Compensation Force

Gas Prices Spike: How Employers in One State are Responding

The Employers Association here in lovely Minnesota has conducted research of employers statewide to learn whether and how they are responding to the high cost of fuel.  Nearly 500 companies responded to the very detailed study.   Guessing that what's happening here probably mirrors trends around the country, I thought the results might be of broader interest and worth a post.  Here goes.

Responding strategies are listed below in order of their prevalence among the surveyed group.

Condensed work weeks.  The most common strategy cited by surveyed employers is a move to a condensed work week.  18.8% are already providing a condensed work week and 5.5% are in the planning phase of such a move.

Telecommuting.  Nearly as common as the condensed work week is the move to offer telecommuting.  18.6% of responding employers have a telecommuting program in place and another 5.1% are planning to implement such a program.

Gas cards as rewards.  Interestingly, a number of employers are using gas cards as service or performance rewards - or, in some cases, as a simple form of subsidy.  The survey doesn't, unfortunately, separate those using cards as rewards from those using them simply as across-the-board subsidies, but 9.0% are already using the cards and another 8.0% are heading in that direction.

Car pools.  The promotion of car pools is rising with 8.4% of employers reporting car pool programs in place and another 4.9% planning to implement car pooling.

Public transportation subsidy.  Currently 6.9% provide a public transportation subsidy and 1.4% are planning to put such a subsidy in place.

IRS Section 132.  Pre-tax payment for certain parking and public transportation costs is available through an employer sponsored plan.  Responses indicate that 6.1% of employers have such a plan and another 1.4% are moving toward providing one.

Direct fuel subsidies.  A small number, 2.7%, of employers surveyed are responding to the rise in fuel costs by directly subsidizing employees fuel expenses to and from work.

Honorable mention (miscellaneous).  A number of other interesting tactics were mentioned by individual responding employers, including: 

• Flex start and end times to avoid peak traffic
• At work pot luck for lunch (purchased a grill for employees) to avoid the need for travel
• Collective lunch runs – take orders and drive one vehicle
• Review travel plans relating to client visits and consolidate meeting times with staff from other departments in order to facilitate car pooling
• Use a company provided fund-raising discount card to save $0.03 per gallon
• Use a small number of company vehicles that employees can use for business travel during the work day
• Subsidize bike lockers or install secure bike parking

Creative Common Photo "Pumping Gas" by Future Atlas

Internet Pay Data: Beyond the Question of Transparency

The democratization of pay information has happened.  Internet pay data is here to stay.  That's a fact.  It is also a fact that this presents a challenge to those of us in HR and compensation positions, as we respond to the questions, demands and - yes - complaints of information-empowered employees.

Several of my favorite bloggers in the HR space (including John Hollon at the Business of Management and Kris Dunn at the HR Capitalist) have posted recently on the topic of Internet pay transparency, particularly in the wake of yet another entry (Glassdoor.com) to the growing list of Internet pay sites.  After a bit of reflection, and coming to the party late as usual, I thought I'd toss in my two cents.

Having been both an employee and a job seeker, I can't deny the value of having access to pay information in order to guide one's employment choices and decisions.  But, and this is a big but, it is important for all parties to recognize that there is a difference between the kind of pay information that employees can access for free on the Internet and the kind of pay information that most employers bank on in reviewing and setting their pay programs and practices.  Most of the survey data that is used and relied upon by employers reveals - for example - not only the timing and method of data collection, but also the number of companies and employees represented in the data for each position and the organizations who submitted data (along with their demographics in terms of size, location, industry, etc.).  Most of the survey data used and relied upon by employers typically relies on data collection via an independent and valid source (like a Human Resources department) - not self reporting by the job incumbents themselves.  And, yes, most of the survey data used and relied upon by employers typically costs money.  Sometimes a lot of money. 

With employee compensation being, for most organizations, a major cost of doing business, it behooves them to make the investments (read survey purchases) necessary to ensure that pay decisions are made based on a valid, accurate and appropriate set of information.  Further, it is the employer's right and responsibility to determine what data it will use and how it will set its practices relative to that data.  Of course, the employer bears the risks associated with any poor decisions or choices in this regard (e.g., paying above or below market norms without a sound rationale for doing so).

And so the parties in this employment relationship find themselves in the situation of relying on two different sets of data, which might (and, in my experience, often does) lead to different conclusions about pay.  What to do?  Really, I think you are best served dealing with it head on and having an honest, adult discussion with the employee about how - and why - their information may be different than that which the company uses.

Transparency is only one part of the challenge presented by the growing abundance of internet pay data; it also involves understanding and reconciling differences in the nature and precision of data typically used by employees versus employers. 

Eliminating Pay as a Reason for IT (or Other) Staff to Leave

In conjunction with Computer World's 2008 100 Best Places to Work in IT study, columnist Frank Hayes shares his thoughts on the top reasons that IT staff would want to leave and his recommendations on what to do about them.  Pay - particularly low pay - tops his list:

There may not be a lot you can do about salaries and raises; they're probably watched like a hawk by your chief financial officer. But you have options. Example: Stop using your bonus pool as a way of supplementing salaries across the board. Instead, pay much bigger bonuses to fewer people for specific, publicly recognized accomplishments. Suddenly, a bonus means something. Everybody on your staff won't hit the jackpot, but everyone will have a chance – based on what he accomplishes.

Good advice methinks.  And not just for your IT staff.

Voodoo Pay Management - or the Perils of Using Structure Data to Track the Market

In yesterday's post on aging survey data, I advised against using structure adjustment data as the basis for aging.  I thought it worth a follow-up post to expand on this topic and share what I believe are the perils associated with using structure and structure adjustment data to manage your salary program.

A quick pause for definitions:

By structure, I mean the salary ranges or schedules used to manage base pay.

By structure adjustment, I mean the amount by which that set of ranges or schedules is adjusted upward, typically on an annual basis, in response to competitive trends.

Structure and structure adjustment data is often offered by surveys in addition to data on actual salaries or actual salary increases.  The key difference?  Structure data represents policy, where salary data represents actual practice.

I think this distinction is an important one.  Having practiced in this field long enough to see how a wide range of organizations actually manage pay, I can tell you that there may be sizable discrepancies between policy and actual practice.  A couple of extreme (but very real) examples to illustrate my point:

Organization A - This organization is facing financial challenges, which have translated into a struggle to keep employee pay competitive.  The organization has faithfully reviewed and adjusted its salary ranges every year, so that they are kept at market levels, but has lagged behind in delivering employee increases.  The result is that while their ranges (as evidenced by their midpoints) are competitive, actual salaries are very low in comparison to both ranges and the external market.  And so, you see, their structure tells a very different story about their pay program and practives than their actual salaries do.

Organization B - This organization has been in business for over 50 years in a relatively stable industry.  Turnover is low to nonexistent, and the average employee has been in their job for over 8 years.  The organization, because it has not experienced much competitive pressure for people, has chosen to manage its salary program and ranges at the lower end of market practices.  Employees, though, being such a long-tenured group, tend to be paid at or near (or even over) the top of their assigned ranges.  Here again, the organization's structure might tell you a very different story about the pay program and practices than their actual salaries would.

My point?  Structure data (e.g., average minimums, midpoints and maximums) and structure adjustment data (how much the average organization has moved its structure) can paint a very different - and even misleading - picture of market pay practices in comparison to using actual salary data.  Salary data - actual salaries and salary increase percents - tell you what's really being done, regardless of what kind of policy and structure posturing might be happening. 

Better to base your analysis and decisions on reality - what and how people are really being paid.  Pay decisions based on anything else ... well, my title speaks for itself!

Aging Survey Data is About Mimicking Market Pay (Not Structure) Movement

Reader Christine asks about the best way to age survey data; whether to use salary structure movement or salary (merit) increase budgets as the basis for aging.

Aging survey data, for the uninitiated, is the process used to update or bring the survey data forward, covering the gap between its actual effective date and the date you need to apply it.  Because most pay surveys are conducted on a periodic basis (the most prevalent schedule still being an annual one) and because in most cases there is a gap - minimally - between the collection/effective date and the date of survey publication, the need to age the survey data is simply an accepted fact of life.

The question that Christine poses, then, is what rate to use in aging the data.  It's a good question, since most salary planning surveys give you both sets of data (salary increases and structure adjustments) to select from. 

Since our ultimate objective is to mimic the rate at which market pay is moving, using the average salary increase amount or salary increase budget is a better indicator of how much the average employee's salary is moving in a year.  Average structure adjustments, on the other hand, reflect the degree to which organizations are moving their pay ranges in order to keep them competitive, which can and often does differ from the average increase planned or delivered.  My experience in watching this data over time would suggest that, on average, structure adjustment numbers tend to run at 60%-70% of salary increase numbers.  Using structure adjustment rates to age your survey data, therefore, puts you at risk of underestimating actual market pay growth.

(In fact, I would argue that structure adjustment data, while certainly interesting, ought to be disregarded entirely when making pay programs decisions, including how much to adjust your own salary structure(s).  Pinning your salary range movement to a rate that lags actual salary movement by 30% to 40% will ultimately leave you with a structure that lags the market.  But perhaps that's a topic for another post.)

My advice in summary: Use salary increase - not structure adjustment - numbers as your rate for aging survey data to ensure that you are simulating market pay movement as accurately as possible.