Workforce Demand Forecasting Techniques
Ward, Dan, Human Resource Planning
Effective workforce planning for specific enterprises involves determining which actions are needed to achieve business objectives, identifying the types and quantities of skills that are necessary to accomplish those actions, determining how those skills may vary from the skills that are currently available, and developing strategies for closing the gaps between today's workforce and the workforce needed to accomplish the business objectives.
Most professional HR departments have well-established practices to handle the identification, acquisition, development, and retention of their workforce. Recent reviews of workforce planning practices reveal, however, that many companies are dissatisfied with their ability to translate business strategies into the specific numbers of employees who would be needed to achieve business objectives. Demand forecasting, the process of determining how many people will actually be needed, was typically reported as the weakest link in addressing workforce requirements.
In theory or in practice, demand forecasting techniques can be grouped into six major categories: Direct Managerial Input, Best Guess, Historical Ratios, Process Analysis, Other Statistical Methods, and Scenario Analysis. This article provides a quick overview of those six techniques.
1. Direct Managerial Input is the most commonly used approach for determining future workforce requirements. This is typically done via an edict that headcount or workforce costs will be a specific number. Today this number is most often expressed as a percentage reduction. There is little analysis of the work effort necessary to meet business objectives. The primary drivers are the desired cash flow and/or adjustments to the company's return ratios such as rate of return, return on capital employed, and discounted cash flow return on investment. This type of approach is easy to calculate and works adequately when a company is substantially overstaffed. The negative is that it is not linked to actual workload requirements and does not distinguish between critical and non-critical skills.
2. A few companies have evolved a Best Guess formalized managerial judgment process. For example, a company formally collects data from each manager and rolls it together for an overall projection. In this process, each manager prepares a forecast of the demand for full-time equivalent employees for the skill groups or job families in their area. The forecast includes (a) the current headcount requirements, (b) a best-guess estimate of the impact of anticipated productivity and technology changes, and (c) the manager's best guess of headcount changes due to anticipated business changes. Summing the current head-count and the anticipated positive and negative changes yields the future estimate.
The strength of this approach is that it provides maximum flexibility to the manager. The major weakness of the best guess approach is that it assumes all managers are willing to spend the time necessary and have the ability to forecast their future work-force needs intuitively.
3. Historical Ratios are used by many companies. Overall headcounts can usually be strongly correlated with other business factors, such as number of items manufactured, numbers of clients served, barrels of oil refined. Some businesses use operating budgets as headcount predictors with high reliability. In terms of total worker requirements, those factors usually provide a good forecast. However, as the mixture of regular employees, temporary workers, and outsourced contractors changes, these historical ratios can change dramatically. Reengineering, reorganization, and restructuring have a substantial impact on the accuracy of these projections. Historical ratios should not be used without allowing for anticipated changes in productivity and alternative staffing strategies.
The major strength of this approach is that it is readily understood and easily developed with simple methodologies such as Excel or Lotus spreadsheets. …