National GDP per Capita and Productivity: The Role of Industrial Engineering

The Bank of Israel (BOI) states that “in a competitive environment, wages are consistent with labor productivity over the long term, and can rise only if productivity increases”. National Gross Domestic Product (GDP) per Capita and Labor Productivity are significantly behind the USA and OECD, and have been there for a long time. This is explained by low rate of (physical) capital investment, decline in the government share of investment in R&D, and low investment in technological education. The suggested directions for increasing productivity include adopting advanced technologies, diverting budget to R&D, expanding professional training programs, enhancing scientific studies in secondary schools and colleges, improving the business environment, and implementing infrastructure reforms.

The last three years exhibit national GDP per Capita at 85% of OECD and 61% of USA, Labor Productivity at 76% of OECD and 55% of USA, while Labor Utilization 12% higher than OECD and 11% higher than USA. Following the conditional convergence theory, poorer economies incomes tend to grow at faster rates than richer economies. Thus, all economies are expected to converge in terms of income per capita, after which they should all grow at similar rates. Yet, comparing national data with OECD illustrates this theory has not materialized.

National data exhibits that industrial sectors with high export rate (e.g. high-tech) perform at higher productivity than sectors with low export rate, explained by global market competition. The USA economy experiences slower productivity increase rate in the service sectors, explained by the characteristics of service, such as labor intensive tasks, focused on individuals, performed by high professionals, difficult to automate and difficult to evaluate quality. Moreover, the service sector employment in USA continues to grow exceeding 80% while manufacturing sector is at 10%. Israel’s employment by sectors is similar, where service also exceeds 80% and manufacturing slightly above 10%.

Scientific management’s definition of productivity is the ratio of outputs (goods and services) to one or more inputs (e.g. labor). Productivity measurement can be used at the national, industry or firm levels. Productivity improvement is driven by:

• Labor (10%) - education and training, workforce reduction, and social overhead
• Capital (38%) - investment in tools and R&D, and cost reduction (e.g. taxes)
• Management (52%) - ensuring labor and capital are efficiently used

Relying on scientific management, inputs (e.g. labor, capital) are efficiently transformed into outputs (goods and services). The essence of industrial engineering is in using methods and tools to efficiency manage knowledge, technology, labor and capital for achieving higher productivity. Consequently, productivity improvement at any level should rely on industrial engineering. Furthermore, the national strategy of productivity improvement should be directed at the service sectors which generate most of the GDP. Industrial engineers, independently and partnering with economists, should embrace this challenge and drive the improvement of productivity.