Report summary: The Measurement of Organisational Performance

This project emerged from The Contribution of Skills to Business Performance, Tamkin (2005), which developed a model that examined the relationship between human resource activity and business performance. This project aims to look at how organisations might measure any changes resulting from their investment in training and development.

The research draws on a literature review, a review of practical guides for employers, and other relevant literature that advises how to record and measure organisational impact, an evaluation of existing data sources and interviews with experts to gather feedback on the practicality of these measures for organisations.

This summary begins by setting out the challenges with measuring business performance. The general measures of performance are then discussed before sector specific measures are examined. Lastly, a set of core measures is developed.

Measuring HR investments

Evaluating the impact of investments in people (such as training) helps to justify the costs incurred, validate the intervention as a business tool, and aid the design and selection of future investment methods. However, in practical terms, isolating the impact on the bottom line is complex and therefore many organisations do not try to measure it very rigorously. Most organisations do not measure the impact of training beyond Kirkpatrick level one and two – ie, reactions to the event, and learning attributed to the event.

Evidencing the impact of HR activities on the bottom line is problematic. Organisations do not operate within an economic model where the impact of variables on measures of performance can be assessed one by one. Many internal and external factors are continually competing against each other and in practice are likely to be impossible to disentangle.

The more aligned an intervention is to business objectives, and the better its quality, the greater the impact is likely to be. The impact is also likely to be affected by market conditions, changes in employment and the business cycle (HM Treasury, 2004).

The timeframe in which to measure impact is also a challenge. The effect of an intervention on performance can occur over a long period of time. The longer the period of time that elapses the more difficult it is likely to be to isolate impact from other factors.

Performance measures

The literature contains a range of performance measures. These can be sequenced along Tamkin’s (2005) Chain of Impact model from those that are measures of human resource deliverables, to corporate financial measures. Appropriate measures will vary according to sector, occupation and the nature of the training involved.

Figure 1: The chain of impact

Figure 1: The chain of impact

Source: The Contribution of Skills to Business Performance, IES, 2005

Measures of innovation are commonly used. Innovation might be considered to relate to improved practices, processes, equipment or products. These improvements in turn drive future productivity and profitability. Innovation can be measured using a subjective rating of the rate of product or market innovation (Delery and Doty, 1996), or by measuring change in the number of new or adapted products over a fixed period of time (Shipton et al, 2006). Subjective measures are not likely to be comparable across organisations and will be open to bias. However, they do have one major advantage. HR respondents are often unsure about detailed financial information or are unwilling to supply it, whereas they are usually willing and able to give answers for subjective measures.

Customer satisfaction measures are often used to assess business performance, especially in the service sector where other outcomes are difficult to measure. Customer satisfaction measures may be most appropriate for particular types of training, and training with the aim of changing customer service levels.

When using productivity as a measure it is important to note that the government has identified five main drivers of productivity: investment, innovation, skills, competition, enterprise (Lindsay, 2004). Therefore measures of productivity are likely to be affected by many other influences. In addition, where prices do not reflect the quality and cost of a good, for example where firms have market power, the reliability of measures such as productivity will be affected.

Turnover and sales measures have the benefit of widely-available data that are already collected for other purposes, and benchmarks are available from

Sectoral issues

Many measures of performance may be more relevant to some sectors than others. When measuring business benefits, the choice of measures should be informed by the sector and business-specific context. Blatt and Moynihan (2004) examined the call centre industry and suggested that maximising labour efficiency by dealing with as many calls as possible in a given time might be at odds with maximising quality and customisation. Therefore the number of calls dealt with in a given time period might not be the most appropriate measure in this instance.

In the case of the public sector the goal is usually to maximise the beneficial impact on society. For example, schools aim to deliver a better educated society, and using the budgets they receive, their effectiveness in doing this represents productivity (HM Treasury, 2003). Public sector performance is also affected by external factors. For example, while the health of the population will be in part owing to the NHS, it is also affected by other conditions including diet and shifts in demographics. Historically, increases in government spending have been translated as a proportionate increase in output. In recent years there has been a move to develop a range of indicators which will allow changes in productivity of public services to be captured.


The further along the ‘chain of impact’ and away from the initial intervention, the more difficult it is likely to be to capture and isolate impacts directly attributable to the initial intervention. There is a wide and often divergent range of measures used, some are generic and others sector-specific. The choice of chosen measures is context-specific.

Measurement of organisational performance is not without its challenges. Measures based on accountancy are, to some extent, open to manipulation and therefore may be difficult to compare over time, or between organisations. Many measures do not necessarily capture the quality of a product or service and where part-time work is frequent, then to be comparable, measures need to take into account hours worked.

Overall, a range of measures is likely to be required to capture changes in the quantity and quality of goods and services owing to HR inputs and to capture the variety of variables that can be affected. These should be used with awareness of the other factors that may influence the results, such as market conditions.

From the literature we have developed a set of ‘core’ measures of organisational performance that have general application, to enable benchmarking and comparison across sectors. The ‘core’ set of measures include:

  1. Productivity: Productivity could be measured using Net added value per hour worked or Net added value per worker. However, this measure will be affected by investments other than those in skills and training, for example in capital.
  2. Profitability: Return on assets is a useful measure of profitability, and measures how well a company is using its assets to generate earnings. However, values can vary substantially between companies and between sectors and therefore for wider benchmarking purposes Profit per employee may be more effective.
  3. Quality: Manufacturing organisations could estimate quality using the Number of defects in a given number of products. More generally, customer satisfaction could be used. Exactly how customer satisfaction is measured is likely to vary from organisation to organisation.
  4. Innovation: Sales (£) from new or adapted products or services is a measure that could be used to benchmark innovation across sectors and which takes some account of the success of the innovation.
  5. Staff performance: a range of staff performance measures are detailed in Tamkin (2005). Forthcoming work by IES will test the resonance and ease of use of these measures with employers and could be used to select relevant core measures of staff performance.

Sector-specific studies measuring business performance have tended to focus on traditional industries and specifically manufacturing. Further investigation may be warranted to develop a range of measures which are better suited to the service sector, particularly where work and products are non-routine and client-specific.


Blatt R, Moynihan L (2004), Human Resource Management, Service Quality and Economic Performance in Call Centres, CAHRS Working Paper Series, Working Paper 04-16

Delery J E, Doty D H (1996), ‘Modes of Theorizing in Strategic Human Resource Management: Tests of Universalistic, Contingency, and Configurational Performance Predictions’, Academy Of Management Journal, Vol. 39, No. 4, pp. 802-835

HM Treasury (2003), Public Services: meeting the productivity challenge, HM Treasury

HM Treasury (2004), Productivity 5: Benchmarking UK Performance, HM Treasury

Lindsay C (2004), ‘Labour Productivity’, Labour Market Trends, November 2004, ONS

Shipton H, West M A, Patterson M, and Birdi A (2006), ‘Human Resource Management as a Predictor of Innovation’, Human Resource Management Journal, Vol. 16 (1)

Tamkin P (2005), The Contribution of Skills to Business Performance, DfES publication RW39, August 2005