Regression Analysis for Human Resource Demand Forecasting

Presented By:Amandeep KaurParamvir SinghGautam Sharda

The statistical technique with an objective to analyze the relationship among quantitative variables.

It is one of the extensively used techniques for forecasting variables.

It involves developing mathematical equations to analyze the relationship between dependant variable and independent variable.

What is Regression Analysis?

How Regression analysis is useful in HR demand forecasting

Regression model would incorporate a rate of change based on the historical productivity improvement trends.

This valuable forecasting technique enables us to plan and execute recruitment, selection, training, and development programs in a planned, proactive fashion to ensure the trained marketing staff are on hand exactly when required by the organization.

These models also can be used to evaluate the required mix of the employee categories.

Regression models are a relatively strong quantitative tool for short, medium and long range forecasting.

Once these models are developed, they can be updated easily and can handle large fluctuations well, when provided with appropriate independent variable.

Advantages of Regression Analysis

It can be implemented ONLY if the Historical data of the organization is available.

If the organization changes its strategies then the historical data will not be effective in order to obtain accurate results.

Disadvantages of Regression Analysis

Technology used for Regression Analysis

SPSS (Statistical program for social sciences)

It is a software which is used for statistical analysis and also regression analysis.

The latest version of the software costs around $2189.

Example of the Regression Analysis

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f(x) = 9.17197452229299 x + 0.808917197452232R² = 0.997556141397425

Chart Title

Y( Number of Marketing Personnel)Y( Number of Marketing Personnel)Linear (Y( Number of Marketing Personnel))Linear (Y( Number of Marketing Personnel))

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