ENTREVISTA TUTORA CARLA

Forecasts of internal supply are based primarily on labour turnover and the movement of people within the organisation. As with demand, the process for forecasting supply uses a combination of quantitative and qualitative techniques.

Measuring labour turnover – quantitative methods

The most common method of measuring labour turnover is to express leavers as a per-centage of the average number of employees. The labour turnover index is usually calculated using the following formula:

Number of leavers in a specified period

–––––––––––––––––––––––––––––––––––––––––––– × 100%

Average number employed in the same period

This measure is used most effectively on a comparative basis and frequently provides the basis for external and internal benchmarking. Labour turnover can vary significantly between different sectors and industries; for example, a recent survey into labour turnover (CIPD, 2002a) reports that the average turnover rate in the UK is 26.6 per cent but this varies from 56 per cent in wholesale and retail to 11 per cent in transport and storage. There is no single best level of labour turnover so external comparisons are essential to gauge whether rates in an organisation are out of line with others in the same industry or sector (IRS, 2001a). However, even organisations with lower than average turnover rates can experience problems if people have left from critical jobs or from posts that are difficult to fill. Conversely, high turnover is not necessarily problem-atic. In circumstances where an organisation is seeking to reduce costs or reduce the 164 Chapter 5 · Human resource planning

numbers employed a high turnover rate might prove very useful (Sadhev et al., 1999).

The main limitation of the labour turnover index is that it is a relatively crude measure that provides no data on the characteristics of leavers, their reasons for leaving, their length of service or the jobs they have left from. So, while it may indicate that an organi-sation has a problem, it gives no indication about what might be done to address it.

Example:

Company A has 200 employees. During the year 40 employees have left from different jobs and been replaced. The turnover rate is 20%.

Company B also has an average of 200 employees. Over the year 40 people have left the same 20 jobs (i.e. each has been replaced twice). The turnover rate is also 20%.

Limitations about the location of leavers within an organisation can be addressed to some extent by analysing labour turnover at department or business unit level or by job category. For example, managers generally have lower levels of resignation than other groups of employees (IRS, 2001a). Any areas with turnover levels significantly above or below organisational or job category averages can then be subject to further investiga-tion. Most attention is levelled at the cost and potential disruption associated with high labour turnover. CIPD survey data (2002a) estimates the average cost per leaver to be

£3933 a year, increasing to £6086 for managers. However, low levels of labour turnover should not be ignored as they may be equally problematic.

Low labour turnover can cause difficulties as a lack of people with new ideas, fresh ways of looking at things and different skills and experiences can cause organisations to become stale and rather complacent. It can also be difficult to create promotion and development opportunities for existing employees.

Nevertheless, many organisations are keen for some levels of stability. While the labour turnover index focuses on leavers, the stability index focuses on the percentage of employees who have stayed throughout a particular period, often one year. This there-fore allows organisations to assess the extent to which labour turnover permeates the workforce. The formula used to calculate stability is:

Number of employees with 1 year’s service at a given date

–––––––––––––––––––––––––––––––––––––––––––––––––––––––– × 100%

Number employed 1 year ago

This can be a useful indicator of organisational stability but does require a pre-set deci-sion about a relevant period for which it is important to retain staff. To return to our earlier example:

Company A has 160 employees with more than one year’s service and has a stability rate of 80%.

Company B has 180 employees with more than one year’s service and has a stability rate of 90%.

As with demand forecasting, labour turnover and stability indices are frequently used to project historical data into the future. So, for example, if an organisation identifies an annual turnover rate of 8 per cent it may build this into future projections of avail-able supply. Alternatively, managerial judgement may predict a reduction or an increase in turnover rates in the light of current circumstances and forecasts can be adjusted accordingly.

More data on the length of service of leavers can be provided through the census method. This is essentially a ‘snapshot’ of leavers by length of service over a set period, often one year. Length of service has long been recognised as an influential factor in labour turnover. Hill and Trist (1955) identified three phases in labour turnover, the ‘induction

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What are the key problems associated with low labour turnover?

Stop and

think

crisis’, ‘differential transit’ and ‘settled connection’. People are more likely to leave during the first few months, as the relationship between the individual and the organisation is unsettled and insecure, and less likely to leave the longer they are in the organisation. The census method can help to identify patterns of leavers and any key risk periods.

Another way of investigating the relationship between labour turnover and length of service is to consider the survival rate, i.e. the proportion of employees recruited in a specific year who are still with the organisation at a certain later date. So, for example, plotting the survival rate of a cohort of 30 graduate trainees might show that 12 remain with the organisation after five years, giving a survival rate of 40 per cent. It is also common to measure the half-life of a cohort, i.e. the time taken for the cohort to reduce to half its original size. Both survival rates and half-life measures can be useful for iden-tifying problem periods and for succession planning purposes.

The major drawback with all quantitative methods of turnover analysis is that they provide no information on the reasons why people are leaving. So, for example, the census method may show that the highest proportion of people leave in the first six months but the information on its own does not show whether this is due to poor recruitment or induction practices, the nature of the job, management style or other fac-tors. Thus, quantitative analyses can help to highlight problems but they give those responsible for planning no indication about how these problems might be addressed.

Measuring labour turnover – qualitative methods

Investigations into reasons for turnover are usually undertaken via qualitative analysis.

Popular methods include exit interviews and leaver questionnaires. Exit interviews are normally conducted soon after an employee has resigned. The benefits of exit inter-views are that they can investigate reasons for leaving, identify factors that could improve the situation in the future and gather information on the terms and conditions offered by other organisations. Generally, exit interviews collect information on the fol-lowing (IRS, 2002a):

● reasons for leaving;

● conditions under which the exiting employee would have stayed;

● improvements the organisation can make for the future;

● the pay and benefits package in the new organisation.

There can also be a number of problems. The interview may not discover the real reason for leaving, either because the interviewer fails to ask the right questions or probe suffi-ciently or because some employees may be reluctant to state the real reason in case this affects any future references or causes problems for colleagues who remain with the organisation, for example in instances of bullying or harassment. Conversely, some employees may choose this meeting to air any general grievances and exaggerate their complaints. Some organisations collect exit information via questionnaires. These can be completed during the exit interview or sent to people once they have left the organisa-tion. They are often a series of tick boxes with some room for qualitative answers. The questionnaire format has the advantage of gathering data in a more systematic way which can make subsequent analysis easier. However, the standardisation of questions may reduce the amount of probing and self-completed questionnaires can suffer from a low response rate.

Reasons for leaving can be divided into four main categories:

● voluntary, controllable – people leaving the organisation due to factors within the organisation’s control, e.g. dissatisfaction with pay, prospects, colleagues;

● voluntary, uncontrollable – people leaving the organisation due to factors beyond the organisation’s control, e.g. relocation, ill-health;

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● involuntary – determined by the organisation, e.g. dismissal, redundancy, retirement;

● other/unknown.

Attention is usually concentrated on leavers in the voluntary, controllable category as organisations can do something to address the factors causing concern. However, dis-tinctions between controllable and uncontrollable factors can become blurred. For example, in some instances, advances in technology and greater flexibility can facilitate the adoption of working methods and patterns to accommodate employees’ domestic circumstances, while the ‘reasonable adjustments’ required under the Disability Discrimination Act can reduce the numbers of people forced to leave work on health grounds. The involuntary category is also worthy of attention as high numbers of con-trolled leavers can be indicative of organisational problems, e.g. a high dismissal rate might be due to poor recruitment or lack of effective performance management, while a high redundancy rate might reflect inadequate planning in the past.

While exit interviews or leaver questionnaires can provide some information about why people are leaving, they do not necessarily get to the root of the problem. For example, someone might say that they are leaving to go to a job with better pay but this does not show what led the person to start looking for another job in the first place. In order to produce human resource plans that address labour turnover problems, organi-sations need to differentiate between ‘push’ and ‘pull’ factors. The former relate to factors within the organisation (e.g. poor line management, inadequate career opportu-nities, job insecurity, dissatisfaction with pay or hours of work) that weaken the psychological link between an individual and their employer (IRS, 2001a). Once an indi-vidual has decided to look for another job they are likely to base their decision on ‘pull’

factors, i.e. the attractions of the new job or organisation in relation to their existing cir-cumstances. A report from the HR benchmark group (cited in IRS, 2002a) listed the top five factors affecting an employee’s decision to stay or leave an organisation as:

● the quality of the relationship with their supervisor or manager;

● an ability to balance work and home life;

● the amount of meaningful work they do – giving a feeling of making a difference;

● the level of cooperation with co-workers;

● the level of trust in the workplace.

One way to identify the key ‘push’ factors is to conduct attitude surveys within the organisation. Over half of respondents to a recent survey (IRS, 2002a) use surveys to gather data that can be used to address labour turnover. Attitude surveys have an advan-tage over exit interviews and leaver questionnaires in that they can identify potential problems experienced by existing employees rather than those that have already decided to leave. This means that any response can be proactive rather than reactive. However, it also means that organisations can make problems worse if they do not act on the find-ings. ‘Telling employees that an organisation cares enough to get their opinion and then doing nothing can exacerbate the negative feelings that already existed, or generate feel-ings that were not present beforehand’ (IRS, 2002a: 40).

The final method to investigate labour turnover to be discussed here is risk analysis.

This involves identifying two factors: the likelihood that an individual will leave and the consequences of the resignation (Bevan et al., 1997). Statistically, people who are younger, better qualified and who have shorter service, few domestic responsibilities, marketable skills and relatively low morale are most likely to leave (IRS, 2001b). The consequences of any resignations are likely to be determined by their position in the organisation, performance levels and the ease with which they can be replaced. The risk analysis grid (Bevan, 1997) shows how the two factors can be combined (Figure 5.2).

This then enables the organisation to target resources or action at the people it would be most costly to lose.

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The traditional approach to HRP

Within human resource planning literature most attention is concentrated on forecasts of people joining and leaving the organisation but internal movement is also a key factor in internal supply. Techniques to analyse movement of employees within an organisation are potentially more sophisticated than the techniques for analysing wastage rates but the most sophisticated tools, e.g. Markov chains and renewal models, are rarely used (Torrington et al, 2002). A simpler approach is to track employee movement to identify patterns of promotion and/or lateral mobility between positions as well as movement in and out of the organisation or function, see Figure 5.3.

In many respects forecasting is the key stage of traditional human resource planning.

A combination of quantitative and qualitative methods can be used to determine the organisation’s future requirements and the availability of human resources. Therefore much hinges on the accuracy of forecasting but there are a number of potential prob-lems that can affect the reliability of any predictions. The first issue here is the difficulty of relying on past data to cope with a volatile and uncertain environment. Recent exam-ples of significant discontinuities include the foot and mouth epidemic in the UK and the terrorist attacks in New York on 11 September 2001. Both events were largely unfore-seen and both had significant impact on certain industries, e.g. foot and mouth affected farming and tourism in the UK and the terrorist attacks severely affected the airline industry. Other problems can include the lack of reliable data, the manipulation of data for political ends and the low priority given to forecasting in many organisations.