With the increase in EMV (Europay, Mastercard and Visa) chip reader usage at checkout, retailers want to understand the impacts EMV devices are having on customer wait times and ultimately store payroll. Some companies are using simple math to estimate the payroll implications. Let’s use the following assumptions for an example retailer:
- 150 retail stores
- 10,000 total transactions per week on average
- 40 percent of all transaction are credit or debit transactions
- 10 second increase in credit and debit transaction time due to EMV
- $10 average hourly wage rate
The result would be an increase of 11.1 hours per week on average or an annualized increase in payroll dollars of $866,666. That is a significant increase in payroll across the chain that companies will look to offset through other improvement initiatives. However, the simple math approach is flawed when dealing with service driven departments like the Front End.
To determine the impact of operational changes to service driven departments, follow these rules to developing an accurate model:
1. Use accurate labor standards data
Regardless if the change to process is increasing (e.g., EMV chip readers) or reducing (e.g., process enhancement) time, the changes need to be reflected accurately in the engineered labor standards. In our example, the labor standards for credit and debit transactions should include the additional delay time for the higher transaction processing.
Retailers should study the processing delays in a controlled lab environment before piloting. This will provide an accurate starting point to adjust the labor standards. Once in pilot, companies should continue to study customer processing times to determine if the labor environment estimates are accurate. Customer sampling is a proven approach where customer queue and transaction delay times are collected for a subset of stores. It is a good practice to conduct the sampling study before piloting and post pilot so that existing delays in the process are quantified in the standards.
Over time as customers become more familiar with EMV and advancements to payment processing reduce the delay, companies should re-evaluate if they need to update their credit and debit engineered labor standards.
2. Use 15 minute volume data instead of daily or weekly data and apply it to the labor standards
Best in class retailers do not use daily or weekly data to derive hours for service departments like the Front End. Instead, the volumes that drives labor (e.g., items sold, transactions, customers) are at the 15 minute level to capture the fluctuations of customer activity throughout the day. By applying the labor standards to the 15 minute interval volume data, the Raw Labor Demand provides labor required to service customers at the right time of day, by each 15 minute interval each day of the week.
3. Apply Staffing Parameters to the Raw Labor Demand
Staffing Adjustment Hours are the additional service requirements that retailers want to have applied to their Raw Labor Demand. Two common types of staffing parameters are Minimums and Rounding.
Minimums set the least number of hours for any department during any 15 minute interval. A typical minimum staffing parameter is 1 full time equivalent (FTE) employee for every open hour of the department. For the 15 minute intervals where the raw labor is less than the minimum, additional hours are provided to increase those intervals to the minimum threshold. For early morning or overnight periods when stores are less busy, service departments may not earn enough demand hours to exceed the minimum.
Rounding parameters are the threshold by which labor hours are increased or decreased to the nearest whole FTE. Retailers cannot staff anything less than 1 whole employee per interval, therefore in the event that the labor demand calls for 1.5 FTEs for a specific interval, the hours need to be rounded down to 1 FTE, or rounded up to 2 FTEs.
There are many other types of staffing parameters like maximums, spreading, productivity, utilization and tiered rounding. Regardless of the staffing parameter type, retailers should have the ability to apply the staffing parameters at week, day and 15 minute level by chain, store, department, sub department and job level.
The combination of Raw Labor Demand and Staffing Adjustment Hours by 15 minute interval are referred to as Staffing Hours. Research shows that the Staffing Adjustment Hours account for 10%-15% of the total Staffing Hours. That is a significant portion of hours that are added to provide the desired service levels.
STAFFING HOURS = RAW LABOR DEMAND + STAFFING ADJUSTMENT HOURS
4. Staffing Hours versus Scheduled Hours
Staffing Hours are the basis for a scheduling system to auto-generate the department labor schedule. The peaks and valleys of the daily customer demand along with employee scheduling rules like shift minimums make it impossible for the Staffing Hours and Scheduled Hours to match exactly. Research shows that Scheduled Hours are typically 3 percent – 5 percent higher than the Staffing Hours on average.
SCHEDULED HOURS = STAFFING HOURS + SCHEDULING RULE HOURS
This is the second instance where additional hours are included in the weekly labor plan. The Staffing Adjustment Hours and Scheduling Rule Hours increase the weekly hours by nearly 15 percent above the Raw Demand Hours. Some of those additional hours will offset the impact from the increased transaction time. The exact amount that is offset will depend upon the specific staffing and scheduling rules of the retailer.
Ultimately, the hours scheduled at your staffing demand should be validated to insure that your service standards are met. This includes a review of service wait times and queue management that align with your service standards. Sometimes the insights that come to light in this validation can lead you to various revisions in fine tuning labor standards, service allowances, or reconsidering your standard operating procedures. It’s important to review these options with an open mind to seize possible savings opportunities. Dynamic express register use, dynamic bagging across lanes, tiered rounding, and modification of queuing or idle time factors by time of day are all part of the process to use your labor standards and the parameters associated with converting raw labor demand to 15-minute scheduling requirements into a plan that will meet your service and productivity needs best.
If your organization is searching for answers on how EMV devices are impacting your payroll, simple math is not the answer. You need to leverage the gradual data available and apply it to a labor model that is specific to the sub department and staffing parameters specific to the time of day.
To provide a thorough analysis driving well-informed business decisions like this, ask yourself – Does your organization have the tools and expertise to:
- Measure the impacts of operational changes quickly?
- Maintain engineered labor standards effectively?
- Support a store and sub department specific labor model?
- Apply store and sub department specific staffing parameters by day of week and by time of day?
- Validate lane throughput and customer queue experience?
- Generate what-if scenario testing using actual volume data?
The answer to these questions can have a big impact on the real cost of EMV implementation in your organization.