How Mojaplaca.hr works?
Methodology behind salary survey
MojaPlaca.hr is a website where it is possible to get a salary comparison for more than 700 job positions. The list of positions reflects the job market and it is being constantly updated.
The salary survey was created in 2007 by the company Profesia, spol. s r.o. The same method of collecting and processing data through salary portals has since been launched in the Czech Republic (Platy.cz) and in Hungary (Fizetesek.hu), as well as in other 16 more countries and on the international portal Paylab.com.
The target group of the portal are people on the job market who want to compare their salaries, and companies that care for fair salaries of their employees.
1. Input data
People in the job market are able to get a comparison of their salaries with other employees in the same position and in the same region. Everyone who answers in the questionnaire that s/he has been working in the selected position for a certain period of time, becomes a respondent and will receive an average salary comparison sample for free. This sample is created by other respondents according to the completed position and region. If the respondent states that s/he has not been working in the selected position, then s/he is not a respondent.
Each respondent's data is valid for one year and there is categorically no interference with the entered information. All data in the salary survey is anonymous. The procedure of collecting and processing the data fully respects and adheres to the GDPR directive on the processing of personal data.
The salary survey collects data in net, and the respondents are asked to enter their salaries with regard to full-time work. Therefore, the survey doesn't contain any bonuses for self-employed or other forms of working, such as part-time.
2. Output data
Before the actual calculations the data sample is 'cleansed'. Firstly, any extreme values are filtered out, for example a salary of 100 HRK/month or 100 Million HRK/month. The second step of the database cleansing is to detect any duplicate questionnaires or extremes. Extremes are defined specifically for individual positions with regards to the region (region of the capital city, or outside of the capital city region). The methodology of extreme data detection (removing data) is based on a rough estimate of the parameters of theoretical salary distribution of the position according to the region.
The salary data from questionnaires which have gone through the cleansing process then enter into the dataset for the Regression Model.
3. Regression Model
The salary survey calculates total and basic salaries through quantitative regression. It takes into account the links between position, region, company size, education, experience and age. This proven method makes it possible to estimate the salary, even with a low number of respondents in the desired sample.
The regression model calculates salary values on the position level, as long as there are at least 10 respondents in the dataset for it. By default, the number of respondents in a position over the last 12 months is surveyed, but if lower, the last 24 months of data is also taken into account or even the last 36 months.
Outputs resulting from the regressive model distinguish the following levels of company size:
- small (up to 50 employees)
- middle (51 - 249 employees)
- large (250 and more employees)
For levels of education the regression model distinguishes:
- lower than high school graduation - where respondents who finished middle school or training school are included
- high school graduation - which includes employees who have graduated from secondary school
- university education - for all employees with a university degree.
Work experience in the regressive model has three levels:
- junior (up to 2 years of work experience)
- middle (3 - 5 years of work experience)
- senior (more than 6 years of work experience)
4. Estimation model
MojaPlaca.hr has developed a special method of estimating salaries where it is not possible
to apply the regressive model. Should there be insufficient data for the
regression model, salary data is estimated using the estimation model. This
model gives a qualified estimate of the salary range for the position, while
real data collected from survey participants further approve the estimates. The
estimation model has its limitations: data by regions cannot be displayed and
it is not possible to calculate the basic salary for the position. Similarly,
as with the regressive model, both financial and non-financial benefits are
calculated using classical statistics on collected data.
5. When it is not possible to display the results
In spite of applying the regressive and estimation models, it can sometimes occur that it is not possible to display the information about the salary on a specific position. This happens especially with new job positions.
When comparing the salary in such cases, the user is offered a document in which we give him/her advice and tips on how to negotiate salaries. The user also has the option to request that a link to the salary comparison be sent automatically by email once a salary estimate is possible.
6. Outputs for people
Basic information from the survey MojaPlaca.hr is based on the national average salary of a position. After filling in the salary comparison questionnaire the user receives a free salary comparison - whether it be the expected one or the actual one. The outputs are displayed directly on the website.
Every visitor has the option to purchase a more detailed version of the output the Salary Report Plus. This offers a much more detailed salary comparison based on median and quartiles. Moreover, this output provides an overview of salaries according to work experience and education, it shows relative provision of non-financial benefits of the specific position and with regards to the region. The information about non-financial benefits will be displayed with at least 10 respondents over the last 12 months in the selected sample.
part of the paid version of outputs for people comes advice and tips on how to
negotiate a salary, preparation of a SWOT analysis of the employee, etc. The
whole Salary Report Plus contains more than 20 pages and is suitable for those
who are getting ready for a job interview or a meeting with their manager,
where salaries may also be reviewed and negotiated.
Users can purchase the paid report via PayPal.
The purchased personal salary analysis is sent via email to the given email address entered when ordering.
7. Outputs for companies
In particular, corporate clients are assigned the Professional Report, which can be purchased online after entering basic data of the requested information. The Professional Report takes into account not only position and region, but also requirements for work experience and company size. The Professional Report summarises the basic overview of remuneration of the selected position, but unlike the Plus Report, it also takes into account other selected parameters. The outputs show the basic and the total salary, and as well as the average value it is also possible to see the salary distribution by the following basic percentiles:
decile - 10% of employees earn less than the given value
1. quartile - 25% of employees earn less than the given value
median - half of employees earn less/more than the given value
3. quartile - 25% of employees earn more than the given value
9. decile - 10% of employees earn more than the given value
The job market situation can also be visualised by a chart showing the respondents' distribution by pay bands. This chart will show what percentage of employees can be found in each of the 10 pay bands for the selected sample.
The Professional Report also contains basic percentiles of the total salary according to the following individual indicators:
- work experience
- company size
as well as always including the other entered criteria.
All of the above-mentioned information in the Professional Report is a result of the Regression Model. With the help of standard statistics, based on respondents' data we can calculate the share of respondents who receive non-financial benefits. This can be shown as long as there are at least 10 respondents in the sample.
In the same way, the share of respondents that receive particular salary components can be evaluated, such as any variable salary components, the 13th salary, annual rewards or bonuses and what the average amount of these salary components is. These values can be shown as long as there are at least 5 respondents in the sample that take into account the selected position, region, work experience, education and company size.
The Professional Report can be purchased online through PayPal. In such cases a PDF output with the report is sent automatically to the email address entered with the order. The client can request to buy the report with an invoice, but the whole process of exporting the report and sending the invoice can take up to two working days.
8. Online tool for companies
Corporate clients have the option to purchase access to the Salary tool. Clients with this service can search salary data for all positions included in the survey and have access for one year. By purchasing this service, the client gets a full year of access to the online tool, during which time s/he can look up salary data for all job positions and compare employees' salaries and ascertain the salary in the job market.
The outputs of the Salary Tool are the same as in the Salary Report Pro. However, when comparing the salary of an employee, the system recommends how to modify a specific employee's salary.
The outputs can be saved for further work on them, or they can be exported into PDF files.
You can purchase access to the Salary Tool online or by contacting [email protected].
9. Custom analysis for companies
The Paylab.com Salary Survey enables the export of data based on different criteria, which is often used for the needs of the media. The collected data and the flexibility of the system offer the possibility of providing companies with different or non-standard analysis tailored for the company. To get more information about such an analysis, please contact mi[email protected]