A Systematic Approach to Employee

Loss Deterrence in Restaurants

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Losses due to employee mistakes, misallocation, and outright theft has always been an unspoken topic, mostly due to the difficulty in detection.  The last few years have seen a number of tools and methods designed to deter losses from employees in restaurants.  These attempts have met with mediocre results for a number of reasons.  The main reason for the somewhat lukewarm results is that all the video- and management-based systems require so much time of the managers and owners.  Even with the latest POS exception-based reporting with corresponding video-clip verification, the biggest problem with these rather elaborate systems is that someone needs to watch the video.  The vast majority of the transactions, when verified through video, prove to be legitimate.  After verifying, for example, that all employee meal discounts for a shift are correct, the owner quickly loses interest.  He will realize that looking for maybe one or two questionable transactions in a haystack of dozens of legitimate ones is not time well spent.

 What Is Needed

Effective theft deterrence requires a multi-dimensional approach.  Information from various sources such as cash drawers, point-of-sale transactions, and video surveillance must be analyzed and compared to information from similar shifts, similar employees, and similar conditions.  This analysis must include behavior patterns, ordering profiles, and other analytics.  As an example, a bartenderís ratio of draft beer to bottled beer must be compared to his own ratio for the same day of the week and shift last year, to his moving historical average, and to the ratio of similar employees for the same shift and day.

All employees develop patterns and habits - for better or worse.  Some employees follow procedures, while others don't.  New computer-based tools are available which are designed to separate the good employee profiles from the poor or dishonest ones. 

To Do It Right

In order to get a complete profile of behavior profiles, a large number of data must be collected from multiple sources.  Data necessary to be collected and analyzed include cash drawer opening sequences, both by key and electronic openings by the point-of-sale system.  All discounts, coupons, gift certificates, open or miscellaneous food and liquor sales, credit card tips must be analyzed.  Voids and no-sales, both before and after being finalized, are compared.  Ratios of bottled beer to draft beer, wine by the glass to wine by the bottle, well liquor to call or premium liquor and even mixed drinks to well drinks must also be compared to other employees performing similar tasks at similar times on similar days of the week during similar seasons or holidays.

 The collected data now need to be sorted a number of ways to detect any patterns of interest.  If, for example, the point-of-sale system used is an Aloha POS, all drawer openings need to be immediately followed by a receipt printing or a no-sale transaction.  Any other time the drawer is open, it must be assumed that the drawer was opened by using a key.  As another example, if draft beer sales are consistently low compared to bottled beer of those of companion bartenders, it might mean that not all draft beer sales are being ordered correctly.  Bottled beer is easy to control, while draft beer is difficult to monitor and an astute bartender might be able to take advantage of this.

Brian McMillan is Director of Product Development of In Sight Commander System, Inc.  a software development company specializing in restaurants and video surveillance systems.  He can be reached at (714) 480-0788 or http://www.insightcommander.com/