Due to the heavy emphasis in HRP on forecasting and simulation models, technique-oriented models are perhaps the most common group of models found in the literature on HRP. Yet, there has been a great deal of criticism levied against these models because they have been rejected by a number of practitioners in the field as too sophisticated and too complex to be useful tools for managers.
The most commonly used techniques involve quantitative analysis of numbers of employees and man-hour projections through the use of time series models, regression models, balancing equations and stochastic models.
These models as follows:
1. Time series models are used to project seasonal manpower requirements. These models analyze recurring manpower requirements over time but are not particularly useful? analyzing probable outcomes of human resource policies or programs.
2. Regression models involve an analysis of labor demand and the appropriate skill mix between line and support staff groups. This analysis is also used to determine the time phasing for various skills utilization for project management teams.
3. Balancing equations, like regression models, include determinants related to manpower levels. These equations are used to project future levels of productivity, output, and retention and the impact these factors will have on manpower requirements.
4. Stochastic models and Markov chains along with simulation models have recently become popular in human resource planning.
These models are used to
(1) forecast future human resource requirements,
(2) analyze the impact of proposed changes in policy and programs,
(3) design and structure systems that will balance the flow of internal human resource supplies and requirements, and
(4) design HRIS capabilities suitable for policy analysis and planning. Another useful application of the stochastic model identifies the anticipated number of managers in a given position for any future period and the expected background of these persons in terms of previous positions held.
Also, a projected change in organizational structure can be analyzed against various career development policies. For the individual manager, the stochastic model is useful in assessing and evaluating the outcome of different career alternatives.