Cost-Effectiveness of Jobs Creation
English: average amount spent by the project on creating one job
French: montant moyen dépensé par le projet pour la création d'un emploi
Portuguese: valor médio gasto pelo projecto na criação de um posto de trabalho
Czech: průměrná částka vynaložená na vytvoření jednoho pracovního místa
What is its purpose?
The indicator measures the average costs of creating a job. It shows the cost-effectiveness of the provided support and helps with calculating its value for money (especially when the costs of the support per each job are considered against the financial and non-financial benefits the job provides to the employee / entrepreneur).
How to Collect and Analyse the Required Data
Determine the indicator's value by using the following methodology:
1) Decide whether you will report on the:
- average costs of creating part-time jobs and average costs of creating full-time jobs (i.e. you will have to report on two different values); or
- average costs of creating one full-time equivalent (FTE) job where FTE means that, for example, if a person works only 2.5 out of 5 days per week, her/his job is considered as 0.5 FTE (see more guidance at this site)
2) Count the number of part-time / full-time or FTE jobs created thanks to the project’s support (guidance on calculating FTE jobs is provided here).
3) Count the total costs paid by the project for creating part-time / full-time jobs or all FTE jobs. This should include not only the project’s direct investments (e.g. training of employees, support to employers, etc.) but also its overhead costs related to creating these jobs (e.g. staff costs, offices, transport, etc.).
4) To calculate the indicator’s value, either:
- divide the project’s costs on creating part-time jobs by the number of created part-time jobs + use the same methodology for full-time jobs; or
- divide the project’s total costs by the number of FTE jobs created thanks to the project’s support
Disaggregate the data by the type of jobs supported (part-time, full-time) and salary level.
1) Since there might be a significant difference between the cost of creating a well-paid job and a poorly paid job, it is highly recommended that you disaggregate the data by salary level.