How Proactive Loss Prevention Monitoring Reduced Improper Employee Discounting by Over 90%

A multi-location QSR network had a discounting problem that looked harmless on the surface. It was costing them a significant share of their sales every single week. Here is what our analysts found, how we documented it, and what changed.

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Why Improper Discounting Is Hard to Catch in QSR

Discounting feels harmless in the moment. An employee gives a friend a price break, applies a healthcare worker discount to someone who doesn’t qualify, or rounds down a regular customer’s bill because they like them. None of it feels like theft, because in the employee’s mind, it usually is not. It is people pleasing, not malice.

That is exactly what makes it so difficult to catch and so damaging at scale. QSRs run on thin margins. When discounts that should never have been applied start happening four or five times a day, every day, across multiple employees and multiple locations, the impact on profit is direct and significant.

What Proactive Loss Prevention Monitoring Identified

Through daily proactive loss prevention monitoring across this operator’s locations, Pembroke’s analysts identified a clear and recurring pattern.

Discounts Applied to Non-Qualifying Customers

Employee discounts are intended for staff working their shift. First responder, healthcare worker, and similar discounts are intended for verified members of those professions. Across these locations, our analysts found those discount codes being applied repeatedly to people who did not meet any of that criteria, most commonly friends, family members, and regular customers with no connection to the business.

At one location, our analysts identified a clear time pattern: a noticeable spike in discount usage between 3 and 5 PM, coinciding with the end of the school day at a nearby school. Friends of on-shift employees were coming in during that window and receiving discounts they did not qualify for.

The Scale of the Problem

At one of the locations reviewed, discounts were being applied to approximately 11% of total sales. Of those discounted transactions, our analysts found that approximately 90% did not meet the criteria for the discount being used.

That means roughly one in ten dollars in sales at that location was being discounted, and the overwhelming majority of those discounts should never have been applied at all.

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The Evidence: Identifying the Pattern, Not Just the Incident

A single discounted order is not a story but a repeated pattern, tracked over time and across multiple employees, is.

Pembroke’s analysts identified the same customers returning multiple times a week and receiving discounts on every visit. In some cases, the same customer was discounted by multiple different employees, suggesting the behavior was an accepted norm among staff rather than an isolated decision by one person.

When our analysts flagged specific instances directly with the client and asked whether any of these customers were authorized to receive the discount, the client confirmed they had no idea who these individuals were.

How the Pattern Was Corrected

Pembroke’s analysts identified specifically which employees were applying improper discounts, to which customers, and how often. That level of detail meant the client was not guessing at a general policy fix. They knew exactly who was involved and exactly how the behavior was happening.

From there, Pembroke continued reviewing transaction data on an ongoing basis, tracking the same employees and the same discount activity week over week. Every time the data was reviewed, it showed whether the behavior was declining or whether it had started up again. That continued tracking is what drove the reduction.

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The Result: Improper Discounting Reduced by Over 90%

Once the pattern was identified, improper discounting at these locations dropped by more than 90%.

That reduction came from sustained, ongoing monitoring, not a single correction. Pembroke continued reviewing transaction data after the initial findings were delivered, confirming the decline week over week and flagging any spike before it could grow back into the pattern that existed before.

What This Means for Multi-Location QSR Operators

Discounting fraud is easy to dismiss because no single instance looks serious. A free drink here, a price break there. It is the accumulation across employees, shifts, and locations that creates a meaningful hit to a business’s margin.

It is also a behavior that tends to normalize quickly. Once employees see that discounts are not being checked, the behavior spreads from one employee to several, and from occasional to routine. Left unaddressed, it becomes the accepted standard at a location rather than the exception.

Proactive monitoring exists specifically to catch this kind of pattern before it becomes embedded in how a location operates day to day.

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Frequently Asked Questions

What counts as improper employee discounting in a QSR setting?

Improper discounting happens when an employee applies a discount, such as an employee discount, a first responder discount, or a healthcare worker discount, to a customer who does not meet the criteria for it. This includes giving discounts to friends, family members, or regular customers with no qualifying connection to the discount being applied.

How common is improper discounting in restaurants that have never been monitored before?

It varies, but proactive monitoring frequently uncovers discounting patterns operators are not aware of. At one location in this case, discounts were applied to roughly 11% of total sales, and approximately 90% of those discounts did not meet the criteria for the discount type being used.

Why is improper discounting harder to detect than other forms of theft?

Because the transaction itself looks legitimate. The employee is not pocketing missing cash or voiding a sale. They are applying a discount that exists in the system for a different purpose. Without analysts reviewing transaction patterns and identifying which customers are receiving discounts and how often, the behavior is very difficult to catch through a standard register audit.

How does Pembroke identify a discounting pattern like this?

Pembroke’s analysts review POS transaction data daily, looking specifically at discount usage by employee, by customer, and by time of day. Patterns such as a spike in discounts at a specific time, or the same customer receiving discounts repeatedly across multiple visits, are flagged and documented as part of a trend-based evidence report.

What can an operator do once improper discounting is confirmed?

The most important step is identifying exactly which employees are involved and exactly how the behavior is happening, which is what Pembroke’s monitoring provides. From there, ongoing tracking confirms whether the behavior is actually declining. In this case, that continued monitoring is what drove the result, not a single policy decision.

Does fixing improper discounting actually move the needle on sales?

Yes. In this case, addressing the pattern reduced improper discounting by over 90%, recovering margin that had been eroding for an extended period across multiple employees and shifts.

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