Italian and UK Manufacturing Compared: Research Has Shown Significant Differences between the Two Countries in Rates of Absenteeism and in the Involvement of Employees in Problem Solving Groups. the Implications for Managers Are Clear
Grando, Alberto, Szwejczewski, Marek, Goffin, Keith, European Business Forum
Although the Italian economy has seen a steady growth in the importance of the service sector, manufacturing still plays a key role in the economy. It employs 32 per cent of the active population and accounts for about 33 per cent of the country's gross national product. For this reason, the performance of Italian manufacturing plants relative to their international counterparts is of considerable domestic importance, as well as highly relevant for those interested in wider European comparisons and benchmarks.
This article reports on a research project that looked at the performance of manufacturing plants in Italy, and in the UK. By using data from the International Best Factory Awards Programme, it was possible to compare the two countries' manufacturing plants in a number of areas, including production lead times, flexibility, labour trends and innovation.
Data for the research was taken from the International Best Factory Awards programme (IBFA)--also known in the UK as 'Management Today Best Factory Awards in association with Cranfield School of Management'. The awards started life in the UK, and have been running in their current form since 1992. The purpose of the awards is to recognise and reward manufacturing excellence. The programme was extended to Germany in 1996 to enable international comparisons to be made, and was subsequently launched in Italy in 1998.
The awards are open to any manufacturing plant. A plant is defined as a relatively self-contained unit with its own management staff, which can be identified either by separate facilities, by separate products or by separate management structure. To enter the competition the plant has to complete a detailed 16-page questionnaire. The information collected in the questionnaire covers descriptive data (e.g. cost structure) management policy data (e.g. market positioning) and performance data (e.g. delivery reliability). The questionnaire focus is on obtaining objective, verifiable data on key manufacturing variables. The approach has enabled an extensive database to be created against which individual plants can be judged. In addition, it allows for international comparisons to be carried out. The data provided by the plants is treated as confidential.
The plants have two incentives to encourage them to complete the questionnaire. First, there is the possibility of winning an award (for example, 'best engineering plant'), and second, all plants that enter receive a 'personalised' benchmarking report that compares their performance against other plants in their industry sector.
Several features of the IBFA approach ensure that the data between the three countries is comparable and that a high response rate is achieved. The programme, for example, uses identical collection methods in Italy, Germany and the UK and focuses on obtaining verifiable quantitative data on key manufacturing variables. This ensures that if a plant is short-listed for an award, a team of judges will visit it and verify the data: plant management understands that it may be cross-examined on the data and required to substantiate its entries. The IBFA questionnaire has been extensively tested in the UK and before being used in Germany and Italy was translated by a native speaker and reviewed by academics and potential users.
Comparison of Italian/UK manufacturing
So how do Italian manufacturing plants compare with their UK counterparts? To investigate this question it was decided to compare the performance of Italian and UK engineering plants. The sample that was used in the research contained 45 Italian engineering plants (which had completed the questionnaire in 1998 and 1999) and 51 UK engineering plants (which had completed the questionnaire in 1998). The two groups of plants were compared on several variables, grouped into five categories; the comparison is summarised in Table 1, left. …