Workforce analytics is a mix of software tools, processes, and methodologies that businesses use to gather and analyze data around the way work happens at the company. It also is used to study its impact on Return On Investment (ROI). Workforce analytics helps you understand your employee engagement, behavior, and overall work processes to ensure you’re operating efficiently. With technology, it is easier than ever to gather and crunch big data, simplifying work for managers wanting to make fact-based decisions for their company.
Did you know?
Workforce analytics and HR analytics are different, although connected. Workforce analytics focuses primarily on people data (though there is a growing trend to include robotic workers in these assessments). HR analytics is broader and can include procedures, operations, or strategies.
Types of Workforce Analytics
All workforce analytics strive to identify issues. Many can suggest courses of action. Depending on the purpose and end goal, they can be divided into the following types: Descriptive, Predictive, Prescriptive, and Diagnostic.
Knowing the type of analytics you want can help define the problem, although sometimes the question may cover more than one solution. For example, here they are applied to the question, “Why do our employees leave after four to seven years?”
This data helps you get a clear view of your employees’ current state or to understand a past event. For instance, a company with high turnover might survey exiting employees to discover the sources of dissatisfaction.
Example: Exit surveys may show that employees leaving after four to seven years are seeking promotions or raises. The company may want to look at its schedule for raises and its promotion practices.
This analysis helps you anticipate future outcomes based on current and existing data. For instance, a company may run analytics on its sales force to determine the qualities in its salespeople that lead to success. They can apply this data to their recruiting and interviewing processes.
Example: Looking at personality assessments and performance records of the employees who stay vs those who leave show that extroverts are more likely to leave the company. Thus, they may want to create more opportunities for communication and interaction among middle managers—or they may decide to focus on hiring introverts.
Businesses use this data to decide better courses of action based on the past. For example, a company with a busy season may find it’s more effective to hire a temporary worker rather than add hours to current employees’ schedules.
Example: A lifestyle questionnaire reveals that most workers leaving are young families who no longer fit the long-hours, work-hard-play-hard culture of the company and that there needs to be a culture shift to retain these workers.
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 churn rate may use workforce analytics to determine if the problem lies in pay, company policies, managers, or office culture.
Example: A survey of employees who continue at the company through the four-to-seven year mark and former employees who left in that timeframe reveals the No. 1 issue was increased workload without commensurate pay or support. The company may adjust job descriptions and responsibilities.
Using Workforce Analytics
With today’s workforce management software, it’s easy to collect workforce 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 just to check in on worker satisfaction. Hiring interview notes, exit surveys, and performance feedback also provide excellent, ongoing data for workforce analytics.
When applying this data, however, you should have a clear game plan.
Start With the Question
Begin with a clear idea of what problem you are addressing and how you want to solve it. Be specific: “Causes for employee dissatisfaction” is very general. “Why do employees leave after four to seven years?” gives you greater focus.
Determine the Information You Need
As with the question, concentrate on specifics. You are looking for data that you can apply to a decision your business can implement. You also need to consider what information you can gather.
How you phrase the question can determine the type of analytics you do. For example:
- Why do they leave? Exit surveys and interviews
- How do we stop them from leaving? Specific questionnaire
- What kind of employees leave after four years? Hiring notes, personality tests, and manager feedback
- 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
Determine the Benchmark Questions and 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 a flexible schedule?
It can also mean getting a certain number or percentage of replies and include what different metrics you use: For example, in the larger question 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.
Knowing your limits can also help you determine benchmarks. For example, if you cannot afford to move your office or offer full-time telecommute, it won’t help to ask if they like the location. However, you may ask if the commute was an issue because you might be able to address that with commuter benefits or occasional work from home options.
To learn more about some of the most common HR workforce data points, check out our list of the most important HR metrics. Your workforce analytics system determines how you will use them.
Decide How to Analyze
When you have your question, information needs, and benchmarks set up, you can determine how to gather and analyze your information. The most common ways are through conducting surveys and analysis of existing data, like performance reviews and training records. However, you can also get a lot of insightful information from resumes, personality assessments, and even social media.
In the example of “why do employees leave after four years?” you may decide to use a wide focus, with analysis of data from a specific year set from hiring to firing and applying them.
- Personality influenced who stayed—how well was this considered in the hiring process?
- Exit surveys said opportunity was an issue—was promotion or training addressed while employed? (For example, you may find employees who made this complaint did not take advantage of the learning center or had historically poor performance reports.)
- Those leaving had started new families—what is the jump in price for health benefits between a single person and family policies? Does the company culture encourage long hours, weekends, and making the office the center of social interaction as well as work?
Using HR and Workforce Management Software for Analytics
- Track key performance indicators and company goals and see what influences their success.
- Use training and learning center-use reports to answer whether extra training helped retention.
- Weigh schedules vs sales to see if there’s a correlation between an employee’s shift length and their number of sales.
- Use the survey function in your software or a collaboration tool like Slack to run frequent informal surveys to gauge workplace health.
- Conduct keyword searches in chat software or company emails to spot flags and trends. Or use keyword searches on resumes of your current workforce to find the most common qualities or experience in your best employees.
- Examine absences to find commonalities—is it a specific department? Manager? Time of year (not just season, but in the ebb and flow of your business)?
- Start succession planning by identifying people who can step into roles vacated by someone who leaves by promotion or termination.
- Optimize shifts by analyzing employee strengths and weaknesses to put together the best mix of talent and personality.
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 later down the line. For example, in the area of churn rate, the Workforce Institute’s 2017 Retention Report found that 75% of reasons for employee turnover are preventable, and it costs nearly 33% of an employee’s annual salary just to replace them. Here are some ways analytics can help.
- Improving Hiring: Who are the best employees for your business, and what factors should you look for in recruiting and interviewing? What benefits and culture attract the best-match candidates? What upcoming organizational changes do you need to plan for now, talent-wise?
- Managing Employees: What do high-performers have in common, and how can managers encourage those traits? What keeps high-performers loyal to the company? What’s the correlation between training and performance? What company policies have improved performance? What factors are affecting absenteeism?
- Organizing Roles: Are there redundant positions? Do you need new ones? (For example, you may find three employees are doing different parts of a task and getting in one another’s’ way. You could reshuffle the project to one employee, whether an existing worker or a new hire.)
- Engaging Employees: What policies affect employee satisfaction overall? How can you improve the office culture to encourage collaboration? Do you need a tool to improve employee communication? How can you keep morale high in stressful seasons?
- Reducing Employee Churn: How healthy is your work culture? Do you lose a lot of employees? When? Why?
Considerations When Gathering and Applying Workforce Analytics
A good workforce study can save you money, but it also takes money to start. As you design your analysis, keep these factors in mind so that you get the most out of your investment.
To get the best results, whether with participation in data gathering or in accepting changes resulting from the study, you need employees to support your efforts. The best way is to understand up-front how the analysis benefits them, and communicate it clearly with enthusiasm.
Along with being clear about the benefits, be open about the process. You don’t need to reveal all the details, but you do need to address any concerns that may affect privacy or regulations like GDPR. In addition, be ready to answer questions. This not only helps with buy-in but also keeps you compliant.
This may seem obvious, as the goal of any workforce analytics is to help make the workplace more productive. But the trend is toward how to improve in-house productivity rather than adding people or positions.
Not all workforce analytics projects require extensive effort or large studies. Before commissioning a study, check what data is immediately available to you. If it can’t answer your question, it could help you refine your study.
Individuals vs Teams
Workforce analytics seems to imply looking at employee data, but you can use the same methods to look at teams—discovering why some are more effective—what composition would be most effective for a project, or whether you should have permanent teams or have employees come together only for specific purposes.
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.