Lecture Notes
Okay so we have covered internally consistent job structures and will now turn to chapter 7 which is Building Market Competitive Compensation Systems. There are four objectives that we will address regarding this topic. The first is to explain the concept of market competitive compensation systems and summarize the four activities that compensation professionals engage and to create the systems. Second, we'll discuss compensation survey practices. Third, we’ll describe how compensation professionals integrate internal job structures with external market pay rates. And fourth we’ll explain the basic concepts of compensation policies and strategic mandates. That is will be looking at pay mix and pay level.
Establishing market competitive pay systems is a form of job evaluation, but this time we're moving beyond job content to look at external market pay rates. So what are market competitive pay systems? That's learning objective one, see slides 3 through 6. Well, market competitive pay systems refer to a company's compensation policy. It refers to the imperatives of competitive advantage and the key role in promoting recruitment and retention of talented employees. There are four steps that compensation professionals can undertake to develop market competitive pay systems, and some of these apply as well to other areas of human resources. So the first, conduct strategic analyses and this is something that we would hope that other areas of HR are looking at. We want to then assess competitors’ pay practices and with that information, integrate our internal job structures so what we looked at in the previous chapter, internal consistency, we want to integrate those with external market pay rates and then we want to conclude with a determination of compensation policies.
So now let's give some thought to, in a bit more detail, to these four activities. The first is strategic analysis. This is something that you should think about with regard to your company, your company as context. Also if you're interested in other companies, you can conduct some research through Google searches to help gather some of this information to give you a picture of a company's strategic position. Strategic analysis entails an examination of the companies’ external market contacts and internal factors. Examples of external context are industry profile, information on the competitors, long term industry prospects. We also consider internal factors such as the company's financial condition and its functional capabilities. That is if it's a manufacturing organization, does it have sufficiently highly skilled employees who can function appropriately in high tech manufacturing environment.
With regard to compensation surveys, we’re interested in collecting and analyzing competitors’ compensation data. Then we want to integrate the internal structure with the external market pay rates identified through compensation surveys and this will also require some analysis. And then compensation professionals recommend pay policies that fit with their companies standing and competitive strategies. Second learning objective focuses on compensation surveys. The information can be found on slides 7 through 28. We're devoting a substantial amount of time in the textbook and in the slides to compensation surveys because these represent the foundation of sound and effective market competitive pay systems.
So to start off with this, we had one of the main considerations is whether we want to develop the survey ourselves or use an existing compensation survey. We also want to make decisions about what information we're interested in assessing. So typically we are looking to collect data on base pay, incentive award structure and the mix in level of discretionary employee benefits. To custom develop these surveys requires a great amount of expertise and usually this is not something you find within many companies. So you will see many companies going to external sources to obtain compensation survey data and what are some of the sources? We can look toward information from professional associations. Professional associations often have compensation survey data that they share with its member organizations and individual members of the organization. Members are more likely to provide information in anonymous surveys to their professional associations because they all have a common interest in understanding what the compensation pay rates and structures are in a particular profession. Companies are interested in learning this information to help them structure competitive pay rates to get and keep the best employees and individuals are interested in learning what the competitive pay rates are so that as they seek employment, they understand their market value. There are many different professional associations that we can find specialized in particular occupational groups, such as engineers and even more in particular, chemical engineers as an example, and in industry association whose members are companies. So for example there is the American iron and steel institute comprised of 31 member companies including integrated and electric furnace steel makers. You can go to industryweek.com to find a long list of associations, especially in the manufacturing industry. Consulting firms represent another source of compensation survey information. The textbook and slide 11 provide a list of consulting firms that specialize in compensation. These firms are very well-known and keep in mind that they are very expensive.
Typically, you find large corporations with the resources to purchase data and survey results from these consulting firms. Other companies with fewer resources and even large companies that choose not to pursue the services of consulting firms might rely on data that are free. And that is we can find a wealth of information about compensation practices in the U. S. bureau of labor statistics website. The federal government publishes all things regarding labor in its US bureau of labor statistics. You may recall from the statistics course, the data analysis project that I asked you to complete in groups. I provided data sets which I extracted from various U. S. bureau of labor statistics surveys. In the area of compensation, there is a wealth of data. There are data available for wages, earnings and employee benefits. You can find the surveys on the U. S. bureau of labor statistics website. Examples are employment cost trends, national compensation, survey data, wages by area and occupation earnings by demographics, industry, county, all kinds of information about the prevalence costs and types of employee benefits offered by companies. And there is some data unfortunately not as updated as I would like to see, on compensation costs in other countries. When you have time, you should go to the bureau of labor statistics website to review what is available, become familiar with it because you may find that those data are very useful. You'll find in those surveys summary tables and you will also, in many cases, be able to download the raw data from those sites at no cost. All of this described within each survey site in the bureau of labor statistics.
The textbook also provides a brief summary of each of the surveys that I mentioned. So for example the compensation cost trends survey publishes quarterly statistics that measure changes in labor costs over time such as the employment cost index. So what is the change in employment costs over a quarterly period of time? And you can also find levels of costs per hours for employee compensation. The best way to learn what these surveys have to offer is to immerse yourself in them rather than my describing them in this pre-recorded lecture and of course I'm always happy to answer your questions about them. As we select surveys we want to give consideration to the relevant labor market and benchmark jobs. Regarding the relevant labor market, we're referring to: where do you find the qualified candidates based on occupational classification, geography, and market competitors.
Benchmark jobs are used to help us link our internal job structures with external market pay rates. We're never going to find a job for job match between any one company's job structure and the external market. So we rely on these benchmark jobs as established, well-known and stable jobs that we find in the market that are typically common across employers that represent the entire range of jobs in different occupational groupings that we will accept for setting pay rates within our company. And even when we find benchmark jobs, we have to be very careful not to simply match those jobs with jobs within our company. Because there are likely to be subtle and even substantial differences in many cases between how we need to find a job within our company and how the benchmark jobs tend to be described in compensation surveys. So this requires going beyond job titles to looking at job descriptions.
Now in surveys there should job description information and you have job description information in your company. With that information we need to engage in a process called job leveling. As I mentioned there are differences between a company's jobs and benchmark jobs. We need to make corrections for these differences and we rely on our judgment to do so. The process for making these corrections is referred to as job leveling and there is a specific type called point level factor job leveling. You can find the example of this on slide 20. The U. S. bureau of labor statistics provides an excellent resource that addresses job leveling in detail. You can find the reference for the source on slide 20 and in the textbook.
Not surprisingly, surveys contain a lot of data, so much data that eyeballing it provides no insights into what they mean. Also we have to keep in mind that when we obtain survey data it's already outdated. We are going to be interested and planning compensation for some future period and we’ll have to rely on some techniques to project ways to make the data relevant for future periods of time. All of this requires that we call on statistical analyses to make sense of these data and to make these adjustments. I won't describe them here but we start off with descriptive statistics and that helps us to summarize the survey data. As you know from the statistics class we can talk about two descriptive properties of data, central tendency and variation. You can look at slides 23 through 27 up to refresh your memory of these descriptive statistics. The textbook also provides information on these measures. As I mentioned a few moments ago salary survey data are old, they’re historical data once we get our hands on them. And compensation professionals are planning for a future period of time. So we are interested in ensuring that our pay rates are not only current at the beginning of the plan year, but also over the course of the plan year. And by the way compensation professionals usually establish compensation plans for a one-year period.
So on slide 28, There is brief review of the consumer price index, the CPI. The U. S. bureau of labor statistics publishes the CPI which is an index of the cost change in goods and services over time. For the entire United States as well as for regions within the United States. Please look at the textbook for brief descriptions of the CPI and their calculations that help you to understand how we can update our salary survey data to project relevance between the start and end of our compensation plan. As always if you have questions I'll be glad to answer them. The consumer price index helps us to make these adjustments. Our interest with it is to consider inflation. Over time we see that the cost of goods and services increase and we want compensation to have the same purchasing power over time. But the CPI is not the only basis for determining adjustments to salary survey data. For example, I was reading an article in the Wall Street Journal that talked about how law firms usually agree to a starting pay rate for first year law associates. For some period of time it was $160,000. Now law firms are considering increasing that amount $180,000. So information from sources other than the consumer price index, can help compensation professionals make adjustments or future pay rates in order to be competitive. I should note that I said that law firms agree to a starting pay rate and that's not exactly true and in fact that might be a form of collusion. Rather, a law firm might decide to increase the rate for a variety of reasons and other law firms can choose to follow and in many cases law firms will do this in order to be competitive.
Now that we have collected our compensation survey data and we've been able to describe it and update it, it's now time to move toward integrating our internal job structure, based on the job evaluation process with these external market pay rates. So our goal is to set pay rates based on the matches between a company's job structure and corresponding benchmark jobs in the external market. This is learning objectives 3 and slides 29 through 33 contain the information. Descriptive statistics usually focus on one variable. So average pay rate in the engineering profession. So one variable, pay rate. Now that we move on to integration, we are introducing the analysis of multiple variables simultaneously. And we rely on regression analysis techniques to do this. As you know, regression analysis is the statistical procedure designed to find the best fitting line between two variables.
Slide 30shows us the basic formula for simple linear regression, that is one independent variable. You can see here what the variables are. We are trying to predict salary based on all kinds of compensation survey data that we've collected. And we predict salary based on job evaluation points. Two other elements of regression equations are the Y intercept, that is the value of Y when x equals 0. In this case when we don’t have a job that's being captured. No job is worth 0 points. And the slope, which is the pitch of the regression line.
Slides 31 and 32 give an illustration of the result of a regression analysis. You could see that for a hypothetical structure involving accounting jobs, so the horizontal axis, and those numbers are job evaluation points. And the Y axis or vertical axis shows the market pay rates. And that regression analysis allows us to summarize the correspondence between our internal job structure, so the variation in job evaluation points with the variation and market pay rates for benchmark jobs. The market pay line is the regression equation that comes from the analysis. And we can predict or say that the typical pay rate for a job in this example of 500 points, is approximately $38,000. We can look at like 32 to compute various values to determine what the typical pay rate should be for a job in our company based on its job evaluation points.
In the statistics course we also studied the r^2 statistic which goes along with regression analysis. As you may remember as well r^2 explains the variation and market pay rates via job structure. So let me back that up, that's the application here. But we are trying to explain the variation in the Y variable based on variation in the X variable. So our Y variable, market pay. Our X variable, job evaluation points. R^2 ranges from 0 to +1, where 0 means that 0 variation and pay rates can be explained by job structure. A value of 1 indicates that entire variation and market pay rates can be explained by our job structure. And then we could see values in between. I've indicated some ranges here and given them labels. So for example 0 to 3.30 for our square represents small variation. These are conventional interpretations. We don't want to spend time trying to say that there is a big difference between an r^2 of .36 an r^2 of .38, so we bracket them up into convenient ranges. The goal in our analysis is to achieve anr^2 that's as high as possible. If you can find something that's at least 0.7, then you've done a good job. We want r^2 to be as high as possible because we are planning to set our pay rates and pay ranges and reference to the marketplace. If r^2 is low, then we're not finding a very good correspondence between how we value jobs and how the market is valuing jobs. Often times, a low r^2 can be the result of poor selection in benchmark jobs and connecting them with our jobs internally.
Learning objective four, addresses compensation policies and strategic mandates. This information can be found on slides 34 through 37. Compensation policies are broken down into two subsets. The first, pay level policies. And the second, pay mix policies. Pay level policies are usually described in one of three ways. We can have a market lead policy, a match, or lag policy. We have to quantify what we mean by those labels and in compensation typically market lead policies are referenced at the 75th percentile. That means that on average 75% of the salary survey rates are below the rate that you are setting in your company. Or you could say that you are in the top 25% of pay. Companies have to make choices based on how critical jobs are to the company, based on supply and demand when determining what the pay level policies should be. This is useful information but when we move to recognizing employee contributions, we’ll be expanding on pay level policies by building pay ranges.
Pay mixed policies, and you could see an example on slide 37, tells us that for every dollar that we spend to compensate an employee, and here I'm referring to total compensation, benefits, wages and the different ways that we can reward employees such as base pay and incentive pay. So for every dollar we spend, what percentage of that is going to these various components. Note that the benefits expenditure is approximately 27%. That's a fairly typical number. If you were to go to the employer costs for employee compensation survey on the U. S. bureau of labor statistics website, you will see that typically companies are spending around 30% of their compensation dollars to provide employee benefits. When we get to employee benefits later in the course we will talk about some of the breakdown in costs of various benefits components. But overall the amount is roughly 30%. To be competitive, companies will usually start off by matching the typical benefits expenditure on a per employee per hour worked basis. Then, in allocating the remaining amount of money, it’s important for compensation professionals to go back to the job description and look at the expectations that are being set for the employee and how can we motivate them to excel. So when we talked about seniority pay for example, that has the potential to lead to employee complacency because as long as they're providing a performance at some reasonable level, they will get a pay increase just because they've been there over time. Merit pay requires employees to perform and so does incentive pay. We might consider incentive pay when we can measure job performance objectively or some part of it objectively. We can find the mix perhaps between merit pay that will sit well with subjective measures and incentive pay for objective performance measures.
I should mention that when we discuss pay level policies and pay mixed policies, we are likely to have more than one set of these within a company. And oftentimes we will find these paired and attached to different job structures. As you've read about, we create jobs structures for similar types of jobs, for example accounting or engineering where we can see a progression in the degree of fundamental compensable factors across jobs. And based on those differences and job duties and expectations, we're likely to see differences and what is needed to attract and retain employees, so thinking about pay level, and the mix of pay in order to help motivate them and direct them toward excellence. Well this concludes the pre-recorded session for internal consistency, that leads to job structures and market competitiveness. In the next pre-recorded session, we will talk about structures that help us to recognize employee contributions. We will build upon everything that we talked about in this pre-recorded session to build those structures.
