File Plan Targeting

Introduction

The File Plan Targeting feature in Records365 provides organizations with a strategic link between Classification Intelligence and Rules to promote more efficient and scalable record classification using known information. This feature allows customers to manually assign a record category, target a specific machine learning model, or use fully automated classification to accurately classify their records.

The integration with Records365 means that organizations can target specific file plan that is trained in Classification Intelligence to increase the accuracy of the classification results. This enables them to focus their training efforts on specific subsets of their data, improving model accuracy and efficiency. Furthermore, the ability to link categories and rules also allows organizations to improve accuracy for categories with inconsistent data quality by linking to more consistently classified categories.

Importantly, the File Plan Targeting feature in Records365 provides organizations with a highly effective tool to improve the accuracy, efficiency, and scalability of their record classification process. By providing a more specific solution that aligns with their unique File Plan, organizations can ensure that their records are classified accurately and consistently, saving time and resources, while also reducing the risk of non-compliance. For example:

• Organizations can improve accuracy and reduce manual review for consistently misclassified record categories by targeting more specific machine learning models and adjusting threshold levels. This reduces the need for manual review, which in turn improves the overall system performance.

• Organizations can also improve prediction accuracy for categories with limited training data by linking related categories and rules to improve machine learning model accuracy.

This documentation provides step-by-step instructions on how to use the File Plan Targeting feature in Records365. By following these instructions, customers can leverage this feature to optimize their record classification and management workflows.

Steps to Use File Plan Targeting

To use this feature, you simply need to follow these steps:

1. Click on the Rules section in the left-hand navigation menu of Records365 to access the Rules tree.
   
   
   

2. Select the node in the Rules tree that you want to target.
   
   
   

3. Click on the Action button for the selected node, and choose the Selected Trained Record Category (referred to as a Disposal Class in some regions) option from the pop-up window.

4. In the drop down, select the specific trained category that you want to align with your trained file plan, then click Save.
   
   
   

5. Repeat steps 3-4 for each node in the Rules tree that you want to target.

6. Finally, click on the Models tab to audit the performance of each model that aligns with your file plan.

By targeting specific parts of your file plan, you can focus your training efforts on specific subsets of your data, which will enable you to be more targeted and increase accuracy. Additionally, this feature allows you to use a multi-model approach, where each machine learning model aligns to each level of your file plan, resulting in a more specific and efficient solution that aligns with your unique File Plan.

Summary

File Plan Targeting is a powerful feature that can bring significant value to organizations by enabling more efficient and accurate record classification. By leveraging this feature, organizations can improve the accuracy of low-performing categories with targeted machine learning models, reducing the need for manual review and improving overall system performance. This not only saves time and resources but also improves compliance and reduces the risk of errors. Additionally, this feature can increase accuracy and reduce manual review for consistently misclassified record categories by targeting more specific machine learning models and adjusting threshold levels.

Another use case for File Plan Targeting is to improve prediction accuracy for categories with limited training data. By linking related categories and rules to improve machine learning model accuracy, organizations can increase the accuracy of their record classification system and reduce the risk of misclassification. In cases where organizations have inconsistent data quality, File Plan Targeting can help improve accuracy for categories with inconsistent data quality by linking to more consistently classified categories. This can help improve the overall accuracy of the record classification system and reduce the risk of errors.

Moreover, File Plan Targeting can help organizations reduce training time and resources by focusing on specific subsets of data, improving model accuracy and efficiency. By targeting specific parts of the file plan, organizations can train their machine learning models more efficiently and accurately, reducing the need for manual review and improving the overall accuracy of their record classification system.

File Plan Targeting is a valuable feature for organizations that want to improve the accuracy and efficiency of their record classification system. This feature can help organizations save time and resources, improve compliance, reduce the risk of errors, and increase the accuracy of their record classification system. By integrating with Records365, File Plan Targeting provides a link between Classification Intelligence and Rules, promoting more efficient and scalable record classification using known information, such as targeting specific models, file plans, or fully automated classification approaches.