The market data cut approach you select in Company Profile flows into the data cut matches used for your employees. This video provides more information on the two options for the Market Data Cut approach: Local data and Geographic Differential.
Local Market Data Cut Approach
First, let’s talk about the Local Market Data Cut approach.
0:20 When using the Local Market Dat Cut approach, Kamsa will match your employees to local data by factoring in each employee’s Country and Work Location (fields on the Employee Data page).
For example, let’s say an employee’s Country is the Netherlands, and their Work Location is Amsterdam; Kamsa will match that employee to the Netherlands market data cut.
Another example is if an employee’s country is the United States, and their work location is Remote. Kamsa will match that employee to the US (All) data cut, which uses the United States national average data to establish the compensation range (instead of a metro city area data cut).
Let’s say you elected to use the Local market data cut approach, and an employee’s Country is the United Kingdom, and their work location is in London. In that case, Kamsa will match that employee to the UK - Inner London market data cut.
Employees located in the United States and are matched to Kamsa’s executive VP and above jobs (for example, Job Levels E1, E2, and E3) will match the Revenue Cut aligned to the revenue target you've selected in the Company Profile. Employees matched to the executive levels located outside of the US will be matched to the Local market data if you choose this Local Market Data Cut approach.
Geographic Differential Market Data Cut Approach
1:48 The second Market Data Cut Approach option is called Geographic Differential. We’ll cover how this method works for US-based and Non-US based employees.
a. For US-based employees: 3 tiers
1:58 For companies with a remote workforce in the United States, a simple way to establish salary ranges for jobs is by using a three-tiered geographic differential.
The first tier we’ll talk about is the US (All) - 115% data cut. By default, due to the cost of labor and cost of living, Kamsa will use 115% of US National data for employees whose country is the United States and who have a work location in either San Francisco or New York City (as well as a 60-mile radius of these cities).
The second tier is the US (All) - 110% market data cut. Employees in the U.S. with a work location of Washington, DC, Los Angeles, Seattle, Austin, or Boston (as well as a 60-mile radius of these cities), have a higher cost of labor and cost of living than many other areas within the US (except San Francisco or New York City).
For employees in the United States that work remotely or have a different work location that has been mentioned (like Denver, Chicago, Dallas, etc.), Kamsa uses the US - (All) market data cut, which uses the U.S. national average to establish the salary ranges.
This is the three-tier geographic differential approach for US-based employees.
Employees who are located in the United States and are matched to Kamsa’s executive VP and above jobs (for example, Job Levels E1, E2, and E3) will still match the Revenue Cut aligned to the revenue target you've selected in the Company Profile.
b. Geographic Differential for global employees
3:38 Now, we’ll talk about the Geographic Differential for employees outside of the U.S.
For companies with employees located remotely worldwide, instead of using local metro area market data cuts, you can use geographic differential tiers based on the US national average data.
Kamsa’s default mapping of a global geographic differential uses our recommended discount percentages by country (based on local market data, then rounded to the nearest 10% discount).
We list our recommended discount %s off of US National market data in the Help Center and reference the Market Data Cut Approach article.
For example, when using the geographic differential market data cut approach, if an employee’s country is the United Kingdom, Kamsa will match that employee to the US All - 80% market data cut, which uses 80% of the US national average data.
Your selection of Market Data Cut Approach in the Company Profile flows into Employee Data and impacts how each employee's Market Data Cuts are matched.
For example, when you change a Work Location and/or Country for an employee or add any new employees (e.g., directly in the Employee Data page, or via a census data file upload), then the Market Data Cut Approach you have selected in the Company Profile will apply.
The employees who are located outside of the US and matched to the executive levels will match their country’s geographic differential.