The Ultimate Guide to Exception-Based Reporting

Businesses are continually searching for ways to leverage data to streamline operations, minimize losses, and make more informed decisions. One powerful tool that has emerged to meet these needs is Exception-Based Reporting (EBR). As industries from retail and restaurants to grocery and pharmacy increasingly adopt EBR, understanding its ins and outs becomes ever more crucial. 

In this guide, we delve into the what, why, and how of EBR, with a particular focus on its applications in loss prevention and operations across various sectors. We begin by demystifying what Exception-Based Reporting is and then delve into how it works.  

As we journey through the history of EBR and witness its evolution, we'll uncover how businesses use this tool to minimize shrink and enhance decision-making processes. We'll walk you through the steps to implement Exception-Based Reporting in your organization and share best practices for using EBR in loss prevention. 

But like any business solution, EBR comes with its challenges. We'll address common hurdles faced when implementing EBR and provide practical tips to overcome them. Finally, we'll guide you on how to choose an Exception-Based Reporting tool that best fits your needs. 

Whether you're new to EBR or looking to optimize your current processes, this guide will equip you with the knowledge and insights you need to harness the power of Exception-Based Reporting effectively. 

What is Exception-Based Reporting? 

Exception-based reporting (EBR) is a strategy used by Loss Prevention (LP) and Operations professionals (among others) to identify anomalies (the 'exceptions') in their day-to-day operations. It's a method of filtering out routine, normal transactions and focusing on the exceptions that could signify potential problems or opportunities. EBR software sifts through large volumes of transactional data, seeking out instances that deviate from the norm. These deviations are then reported for further investigation. 

The concept of 'normal' or 'expected' behavior is defined based on a set of rules or parameters established by the business. These rules can be simple e.g., any refund over $100 or complex e.g., any transaction where a single item constitutes more than 50% of the total purchase value. 

The underlying principle of EBR is that most transactions conducted within a business follow a standard pattern, while fraudulent activities or operational inefficiencies tend to deviate from these patterns. For instance, in a retail setting, it might be normal for cashiers to issue a few refunds each day. However, if a cashier starts issuing significantly more refunds than their peers, this would be considered an exception and flagged for further investigation. 

How EBR Works 

EBR systems are complex, but they work in a simple and intuitive way that’s easy to understand. Here's a step-by-step overview of how exception-based reporting works, from software setup to actually taking corrective action: 

1. Data Collection: EBR software collects transactional data from various sources such as point-of-sale (POS) systems, inventory management systems, and customer relationship management (CRM) systems. 

2. Rule Setup: Businesses establish a set of rules or parameters that define 'normal' behavior. Any transaction that falls outside these parameters will be considered an exception. 

3. Data Analysis: The EBR software analyzes the collected data and compares it against the established rules. 
 
4. Exception Identification: The software identifies and flags any transactions that deviate from the established rules. 
 
5. Report Generation: The EBR system generates reports and alerts detailing the exceptions for further investigation by management or a loss prevention team. 
 
6. Action: Based on the report, the Loss Prevention analyst or other user can take appropriate action – this might involve investigating potential theft or fraud, addressing operational inefficiencies, or identifying opportunities for improvement. 

 

The 4 Key Components of Exception-Based Reporting 

Understanding the individual components mentioned above can help users implement and manage their EBR systems more effectively. Let’s dive and explore each of these steps in a little more depth.  

Data Collection and Management in EBR 

The first step in any EBR system is data collection. This involves gathering transactional data from various sources within the business, such as point-of-sale (POS) systems, inventory management systems, customer relationship management (CRM) systems, and other operational databases. 

POS systems are an important data source for EBR. POS exception reporting involves analyzing transaction data from POS systems to identify unusual or suspicious activities. These might include transactions that fall outside normal patterns or violate established rules, such as refunds, voids, or discounts that exceed certain thresholds. 

Once collected, this data needs to be managed effectively. This involves ensuring the data's accuracy, consistency, and security. Inaccurate or inconsistent data can lead to false positives or negatives in the EBR system, while data breaches can expose sensitive business information. 

Rule Setup and Management for Effective EBR 

The next component of an EBR system is rule setup and management. These rules define what constitutes 'normal' and 'exceptional' behavior within the business. For instance, a rule might state that any refund over $100 is considered an exception. 

Setting up effective rules requires a thorough understanding of the business and its operations. Rules should be broad enough to catch a variety of exceptions but specific enough to avoid overwhelming the system with false positives. 

Moreover, these rules aren't static - they should be regularly reviewed and updated to reflect changes in the business environment or operational strategies. 

Alert and Notification System in EBR 

Once the data has been collected and the rules have been set up, the EBR system will start identifying exceptions. When an exception is detected, the system needs to alert the relevant individuals or teams. This is where the alert and notification system comes in. Agilence Analytics contains alert functionality that allows LP professionals to monitor key business operations and automatically send prescriptive alerts to in-store teams in order to quickly resolve issues. 

Report Generation and Distribution in EBR 

The final component of an EBR system is report generation and distribution. Once exceptions have been identified and alerts have been sent out, the EBR system needs to generate detailed reports for further investigation. 

These reports should provide enough information for the LP team or management to understand the nature of the exception and take appropriate action. Once generated, these reports need to be distributed to the relevant individuals or teams. This involves not just sending the reports, but also ensuring that they are easy to understand and act upon. 

The Role of Exception-Based Reporting in Loss Prevention 

Exception-Based Reporting (EBR) plays a pivotal role in loss prevention by enhancing operational efficiency, improving decision-making processes, mitigating risks, and preventing fraud. It has proven to be a valuable tool across various industries, including retail, restaurants, and pharmacies. 

The Birth of EBR 

Exception Based Reporting (EBR) was initially created as a tool for retail and restaurants in the mid-1990s. Client-server environments using relational databases were spun up for Loss Prevention teams to allow them to mine POS transactional data across their entire chain of stores from one central point, typically located in their central corporate offices.  

The EBR concept dramatically revolutionized LP processes, allowing teams to look for patterns of internal fraud using an analytics software tool as opposed to manual processes already in place. The focus from the LP community was to identify fraudulent activities by their employees using refunds, voids, employee discounts, and sweethearting. At this time, database storage was expensive and network speeds were too slow to get the critical POS data and not interfere with in-store technology functions, while many industries like restaurants, C-Stores, and grocers were not even capturing detailed POS data.  

How EBR Evolved to Become a Mission-Critical LP Tool   

As EBR technology matured, it became a mission-critical solution for LP departments. It allowed them to drive significant ROI back to their organizations and created a healthier in-store environment. In one survey conducted by LP Magazine, 95% of survey respondents said that EBR was what they use to accurately identify cases of internal loss.  

As faster networks evolved, the capabilities of EBR tools and the productivity of LP teams improved. POS systems continued to evolve, making POS data more robust. Reduced cost in data storage allowed EBR tools to store years of detailed historical data. Video systems became the norm for in-store visibility and EBR systems added links to cameras overseeing the registers. Now, when a cashier was flagged in the data for a possible refund fraud scheme, LP teams could push a button and get the corresponding video of that cashier and transaction. Cloud computing with web and mobile access has driven costs down for LP teams and made their systems easily deployable to corporate, field, and store users. This dramatically reduced the burden on corporate IT teams. 

Enhanced analytical capabilities have been built into EBR tools to allow users to pinpoint exceptions across massive data sets. Each retailer is unique, requiring fine-tuning of the analytics based on their POS, policies, procedures, and the way the employees interact with the POS. These findings are built into deliverable reports and prescriptive alerts mentioned above that LP users and store management can review and act upon.  

EBR for Shrink Reduction 

EBR systems sift through millions of transactions, identifying anomalies that could indicate potential losses as well as providing valuable insights that can guide decision making. By focusing on these exceptions rather than every single transaction, businesses can allocate their resources more effectively, enhancing operational efficiency. 

For example, in retail, EBR can help identify unusual patterns such as excessive voided transactions, refunds, or discounts, which could indicate fraudulent activity or operational inefficiencies.  

In the restaurant industry, EBR can flag suspicious patterns such as consistent over-portioning of certain ingredients, unusually high wastage levels, or irregularities in cash handling. Learn more about exception-based reporting for restaurants.  

Pharmacies can use EBR to identify prescription errors, detect potential cases of insurance fraud, or monitor drug inventory discrepancies. 

EBR is an effective tool for mitigating risks and preventing fraud. By identifying exceptions early, businesses can take proactive steps to address issues before they escalate. If an EBR system identifies a sudden spike in refunds issued by a particular cashier, management can quickly intervene to determine if this is due to fraud, customer dissatisfaction, or another issue. 

EBR for Broader Organizational Decision Making 

By identifying trends and patterns in the data, EBR can help businesses to understand where losses are occurring and why. For instance, if an EBR system consistently flags a particular store location for high numbers of voided transactions, management can investigate further to determine if this is due to employee error, insufficient training, or potentially fraudulent behavior. 

Today, the most effective LP Teams are focused on far more than just catching employee theft cases with their EBR systems. Leading retailers look at shrink not just in losses but also across all areas of the business impacted, including labor, margin, compliance, customer retention, and lost sales. Organizational leaders look to LP to provide fast, accurate data for more significant insights into business operations. As a result, LP is partnering with other functional groups to gain insights into everything from store-level operations to COVID-19 health and wellness protocols. By using EBR data analytics and advanced tools, retailers can gain insights into: 

• What’s the quick read on items selling? 
• Are we getting loyalty sign-ups? At what frequency? 
• How well is that promotion doing in New York and California? 
• Are employees overriding prices to start early or extend the weekend promotion? 
• Are employees “up-selling” accessories and or added desserts? 
• How many of my BORIS (Buy-Online-Return-In-Store) transactions are really happening, and are they being converted into exchanges? 
• Are our self-checkout lines as effective and secure as we need them to be?

How to Implement Exception-Based Reporting  

Implementing Exception-Based Reporting can be a complex process, but the benefits make it worthwhile. The steps to implementation and common challenges may vary across different sectors like retail, restaurants, and pharmacies, but the underlying principles remain similar. 

Step-by-Step Guide to Implementing EBR

1. Data Collection

The first step in implementing EBR is data collection. This involves gathering transactional data from various sources within your business, such as point-of-sale (POS) systems, inventory management systems, customer relationship management (CRM) systems, loyalty, HR, production, location, alarm, RFID, and other operational systems and data.

2. Define Rules

Once you have your data, you need to establish a set of rules that define 'normal' and 'exceptional' behavior within your business. These rules should reflect your business operations and potential areas of risk.

3. Implement EBR Software

Next, implement EBR software that can analyze your transactional data according to your defined rules. There are many EBR solutions available on the market, so choose one that fits your business size, needs, and budget.

4. Train Staff

Ensure your staff is trained on the EBR system. They should understand how to interpret the reports and alerts generated by the system and what actions to take when exceptions are identified.

5. Monitor and Adjust

Finally, continuously monitor your EBR system and adjust as necessary. Regularly review your rules to ensure they are still relevant and adjust them as your business evolves. 

Common Challenges in EBR Implementation and How to Overcome Them

1. Data Quality

Poor data quality can hinder the effectiveness of an EBR system. Ensure your data is accurate and consistent by implementing robust data validation processes and regular data audits.

2. Rule Definition

Defining effective rules can be challenging. Rules that are too broad may result in too many false positives, while rules that are too narrow may miss important exceptions. Regularly review and adjust your rules to ensure they effectively identify exceptions without overwhelming your system.

3. Staff Training

Staff may struggle to understand and act upon the reports generated by an EBR system. Provide comprehensive training and ongoing support to ensure your staff can effectively use the EBR system. 

Best Practices for Exception-Based Reporting in Loss Prevention 

Exception-Based Reporting (EBR) can be a powerful tool for loss prevention, but only if it's used effectively. Here are some best practices that can help businesses maximize the benefits of their EBR systems. 

Setting Up Effective Rules and Alerts in EBR 

An EBR system's effectiveness largely depends on the rules set up. When setting up rules, consider the unique aspects of your business operations and potential areas of risk. For instance, a rule might state that any refund over a certain amount is considered an exception. This amount may vary depending on the average transaction size in your business. 

If setting up these rules seems daunting, don’t worry. An EBR system will help take the guesswork out of deciding where those thresholds should start. For instance, when setting up Agilence as your EBR system, we can automate statistics so thresholds can be tested based on different factors: risk scores; percent of sales at, company, region, store; average count/amount; velocity; # of standard deviations for the mean; and others. 

In addition to setting up effective rules, it's important to set up effective alerts. These alerts should be timely, clear, and actionable, providing enough information for the relevant individuals or teams to understand the nature of the exception and take appropriate action. Agilence Analytics contains alert functionality that allows LP professionals to monitor key business operations and automatically send prescriptive alerts to in-store teams in order to quickly resolve issues.  Additionally, you can track and analyze the follow-up actions to monitor effectiveness and improve the alert efficacy.  

Regularly Reviewing and Updating the EBR System 

An EBR system isn't something you can set up and forget about. It needs to be regularly reviewed and updated to reflect changes in your business operations or environment. 

This might involve updating the rules to account for new products or services, adjusting the alert thresholds to reflect changes in transaction volumes, or adding new data sources to the system. 

Regular reviews can also help identify any issues with the EBR system, such as inaccurate data or ineffective rules, so they can be addressed promptly. 

Training Staff on How to Use and Interpret the Reports from EBR 

Training is a crucial component of any successful EBR implementation. Staff need to understand how to use the EBR system, interpret the reports it generates, and take appropriate action when exceptions are identified. 

This training should cover the basics of how the EBR system works, the meaning of different types of exceptions, and the steps to take when an exception is identified. It should also give staff the opportunity to ask questions and clarify any confusion. 

To learn more, check out our article on 5 Tips to Maximizing the Value of Exception-Based Reporting Systems.  

Choosing an Exception-Based Reporting Tool 

Choosing the right Exception-Based Reporting (EBR) tool is crucial for your business. It can significantly impact the efficiency of your operations, your ability to prevent loss, and ultimately, your bottom line. Here's some guidance on how to choose the right EBR tool: 

Ease of Use: An effective EBR tool should be intuitive and user-friendly. You don't want to spend valuable time trying to understand complex interfaces or navigate through complicated processes. Agilence Analytics is well-known to be one of the easiest-to-use options on the market, specifically designed for the needs of LP and operational professionals, allowing for advanced querying without advanced experience in analytic tools (although if you want to dive deep, you can!).

Customization: Every business is unique, and so are its needs. The EBR tool you choose should allow for customization, enabling you to set your parameters for what constitutes an exception.

Integration: The tool should easily integrate with your existing systems, like POS or inventory management systems, to ensure a seamless flow of data. Agilence Analytics integrates with over 200+ sources like point-of-sale (POS), eCommerce, HR/labor, inventory, product/SKU, location, third-party delivery platforms, alarms, case management, loyalty, access control, video surveillance, and more.

Real-Time Reporting: In today's fast-paced business environment, having access to real-time data is invaluable. Your EBR tool should offer real-time reporting to enable swift action. 
 
Scalability: As your business grows, your EBR tool should be able to grow with it. Make sure the tool is scalable and can handle increased data volume without compromising performance. 

Agilence Analytics is the leading exception-based reporting tool for Loss Prevention professionals. Agilence has helped hundreds of retailers, restaurant operators, and grocers to increase their profit margins by reducing preventable loss across the business, with the average customer receiving a 33x ROI and 38-day breakeven, according to third-party research.  

Instead of sorting through millions of lines of POS records for unusual sales-reducing activities like voids, refunds, or discounts, Agilence 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.  

Agilence Analytics can automatically notify managers when acceptable thresholds are exceeded with prescriptive alerts delivered directly to their mobile or tablet inbox. 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. 

To learn more, schedule a demo to see it in action.