What Is Workforce Analysis? (And Its Importance With Steps)

Understanding the workforce's strengths, weaknesses and future requirements can help human resource (HR) professionals make efficient staffing decisions. Workforce analytics is a formal process of collecting and analysing employee data and turning them into actionable insights. As an HR professional, knowing how to conduct workforce analytics can help you make informed hiring and training decisions. In this article, we explain workforce analysis, its importance, types, key measurements and a sample case study and share a guide to conducting workforce analytics.

What Is Workforce Analysis?

Workforce analysis (also known as workforce planning) is a process organisations use to gather, analyse and interpret internal and external data to evaluate the strengths and weaknesses of their employees and determine the overall organisational growth and health. Workforce planning helps companies derive critical insights that help in achieving workforce success. It is a technique that HR teams use to transform workforce data into actionable points that help plan a business's key performance indicators (KPIs). It helps companies make informed decisions about workforce management, hiring and retention.

Related: What Is Workforce Planning? (Definition And Steps)

Importance of workforce analytics

Workforce analytics helps organisations make faster, smarter, data-driven decisions to optimise the workforce, increase employee satisfaction and performance. It helps a company gain more significant insights into employee performance, productivity, engagement and other employee-related details. You can then use these insights to identify potential workplace improvements, like finding ways to eliminate unproductive work and automating routine tasks. It also helps HR teams better understand workplace dynamics that impact the ability of individuals to work together as a team and achieve shared goals. It helps companies achieve the following:

• Discover and eliminate employee inefficiencies

• Identify and overcome staffing problems

• Address employee knowledge and skill gaps

• Monitor employee engagement

• Optimise workforce scheduling

• Predict and prioritise recruitment

• Enhance employee onboarding, training and offboarding

• Create high-functioning teams that work cohesively

• Increase employee retention and loyalty

• Reduce employee turnover and absenteeism

• Control employee costs

• Design efficient workflows

• Improve individual and overall team performance

• Monitor and enhance employee wellness

• Increase brand value

Related: Workforce Planning: Definition, Types, Importance And Steps

What Does Workforce Analytics Measure?

Workforce analytics can measure any parameter that helps organisations better understand workplace performance. The three primary factors that it tracks are:

• Employee productivity: It measures critical factors like employee work hours, training time, and skill levels to accurately monitor individual and team productivity.

• Employee engagement: Engaged employees are more devoted to the team's goals and the company's mission. Workforce analytics tracks critical engagement metrics like work-life balance, professional milestones, employee satisfaction and attrition rates.

• Organisational adaptability: Tracking and analysing metrics like work styles and organisational hierarchy can help you measure the organisation's ability to adapt to changing market conditions.

Related: How To Calculate Productivity (With Methods And Importance)

3 Types Of Workforce Analytics

Here are three primary subcategories of workforce analytics and how it impacts the workforce planning process:

1. Workforce supply analysis

It is the process of analysing the current workforce as it is. It includes tracking the skill sets, competencies and demographics of employees. Depending on the results of the analysis, you can make projections on the resignations, terminations, promotions and retirements to expect in the next few months or the next quarter. In simple terms, supply analysis identifies how the workforce would look if it continues exactly as it is now.

Example: Assume that 10% of an organisation's employees resign yearly. If the total number of employees in the company is 10,000, approximately 1000 employees quit each year, based on prevailing resignation trends.

Related: What Is HR Analytics And Why Is It Important? (With Types)

2. Workforce demand analysis

Demand analysis is the process of reviewing organisational trends to predict the required future workforce supply. It analyses internal and external data sets to predict future workforce requirements to achieve business KPIs accurately. Demand analysis considers the following factors:

• External labour market

• The projected growth of the company

• Method of sourcing candidates

• Existing employee retention and satisfaction levels

Example: Assume that an organisation decides to launch a new service. By analysing the team sizes of other businesses in the same industry, you can determine the projected workforce requirements for launching this new service.

Related: Employee Engagement Tools (With Features And Examples)

3. Workforce gap analysis

Gap analysis is the process of comparing workforce supply and demand. It analyses the gap between the current workforce and the projected workforce requirements. Gap analysis can reveal whether you require more senior hires or employees with a specific skill set.

Example: In an organisation, 10% of the employees resign annually. The company plans to launch a new product in the next quarter. Gap analysis would reveal that the company would be understaffed to launch the new product successfully. Based on the insights derived from gap analysis, the company can proactively hire new employees to avoid understaffing.

How To Conduct A Workforce Analysis

Here are the basic steps that help you execute workforce planning:

1. Identify a workforce challenge

The first step to workforce planning is identifying a specific workplace challenge you wish to solve. For example, if the company plans to introduce a new service in the next six months, knowing the capabilities of your existing workforce and identifying the number of new employees you require to deliver the proposed service can ensure that the new service is a success. Here are a few questions that you can ask yourself during this stage:

• Does the current workforce have the skills and core competencies to launch the new product or service?

• What training do they require to bridge any gaps in skills?

• How many more employees do you require to deliver the new product or service?

• How do you plan to recruit new employees with the required skills?

• What are your strategies to attract new employees?

• How do you plan to retain the existing workforce?

• Do you expect any other workforce changes for the new product or service?

2. Collect relevant data

Once you have identified the workforce challenge, the next step is to gather relevant data to address this specific issue. You can collect this data on your own or with the help of the HR team or a third-party data provider. You can use any of the following data sources to collect information:

• Workforce demographic data

• Performance data

• Skills data

• Employee survey results

• Training completion data

3. Select the analysis method

Once you have collected relevant data, the next step is to determine a suitable data analysis method. You can request the data analysis team's help to evaluate the collected data. Alternatively, you can upskill the HR team in data analytics to ensure they can independently handle workforce planning. Here are some of the popular data analysis methods:

• Correlation analysis: It studies the strength of a relationship between two variables. For example, low employee engagement might result from improper training and improving the latter can help you overcome the former.

• Diagnostic analysis: It analyses the root causes of a failure to avoid repeating them. For example, if you notice a drop in employee retention rates right after promotions, diagnostic analysis can help you discover why this is happening.

• Predictive analysis: It uses machine learning algorithms and historical data to predict the likelihood of future outcomes. By analysing past business data, you can make more accurate forecasts.

• Prescriptive analysis: It relies on historical data. Generally, companies use prescriptive and predictive analysis to determine the best course of action to achieve their goals.

• Trend analysis: It is the process of comparing data over a period to identify trends and use them to make future decisions. For example, if productivity drops after lunch, you can use these findings to determine the cause and implement the right strategies to improve post-noon productivity.

Related: 10 Valuable Data Analysis Skills

4. Analyse and showcase the results

Once you have chosen the appropriate analysis method, the next step is to implement your preferred data analysis strategies and present the results to senior management, business leaders and other stakeholders. You can showcase the findings as a report or presentation. Visual tools like bar graphs, pie charts and infographics can help you present the information clearly and concisely in an easy-to-understand format.

Related: What Is Data Presentation? (Definition, Types And How-To)

5. Decide appropriate actions based on the insights

The final step of workforce analytics is determining an appropriate course of action based on the insights. For example, if the results indicate a requirement for ten machine learning engineers over the next six months, you can start planning your recruitment strategies immediately. You could upskill existing engineers on your team with machine learning skills or you might hire new team members and decide how to integrate them into the current team.

Sample Case Study Of Workforce Analytics

Here is a sample case study to consider:

Gobo is a software company with high employee turnover. The yearly employee resignation was 5% higher than industry standards. Workforce analytics helped them identify the critical factors that impact employee attrition. For example, they discovered that employees with daily commutes of more than one hour were more likely to resign. Also, teams with over 15 people had higher attrition due to low employee satisfaction. Using the insights gained from workforce analytics, the company began offering flexible working and reduced maximum team sizes to 12 employees. As a result, the company could minimise employee resignation to below 2%.

Please note that none of the companies, institutions or organisations mentioned in this article are associated with Indeed.