According to the PCI-FDI 2017 report, 69% of FDI enterprises in Vietnam faced difficulties in recruiting skilled technical staff. This may be indirectly linked to challenges in forecasting human resource demand due to insufficient labor skills data. Therefore, it is essential to understand how to accurately forecast human resource demand, as explained in the following article:
What Is Human Resource Demand Forecasting?
Human resource demand forecasting is the process of using available data to predict how many employees a company will need, with which skills, in which positions, and at what time. This enables businesses to create comprehensive workforce plans, ensuring they always have qualified employees to complete organizational tasks effectively.
There are two main types of forecasting you should know:
- Short-term (less than 1 year):
Suitable for industries that require seasonal or rapidly changing labor needs, such as seasonal manufacturing. - Long-term (3–7 years):
Closely aligned with the company’s overall business strategy. This type is often applied to key positions such as senior management or accounting departments, where long-term talent development planning is essential.
Classical Methods of Human Resource Demand Forecasting
Methods for Short-Term Forecasting
In this approach, calculations are based on the actual workload. For example:
Task and Workload Analysis
Identify the tasks that need to be completed and calculate the required labor hours using conversion factors or staffing standards (e.g., how much work one employee can complete in a day). The company then converts this into the number of employees needed for each job category.
Productivity-Based Method
Formula: D = Q / W
Where:
- D = labor demand
- Q = planned total output
- W = average labor productivity
This means that if production volume increases but productivity does not, additional staff will be required.
Staffing Standard Method
This method is based on clear job descriptions and divides the unit’s workload by the standard output per employee.
Example: If a team needs to process 100 orders per day and each employee can handle 20 orders, the company will need 5 employees.
These methods are highly practical when quick adjustments are required, such as when a company receives unexpected orders.
Methods for Long-Term Forecasting
This approach is divided into quantitative methods (data- and mathematics-based) and qualitative methods (based on human judgment).
Trend Analysis
Using available data, businesses plot charts to forecast future situations. For instance, if the number of sales staff has historically increased with annual revenue, you can project demand for the following year. However, this method is relatively simple and less accurate when there are major changes.
Averaging Method
Forecast future demand by averaging human resource needs from previous years. This is suitable for stable businesses.
Correlation and Linear Regression Analysis
A more advanced approach that uses mathematical models to examine the relationship between workforce demand and factors such as production output, revenue, or household income.
Formula: y = f(X1, X2, …)
- y = workforce demand
- X1, X2, … = variables from historical data
Regression analysis is highly accurate as it considers multiple factors, but it requires large datasets and can be complex.
Qualitative Methods
Gather insights from experienced managers and experts through group discussions. The strength of this method lies in its diverse perspectives, though it can be influenced by personal bias.
Delphi Method
- Similar to expert consultation, but in this case, experts provide independent opinions through written responses or individual consultations to avoid group bias. Their inputs are then aggregated, making the results more objective.
Applying AI and Data Analytics in Human Resource Demand Forecasting
In the era of the Fourth Industrial Revolution, everything is transforming rapidly—including human resource management. Instead of manually calculating forecasts with outdated Excel spreadsheets, AI (Artificial Intelligence) and Data Analytics can now help predict workforce demand with greater accuracy, speed, and efficiency. Here is how they work:
- AI learns from data to identify patterns and trends for predictions, while Data Analytics collects and analyzes massive amounts of information—from internal data such as employee turnover rates and performance metrics, to external data such as labor market trends and economic shifts. Combined, they automate the forecasting process, minimize human error, and save time.
- Through predictive analytics, systems can analyze employee records, recruitment trends, and even global economic data to forecast how many new employees will be needed in the next 6–12 months. Moreover, AI can provide early warnings about rising turnover rates in specific departments, enabling timely recruitment planning.
- AI also helps businesses automatically screen CVs, identify potential candidates based on historical data, and even predict cultural fit within an FDI environment. Meanwhile, Data Analytics leverages data from platforms like LinkedIn or industry reports to forecast emerging “hot” skills—such as digitalization skills for smart manufacturing.
Comprehensive Solutions from KMC: Eliminating the Risk of Strategic Talent Shortages
With 17 years of experience supporting numerous FDI enterprises—particularly Japanese-invested companies—KMC understands the unique challenges you may face, such as:
- Difficulties in recruiting senior-level personnel who meet international standards
- Language barriers and cultural differences in management
- Intense competition for talent from multinational corporations
That is why our professional recruitment services are designed to:
- Thoroughly analyze your company’s requirements and expectations
- Recruit across multiple channels to maximize the chance of finding the right candidates
- Carefully evaluate candidate competencies through structured interviews and assessments
From there, KMC delivers the most effective recruitment strategies along with high-quality candidate recommendations.
Are you concerned about calculating workforce demand? There are several effective and accurate forecasting methods mentioned above—start applying them now. Alternatively, you can leverage AI and Data Analytics for even greater precision.
