The future development of productivity is a key factor in economic and social development. Its main driver over the last 250 years has been the replacement of human labour by machine functions, which has dramatically reduced the working time required to produce many goods and services. Today, on the one hand, there is a great deal of guesswork in science about future productivity potential. On the other hand, digitalisation is clearly opening up new possibilities for the automation of activities that previously seemed inaccessible to automation. An assessment of future productivity potential can be derived from knowledge of the degree of automation of today's manufacturing processes and their future automation potential.

However, it is difficult to quantify the current level of automation globally or even in the most developed countries. Essential core questions can largely only be answered today as an educated guess, as the quality of empirical data on current and estimated future levels of automation is poor.

This paper outlines a project that aims to improve the empirical basis for the development of automation levels and future potential. The aim is to analyse the current status of automation and to make a well-founded assessment of future potential for key products and production stages in all areas of the company. Sectors of labour systematically and empirically. The project has a modular structure and is designed as a long-term IGZA research line. In the first phase, selected areas of gainful employment are recorded. Other sectors with their typical products and production stages as well as family and domestic work will be added in the following years. The aim is to achieve internationalisation.

The more precise way of measuring the degree of automation determines the Necessary human labour time of each production section for a given level of technology and organisation, adds up the total working time of the chain and compares it with the reference system of work with simple tools.

The degree of automation determined in this way indicates the part of the working time that is taken over by the machinery. The image shows an initial conservative estimate the degree of automation of working time in the various sectors of labour based on the figures from the matrix materials. This degree of automation indicates the proportion of necessary labour that is currently performed by machines. The reference in each case is work with simple tools. The degree of automation and productivity run in parallel. The upper scale in the image shows the degree of automation and the lower scale shows the corresponding increase in productivity compared to working with simple tools.