Human capital is the most valuable asset a company possesses. Human resource planning is a process used to predict future human resource requirements. Human resource forecasting, also known as HR forecasting, generally utilizes past sales data in order to more accurately estimate future staffing needs.
HR forecasting begins with performing comprehensive job analyses and estimating employee output levels. Factoring in the labor market and labor supply helps with both human resource planning and resource management optimization.
There are both quantitative and qualitative approaches for forecasting human resource demands. While quantitative methods are heavily reliant on mathematical and statistical analysis, qualitative forecasts generally depend more on managerial judgement techniques.
Both internal and external factors must be considered during the HR forecasting process. An example of an internal factor is the release of a new product, and an example of an external factor is a technological advancement.
While some businesses may choose a single demand forecasting technique, other businesses may utilize multiple forecasting techniques collaboratively. Regardless of which forecasting processes are used, it is crucial for human resource management professionals to also consider their own expertise and intuition.
Methods of Demand Forecasting
Demand forecasting techniques used for human resource planning are broadly categorized into two types:
- Qualitative Techniques
- Quantitative Techniques
Qualitative Techniques
These rely on collecting data on the buying behaviour of consumers from experts or through conducting surveys in order to forecast demand. These techniques are generally used to make short-term forecasts of demand.
Qualitative techniques are especially useful when historical data is not available—for example, during the introduction of a new product or service. These techniques are based on experience, judgment, intuition, conjecture, etc.
Survey Methods
Survey methods are the most commonly used methods of forecasting demand in the short run. This method relies on the future purchase plans of consumers and their intentions to anticipate demand.
Thus, in this method, an organization conducts surveys with consumers to determine the demand for their existing products and services and anticipate future demand accordingly.
Opinion Poll Methods
Opinion poll methods involve taking the opinion of those who possess knowledge of market trends, such as:
- Sales representatives
- Marketing experts
- Consultants
Quantitative Techniques
Quantitative techniques usually make use of statistical tools. In these techniques, demand is forecasted based on historical data. These methods are generally used to make long-term forecasts of demand.
Unlike survey methods, statistical methods are cost-effective and reliable, as the element of subjectivity is minimum.
1. Time Series Analysis
Also known as the trend projection method, this is one of the most popular methods used by organizations for predicting demand in the long run. A time series refers to a sequence of values of a variable (called trend) at equal time intervals.
Using trends, an organization can predict the demand for its products and services for the projected time.
Components of Time Series Analysis:
- Trend Component: Accounts for the gradual shift in the time series to a relatively higher or lower value over a long period of time.
- Cyclical Component: Accounts for the regular pattern of sequences above and below the trend line lasting more than one year.
- Seasonal Component: Accounts for regular patterns of variability within specific time periods (e.g., a year).
- Irregular Component: Accounts for short-term, unanticipated, and non-recurring factors that affect time series values.
2. Smoothing Techniques
Used when time series lacks significant trends. These techniques help eliminate random variation from historical demand, identifying patterns and levels that help estimate future demand.
Common Smoothing Methods:
- Simple Moving Average Method: Calculates the mean of average prices over a time period and plots these on a graph.Example: A 5-day simple moving average is the sum of 5 values divided by 5.
- Weighted Moving Average Method: Averages based on a predefined number of time periods, all having the same importance.Example: A 4-month average where each month contributes 25%.
3. Barometric Methods
These are used to speculate future trends based on current developments and are also called the leading indicators approach. Many economists use barometric methods to forecast business activity trends.
Types of Indicators Used:
- Leading Indicators: Predict future events based on past occurrences. Example: Data on working women used to forecast demand for working women's hostels.
- Coincident Indicators: Move simultaneously with current events. Example: Employment rates, unemployment, per capita income.
- Lagging Indicators: Follow changes and help interpret economic direction. Example: Inflation and unemployment levels.
4. Econometric Methods
These use statistical tools combined with economic theory to assess various economic variables like price changes, income levels, and policy changes for demand forecasting.
Forecasts made using econometric methods are more reliable than any other forecasting method.
An econometric model may involve:
- Single Equation Regression Analysis
- System of Simultaneous Equations
Regression Analysis
A statistical tool used to estimate unknown values of one variable based on known values of another variable. More statistically sophisticated than ratio-trend analysis.
A firm may:
- Plot a diagram of sales vs. workforce size.
- Calculate a regression line that cuts through the center of data points.
- Use this to estimate required employees for different sales volumes.
Regression Equation Example:
y = A + Bx
Where:
y= Manpower requirementx= Production outputA= Minimum requirement (constant)B= Regression Coefficient (slope)
Advantages of Regression Analysis:
- Estimates dependent variables from known independent variables.
- Identifies errors involved in estimation using the regression line.
- Measures the degree of association between two variables.
Work Study Techniques
These are applied where work measurement is possible to calculate the length of operations and required labour.
Steps in Manufacturing HR Forecasting:
- Start with the production budget (volume of salable products).
- Use budgets of productive hours per unit.
- Multiply with planned volume to get total planned hours.
- Divide by actual working hours per operator to get operator count.
- Factor in absenteeism and idle time.
Work study techniques for direct workers can be combined with ratio-trend analysis to forecast for indirect workers, by establishing ratios between these categories.
The same logic can be extended to any category of employees.
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