Risk Scoring Logic for Data Storage Error Prioritization

The patent applies local quality by assigning different priority levels (P1-P4) to different errors based on their specific characteristics such as data risk, customer impact, and system criticality. This allows each error to be handled with the appropriate level of resource allocation rather than treating all errors uniformly, thus protecting customer data while avoiding unnecessary operational complexity for low-risk errors.

The patent changes the parameter of error handling priority from a uniform state to a variable state based on multiple factors including data risk assessment, customer SLA levels, and error severity. This parameter transformation enables dynamic resource allocation that protects critical data while optimizing operational efficiency.

The patent segments the error handling process into distinct priority levels (P1-P4) with differentiated response requirements. Critical errors (P1) receive immediate attention with dedicated resources, while lower priority errors are handled systematically. This segmentation ensures both rapid response to critical issues and comprehensive resolution of all errors.

The patent applies partial action by allocating service resources proportionally to error priority levels rather than distributing them equally. Critical errors receive excessive resource allocation to ensure rapid response, while lower priority errors receive appropriate but reduced resources, achieving both fast critical response and complete error resolution.

The patent implements feedback mechanisms where service professionals assess errors and assign priority levels, which then feed into automated routing and resource allocation systems. The system continuously learns from these assessments and refines its automated decision-making, combining human flexibility with machine speed and consistency.

The patent introduces an automated error management system as an intermediary between service professionals and error handling execution. This intermediary translates subjective professional assessments into objective priority classifications and automatically routes errors to appropriate resources, bridging the gap between flexible human judgment and efficient automated processing.

The patent applies preliminary action by implementing automated error triage and classification before full service professional intervention. The system pre-assesses errors using multiple criteria (data risk, customer SLA, error type) to identify and flag potentially critical errors, ensuring they are not filtered out while enabling efficient handling of routine errors.

The patent replaces manual error filtering with an automated electronic classification system that uses predefined rules and algorithms to assess error criticality. This substitution maintains high detection precision for critical errors while dramatically improving resource efficiency by automating the initial assessment and routing process.