U.S. Economy – Page 8 – Economic Thinking In Action

Time clock rounding analysis in wage and hour/FLSA case example

(Work in progress…)

An example of a time clock rounding analysis in a wage and hour case. In this case, we describe a case example involving a large mid western employer. The data utilized in this analysis is the time data received for the February 28, 2003 to December 18, 2011 time period. The data contained 66,452 records.

In this wage and hour time rounding case the defendant and plaintiff disagree on a number of key data issues. One party states, that in his analysis “all 66,452 shifts described in the data set were considered.” The other party states that this statement is completely incorrect use of the data in this case. First and foremost, they argue that there are 13,877 records which do not have any rounded time entries or punch time entries. It appears as though one party utilized these records in his calculations of percentage

In those records where there are no time entries, the record would appear to have neutral rounding (that is, blank compared to blank). Including these records in the data artificially increases the number of neutral rounding. One party argues that this is especially problematic because the opposing expert includes the neutral rounding in with the rounding in one party’s favor, which distorts the results.

Second, parties argue that there are an additional 7,089 records with inappropriate pay code names that should not be included in the meal or rounding analyses. These codes have duplicate entries of the time data, no hours paid, or have $0 associated with them in the pay data.

Third, further analysis showed that there are an additional 8,245 records that have duplicate entries for the start time, end time, and punch times from other records on the same days. These records also contain paid hours that would need to be included in determining the total number of hours paid in a particular day. For these records, the number of hours paid should be included in the total number of hours paid for that day. However, the parties argue the rounded time and actual time worked should not include the duplicated time records for these days.

After the three cuts described above, one side argues that the remaining 35,000 or so records are the appropriate starting point for the analysis. The parties argue that utilizing the data cuts results in drastically different results in the time clock rounding analysis.

Definitions:
1. Total rounded time is calculated from the start and end times in the data. Total actual time is calculated from the punch in and out times in the data. The amount of time that was rounded is calculated by comparing the rounded time to the actual time worked.
2. The percent of punch sets with time gained is the number of instances where the punch set showed a rounding in the employees’ favor, divided by the total number of punch sets. Whereas the percent of punch sets with time lost is the number of instances where the punch set showed a rounding in the employers’ favor, divided by the total number of punch sets.
1. Time gained due to rounding is the total amount of time rounded in instances where the punch set showed a rounding in the employees’ favor. Time lost due to rounding is the total amount of time rounded in instances where the punch set showed a rounding in the employers’ favor. Net time gained / lost due to rounding is the sum of time gained and time lost.

Time clock rounding analysis in wage and hour/FLSA case example

(Work in progress…)

Definitions:
1. Total rounded time is calculated from the start and end times in the data. Total actual time is calculated from the punch in and out times in the data. The amount of time that was rounded is calculated by comparing the rounded time to the actual time worked.
2. The percent of punch sets with time gained is the number of instances where the punch set showed a rounding in the employees’ favor, divided by the total number of punch sets. Whereas the percent of punch sets with time lost is the number of instances where the punch set showed a rounding in the employers’ favor, divided by the total number of punch sets.
1. Time gained due to rounding is the total amount of time rounded in instances where the punch set showed a rounding in the employees’ favor. Time lost due to rounding is the total amount of time rounded in instances where the punch set showed a rounding in the employers’ favor. Net time gained / lost due to rounding is the sum of time gained and time lost.

Analyzing time clock rounding allegations in a wage and hour or FLSA case: The Data Two-Step

At its core, the analysis of time clock rounding allegations in a wage and hour or FLSA case is straight forward That is, the analysis typically involves determining if the time clocking rounding was neutral or did it favor the employee or employer, more times than not?

In practice, the analysis can be surprisingly somewhat complicated. The complications generally arise with reading and converting data to a usable format and interpreting the time punch entries. Both of these steps can have an impact on the underlying time clock rounding calculation A two step data process is common in a lot of wage and hour and FLSA time rounding cases.

Generally, getting the time punch data into an electronic format is preferable to data entry. However, the data provided by many time keeping systems, such as Kronos or others, are not directly compatible with popular spreadsheet and data base programs like Excel and Access. In many (if not most) instances, the data will need to be converted before it can be used for an analysis in a wage and hour or FLSA case analysis.

Step 1: Converting the data

First, the time punch is converted using either OCR or text conversion programs to a raw text format. The raw format of the time data is typically very messy. However, as long as the conversion is accurate and the data is laid out in the same format, the messiness of the data is typically not a big problem.

Step 2: Producing a usable data set

Second, computer routines written in data analysis programs, such as STATA, are used to convert the data into an analyzable format. A usable data format for data in a wage and hour or FLSA time rounding case is one where the data is laid out into. columns and rows of data.

Calculating FLSA overtime (OT) and total compensation owed

Calculating OT correctly for non-exempt employees can be complicated. The complication often revolves around the fact that there is one definition of a overtime rate but there are multiple ways to calculate the total overtime and straight time compensation owed to an employee. If the underlying components of the OT computation are correctly calculated then the different methodologies should yield equivalent total compensation amounts .

Background

Under FLSA, non-exempt employees are paid OT at a rate of one and half times the regular rate. The regular rate of pay is based on the individuals total compensation, which includes the employee’s base rate of pay and certain bonuses and total hours worked in the work week. Generally, under FLSA OT is paid on all hours above 40 in a work week.

The FLSA does not explicitly define a work week(http://biznik.com/articles/department-of-labor-approves-9-day-work-schedule-w-o-overtime.) For some employees a work week is typically defined as a 7-day Sunday to Saturday time period. For some job positions, like fire fighters and employees on alternative week schedules the employers overtime rate calculation is based on a different work week schedule. The 9-80 work week is an example of a compressed work week schedule. ( http://www.wage-hour.net/post/2012/05/26/What-Is-A-980-Pay-Plan.aspx) Under the compressed work week the employee works 9 days in a two week period but not more than 40 hours in either workweek. According to Fisher Phillips:

Under a typical 9/80 arrangement, the non-exempt employee works four 9-hour days, followed by an 8-hour workday day that is split into 4-hour portions by the mid-day ending of the first workweek, and then works four more 9-hour days in the second workweek. The key is that the employee’s workweek ends during the 8-hour workday, causing the first four hours worked that day to fall into one workweek and the remaining four hours worked that day to fall into the next workweek. In this way, the employee’s hours worked in each workweek do not exceed 40.

There are certain conditions that the employer must meet to be able to switch to a compressed work week.

Law enforcement and fire protection employees also typically have a different work week. (http://www.dol.gov/whd/regs/compliance/whdfs8.pdf). For these employees,

A “work period” may be from 7 consecutive days to 28 consecutive days in
length. For work periods of at least 7 but less than 28 days, overtime pay is required when the number of hours worked exceeds the number of hours that bears the same relationship to 212 (fire) or 171 (police) as the number of days in the work period bears to 28.

In certain states, like California, individuals are paid OT on the hours above 8 worked in a day. In California, individuals are generally paid double time or 2 times their regular rate of pay, on hours worked in excess of 12 in a day. There is no provision for double time under the FLSA.

In California, employers may adopt what are known as Alternative Work Week Schedules that define a workweek differently from the standard 7 day time period or 5 day, 40 hour week from Monday to Friday. Before adopting an alternative work week schedule the employer must meet certain criteria and the alternative work week must be approved by the employees in an election. Alternative work week schedules include 4/40, 8/80 and 9/80. (http://www.calhr.ca.gov/employees/pages/alternate-work-week-policy.aspx)

This site provides a database of the Alternative Work Week adoptions for the State of California. http://www.dir.ca.gov/databases/oprl/DLSR-AWE.html. See also http://www.calpeculiarities.com/2013/05/29/tired-of-the-9-5-grind-consider-an-alternative-workweek-schedule/

Crude oil prices and natural gas prices decreased from September to October

prices_2014_10 Crude oil price decreased from $91.17 per barrel in September 2014 to $80.53 per barrel in October 2014. Natural gas price went down from $4.14 per million BTU (one million BTU is approximately 974 cubic feet) in September 2014 to $3.76 per million BTU in October 2014.

Texas crude oil production for August 2014 was 69,204,407 barrels, down from 73,329,467 barrels reported in July 2014. Texas natural gas production was 621,505,586 Mcf (thousand cubic feet) of gas in August 2014, down from the July 2014 gas production total of 662,617,068 Mcf.

Sources: eia.gov, rrc.state.tx.us

Recalculating a jury award in a California Med Mal case

The Medical Injury Compensation Reform Act (MICRA) of 1975 was a statute enacted by the California Legislature in August 1975. One of the provisions of the statute was to allow doctors to make periodic payments of awards in Med Mal cases.

Accordingly, in California in those instances, the jury is required to award/come back with both un-discounted and present value discounted amounts. If the defendant chooses to make periodic payments, then the un-discounted award amounts come into play.

In a recent the jury came back with an award but only mentioned present value numbers and no future values.

The Court and the attorneys agreed that it was better to not send the jury back to give a future value award. Instead they decided to have the economists figure out what the undiscounted future values are based on the present value numbers that the jury awarded.

So the following approach was offered.

Both economists used the ratio of the award to the present value numbers to future value numbers to back into the jury’s implicit undiscounted amount. For example, if the award was about 25% more than what testified to, then the future value was increased by the same percentage.

So for example if you two both used a 3% rate and calculated the present value of a loss over 10 years, the PV factor is 8.5302 (old school approach using tables!). If you calculated a $50,000 loss and the opposing expert calculated a $75,000 loss that would give you present value amounts of $426,510 and $639,765 respectively.

If the jury came back with a present value number in between the two experts then this would be about $539,137,. The annual loss that the jury implicitly used to arrive at the $533,137 figure is about $62,500. The annual loss number is right in the middle of the two experts.

	Annual Loss	PV factor	PV of Award
Economist 1	$ 50,000	8.5302	$ 426,510
Economist 2	$ 75,000	8.5302	$ 639,765

Jury			$ 533,137.50

Your 50% Guess (based on Jury award)	$ 62,500.0	8.5302	$ 533,138

California and Texas both saw greater decrease in job openings than US for August

California and Texas both experienced a greater decrease in job openings than the US for the month of August.

August 2014

Location	Total_Openings	Monthly_Change	Yearly_Change
CA	566,834	-0.67%	27.78%
TX	364,236	-1.23%	27.59%
US	4,543,314	-0.56%	27.82%

Source: BLS

Return on education, student loan interest and repayment periods

Education remains the best investment around. One economic question that always comes up is: are student loans worth it? That is, should I take out a loan (if that is the only way I can attend college)?

The quick answer is usually yes for attendance at a reputable institution. So how do you calculate the return on education investment? Generally, the calculation subtracts the explicit cost of attendance (tuition, fees, books, and student loan costs both current and future) and the opportunity cost of attendance (that is the job you could have gotten) from the added income that the person will make over their working life due to the education investment.

See: https://studentaid.ed.gov/repay-loans/understand/plans

Student loans come in two forms: subsidized and unsubsidized. Subsidized loans are usually financial need based; unsubsidized loans are not. Both types of loans have requirements regarding school attendance (usually at least half time).

The type of loan also impacts the interest rate; higher the interest rate the lower the return on education.

Student loan repayment periods also vary. Nowadays, student loan time periods range from 10 to 25 years. There are programs that allow the repayment to increase over time, change with income, and ones that are fixed over time.

Generally, the shorter the repayment time period, the higher the return on the education investment. In short, less loan interest is paid on a shorter loan period.

Selecting a weighted random sample in wage and hour analyses

In some wage and hour analyses a statistical random sample is needed to help address liability and damage issues. A sample may be required in employer’s self audit, regulatory investigation, or lawsuit involving FLSA, overtime, and wage and hour issues, such as unpaid meal periods..

In some instances, a weighted sampling routine may be appropriate. For instance, in this example.we are going to select a random sample of 100 employees for an employer’s self audit of its wage and hour practices. Time and payroll data for the sample of employees will be assembled by the employer for the selected individuals.

The sample contains four different types of employees that work at the company. The goal is to have the employee sample be representative of the overall universe of employees at the company.

Roughly half of the employees in the sample are type I employees, 25% are type II, and 20% are type III employees. 5% are type IV employees. The employer maintains the data for each type of employee in separate modules of its database and must access each type of employee separately

In this instance, some type of weighted sampling routine would be appropriate. .For instance, the sample could be selected by first randomizing the employees of each type. Then a weighted sample based on the proportion of each type of employee at the company can be selected. For instance, 50 random employees of type I, 25 random employees of type II, 20 random employees of type III, and 5 random employees of type IV.

Accounting for incremental costs in lost business profits analyses in commercial litigation

In business and commercial litigation, it is frequently alleged that the offending party’s actions resulted in a lost of business profit for the other party. In some instances, the issue is that the offending party’s actions prevented the pursuit of a given business opportunity as opposed to the reduction of profits or revenue from existing business. In other words, because of the offending party’s actions the business revenue and associated profit, simply did not happen.

For instance, a local check cashing company that was looking to expand into different areas of the city, was denied a business permit by the City. The City explicitly stated that they were looking to limit the expansion of checking cashing and pay day loan companies within the City limits, so they denied the company’s business permit application. The check cashing company sued the City and claimed a loss of business profits.

In this instance, the new location, and any revenue and profit, did not happen so this would be an example of lost profits as opposed to reduced profits. In this case, and similar ones, the calculation of lost profits requires, an analysis of the incremental cost associated with the revenue that would have been generated from the lost business opportunity, Incremental costs are those costs that are associated with the services or products that would have been produced had the business opportunity taken place.

In this instance,incremental cost would include items such as additonal salaries, office supplies, rents, and fees that the new location would have incurred. A number of items, such as advertising, would be classed as fixed overhead, since they were carried out at a higher organizational level and would not have been effected by the opening of the new location. In determining what is incremental costs versus a fixed cost, the time frame of the damage analysis is frequently a a factor.