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Geographic Differential

For companies with a remote workforce, a simple way to establish job salary ranges is using a geographic differential (“geo diff”).

Guide for US geographic differential

For companies with a remote workforce in the United States, a simple way to establish job salary ranges is using a three-tiered geographic differential (“geo diff”).

  1. The US - (All) market data cut is the U.S. national (average across the U.S.)
  2. For Seattle, Austin, and Boston (and a 60-mile radius of these cities), use the US (All) - 110% market data cut (e.g., 10% premium to the US national average)
  3. San Francisco (“SF”) and New York City (“NYC”) (and 60-mile radius of these cities) typically require a higher range (e.g., due to cost of labor and cost of living), so using the US (All) - 115% data cut is best practice. 

For all other US locations, like Los Angeles (“LA”), District of Columbia (“DC”), Denver, Chicago, etc., you can use the US (All) Market Data Cut because the local market data is so close to US national data. 

Employees in the United States matched to Kamsa’s executive VP and above jobs (e.g., Job Levels E1, E2, and E3) still match the Revenue Cut aligned to the revenue size range selected in the Company Profile. 

Global Geographic Differential

For companies with employees located remotely worldwide, you can use geographic differential (“geo diff”) tiers based on the US national average data instead of local metro area market data cuts. 

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%).

Location Default Geographic Differential vs. the U.S. 2022 Geo Diff difference from prior year
San Francisco Bay area (“SF”)
New York City area (“NYC”)
115%
Austin, Boston, Seattle 110%
Atlanta, Chicago, Dallas, Denver, Los Angeles, Philadelphia, Phoenix, Washington, D.C. metro area 100% -10% for Los Angeles and Washington, D.C.
Switzerland 100%
United States (US) - All 100%
Canada - Toronto 90% +10%
Canada - Vancouver 90% +10%
Denmark 90% +10%
Israel 90% +10%
UK - Inner London 90% +10%
Australia 80%
Austria 80% +10%
Canada (All) 80%
Germany 80%
Ireland 80%
Luxembourg 80% New
Netherlands 80% +10%
Norway 80% +10%
Puerto Rico 80%
Singapore 80% -10%
Sweden 80% +10%
UK (All) 80%
United Arab Emirates (UAE) 80%
Belgium 70%
Finland 70%
France - Paris 70% -10%
France (All) 70% -10%
Hong Kong 70% -10%
Japan 70%
New Zealand 70%
China - Tier 1 Cities 60% +10%
Ghana 60% New
Italy 60%
Malta 60%
Mauritius 60% New
Portugal 60%
South Korea 60%
Spain 60%
Albania 50%
Bolivia 50% New
Cabo Verde 50% New
Cambodia 50%
Chile 50%
China (All) 50%
Croatia 50%
Cyprus 50% New
Dominican Republic 50%
Ecuador 50% New
El Salvador 50% New
Georgia 50% New
Greece 50%
Guam 50% New
Guatemala 50% New
Honduras 50% New
Indonesia 50% New
Jamaica 50%
Jordan 50% New
Kenya 50%
Kosovo 50% New
Kyrgyzstan 50% New
Latvia 50%
Montenegro 50% New
Morocco 50%
Namibia 50% New
Nicaragua 50% New
North Macedonia 50% New
Panama 50% New
Slovenia 50%
South Africa 50%
Sri Lanka 50% New
Thailand 50% New
Uzbekistan 50% New
Venezuela 50% New
Algeria 40% -10%
Belarus 40% -10%
Bosnia and Herzegovina 40% -10%
Brazil 40% -10%
Costa Rica 40% -10%
Czech Republic 40% -10%
Estonia 40% -10%
India - Bangalore 40% -10%
India (All) 40% -10%
Lithuania 40% -20%
Malaysia 40% -10%
Mexico 40% -10%
Moldova 40% -10%
Nigeria 40% -10%
Peru 40% New
Poland 40% -10%
Romania 40% -10%
Serbia 40%
Slovakia 40% -10%
Taiwan 40% -10%
Ukraine 40% -10%
Vietnam 40% -10%
Argentina 30% -20%
Bulgaria 30% -20%
Colombia 30% -20%
Egypt 30% -20%
Hungary 30% -20%
Kazakhstan 30% -20%
Pakistan 30% -20%
Philippines 30% -20%
Russia 30% -20%
Turkey 30% -20%
Uruguay 30% -20%