Limitations of Human Resource Planning

Human resource planning is said to consist of three clear steps:

● Forecasting future people needs (demand forecasting). 

● Forecasting the future availability of people (supply forecasting). 

● Drawing up plans to match supply to demand.

But as Casson (1978) pointed out, this conventional wisdom represents human resource planning as an ‘all-embracing, policy-making activity producing, on a rolling basis, precise forecasts using technically sophisticated and highly integrated planning systems’. He suggests that it is better regarded as, first, a regular monitoring activity, through which human resource stocks and flows and their relationship to business needs can be better understood, assessed and controlled, problems highlighted and a base established from which to respond to unforeseen events; and second, an investigatory activity by which the human resource implications of particular problems and change situations can be explored and the effects of alternative policies and actions investigated.

He points out that the spurious precision of quantified staffing level plans ‘has little value when reconciled with the complex and frequently changing nature of manpower, the business and the external environment’. The typical concept of human resource planning as a matter of forecasting the long term demand and supply of people fails because the ability to make these estimates must be severely limited by the difficulty of predicting the influence of external events. There is a risk, in the words of Heller (1972), that ‘Sensible anticipation gets converted into foolish numbers, and their validity depends on large, loose assumptions.’ 

Human resource planning today is more likely to concentrate on what skills will be needed in the future, and may do no more than provide a broad indication of the numbers required in the longer term, although in some circumstances it might involve making short term forecasts when it is possible to predict activity levels and skills requirements with a reasonable degree of accuracy. Such predictions will often be based on broad scenarios rather than on specific supply and demand forecasts.