Work force analyses build on staff audits to analyze and forecast the structure of the work force and then match that structure to the requirements of the infrastructure enterprise.
Work force analysis comprises a set of tools that provides a bridge between the details of staff audits, benchmarking, and the wider organization design issues. Those tools, however, still provide only part of the information needed for detailed assessments of downsizing requirements and methods of selection.
Work force analysis is very similar to a human resource planning exercise, but in this context it is focused on the information needed for work force restructuring in preparation for PPI. Detailed work force analysis is particularly useful when a large enterprise is being broken up into new operating units, as illustrated by Brazil Railways in box 3.11. The purpose of work force analysis is to identify staffing requirements at the unit or operational level, and it will help managers in the implementing agency and the enterprise to:
Work force analysis is a staffing planning activity focused on operational units in the context of work force restructuring.
This section summarizes some tools that can be used by managers of the enterprise or the implementing agency to better understand the structure and composition of the work force.
A shared understanding of staff audit and benchmark findings is an essential starting point.
The information gathered from staff audits and benchmarking is a critical baseline for conducting work force analysis. It is essential that this information is disseminated and shared by all enterprise managers who will be involved in work force analysis so that they have a common understanding of staff data. Rigorous debate and discussion on the staff audit and benchmarking data can then be a powerful catalyst for prompting managers to review current staffing assumptions and norms.
Functional reviews ask tough questions, but can reveal whole units or activities that are no longer required.
Work force analysis must be informed by a wider organizational perspective. This may be provided by a corporate plan, a reform plan, or government policy, although in some cases such documents may not exist or may be too vague to be helpful. In those cases one of the most basic tools is a functional review of operating units. This review can be undertaken by managers themselves or be facilitated by consultants, and it can draw on the knowledge of the work force. Workers–and unions– may have perspectives and answers that are beyond the institutional knowledge of management or consultants.
Functional reviews challenge the existing organizational structure and norms by asking some straightforward but difficult questions:
Those questions are simple but getting the answers may be difficult. They also may be highly contentious and fiercely debated. Nonetheless, functional reviews are critical because they can expose whole activities, units, or operations that are redundant. These noncore activities are potential candidates for work force reduction.
In grossly overstaffed enterprises, functional analysis can be implemented as a zero-based approach. Argentina's national oil company, YPF, was so overstaffed that the company and its consultants "decided to eliminate all positions and start from a clean slate while building the new organization frame" (Grosse and Yañes 1998, p. 57). (The organization shrank from about 52,000 employees to less than 6,000; 50,000 employees left with generous severance packages and 3,500 new staff were hired).
There are many other approaches to organizational review, but functional analysis is one that closely relates to the wider reform agendas of many PPI plans.
Ratio analysis can improve managers' understandings of the source of overstaffing and the differences between operational units.
Data from the staff audit can enable detailed analysis, such as that undertaken by Brazil's federal railway (box 3.11). Staffing ratios can be used as internal benchmarks to compare regions, units, or operations. Types of ratio analysis are:
As with benchmarking, it is the process of examining, reviewing, and challenging staffing ratios that can yield the most benefits.
Following unsuccessful attempts to restructure Brazil's federal railway, RFFSA, under the public umbrella, the government included RFFSA in the National Privatization Program in 1992. Implementing the proposed privatization plan required some degree of reduction in RFFSA's employment. Although RFFSA had already made significant progress in reducing its employee headcount, the company's labor productivity continued to be low. RFFSA had reduced its total staff from about 110,000 in 1975 to about 42,000 in May 1995. That reduction led to a substantial increase in labor productivity– from 250,000 to almost 1 million net ton-kilometers per employee. That level of labor productivity continued to be insufficient, however, when compared not only with similar North American companies but also with recently restructured and privatized railways in Argentina and Chile.
The strategy to deal with the excess labor had to be subtle. There were significant differences in labor productivity across RFFSA's regions and uniform cuts across the board would not make sense.
The solution was to come up with new cost reduction plans for each of the six regional areas to be privatized, based on new operational procedures, with redundant activities identified by job categories. This was essentially a very meticulous job that required a very detailed study based on the best international practice. The redundancy estimates were to be conservative to avoid second-guessing what the concessionaire would actually need and avoid forcing the concessionaire to have to rehire "fired" workers as had been the case in Argentina and the United Kingdom. In addition, there had to be enough staff remaining at the company at the time of transfer to the private operator to avoid interruptions in service. To ensure that, a detailed analysis was conducted by the regional managers to assess both the staffing needs for each function and the number of excess workers. By the end of this analysis, RFFSA's management had reasonable estimates of the staff reduction needs in each regional area. In May 1995 this process led to an employment reduction target number of 20,000 workers. Between May and September 1995, almost 2,000 workers voluntarily decided to leave the company, so that by the time the first concession was announced in September 1995 the new reduction target number was 18,047.
Source: Estache, Schmitt de Azevedo, and Sydenstricker 2000.
In large infrastructure organizations, labor productivity reviews can build on benchmark data.
Determining the number of staff needed to undertake a particular task is, in theory, just a simple formula:
This formula, however, does not take into account new technologies, alternative working methods, skills levels, work rate, and the impact of constraints on labor productivity. It is usually not sufficient to rely on such analysis alone because it does not challenge managers to find new ways of improving labor productivity.
In some enterprises the combination of government regulations, accumulated work force numbers, and "custom and practice" may have created wellestablished but now inappropriate labor productivity norms. These can be tackled through:
Age profiles help predict the structure of the work force over time and the numbers of staff leaving or taking early retirement. There are three basic elements to such profiles:
An illustration of age profiling is shown in figure 3.2.Age profile analyses will be particularly important if there have been recruitment surges or freezes that have distorted the "normal" age profile of the work force.
Mechanisms for preparing age profiles will vary from enterprise to enterprise but the underlying calculations are variants of factors such as present strength, expected new recruitment, average rate, and forecast strength over the next few years (see an actual example of such calculations).
The implementing agency can ask enterprise human resource managers to use such profiles to calculate the impact of hiring freezes or the rate of loss of key skill sets. Those calculations can be informed by ratio analyses, such as labor turnover rates, length of service, and cohort analyses.
Age profile approaches can also be disaggregated to assess particular groups of workers, perhaps by gender, particular skills sets, or particular locations.
Work force analysis will not only inform the process of downsizing. In many cases enterprises need to both retrench and recruit at the same time. Many public enterprises have both a surplus of unskilled staff and a deficit in key technical, commercial, or managerial skills (often because they are unable to pay enough to recruit high-quality staff). Forecasting the supply of staff, by category, will be particularly valuable where there are known skill shortages (for example, financial skills, or skills in electronic engineering in a telecommunications enterprise) or where there is evidence of difficulty in recruitment or high levels of out-migration, HIV/AIDS, or other factors.
Supply forecasts will be informed by the skills assessments component of the skills audit. Forecasts will draw on information such as:
To facilitate any subsequent downsizing, these supply forecasts should be matched against categories of workers (grade, level, function, and cohort) to identify any group(s) that should or should not be selected for downsizing.
