The goal of any Loss Prevention or Asset Protection department is to reduce enterprise losses and maximize profits. However, achieving that goal is often easier said than done in the fast-paced environment of increased workloads, budget limitations, turnover issues, corporate agendas, and ever-increasing avenues for fraud and other shrinkage.
Agilence's 20/20 Data Analytics Platform empowers users to work smarter, not harder by adopting a top down approach to identifying exceptions and margin erosion, staying compliant, and identifying opportunities to increase sales, improve customer experience, and boost operational efficiency.
Instead of sorting through millions of lines of POS records for unusual voids, refunds, or discounts, 20/20 can automatically scan your data for these and other “red flags” such as cash drawer skims, loyalty/rewards abuse, multiple low-value sales, and more.
Automatically notify managers when user-defined criteria are met with prescriptive alerts delivered directly to their mobile or tablet inbox. Ensure compliance with step-by-step documentation on how best to resolve the issue at hand.
Move beyond the traditional four categories of shrink (internal theft, external theft, administrative errors, and vendor fraud) to better combat the complexity of modern omnichannel environments. Easily integrate with various data sources to identify loss of all types.
Video streams can be tied to the item level of a receipt so that drilling-down into anomalies, training issues, and more can be validated instantly with the corresponding video for each event.
Reducing enterprise-wide loss requires visibility into the various channels where loss can occur. Transactional data, payment information, video streams, inventory, and other sources offer massive amounts of data just waiting to be collected and analyzed. 20/20 provides a simple yet powerful view into these and more metrics to deliver data-driven insights to key decision-makers and drive better business outcomes.
See how Agilence's 20/20 Data Analytics Platform can help enhance your loss prevention efforts and deliver key insights to decision-makers in these four examples:
One Agilence customer saw a total of $12 million in total annual savings attributed to insights uncovered in 20/20. Reducing price overrides yielded a $123k margin increase over just 30 days.
Identified and reduced promotion abuse by 40% enterprise-wide in the first year after implementation. Reduced inventory shrink by approximately 1% within the first year of using 20/20.
Using 20/20 Grocery, one grocery chain revealed nearly $64,000 in bag purchases that were not rung into the POS in just 30-days across all California locations. This could amount to over $750,000 in additional profits annually. Improved regulatory compliance helps the enterprise avoid preventable fines and
protects their license to sell to WIC, EBT, and food stamps program users. For the organization mentioned above, these transactions make up approximately 5-20% of total grocery transactions at any given time.
Five Below wanted to build a new asset protection department from the ground up, but they did not have the right tools in place to build a solid foundation. They were able to generate high-level reports in Excel, but these reports were unable to provide users with actionable insights and relied on IT to create and distribute reports. With the green light to evaluate best in class analytics applications, they created a list of business requirements and soon found the one solution that met them all: 20/20 Data Analytics Platform.
Agilence's 20/20 Data Analytics Platform provides the tools and resources you need to combat loss across the enterprise. 20/20’s loss prevention functionality helps your teams bring hidden sources of profit loss to light through analysis of common fraud schemes, training processes, and procedural issues that can be improved upon. Anything identified to be suspicious or warrant attention is then available as a closed loop workflow so that you can ensure that issues are being addressed appropriately.