10 SOLID REASONS NOT TO TRUST OPEN-SOURCE SALARY DATA TO MAKE INDIVIDUALIZED DECISIONS

One of the questions we hear most frequently is where salaries are at across a range of titles, based on open-source data. Such an inquiry is understandable for companies and individuals trying to make salary-related decisions, but trusting this data is problematic. 

We have run large salary surveys that measured tenure, type of work, project budgets, geographic area, job satisfaction, manager relationship, benefits package, historical bonus, and interest in changing jobs.

We were surprised to find the data didn’t make sense. We expected to see a clear correlation between experience and earnings, but this was not the case. Based on our personal knowledge of some of the people who participated in the survey, we could tell there must be more going on in determining salaries than our surveys revealed.

QUALIFICATION

In this article, I will make bold claims based on my experience as a recruiter after working with thousands of candidates, seeing a variety of company cultures, and participating in many hires. I cannot substantiate every claim I’ll make with hard data, but I offer to you my conclusions after these thirteen years of relevant experience. 

LOOKING FOR COMPENSATION DATA MAKES SENSE

Markets are always moving, so it’s understandable that good companies want to do their research, in order to keep up with current trends and pay their employees a fair salary; and of course, employees want to make what they believe they’re worth on the open market.

We are taught to look for hard data to determine the appropriate salaries. It’s everwhere.

HOWEVER

Here are all the important and unique variables that impact compensation. Can you think of more?

1. the rank of skillset relative to peers from passion for excellent work
2. degree of proven company loyalty
3. challenge and cost to replace the employee
4. problem-solving skills
5. relationship/influence with peers
6. management ability
7. relationship and trust with ownership
8. customer-facing communication skills
9. project load and profit potential for the company

The problem is average data accommodates none of these specific conditions. You are not average, you are not looking for average team players, and your products are not marketed as average.

Why would average salaries prove useful?

Furthermore, average data can work against you as easily as it works for you, on either side of the negotiation. If you are comfortable asking for a raise or making a lower offer due to average salaries, are you also amenable to being similarly moved by market conditions out of your control?

Of course not.

10 REASONS INDUSTRY WAGE DATA DOESN’T HELP

1. It is difficult to prove the accuracy or inaccuracy of salary data. Salary data is gathered only from those companies and individuals willing to share their information. The employees who share salary information have an incentive to provide exaggerated data, in order to drive up the averages. Likewise, employers may provide lower data to drive averages down and limit their employees’ ability to negotiate higher salaries. There is no comprehensive audit to confirm the accuracy of the information collected.
2. Specific needs sometimes necessitate overpaying an employee. There are times an employer is desperate and must overpay, in order to fill a role, such as after the loss of a key employee, driving up averages. 
3. An employee’s relationships and organizational trust greatly impact earnings. Sometimes people get paid more for who they know than for what impact they have on the overall earnings of the company. 
4. Years of experience impacts compensation, but not as much as raw performance. We’ve seen many long-tenured but incompetent employees far outshone by less tenured but conscientious and diligent professionals. Salary surveys focus on tenure as a greater indicator of value, which is often fallacious.
5. A person’s job satisfaction is based on more than salary. Many have left a higher-paying job due to the brutal work culture for a lower wage to enjoy the better lifestyle that went along with it. People remain happy in their jobs for any number of reasons, including organizational pride and appreciation for their employer, relationships with coworkers, self-respect for their work performed, and optimism for the company’s future. 
6. Benefits packages provide additional monetary value, often inadequately accounted for by salary surveys. Many people don’t realize what their benefits package is worth, much less detail its value on a survey, but not every benefits package is of the same value. Many surveys don’t even ask such questions. More importantly, regardless of the actual financial cost to the employer, employees place a different subjective value on their benefits. 
7. Bonus structures vary greatly from company to company. Bonus structures reflect a distinct entrepreneurial approach to sharing the risk and rewards with employees. Companies that encourage employees to “own” their work accomplish this by creating a generous bonus structure, in which case salaries are lower but overall compensation has a higher earning potential.
8. Salary data cuts both ways. Salary data is collected by people using it to justify higher salaries or by companies trying to keep salaries lower. When averages run higher, employees point to this data. But when times are tough and profits are down, the same employees don’t want to point to that data. People and companies tend to use data to serve their own ends without much concern for the good of the other party.
9. Personal perspectives on salary ranges are not trustworthy. Even highly experienced recruiters see the impossibility of making sweeping salary-related conclusions based on simple statistical data.
10. Salary data is no replacement for taking careful stock of an employee’s actual contribution, loyalty, and growth potential. What will it cost to lose them? What will it cost to replace them? What will be lost until they are lost? Salary survey-driven compensation structures lead to organizational structures out of touch with personal contribution and value.

WHAT TO DO INSTEAD?

Comparing even two people’s skillsets, benefits packages, salaries, bonuses, goals, commitment, and future potential is hard; doing this for a whole industry is impossible.

Companies often do not have the resources to evaluate their employees’ individual contributions specifically, so they fall back to salary data.

The question which must be asked is, what is this person worth to the organization?

Great companies build great teams by paying higher-than-average wages because the exceptional performance of their team produces great financial profits.

It should be noted that great performance must be hired and inspired but cannot be simply bought or demanded. Great performance is driven by personal ethics, respect, and tangible reward.

Employees who seek to earn significant compensation should contribute maximally to the company’s success and continuously improve the value of their contribution. They should not look horizontally to see what others are earning, then complain.

The best employees will set the earnings standard by performing well, rather than chasing the earnings of others.

Employers who seek to pay competitively should pay careful attention to profitability, employee contribution, personal loyalty, the potential for loss, or the possibility for reward, then pay what people are worth for the long-term success of the company. This is dialed-in management that helps engaged team members achieve their earnings goals.

If loyalty is cultivated and the mission is worthy, then the company builds a strong foundation and its employees receive fair compensation, irrespective of data surveys.