Data Mining is the process of extracting hidden predictive information from large amounts of data. Becoming an increasingly important tool in the retail environment, this technology can be utilized for a spectrum of projects with great potential to help companies focus on and utilize the most important information in their databases. Most companies already collect and refine mass quantities of data. Data mining techniques can be implemented rapidly on existing software and hardware platforms to enhance the value of existing information resources, and can be integrated with new products and systems as they are made available.
Data mining techniques are the result of a long process of research and product development. This evolution began when business data was first stored on computers, and has continued to develop with improvements in data access and technologies that allow users to navigate through data in real time. In the evolution from business data to business information, each new step has built upon the previous one.
Data mining tools can help to predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. It can be used for tracking and documenting sales, or for managing functions such as inventory/stock levels, product replenishment, customer purchase patterns, and other business applications. With the ability to scour extensive information from our databases searching for hidden patterns loss prevention applications are clearly evident, and data mining has become one of the most useful tools in the loss prevention toolbox. As retail databases continue to grow at unprecedented rates, data mining will become an increasingly important tool for transforming this information into useful knowledge.
An Exception Report is a data mining program designed to pull out data from the company computer system by identifying data anomalies, or “exceptions” above or below expected parameters. Exception Reports are commonly used to flag register activity that is outside of the ordinary in report form so that these situations can be further investigated and resolved. Depending on which POS system your company uses and the reporting capabilities of the particular system, a wealth of information may be available that can assist in any number of investigations or metrics analysis.
The limits of this important loss prevention tool are only restricted by the bounds of technology, the sophistication of the program and the data that is available. Many systems come with their own exception reporting capabilities, while other systems have the capability of adapting to 3rd party exception reporting programs. While most loss prevention professionals are very familiar with the use of exception reporting, the value of this management tool cannot be overstated and will certainly continue to hold merit as we move forward.
By capitalizing on opportunities to enhance our knowledge and education, we are making an investment in our own future. To learn more about data mining and the certification process, visit losspreventionfoundation.org.