In the wake of the pandemic and the shift to virtual work, figuring out how much to pay employees has become harder. It used to be so simple. As an employer, you could look at what similar companies in your industry and region were paying people in similar positions. The assumption was that while employees might move for a new job, there were enough barriers in place that setting pay levels based on geography worked well.

Then the pandemic changed everything. Now that many people are able to work from just about anywhere they have an internet connection, how do you go about looking for comparisons for their pay? Should you base their income on what we might call local levels? Or do we need to look at national data to set an employee's pay? The answer depends greatly on the kind of work your employee will be doing.

Working Local

As I mentioned earlier, setting pay based on local norms was the traditional way. And this can still work for employees who need to be physically present to do their jobs. Thinks jobs that fall into the bucket of direct labor, like machinists or warehouse workers. Just about any kind of hourly job falls into this category. Why? Because it's not likely someone will move across the country to get hired in a similar position elsewhere.

Take a warehouse worker in Georgia as an example. A person interested in applying for this job is probably not also looking for similar jobs in Los Angeles. They're likely just looking for employment in their region.

So with jobs like this, it's best to set pay levels based on the state or region your company is physically located in.

Crossing the Country

While some remote jobs existed before the pandemic, we've seen an explosion in the number of people interested in working from home -- even if the home is hundreds, or even thousands, of miles away from the company headquarters. You might have a computer programmer living in Iowa working for a Silicon Valley company.

These situations create new challenges because you can't compete to keep this employee in-house if you insist on paying average wages in Iowa. It would help if you were willing to look at more of the national average for the position as your new baseline. Otherwise, the programmer can go work for another company willing to pay them more without the need to move.

A Blended Solution

But there's another wrinkle regarding high-value remote employees like tech talent, or executives like a chief marketing officer or a VP of finance: When the local pay level may exceed the national one. If your business is based in a big city, where pay levels top the national average, but your employee lives elsewhere, should you pay them at the highest level?

The opposite dynamic might also be true. For instance, I was working with a company based in a small town in rural Texas. But they were looking to hire a high-level IT person who lived in New York City. The company struggled to understand whether it should base its offer on what that person might get from a company based in New York City, which was above the national average for pay at that position and massively above the local compensation data.

The solution we arrived at was to come up with a blended pay level that fell between the NYC high and the national average. That felt fair to the company, which was paying far above what it might need to pay someone from the local area, and yet it wasn't quite at the peak that a company in New York or even Silicon Valley might be willing to offer. To be fair, the costs for the employee didn't reach those levels either, so the lifestyle available was highly competitive.

A New Pay Dynamic

When we think about compensation, we must realize that the days of simply basing pay on local levels alone are gone. While you might be able to set some income based on local data for some of your positions, the higher value and more portable the work becomes, the more you'll need to look at national averages and blended pay as your new baseline. Ultimately, you need to think about the lifestyle the compensation can buy that employee.