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Aging Survey Data
Aging survey data can be an invaluable tool to keep compensation strategies competitive. Learn how it can aid in making informed decisions and keeping you ahead of the competition.
What Does It Mean to Age Survey Data?
To understand what it means to age survey data and why you would want to, we need to understand salary surveys.
Salary Surveys
A salary survey collects information about employee compensation, including wages and benefits, in order to determine salary levels for specific job categories. The survey is carried out by region, sector, or job classification. Salary surveys help organizations compare market pay and benefits in their industry or region to see how competitive they are. Salary surveys are generally conducted by experts and purchased by companies, or companies may commission specific surveys through a third party. The data collected in a salary survey includes quantifiable aspects such as base salary, salary increases, salary ranges, incentives/bonuses, assignments, and work hours, as well as non-quantifiable aspects such as educational requirements, geographic location, hiring sources, and working conditions. All wage studies face the challenge of currency, as collecting data and carrying out comprehensive analyses can be time-consuming, particularly when dealing with extensive data sets. In an economy that experiences fluctuations, the information gathered may become irrelevant or outdated by the time the salary survey is published. Rather than purchasing new data every time it's needed, it may be beneficial to age the data.
Aging Survey Data?
To age data is to adjust data collected in the past so as to estimate what that data might indicate currently or at a future point in time. In human resources, the term aging survey data refers specifically to applying this data analysis tool to employee salary surveys. This “aging” is typically done to make the data more relevant and accurate for decision-making purposes, such as when the data is used to consider changes in salaries, benefits, or compensation packages or to remain competitive in salary offerings.
Should Companies Age Survey Data?
Aging survey data can help by ensuring data relevance and accuracy for decision-making purposes. However, there may be cases where it doesn't make sense for a company to age survey data.
Reasons to Age Survey Data
- Reflect current market conditions. Aging survey data to a common point in time allows companies to compare data from different surveys and adjust for market movements. This ensures that the data reflects current market conditions and is therefore more relevant and accurate.
- Provide more relevant information. Using aged survey data can yield more relevant information if there isn't current salary survey data available or you’re looking to make decisions based on a future date. This leads to more informed decisions, such as setting salaries or compensation packages that are competitive and in line with market trends.
- Help companies stay competitive. Aged survey data allows companies to stay competitive by understanding the latest market trends and adjusting compensation strategies accordingly. This helps attract and retain top talent, which is crucial for business success.
Reasons Not to Age Survey Data
- Costly and time-consuming. Aging survey data can be a time-consuming process that requires specialized knowledge and expertise. It can be costly if companies need to hire external consultants or commission custom surveys to help with the process.
- May not reflect market conditions accurately. Aging survey data relies on market movement factors that may not accurately reflect current market conditions, as there are no guarantees that they will continue to trend in the same way.
- May not be necessary in some cases. In some cases, companies may not need to age survey data if the current data is in line with decisions being made (current data for current decisions) or if you are internally benchmarking (internal benchmarking is essentially comparing data that comes from within your own organization—for instance, to look at pay equity). In these cases, external data from a salary survey—aged or not—does not provide any additional value or benefits.
How to Age Survey Data
If you’ve never aged data before, don’t fret. This simplified step-by-step guide shows how simple it can be.
Step 1: Collect the Data
In order to age survey data, you need to have data to age. A quick Google search for reputable compensation survey services can easily leave you overwhelmed. So, what data sources should you use? In this article, the Society for Human Resources Management offers this advice: “There are several options when contemplating salary data sources:
- Purchase a salary survey from a survey organization such as a consulting company.
- Purchase a salary survey from a trade organization or association.
- Use wage data from the Bureau of Labor Statistics (BLS).
- Commission a custom survey.”
Wherever you get the data, it must be reputable. Misaligned data can fuel the fire for potential unionization or unrealistic pay expectations. This is a step you don’t want to skip if you’d like to avoid the “But the internet says I should be paid X much!” conversation.
Step 2: Determine the Aging Factor
The aging factor is the percent by which you would like to age the data. This factor can be found in the reliable salary survey data source you chose in step 1. Let’s say you want to determine the appropriate annual compensation for a new position. You purchase survey data that has an effective date of six months ago, and it states that the average annual income for this position is $80,000. The survey data also tells you that the total average increase for the next year is 3.8%. Therefore, 3.8% would be an acceptable aging factor to use. However, in order to bring your salary data current, you’d divide this rate of increase in half, as the 3.8% is based on one year and you’re looking to age the data only six months. Your aging factor is now 1.9%.
Step 3: Apply the Aging Factor
Now that you have a survey aging factor of 1.9%. You’d then multiply the salary survey information by your survey aging factor ($80,000 x .018) to get the estimated amount the annual salary would increase by 6 months ($1,440). Add those two figures to have the aged result of $81,440, and you have an idea of a salary to offer for your new position that is competitive and current.
Examples of Aging Survey Data
There are numerous scenarios in which a company may choose to use aged data. They include setting new compensation packages, setting compensation for new positions, and considering cost-of-living increases.
New Compensation Packages
In this example, Company A wants to set new compensation packages for its employees based on market trends. To do so, they need to age the survey data they bought last year so it reflects current market conditions. The survey data has an effective date of January 1, 2022, and the company wants to implement new pay ranges on July 1, 2022. The company's research shows that wages are moving, on average, 4% per year. Since there are six months between January 1 and July 1, the aging factor is calculated by multiplying the wage movement percentage by the proportion of time that has passed, resulting in an aging factor of 2%. The company can apply this factor to the survey data to calculate the projected rates for July 1, 2022. For example, if the survey data reports that the 50th percentile for a given job on January 1, 2022, is $15.00 per hour, the projected rate on July 1, 2022, would be $15.30 (an increase of 2%, or $0.30). The company can then use this projected rate to develop new pay scales for July 1, 2022 based on current market conditions.
Determine the Average Salary for a Specific Position
Company B wants to hire a new software engineer. In order to offer a competitive wage on the job listing, the company needs to determine the average salary for a software engineer in their region. They find a relevant survey with data from the previous year, but they want to ensure the data is up-to-date. They decide to age the data to the current year using a calculated aging factor of 2%. If the survey data shows that the median salary for a software engineer was $80,000 in the previous year, the aged data for the current year would be $81,600 ($80,000 + 2% of $80,000). The company can then use this updated data to inform their decisions on salaries for software engineers.
Account for Cost of Living
Let's say Company C is based in a city where the cost of living has been increasing steadily over the past few years. The company wants to use a survey to determine a fair salary for their employees, but they are concerned that the data may not accurately reflect the current cost of living in their area. To account for this, they decide to age past regional survey data using an aging factor of 3% (which they believe is the approximate increase in cost of living over the past year). This will allow them to adjust the survey data to better reflect the current cost of living in their city. If the survey data shows that the median salary for a software engineer was $90,000 in the previous year, the aged data for the current year would be $92,700 ($90,000 + 3% of $90,000). The company can then use this updated data to inform their decisions on salaries for software engineers, taking into account the increased cost of living in their city.
Topics
Kayla Farber
Kayla is the Chief Innovation Officer at Hero Culture, where the passion is to create company cultures of retention using the power of personality.
Frequently asked questions
Other Related Terms
Eddy’s HR Mavericks Encyclopedia
Aging Survey Data
Aging survey data can be an invaluable tool to keep compensation strategies competitive. Learn how it can aid in making informed decisions and keeping you ahead of the competition.
What Does It Mean to Age Survey Data?
To understand what it means to age survey data and why you would want to, we need to understand salary surveys.
Salary Surveys
A salary survey collects information about employee compensation, including wages and benefits, in order to determine salary levels for specific job categories. The survey is carried out by region, sector, or job classification. Salary surveys help organizations compare market pay and benefits in their industry or region to see how competitive they are. Salary surveys are generally conducted by experts and purchased by companies, or companies may commission specific surveys through a third party. The data collected in a salary survey includes quantifiable aspects such as base salary, salary increases, salary ranges, incentives/bonuses, assignments, and work hours, as well as non-quantifiable aspects such as educational requirements, geographic location, hiring sources, and working conditions. All wage studies face the challenge of currency, as collecting data and carrying out comprehensive analyses can be time-consuming, particularly when dealing with extensive data sets. In an economy that experiences fluctuations, the information gathered may become irrelevant or outdated by the time the salary survey is published. Rather than purchasing new data every time it's needed, it may be beneficial to age the data.
Aging Survey Data?
To age data is to adjust data collected in the past so as to estimate what that data might indicate currently or at a future point in time. In human resources, the term aging survey data refers specifically to applying this data analysis tool to employee salary surveys. This “aging” is typically done to make the data more relevant and accurate for decision-making purposes, such as when the data is used to consider changes in salaries, benefits, or compensation packages or to remain competitive in salary offerings.
Should Companies Age Survey Data?
Aging survey data can help by ensuring data relevance and accuracy for decision-making purposes. However, there may be cases where it doesn't make sense for a company to age survey data.
Reasons to Age Survey Data
- Reflect current market conditions. Aging survey data to a common point in time allows companies to compare data from different surveys and adjust for market movements. This ensures that the data reflects current market conditions and is therefore more relevant and accurate.
- Provide more relevant information. Using aged survey data can yield more relevant information if there isn't current salary survey data available or you’re looking to make decisions based on a future date. This leads to more informed decisions, such as setting salaries or compensation packages that are competitive and in line with market trends.
- Help companies stay competitive. Aged survey data allows companies to stay competitive by understanding the latest market trends and adjusting compensation strategies accordingly. This helps attract and retain top talent, which is crucial for business success.
Reasons Not to Age Survey Data
- Costly and time-consuming. Aging survey data can be a time-consuming process that requires specialized knowledge and expertise. It can be costly if companies need to hire external consultants or commission custom surveys to help with the process.
- May not reflect market conditions accurately. Aging survey data relies on market movement factors that may not accurately reflect current market conditions, as there are no guarantees that they will continue to trend in the same way.
- May not be necessary in some cases. In some cases, companies may not need to age survey data if the current data is in line with decisions being made (current data for current decisions) or if you are internally benchmarking (internal benchmarking is essentially comparing data that comes from within your own organization—for instance, to look at pay equity). In these cases, external data from a salary survey—aged or not—does not provide any additional value or benefits.
How to Age Survey Data
If you’ve never aged data before, don’t fret. This simplified step-by-step guide shows how simple it can be.
Step 1: Collect the Data
In order to age survey data, you need to have data to age. A quick Google search for reputable compensation survey services can easily leave you overwhelmed. So, what data sources should you use? In this article, the Society for Human Resources Management offers this advice: “There are several options when contemplating salary data sources:
- Purchase a salary survey from a survey organization such as a consulting company.
- Purchase a salary survey from a trade organization or association.
- Use wage data from the Bureau of Labor Statistics (BLS).
- Commission a custom survey.”
Wherever you get the data, it must be reputable. Misaligned data can fuel the fire for potential unionization or unrealistic pay expectations. This is a step you don’t want to skip if you’d like to avoid the “But the internet says I should be paid X much!” conversation.
Step 2: Determine the Aging Factor
The aging factor is the percent by which you would like to age the data. This factor can be found in the reliable salary survey data source you chose in step 1. Let’s say you want to determine the appropriate annual compensation for a new position. You purchase survey data that has an effective date of six months ago, and it states that the average annual income for this position is $80,000. The survey data also tells you that the total average increase for the next year is 3.8%. Therefore, 3.8% would be an acceptable aging factor to use. However, in order to bring your salary data current, you’d divide this rate of increase in half, as the 3.8% is based on one year and you’re looking to age the data only six months. Your aging factor is now 1.9%.
Step 3: Apply the Aging Factor
Now that you have a survey aging factor of 1.9%. You’d then multiply the salary survey information by your survey aging factor ($80,000 x .018) to get the estimated amount the annual salary would increase by 6 months ($1,440). Add those two figures to have the aged result of $81,440, and you have an idea of a salary to offer for your new position that is competitive and current.
Examples of Aging Survey Data
There are numerous scenarios in which a company may choose to use aged data. They include setting new compensation packages, setting compensation for new positions, and considering cost-of-living increases.
New Compensation Packages
In this example, Company A wants to set new compensation packages for its employees based on market trends. To do so, they need to age the survey data they bought last year so it reflects current market conditions. The survey data has an effective date of January 1, 2022, and the company wants to implement new pay ranges on July 1, 2022. The company's research shows that wages are moving, on average, 4% per year. Since there are six months between January 1 and July 1, the aging factor is calculated by multiplying the wage movement percentage by the proportion of time that has passed, resulting in an aging factor of 2%. The company can apply this factor to the survey data to calculate the projected rates for July 1, 2022. For example, if the survey data reports that the 50th percentile for a given job on January 1, 2022, is $15.00 per hour, the projected rate on July 1, 2022, would be $15.30 (an increase of 2%, or $0.30). The company can then use this projected rate to develop new pay scales for July 1, 2022 based on current market conditions.
Determine the Average Salary for a Specific Position
Company B wants to hire a new software engineer. In order to offer a competitive wage on the job listing, the company needs to determine the average salary for a software engineer in their region. They find a relevant survey with data from the previous year, but they want to ensure the data is up-to-date. They decide to age the data to the current year using a calculated aging factor of 2%. If the survey data shows that the median salary for a software engineer was $80,000 in the previous year, the aged data for the current year would be $81,600 ($80,000 + 2% of $80,000). The company can then use this updated data to inform their decisions on salaries for software engineers.
Account for Cost of Living
Let's say Company C is based in a city where the cost of living has been increasing steadily over the past few years. The company wants to use a survey to determine a fair salary for their employees, but they are concerned that the data may not accurately reflect the current cost of living in their area. To account for this, they decide to age past regional survey data using an aging factor of 3% (which they believe is the approximate increase in cost of living over the past year). This will allow them to adjust the survey data to better reflect the current cost of living in their city. If the survey data shows that the median salary for a software engineer was $90,000 in the previous year, the aged data for the current year would be $92,700 ($90,000 + 3% of $90,000). The company can then use this updated data to inform their decisions on salaries for software engineers, taking into account the increased cost of living in their city.
Topics
Kayla Farber
Kayla is the Chief Innovation Officer at Hero Culture, where the passion is to create company cultures of retention using the power of personality.
Frequently asked questions
Other Related Terms
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