Number of Jobs Created

The indicator measures the number of full-time equivalent (FTE) jobs that were created thanks to provided support. It aggregates part-time and full-time jobs.

Determine the indicator's value by using the following methodology:

1) Use reviews of relevant project documentation (e.g. M&E reports) and interviews with the people who gained jobs (or the businesses who created them) to make a list of all the jobs that were newly created (i.e. did not exist before) thanks to the project’s support. If you work with formal businesses, you can also review the number of people on their payroll.

2) Per each supported job that is only part-time, calculate the approximate number of hours the person works per week (e.g. 2.5 days per week multiplied by 8 hours = 20 hours per week). For each supported job that is only seasonal, calculate how many months (or weeks) the person works per year (e.g. 3 months per year).

3) Since it is possible that, for example, 4 part-time staff can work and earn less than one full-time staff doing the same type of work, you must convert all the part-time and seasonal jobs into “full-time equivalent” (FTE) jobs. For example, a full-time working week is 40 hours. If a person works only 20 out of 40 hours per week, s/he works 20 divided by 40 = 0.5 FTE. Similarly, if a person has a seasonal job and s/he works 3 out of 12 months a year, the FTE is calculated as 3 divided by 12 = 0.25 FTE. If a person has a regular, full-time job (40 hours per week or other number based on the local custom), s/he has 1 FTE. This process is important as reporting jobs in FTE provides a much more accurate overview of the project’s contribution to employment creation.

4) To calculate the indicator’s value, sum up the FTEs for all the jobs that were created thanks to the project’s support. For example, if one person works full-time (= 1 FTE) and another two persons work only 20 hours per week (= 0.5 FTE), their employment equals to 1 + 0.5 + 0.5 = 2 FTE.

Disaggregate the data by gender, type of job (part-time, full-time), salary level, persons with a disability, and the types of profession the employees do. Box 4 in DCED guidance below (page 38 / 43) provides useful tips on what to be careful about when disaggregating jobs by gender.

1) Minimize the incidence of "fake reporting" by verifying the employment information from several different sources, such as relevant documentation (contract, payroll), the employee, employer, other key informants, and by conducting unannounced visits at the place of employment.

2) If you lack the data required for counting the number of FTEs, you can use a rule of thumb recommended by ILO stating that two part-time jobs equal one FTE job (source: ILO’s webinar Measuring Job Creation, 12^th February 2019). This method is less precise and should be used only if it is impossible for the project to use the methodology described above.

3) In addition to reporting on the number of FTEs, report separately on the total number of people who gained any type of job (full-time, part-time, seasonal). This will show you the number of people who were reached by the project’s employment-creation support.

4) Since there is a significant difference in the value of a very poorly paid job and a well-paid job (for example, one that pays at least an average salary), it is highly recommended that you disaggregate the data by salary level.

5) It is recommended that you document the contact details (phone numbers / e-mails / addresses) of those people who gained employment, so that you can later easily contact them to see how many of them managed to retain their job.

6) Consider complementing the provided results by the following indicators:

   - Proportion of Jobs Retained

   - Income from Employment

   - Employee Satisfaction Index

   - Security in Employment

7) Consider measuring the number of directly as well as indirectly supported FTEs. Jobs that were directly supported are those provided by employers you directly worked with (e.g. fruit processing factories that you supported directly with training or access to finance). If the support results in other value chain actors (e.g. more traders collecting fruit, or more farmers producing fruit, based on the growth of the fruit processors) having to employ more people, these jobs can be counted as indirectly supported FTEs. Value chain maps can be a useful way to analyse and display the direct and indirect jobs that a programme is responsible for. To calculate the number of indirectly supported FTEs, you can use a similar methodology as the one described above. At the same time, due to the difficulty related to counting the number of indirectly supported FTEs, it is important that you acknowledge in your reports / presentations that the numbers of indirectly supported FTEs are well-founded estimates (based on all the available data) rather than precise measurements.

8) For more guidance, read chapter 3.3 of DCED’s publication below.