HR Demand forecasting must consider several factors-both external as well as internal. Among the external factors are competition (foreign and domestic), economic climate, laws and regulatory bodies, changes in technology, and social factors. Internal factors include budget constraints, production levels, new products and services, organisational structure, and employee separations. Demand forecasting is common among organisations, though they may not do personnel-supply forecasting.
The econometrics model analyzes the relationship of a dependent variable with an independent variable. An example of a dependent variable are human resources and an example of an independent variable are sales.
Statistical and mathematical techniques used throughout the econometrics model allows human resource management professionals to estimate future demand with significant accuracy.
HR Forecasting Techniques
HR Forecasting techniques vary from simple to sophisticated ones. Before describing each technique, it may be stated that organizations generally follow more than one technique. The techniques are:
Work Study Technique
Commonly referred to as workload analysis, the work study technique predicts comprehensive activities and production for a specified future time period. The end result of the work study technique is an estimation of the work hours required per unit produced.
When estimating future work hours needed, human resource management professionals must take into consideration-
- Technical difficulties
- Turnover rate
The managerial judgement technique includes the bottom up approach and top down approach. In the bottom up approach, line managers communicate human resource requirements to top management.
Applying the information received directly from their line managers, top management forecasts human resource requirements. The end result of the bottom up approach is a demand forecasting process that incorporates input from various departments.
In the top-down approach of the managerial judgement technique, top management begins the demand forecasting process. After their human resource forecasting is completed, top management sends the forecast to departments for them to analyze and accept.
A combination of the top down and bottom-up approach is referred to as the participative approach. The participative approach allows department heads and top management professionals to forecast human resource requirements collectively.
The participative approach is a human resource planning forecasting technique that encourages collaboration while decreasing communication gaps. For this reason, the participative approach is generally preferable to the top down and bottom up approach.
- Ratio-trend Analysis
This is the quickest HR forecasting technique. The technique involves studying past ratios, say, between the number of workers and sales in an organization and forecasting future ratios, making some allowance or changes in the organization or its methods.
- Regression Analysis
This is similar to the ratio-trend analysis in that forecast is based on the relationship between sales volume and employee size. However, regression analysis is more statistically sophisticated. A firm first draws a diagram depicting the relationship between sales and workforce size.
It then calculates a regression line a line that cuts right through the center of the points on the diagram. By observing the regression line, one can find out the number of employees required at each volume of sales.
- Work-study Techniques
Work-study techniques can be used when it is possible to apply work measurement to calculate the length of operations and the amount of labor required.
The starting point in a manufacturing company is the production budget, prepared in terms of volumes of saleable products for the company as a whole, or volumes of output for individual departments.
The budgets of productive hours are then compiled using standard hours for direct labour. The standard hours per unit of output are then multiplied by the planned volume of units to be produced to give the total number of planned hours for the period.
- Delphi Techniques
Delphi Technique Named after the ancient Greek Oracle at the city of Delphi, the Delphi technique is a method of forecasting personnel needs. It solicits estimates of personnel needs from a group of experts, usually managers. The human resource planning (HRP) experts act as intermediaries, summarize the various responses and report the findings back to the experts.
- Flow Models
Flow models are very frequently associated with forecasting personnel needs. The simplest one is called the Markov model. In this technique, the forecasters will:
- Determine the time that should be covered. Shorter lengths of time are generally more accurate than longer ones. However, the time horizon depends on the length of the HR plan which, in tum, is determined by the strategic plan of the organization.
- Establish categories, also called states, to which employees can be assigned. These categories must not overlap and must take into account every possible category to which an individual can be assigned. The number of states can neither be too large nor too small.
- Count annual movements (also called ‘ flows’) among states for several time periods. These states are defined as absorbing (gains or losses to the company) or non-absorbing (change in position levels or employment status). Losses include death or disability, absences, resignations, and retirements. Gains include hiring, rehiring, transfer, and movement by position level.
- Estimate the probability of transitions from one state to another based on past trends. Demand is a function of replacing those who make a transition.
There are alternatives to the simple Markov model. One, called the semi-Markov, takes into account not just the category but also the tenure of individuals in each category. After all, the likelihood of movement increases with tenure.
Another method is called the vacancy model, which predicts probabilities of movement and the number of vacancies. While the semi-Markov model helps estimate movement among those whose situations and tenure are similar, the vacancy model produces the best results for an organization.
Markov analysis is advantageous because it makes sense to decision-makers. They can easily understand its underlying assumptions.
They are, therefore, likely to accept results. The disadvantages include:
(i) Heavy reliance on past-oriented data, which may not be accurate in periods of turbulent change.
(ii) Accuracy in forecasts about individuals is sacrificed to achieve accuracy across groups.