Compensation.BLR.com’s rate ranges can be used to establish compensation levels for any job in any organization. By assigning a rate range for each salary grade, you create a compensation structure based on market data that has internal equity built into the process. These rate ranges are updated regularly to reflect current economic trends and conditions.
Including:
• Definition & why a Rate Range is important
   to your business

• Rate Ranges for 3 job classes:

  • Nonexempt plant or manufacturing and
     service jobs
  • Nonexempt office or clerical and
     technical jobs
  • Exempt
• BLR’s calculation of the midpoint for each
   rate range, which will include:

  • The minimum of a salary range, which is
     calculated at 75% of the midpoint for
     the grade
  • The maximum of a salary range, which is
     calculated at 125% of the midpoint for
     the grade
What you have as a result of your job evaluation program is a hierarchy of jobs based on point values (or some other set of reliable criteria.) In other words, you can be assured of internal equity when it comes to matching up the various evaluation "scores" with actual wage levels because all of the jobs in the organization have been compared with each other and have been evaluated accordingly. But internal equity alone can't guarantee employee satisfaction or protect your firm from a legal challenge. You must be aware of what other firms in your area or industry are paying for similar jobs. Once this information has been obtained and you have determined that your wage and salary structure compares favorably, you have achieved external equity as well.
The most common means of obtaining this information is through wage and salary surveys. Although conducting such a survey or even trying to make sense of the hundreds that are available might seem like an overwhelming and probably unnecessary task to the small or medium-sized employer, it should be remembered that almost every company does take surveys, even though they may only do so informally. For example, most employers pay attention to the salaries that job applicants are demanding, to the rates that departing employees say they will be receiving from their new employers, to the information about wages that is passed around at seminars and business meetings, and to what is said about wages in the news media. The informal survey activity is going on all the time, and from the fragments of information that are collected emerge decisions concerning pay increases, fringe benefits, and overall pay policies.
If your company isn't in the habit of consulting or conducting wage and salary surveys and yet has always managed to attract and maintain a sufficient number of qualified employees, you may not see the need for any kind of formal survey activity. But consider the following: A $1 per hour overpayment in a labor-intensive firm can have a drastic effect on its ability to compete and even on its economic survival; while a $1 per hour underpayment can lead to higher recruiting costs, the hiring of less skilled employees, increased training costs, and more turnover-not to mention lower morale and motivation throughout the organization. In short, you may think you're surviving just fine without all this concern about what other companies are paying their employees, but you have no way of knowing just how much your lack of concern is costing your firm in other, less obvious ways.
How Compensation Surveys Are Used
Most employers that do utilize wage and salary surveys on a regular basis have found them to be an invaluable planning tool. Among other things, wage and salary surveys can be used to:
  • Determine where your company's pay rates for certain jobs or groups of jobs stand in relation to the labor market;
  • Double-check the results of the company's evaluation program;
  • Determine how competitive your company's starting salaries are in relation to those elsewhere;
  • Determine the need for (and the amount of) an across-the-board increase; and
  • Prepare for wage negotiations with union representatives.
But surveys should never be regarded as a cure-all for the company's wage and salary problems. Many human and technical factors come into play that can undermine the usefulness of survey data and the conclusions or recommendations based on them. Incomplete data, for example, can do more harm than good. A wage and salary analyst who is not really up to the task may simply chart his company's pay rates against the rates obtained in a survey, and submit this chart to management without analyzing the company's position and recommending an appropriate course of action. Similarly, an analyst who doesn't really understand the purpose of the survey may end up pursuing the wrong objective.
Despite the evidence that wage and salary surveys can and do serve a number of valuable purposes, they have fallen into disfavor in a number of circles because of the ways in which they have been abused or misused in the past. Most of these abuses can be traced to the individual(s) who either conducted the survey or analyzed its findings. This is why a thorough grounding in the basics of survey selection and survey analysis is essential before the resulting data can be put to use.
Using professionally prepared surveys
One of the first decisions you'll have to make is whether to use one (or more) of the many professionally prepared surveys that are available or to conduct a survey of your own. Because conducting your own survey is a considerable undertaking, we will deal with prepared surveys first.
Obtaining these surveys is usually just a matter of calling associations, government agencies, and other organizations to find out what surveys are available. However, don't let the ease with which surveys may be obtained fool you into thinking that all available survey data is useful. You should screen the information carefully before taking any action on it.
In deciding what survey information to use, one of your primary concerns should be the "market" from which you wish to obtain data. For example, each work group within the company draws job applicants from its own market. For clerical employees, this market is probably defined by a reasonable commuting distance from your company's doors. Craft and semiskilled workers may be willing to commute a bit further, but they would be unlikely to relocate for a new job. However, higher-level employees-such as executives, engineers, and sales professionals-are drawn from a market that is at least regional and possibly national or international in scope.
It is obvious, then, that the market concept will limit the usefulness of some of the surveys that are available to you. If your firm is geographically centralized, you won't find a nationwide survey of clerical salaries very meaningful. So you will have to exercise judgment in determining which surveys to use. If 90 percent of your clerical employees live within 30 minutes commuting time from the company, it would make sense to seek out surveys that include salary data from firms located within this range.
Don't, however, overlook the fact that employees who commute 30 minutes to work could just as easily travel 30 minutes in another direction if pay scales at another firm were more advantageous. So you'll want to find surveys that cover firms beyond this 30-minute radius if you want to be certain you're getting data from the appropriate market. One other important point: don't forget that 30 minutes on a highway doesn't represent the same distance as 30 minutes on busy city streets.
What other considerations might influence your choice of a wage and salary survey? Here are some questions to ask yourself:
  • Are the companies that have participated in the survey about the same size as our company? (You don't want to end up comparing yourself to a few corporate giants.)
  • Does the survey cover jobs that are similar to those in our firm?
  • Are the survey findings affected by a few particularly high- or low-paying firms, or has the average company been given sufficient weight?
  • Do the participants have formal job evaluation and wage and salary administration programs, or do they set their rates arbitrarily?
  • Have any of our employees left the firm to go to work for other companies that have participated in the survey?
  • Have we hired many employees from these participating companies?
  • Does the survey cover at least some firms that we regard as competitors?
Your aim should be to select surveys of competitive companies within a relevant geographic area. The participants should all have sound wage and salary programs, and survey data should not be unduly influenced by a few large, progressive companies that can afford to pay more.
Professional surveys are conducted regularly by large employers, professional and consulting organizations, trade associations, and the government. See the links below for the surveys offered by the operator of this website, Business and Legal Reports Inc. (BLR)
Metropolitan-area chambers of commerce also conduct salary surveys, as do a number of state governments. For data targeted to specific industries, especially "exotic" or newly emerging industries, trade association surveys may be the only source of data.
Conducting Your Own Survey
The other approach, of course, is to design and conduct your own compensation survey. The big advantage here is that you can pick the companies who will participate in the survey, and thus you can be more certain of getting the type of data you want. But the collection and analysis of survey data is an expensive undertaking, and you should be sure that the benefits will outweigh the costs involved. If a "canned" survey developed by another organization will supply the data you need for decision-making purposes, there is little to be gained by going to all the trouble yourself-and possibly much to be lost through your lack of experience.
Most companies who perform their own surveys do so in order to remain competitive within the local area where they recruit their employees. A compensation survey of the area enables the company to know what rates of pay the local market demands, and to direct its efforts toward recruiting and retaining the best possible workers.
While this isn't the place to get involved in a detailed discussion of survey design and implementation, mention should be made of the fact that a good compensation survey requires both planning and expertise. A human resources manager with no experience in conducting such surveys cannot expect to elicit the needed information without doing a great deal of research and preferably obtaining some outside help. It is difficult enough to be sure you're getting accurate, unbiased information without having to worry that you've inadvertently undermined your own objectives. Your goal should be to obtain a true picture of the rewards being offered by all organizations competing in the labor market. A survey that limits itself to a particular industry, to companies of a certain size, to a sector of the economy (public or private), or to only a portion of the actual labor market will result in biased data that may cause compensation problems instead of clarifying or solving them.
There are legal pitfalls involved in collecting survey data yourself. In a federal case involving an association of local hospitals in Salt Lake City, the U. S. district court held that certain practices amounted to illegal wage-fixing and violated the antitrust laws. If you intend to call local firms in your industry for salary information on specific employee categories, ask yourself whether your inquiries are likely to have an anticompetitive effect. If so, you probably ought to consult competent legal counsel before making the first call.
Analyzing Survey Data
Analysis of survey data first requires the selection of jobs in the survey that are similar to those in the firm. Therefore, it is necessary to study the brief job descriptions provided with the survey, compare these to the firm's job descriptions, and reject those that are not well-related. For example, if the machinists in the survey are really machine operators while those in the firm both set up and operate, the jobs are not comparable. Some organizations that conduct wage and salary surveys will require that a wage analyst visit each participating company to assure that the data reported is for truly similar work, but the time and expense of this process precludes its use in most surveys. Nevertheless, brief, accurate job descriptions should be included in both the original survey questionnaire and the final survey results because comparison based on job titles alone is likely to be highly unreliable.
Once comparable jobs have been selected it is essential to be certain that the rates of pay reported in the survey are clearly defined. Base rates, as an illustration, should not include shift differentials, overtime rates, or other premium payments; also, comparison of incentive rates to regular rates should be avoided. The intention here is to eliminate as fully as possible the extraneous variables that will reduce the accuracy of the comparison.
From among the comparable jobs in the survey select a set of key or "benchmark" jobs for detailed analysis. These jobs should meet a number of criteria. In addition to being similar to jobs in the firm, the key jobs should be relatively stable in terms of job content and should be performed relatively similarly in surveyed firms-jobs such as clerk-typist, bookkeeper, plant guard, custodian, and truck driver tend to meet these criteria. Again, such careful job selection reduces extraneous variables that may cause wide fluctuations in rates of pay from one organization to the next.
Lastly, select surveyed jobs that are representative of the full range of work being performed in the firm. As an example, if the purpose of analyzing the survey is to review rates paid to nonexempt employees, jobs should be selected that cover a broad range of pay grades-as from clerk at the lowest level to executive secretary at the highest, with a representative sampling of those in between. They should also be selected from a number of different nonexempt job families, such as clerical, accounting, drafting, and data processing. Selection based on these criteria will assure the availability of data for comparison to most, if not all, nonexempt pay grades, and further assumes that the data will not be overly biased by labor shortages in one particular job family.
Making sense of the numbers
Once the surveys have been selected and the benchmark jobs picked out, it becomes necessary to choose the statistical measure upon which the comparisons will be based. Surveys typically report the following measures:
Mean: The average rate. The mean is the most sensitive measure of the central tendency of data because any variation in the data, especially any unusually high or low numbers, tends to be reflected in the resulting mean. The mean may be calculated for an entire population of employees in a particular job or for a subgroup, such as the middle 50 percent of the sample.
Median: That number which, when the data are arrayed from high to low, splits the data in half; in other words, that number that is larger than half the data and smaller than half the data. The median is a good measure of central tendency that is not greatly influenced by a few high or low numbers.
Mode: The number that appears most frequently. This measure is usually not of much use in wage survey analysis.
Middle 50 percent: Also termed the inter-quartile range, this measure is the range of data resulting from discarding the highest 25 percent and lowest 25 percent of the reported data.
For several reasons the ideal measure for survey comparison is the mean of the middle 50 percent of reported rates. The exclusion of the high and low quartiles eliminates from the data the trainees and persons who are grossly overpaid and with whom comparison is not desired anyway; this reduces the main drawback of the mean-its sensitivity to extremes-and yields the most accurate possible measure of central tendency for survey analysis.
By way of illustration, consider the following hypothetical array of reported survey data: $340, 340, 340, 350, 350, 350, 360, 360, 360, 360, 370, 380, 380, 380, 390, 420. The mean reported rate in this array is $364.38, which is somewhat higher than either the median of $360 or the mode, also $360. This discrepancy between the mean and the median results from the inclusion of a few very high rates, especially the one at $420. By excluding the highest and lowest 25 percent of the data, we reduce the range of the array, which is now $340 to $420, down to $350 to $380; the mean of this middle 50 percent range then becomes $361.25, which is considerably closer to the median, because of the elimination of the extreme rates.
If the mean of the middle 50 percent is not provided, then the mean of the total range of data should be used. The exception to this would be when the reported mean and median for the same job are quite different, indicating that a number of extreme rates are skewing the mean, in such case it is reasonable to use the median.
An additional point-it should be recognized that survey data are often published months after being collected. In some Bureau of Labor Statistics surveys, for instance, the survey may not be made available until as long as nine months after the data were collected, and rates of pay in the market will of course have changed in that time. One way to deal with this lag for the short period is to update the survey data in proportion to the change in the cost of living, as measured by the Consumer Price Index (CPI). In this way survey data several months old may be made usable, as increases in rates of pay tend to be fairly closely correlated to increases in the CPI.
A final consideration is the possible impact of the firm's participation in the survey on the reported statistical measure. The firm obviously desires not to compare itself to itself, but rather to other firms; therefore, if the firm participated in the survey, its rates should be deleted from the reported survey data before a comparison is made. This can be done in several ways; a simplified approach is demonstrated in the following example:
  • Assume the survey reports a mean weekly salary for 121 clerk-typists of $314.
  • Also assume that included in those 121 clerk-typists are 13 from your firm, for whom a mean rate of $306 was reported at the time the survey was taken.
  • The mean salary for the companies excluding your firm may be calculated as follows:
The total number of employees times their mean, divided by the number of employees reported by the other companies,
or:
121 ($314)-13($306) =315
108
In the example given, the mean of the rates reported by companies not including your firm would thus be $315. Where the number of employees reported by a particular firm is a small proportion of the total, the impact of the firm's rates will be minimal. Nevertheless, this potential impact should be considered and dealt with if necessary.
Summarizing the Survey Data
Generally speaking, a good place to begin a detailed statistical analysis would be a simple summary, as shown in the table below, which reflects the figures resulting from abstracting data from the survey.
Labor Grade Firm's Job
Evaluation Points
Benchmark Job title Weekly Pay
(Survey Data)
21 320 Clerk $381
22 345 Data Entry Operator $386
23 440 Clerk-Typist $412
24 550 Junior accounting Clerk $428
24 565 Payroll Clerk $470
25 675 Junior Drafter $473
25 745 Secretary B $478
26 850 Purchasing Expeditor $486
27 1000 Secretary A $490
27 1090 Senior Clerk $498
27 1120 Senior Accounting Clerk $502
28 1250 Senior Drafter $542
29 1350 Executive Secretary $569
From this summary you can prepare a "scatter chart" or "scattergram" that shows job evaluation points and labor grades along the bottom axis and survey dollar values on the vertical axis. Dots representing various benchmark jobs are plotted on the chart by finding the proper number of evaluation points along the bottom or x-axis and then moving vertically up the y-axis to the appropriate survey wage. Each dot, as can be seen in the scattergram, can be said to represent the relationship between what the company feels the job is worth internally (job evaluation points) and what is being paid for similar work in the labor market (survey dollar values).
The higher the internal job evaluation points are, the higher the surveyed dollar rate tends to be. Such a relationship is to be expected and is a means of verifying the accuracy of the evaluation process. If the points got higher as the survey dollar values got lower, this would certainly be an indication that something was wrong. Even more clearly than the summary table, however, the scattergram demonstrates that as the evaluation points rise, so do the dollar values in the labor market, but with some variance.
The next objective is to find the one, single straight line that when drawn through the dots will be the average of all the data. This form of analysis can best be done using a statistical procedure known as a "least-squares conversion." The exact steps to be followed are described in most books on statistics. However, a high degree of accuracy can be obtained simply by looking at the data and fitting a line through the dots carefully with a ruler.
This line represents the average relationship between internal job worth as measured in job evaluation points, and external job worth as measured by labor market surveys. In the jargon of wage and salary administration it is called the "community wage curve." When an employer states that it pays wages "equal to or better than the going rate in the community," this line represents that promise. To be more precise, if the organization wants to pay its employees the going rate, it will use this line, which represents the average pay in other firms for similar work, to determine how much its "average" employees will be paid.
A line is drawn horizontally at the point where each labor grade intersects the community wage curve. This line will become the midpoint of the rate range for each grade. Now for some definitions:
Midpoint: is the going rate in the salary survey sample and the rate that will be established for the employee performing 100 percent of the job duties at 100 percent efficiency under normal supervision. It should be halfway between the minimum and the maximum.
Minimum rate: is the level of pay to which an employee who meets the minimum qualifications for the job is entitled (depending on company policy, this may mean the ability to perform 75 percent of the job duties at 75 percent efficiency, under normal supervision).
Maximum rate: is the highest rate to be paid for work in the labor grade. Normally this would be paid only to a person who performs duties well beyond those called for in the job description, at the highest possible efficiency under little supervision
Spread: is the distance between the minimum rate and the maximum rate, expressed as a percentage of the midpoint. In other words,
Spread= Maximum-Minimum

Midpoint

If you want a 30 percent spread for a grade with a midpoint of $400, then .30 x $400 = $120, thus the minimum rate will be $340 and the maximum rate $460. There is no rule as to how great the spread must be; however, these guidelines may be of help: First, there is probably no job that requires a spread of more than 50 percent. Second, as a starting point, use this formula as a guide to setting the spreads: Convert the midpoint to a weekly rate, add 100 to it, divide by 1,000, and multiply that amount times the midpoint to get the spread. For example, with a grade that has a midpoint of $360, add 100 to it (460), divide by 1,000 (.46), and multiply that times the midpoint (.46 x 360 = $166). This amount is the distance between the minimum and the maximum, resulting in a rate range that looks like this:
Minimum Midpoint Maximum
$277 $360 $443
At first this may appear to be a complicated procedure, but it gets easier with experience and it works well.
This greater distance between the minimum and the maximum is necessary because promotions come less often to persons in higher grades, and a wider spread is needed to offer these individuals incentives over a longer period of time. Also, there is a wider range of performance exhibited in the upper grades; to illustrate, the difference between the worst performance of a clerk and the best performance is not really all that great but the difference between the best and worst executive secretary is significant, and the rewards for varying levels of performance must be built into the rate structure.
To implement the structure, all existing employees can be plotted in on the rate range chart. That is, for each employee, a dot is placed on the chart that corresponds to the evaluation point score of the job he or she is performing and the actual rate of pay received. This will inevitably result in two problems: Blue-circle rates, or dots representing employees paid below the minimums just established, and red-circle rates, or dots showing employees paid above the maximum. Blue-circle rates are easy to deal with; over a period of time, the employee's pay is raised to the point where it equals the position in the rate range that corresponds to the employee's actual performance.
Red-circle rates are another story. Obviously, cutting the pay of an employee will not do much to gain acceptance for the new wage program, so other alternatives have to be considered. One is to "grandfather" the employee; this means allowing the employee to stay above the maximum until the person is promoted, terminated, or retired. Another approach is to freeze the employee at that red-circle rate until adjustments to the rate range finally capture the employee's rate back into the structure. Still another approach is to increase the employee's wage by only half of the adjustments made to the range, again until the rate is recaptured.
A similar problem exists with employees who are under- or overpaid in relation to actual performance. As defined above, the minimum, midpoint, and maximum rates are each definitions of pay for specific levels of performance. So if an employee who performs 100 percent of the job duties at 100 percent efficiency under normal supervision is paid above the midpoint, this is similar to a red-circle rate except that it is within the rate range. In this case, counseling and performance evaluation feedback are needed to bring performance in line with pay.
A final consideration in job pricing is maintenance of the rate structure. When the inflation rate is high, rate ranges go out of date very quickly. The range that was established a year ago may no longer be effective in recruiting and retaining employees, and it must therefore be updated. This should be done by analyzing wage surveys on a continuous basis; when the community wage curve described above starts to move above the established midpoints of the rate ranges, it's time to think about adjusting the structure. Another item to watch is the cost of living. This is usually monitored through the Consumer Price Index published monthly by the Bureau of Labor Statistics of the U.S. Department of Labor; figures are made available on the United States as a whole and for certain geographic areas within the country. Two other measures that may be even more directly related to the actual impact of inflation on employees are the Producer Price Index and the Gross Domestic Product Chain-Weighted Index. Each of these measures has its pros and cons, but the CPI is the most universally recognized and widely used.
Adjustments made to rate ranges should be done on a percentage basis rather than by adding a certain number of dollars to each range. This is because the percentage approach maintains the original relationship between grades. For example, if the midpoint of grade 21 is $385 and that of grade 22 is $410, this is a difference of about 6.5 percent. If we increase these midpoints over time by $18 this year, $20 the next year, and so on, eventually the midpoint of grade 21 will be, say, $445 and grade 22, $470. The difference will have shrunken to only 5.6 percent. This is called "wage compression." Eventually there will be so little difference between grades that there will be no incentive for employees to seek promotion. On the other hand, if instead of adding dollars to the ranges we increase them by percentage points, then when the midpoint of grade 22 has reached $470, that of grade 21 will be $436, thus retaining the 6.5 percent differential we established in the beginning.
Job Pricing and Pay Equity
Even from this brief explanation of how most employers decide what to pay for certain jobs, it can be seen that "market rates" play a major role in wage determination. Some people believe that this process of comparing jobs in the company to the community wage structure imports community biases-most commonly, biases against women and members of racial minorities-into the wage structure of the company. Conversely, if an employer who has allowed discriminatory attitudes to creep into the wage determination process participates in a compensation survey, this bias will in turn become part of the community wage structure. In other words, by using local wage and salary surveys in calculating wages and by contributing to them regularly, employers in some communities are simply reinforcing existing biases in the labor market.
While this view may have some validity, the fact remains that wage and salary surveys are among the most reliable methods of pricing jobs. And since no one has yet come up with a means of eliminating the bias that appears to be built into much of our economic system, it seems likely that market rates will continue to play a significant role in job pricing. What, then, is the concerned and perhaps even legally vulnerable employer to do about it?
One strategy is to go beyond market studies in establishing internal wage structures. Most employers have some form of job evaluation, and this has emerged as an effective defense against pay bias. Focused efforts in this area can avoid complaints of pay inequity and prove to employees who may have suffered disadvantages in the marketplace that you are sincere in wanting to pay them what they're really worth. If you choose your compensable factors in a nondiscriminatory way, and if you evaluate jobs in the same way regardless of the predominant sex or race of the job-holders, you will bring about a degree of pay equity that employees can recognize and respect.
Activists in this area hope that by concentrating employers' attention on job analysis and job evaluation programs, much of the existing bias can be removed from corporate wage structures And they hope that eventually this trend will be picked up by community or industry wage surveys. In fact, this has been happening gradually as the pay equity movement has matured, and the gap between the pay rates of men and women, on the one hand, and whites and non-whites, on the other, seems to be narrowing with each passing year.
Other Salary Center Resources
Grade A Job - Can’t find survey data for a unique job? Use this tool to determine rate range pay scale for any job. Simply score the job on nine (1-9) standard factors to determine its pay grade. Then, apply your demographic selections to determine relevant and current ranges for that job.
Salary Finder - Online Salary Finder provides you with the resources to search and access more than 2,400 jobs at the national, state, and local level, as well as for hundreds of different industries.
Merit Increases - Determine what other organizations are budgeting for merit increases. BLR conducts an annual survey of over 1,100 organizations to provide you with the information you need to develop your merit increase budget for the coming year.
My Custom Reports - Create and save benchmark salary data reports the way you want them. Reports can include data for multiple jobs, metros, states, and industries, all downloadable to Excel.
My Saved Jobs - Save salary data for specific jobs and demographic profiles generated using the Salary Finder. Keep a library of positions you evaluated using the Grade a Job tool you can retrieve and compare positions
My Demographic Profiles - Create and save multiple combinations of industry, company size and geographic selections relevant to your company. View, sort, and edit all your company’s saved demographic profiles.
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