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The 2023 General Compensation Survey is reflecting
salary trends and practices in Latvia. 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 Latvia,
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 Latvia can be found
HERE
© Figure
Baltic Advisory 2023
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.
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 2023. The monthly base salary data is
provided as of June 2023. 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.
Look for the tabs at the top of the dashboard, usually labeled
with names or categories. For example, ‘Summary’.
Click on a tab name to switch between different sections of the
dashboard.
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.