User Performance Scoring in Data Storage Systems
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Solution Overview
Problem
Current data storage solutions face challenges in efficiently managing and protecting data due to rapid growth, with users consuming disproportionate support resources, and existing metrics for evaluating user performance are inadequate, failing to account for contextual factors such as hardware and software configurations.
Innovation Solution
A system that assigns a performance score to users based on incident management and community participation, normalized by contextual factors like hardware and software configurations, to assess user performance and provide targeted educational efforts, thereby optimizing support interactions and user behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users are provided with extensive support resources and educational efforts, then user knowledge and self-service capability improve, but support personnel time and costs increase disproportionately for certain users
Solution Approach 1:
The system implements a feedback mechanism by tracking user interactions with support resources and calculating performance scores. Users who engage with educational materials and self-service resources receive positive feedback through improved performance scores, while users who repeatedly open incidents without utilizing available resources receive targeted educational recommendations. This feedback loop encourages users to become more self-sufficient without proportionally increasing support personnel time.
Solution Approach 2:
The patent promotes self-service by providing users with accessible support resources including knowledge bases, documentation, and educational materials. The system automatically identifies users who would benefit from specific educational content and directs them to appropriate self-service resources, enabling users to resolve issues independently without requiring support personnel intervention for every incident.
2Device complexity
If traditional incident counting metrics are used to evaluate user performance, then simplicity is maintained, but accuracy and fairness in assessment deteriorate due to lack of contextual factors
Solution Approach 1:
The system transforms the单一的 incident counting metric into a multi-parameter performance score that incorporates contextual factors such as hardware configuration, software version, incident type, and user engagement with support resources. This parameter change enables more accurate and fair assessment of user performance while maintaining system manageability through automated calculation and standardized weighting schemes.
3Ease of manufacture
If uniform support resources are provided to all users, then ease of implementation is maintained, but effectiveness deteriorates because users have different needs and configurations
Solution Approach 1:
The system applies local quality by customizing support resource recommendations based on individual user characteristics including their hardware configuration, software version, incident history, and performance score. Instead of providing uniform resources to all users, the system identifies specific educational materials and support resources most relevant to each user's context, thereby significantly improving the effectiveness of support resources while maintaining ease of implementation through automated personalization.
Data Source
AI summary
According to certain aspects, a method of assessing users of a data storage system can include receiving configuration information relating to a deployed configuration of a first data storage cell and including number of installed data storage hardware and/or software components, the first data storage cell comprising a plurality of client computing devices and being configured to create and store one or more secondary copies of primary data generated by the plurality of client computing devices. The method may also include receiving information relating to an incident opened by a user of the first data storage cell. The method may further include updating a performance metric associated with the user to a new value to reflect a negative impact on the performance metric resulting from the opening of the incident by the user, wherein the degree of the negative impact is based at least in part on the configuration information.