Salary survey

This is the traditional approach where consulting companies obtain survey input data from specific companies. Companies are provided with a wide-ranging questionnaire to gather information about the company and its employees.

• Long-term experience - these are global companies with long histories in the vast majority of cases.
• Brand recognition - these companies are well-established on the market and have already created a reputation. Brands such as PayWell (PricewaterhouseCoopers/PwC), AON Hewitt, Culpepper, Mercer, the Hay Group and Willis Towers Watson are recognised by nearly all human resources and remuneration specialists.
• Consulting activities - given that salary surveys are one of the primary lines of business for these companies, they have consultants on staff who can deliver their consulting expertise in obtaining input data (ensuring data is aggregated using the correct method) and other more wide-ranging consulting activities. Such consulting may include job descriptions, evaluating specific jobs and even the creation of a salary system.
• Detailed catalogue of positions - jobs must be assigned to the correct position during the survey to ensure the compared salary corresponds to the work performed. Positions are described in detail in the survey given the long-term experience and direct connection to parent companies. The same is true of responsibilities, powers and subordination, and superiority structures, in addition to the actual job description itself.
• They facilitate international salary comparison - international salary comparisons for individual positions are possible given that the operators of these salary surveys are companies with international know-how, and identical methods are applied in dozens of countries around the world.

• Lengthy process of completing the form - time demands are high given the detailed nature of the form used to obtain input data. The questionnaire includes questions that require answers from multiple departments: financial (company profits) and human resources (salaries, numbers of employees, training and education costs, etc.). A company may not answer some questions clearly if it monitors specific indicators in a different structure and if estimates are provided in the questionnaire, which deform the results.
• Partial coverage of the entire market - the goal of any salary survey is to include all types of companies, big and small, domestic and foreign, in various industries, etc. Given that only the companies that buy such a survey are involved, these surveys do not cover the entire labour market. Often they only include large and wealthy industries such as IT, telecommunications, pharmaceuticals, banking, cars, electronics, etc. Other industries such as sales, other industry, construction, etc. are composed of companies that cannot afford such a salary survey, which means their industries are not completely covered.
• Sensitive data - not every company wants to disclose sensitive data on profitability, fluctuations, and employee salaries in any specific form. Survey participants cannot avoid these questions.
• Non-current data - salary surveys based on data from employers aggregate input information over a matter of months. The standard data aggregation period is 3 to 4 months. Processing follows, which may take another 2 months. Companies may only receive the data they need after a half-year delay. The labour market changes over this time, in particular in times of economic growth, and the data is no longer up-to-date after aggregation, processing and evaluation.
• High price - salary surveys based on this approach are expensive. Prices are in the thousands of euros, depending on if the company is actively involved in the survey or does not participate and only purchases the survey results (more expensive in this case).

Aggregating data from employees primarily refers to the aggregation of data using the Internet. Such methods have long been established in the US and Western Europe, and are now establishing themselves in Central and Eastern Europe, Asia and the Middle East.

• Large sample of respondents - salaries are of interest to every employee, and providing information about themselves gives the opportunity to compare their current situation with others on the labour market. It is no surprise that these types of salary surveys have a large sample of respondents. Surveys are equipped with technical resources to expose duplicate records, thereby rendering fears of misuse unjustified.[2]
• All types of companies - employees in all types of companies are interested in salaries, regardless of the type of work, region, industry, size, company ownership, etc. Such surveys aggregate data from a multitude of different companies.
• Transparency of results - this method provides fast access to the most in-demand information to support decision-making; the information is also transparently depicted and easy to understand.
• Results without providing company data - companies use the results of such surveys without actually providing their own data. This provides an opportunity to exploit information about the market without concerns over a loss of sensitive data.
• Easy access to the required data - salary surveys of this type are accessible over the Internet. Companies have access to them anywhere with Internet connection: in offices, cafés, hotels, at home, etc.
• Currentness - data is continuously added to this type of survey; the database is propagated with new data on a daily basis with old (year-old) data automatically replaced.
• Financial accessibility - the survey method based on data from employees does not incur the same costs as surveys based on data from employers. These surveys are at a much more accessible price point for this reason. Small and medium enterprises primarily use this type of survey.
• Real employee salaries and benefits - surveys based on data from employee are directly connected to the specific positions in which the employees work. The resulting data describes the situation of a specific employee and not the general situation in the company. Companies often declare benefits such as company mobile phones, but in practice an employee may actually only be eligible for such benefit in select positions and after working for the company for at least one year.

• Temporary mistrust in this method - a lack of confidence occurs in undeveloped countries based on the argument that "people lie on the Internet". Experience has shown that people do not lie but rather complete questionnaires accurately if they want to obtain reliable information from a website. Respondents provide details of their own salary because they are motivated to compare their salary with others. An attempt to provide misleading information is basically lying to oneself.
• Less brand awareness - these salary surveys do not enjoy the same brand recognition as traditional salary surveys, and companies are only starting to have confidence in their results. Experience from abroad shows that it is only a matter of time until this type of surveys finds users.
• Internet population - this type of survey requires that respondents are computer literate and have Internet access. This leads to an assumption that the structure of respondents correlates to the structure of the Internet population. This population has a lower share of employees with lower levels of education and from smaller communities. This effect is mitigated by the increasing levels of computer literacy and Internet coverage.
• Level of detail of results - survey output data is a reflection of the data provided by the respondents, i.e. company employees. They cannot be asked specific details concerning remuneration as they are asked in surveys using data from companies. The average employee does not know how much education and training activities cost, company revenues, etc. As such, the survey outputs do not provide such detailed data. They are based on the most basic indicators on which salaries depend: position, region, industry, previous experience, education, etc. – all questions the respondents can answer.

The Society of Petroleum Engineers, a non-profit association, conducts an annual survey of professional members. The salary survey report provides petroleum engineer salary information[3] by region, job category, years of experience, and more. In 2017, the average (base pay) was US$151,122. In 2016, the average was US$143,006. The average salary and bonus pay in 2017 was US$194,649 and was US$185,001 in 2016.[3]

The Economics Research Institute provides salary survey benchmark information which can be viewed by job title, location, and more.[4]