Human capital is the most important asset a company has. The process of human resource planning helps to forecast future needs. Human resource planning is also called HR forecasting. It uses past sales data to better predict future staffing requirements. HR forecasting starts with job analysis and estimating employee output levels. The ability to factor in labor market and supply is essential for both resource planning and optimization.
Forecasting the demand for human resources can be done in both quantitative and qualitative ways. Quantitative forecasts are heavily dependent on statistical and mathematical analysis. Qualitative forecasts, however, rely more on managerial judgment techniques. During the HR forecasting process, it is important to consider both internal and external factors. A new product’s release is an example of an internally important factor. Technological advancements are an external factor. Some businesses might choose to use a single forecasting method, while others may employ multiple techniques. It doesn’t matter which forecasting process is used, it is important for human resource managers to consider their own intuition and expertise.
For human resource planning, there are many demand forecasting methods. The following are some common forecasting methods used to estimate human resources demand:
- Managerial Judgment
There are two approaches to managerial judgment: the top down and bottom up. The bottom-up approach is where line managers communicate the human resources requirements to top management. Top management uses the information from their line managers to forecast human resource needs. The bottom-up approach results in a demand forecasting process which incorporates input from different departments. Top management initiates the demand forecasting process using the top-down approach to the managerial judgment technique.
Once their human resource forecasting has been completed, the top management forwards the forecast to the departments for them to review and accept. The participative approach is a combination of both the top-down and bottom-up approaches. Participative approaches allow top managers and department heads to jointly forecast human resources needs. Participative approach to human resource planning is a technique that encourages collaboration and reduces communication gaps. The participative approach is preferred to the bottom-up and top-down approaches.
- Work Study Technique
The work study technique, also known as workload analysis or simply “workload analysis”, predicts the future activities and production. The work study technique estimates the amount of work required to produce each unit.
Human resource managers must consider the following when estimating future work hours.
- Technical problems
- Turnover rate
The more skilled the professionals in human resource management who are performing the work study technique, the more accurate they will be at estimating the resources needed.
- Econometrics Models
The econometrics modeling analyzes the relationship between a dependent variable and an independent variable. Human resources are an example of a dependent variable, while sales is an example of an independently variable. The econometrics model uses mathematical and statistical techniques to allow human resource managers to accurately forecast future demand.
- Delphi Technique
The Delphi technique utilizes expert feedback in order to predict the human resources requirements that are necessary in the future. Human resource management professionals gather responses and develop reports that comprehensively summarize expert opinions. The process of collecting feedback and creating reports is continued until a unified consensus is reached between the experts. For this reason, the Delphi technique can be a long term process if experts do not agree.
- Regression Analysis
Regression analysis uses statistical methods to identify trends in data. Recognizing trends can help business professionals better understand their human resources requirements and optimize the labor supply. Regression analysis examines the relationship between a predictor or target. Also known as independent and dependent variables, Businesses are trying to predict and gain more insight into the dependent variable. Independent variables include factors that could or might not have an impact on the dependent variable. Remember that dependent variables can never be predicted with 100% accuracy by independent variables.