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The 2023 Pharmaceutical Industry Compensation Survey is reflecting salary trends and practices in Estonia. The survey includes information about different positions’ compensation levels and practices.
The purpose of the survey is to provide organizations with objective information that is necessary to make smart decisions related to employees’ compensation. The survey presents an overview of the current salary market (as of June 2023), compares changes to the previous year and describes expectations organizations have regarding employee compensation.
The Top Executive Compensation Survey which gives a thorough overview about the compensation of members of the board as well as chairmen of the board (top executives) will be published at the end of November. In January we will publish the Forecast Survey to our clients which maps out the salary market expectations for the forthcoming year. According to our clients’ needs, different sector surveys have also been delivered (for example in 2023 finance, ICT and pharmaceutical).
Our compensation surveys are conducted in all three Baltic States and provide convenient salary comparisons thanks to the united methodology.
Since 2013 Figure, in corporation with Mercer, is conducting Mercer’s Total Remuneration Survey (TRS) in Estonia, which provides thorough information on different employee remuneration systems and is conducted worldwide in more than 150 countries. Therefore; we can also offer international salary information to clients.
The dashboard provides: (1) analysed information on compensation changes and compensation policies, and (2) detailed compensation - related analysis according to job families, levels and points. Full list of survey deliverables and their descriptions can be found HERE.
We would like to extend its gratitude to all participants who helped compiling the present survey.
Sincerely yours,
Figure Baltic Advisory
Our team and contact information for Figure Estonia can be found HERE
19 Organizations
56%
100%
85%
MANUAL - PRESS ME
278 Incumbents
18%
8%
84%
2 379 EUR
This is a list of participating organizations in this year’s survey. Please, note that you can export data in different format, and you can use this document, for example, to order “Special Analysis”.
Participants and Target Group
The purpose of the General Compensation Survey is to provide each organization’s compensation analysis and comparison, based on structured high-quality market information in Latvia.
The survey helps to follow and to evaluate changes in the labour market, to make compensation related decisions and to define the right compensation package for employees consistent with the current situation.
Job Classification
To ensure a precise compensation comparison among jobs with similar responsibilities and functions, all jobs present in organizations are classified into specific job families (by the function and content) and levels (by the responsibility and job complexity) using the General Job Description Catalogue and ICT Job Description Catalogue. All job families and levels have also been evaluated using analytical job evaluation method (see ‘MORE’ - Analytical Job Evaluation Method & Terms), in order to facilitate comparison between different job families (in points).
Job descriptions used or classification are represented prior to a respective salary table.
Salary and Compensation Data Gathering and Analysis
Salary data was gathered using two complementary data forms: salary tables and questionnaires regarding compensation policy.
Data was asked for all jobs in an organization. The data was collected, processed, and analyzed between May to July 2022. The monthly base salary data is provided as of June 2022. When calculating the amounts of annual total cash, paid out variable short-term incentives and assigned long term financial incentives/bonuses for the previous 12 months are taken into account.
Compensation changes in job families and levels have been calculated for employees whose position, duties and responsibilities have not changed during last year as well as for employees whose position, duties and responsibilities have changed (for example, who work on a higher or lower position than last year or with increased responsibility and duties).
In addition to the detailed compensation data, the representatives of the organizations provided information on compensation policies. The information was gathered from the questionnaire in five general parts - general information on the organization, compensation system, compensation parts (including incentive schemes), benefits and training, other additional questions. The electronically obtained data was checked and streamlined. RStudio Desktop 2022.02.3+492 as well as spreadsheet application MS Excel were used for statistical analysis.
When the answers were submitted for statistical processing, usually the median value and/or the arithmetic average was calculated; for salary data other positional averages, such as the median, 10%, 90% deciles and 25%, 75% quartiles, were also used (see ‘MORE’ - Analytical Job Evaluation Method & Terms). The percentages presented in the tables and graphs represent the weight of an answer among the total number of answers to the questions at hand (respondents who did not answer have not been taken into account).
The salary information has been presented based on two principles:
Therefore, the criterion of the minimum number of organizations has been used upon analysis. All numbers are presented in gross amounts and in EUR.
Organization weighted approach (extension ORG) – a job market distribution computed using the averaged incumbent pay for each organization. Each company is weighted equally so no company can influence the distribution statistics based on a large share of the incumbent sample. The “Organization weighted” part of this term indicates that it is a reflection of what the typical company is paying. The calculation first determines the average pay for a job at each unique company, and then calculates the average of those averages.
Incumbent weighted approach (extension IND) – a job market distribution computed using individual employee (incumbent) pay data regardless of affiliation with a company. While each incumbent is weighted equally, organizations with large share of the incumbent sample may influence the distribution statistics. The “Incumbent weighted” part of this term means it is the average pay for each person in the labour market.
Compensation survey consists of two different approaches of calculation: organization weighted approach and incumbent weighted approach.
The Compensation Analyzes Tool represent both organization weighted and incumbent weighted approach. Trendlines in the Compensation Analyzes Tool are based on organizations!
Explanation
Say we have companies A (with 3 employees), B (with 2 employees), C (with 9 employees), D (with 2 employees) and E (with 4 employees).
If we want the average salary based on companies (organization weighted approach), we´ll start by calculating the average salaries inside the companies and then find the average total (by summing up the averages of the companies and dividing the sum by 5).
If we want to know the average salary based on the employees (incumbent weighted approach), we sum up the salaries of all the employees and divide the sum by 20 (the total employees of 5 companies altogether).
Analytical job evaluation is a technique designed to enable trained evaluators to evaluate and judge the size of one job relative to others. Analytical job evaluation method is described in Handbook of Job Evaluation of Intellectual and Physical Jobs. The method has been created and developed by Figure and bases on ILO recommended method. It is used in all three Baltic States.
Analytical job evaluation method is universal and is applicable in every organization and with all jobs. When compared with job family classification method analytical method is more precise and enables to evaluate and compare jobs for which there is the small amount of similar jobs description available in the labour market. Our analytical job evaluation points scale and job family classification scale are compatible
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Flexdashboard is a user-friendly tool with improved data overview that enables you to effortlessly navigate and interact with survey results. This guide is designed to help you make the most of this document without requiring any technical knowledge. Whether you’re new to Dashboards or looking for a quick reference, this guide provides the information you need to effectively utilize the survey results.
Identify charts or visualizations on the dashboard, such as pie charts, bar graphs, line plots, or tables.
Hover your mouse cursor over the charts to see additional information or tooltips, if available.
You may be able to interact with the charts in various ways, which are described in more detailed on the right side of this page - “Plot Toolbar Options Guide”.
If the dashboard includes tables with filters or dropdown menus, you will usually find them positioned near the top or side of the page. Please, note that in some cases it is possible to download tables in different formats (see tab ‘Participants -> Participants list’).
To refine the displayed data, select one or more options from the available choices, and the content will update accordingly.
By following these steps, you can navigate between tabs, interact with charts and use filters or dropdowns (if available) within this Dashboard document without needing technical knowledge. Before, you can check “Plot Toolbar Options Guide” on the right, and experiment with the figures below. Enjoy exploring the insights and information presented in this dashboard!
When working with interactive charts, you will encounter a toolbar that provides various options for interacting with the chart. Here is a guide to help you understand and utilize the different options available:
Download plot as a png (1): Allows you to download the current chart as a PNG image file.
Zoom (2, 6, 7): Allows you to zoom in on a specific area of the chart by clicking and dragging the cursor over the desired region. This helps you examine the data in more detail.
Pan (3): Enables you to pan or move around the chart by clicking and dragging it. This is useful when you want to explore different sections of a large chart.
Box Select (4): Lets you select a rectangular region by clicking and dragging the cursor. The selected data points can be further analyzed or used for filtering purposes.
Lasso Select (5): Allows you to draw a free-form shape around the desired data points by clicking and dragging the cursor. The selected points can be used for analysis or filtering, similar to the Box Select option.
Autoscale (8): Automatically adjusts the axis scales to fit the data in the chart, ensuring all data points are visible. This is particularly useful when zooming or panning has been applied.
Reset axes (9): Returns the chart to its original view, resetting any zooming or panning you may have applied.
Hover (10, 11): Enables a tooltip-like interaction. When you move the cursor over a data point, additional information related to that specific point is displayed, such as its value or labels. Latter option allows to compare multiple data points on x axis.
Feel free to explore and experiment with these options to interact with the charts (examples on the left side), gaining deeper insights into the data and customizing the visualizations according to your needs.