GUI Icon Rearrangement for Availability-Based Candidate Selection
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Solution Overview
Problem
The current process for staffing professional services, such as in law firms, is inefficient due to ad-hoc and experience-based team assembly, leading to inaccurate assessments of attorney availability and poor team fit for specific tasks.
Innovation Solution
A system comprising a central server and user terminals that allows for the optimization of professional services resources by determining optimal candidates for staffing based on calculated matter and user input values, displayed to users for selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If ad-hoc and experience-based team assembly is used, then the process is simple and flexible, but the accuracy of attorney availability assessment and team fit deteriorates
Solution Approach 1:
The patent introduces a central server as an intermediary between partners and attorneys. The server receives availability inputs from attorneys, processes this data along with matter requirements, and generates optimized team assignments. This intermediary system maintains the simplicity of the user interface while performing complex calculations behind the scenes, thus preserving ease of operation while improving measurement precision of attorney availability and team fit.
Solution Approach 2:
The patent replaces the manual, experience-based mechanical process of team assembly with an automated computational system. Instead of partners manually discussing and assessing attorney availability, the system uses algorithms to process availability data and generate optimal assignments. This substitution maintains operational simplicity for users while dramatically improving the precision of availability assessment through systematic data processing.
2Adaptability or versatility
If manual team assembly discussions are used, then the process allows for informal flexibility, but the productivity and efficiency of staffing deteriorates
Solution Approach 1:
The patent implements preliminary action by having attorneys pre-input their availability information into the system before matters are assigned. The central server then processes this pre-collected data along with matter requirements to generate ready-to-use team assignments. This preliminary data collection and processing maintains flexibility in how attorneys report availability while dramatically improving staffing efficiency by eliminating manual discussion time.
Solution Approach 2:
The patent enables self-service by allowing attorneys to independently input their own availability information into the system. This eliminates the need for partners to manually inquire about each attorney's availability, maintaining the flexibility of individual availability reporting while significantly improving overall staffing productivity through automated data collection and processing.
3Measurement precision
If a centralized optimization system is implemented, then the precision of candidate selection improves, but the device complexity increases
Solution Approach 1:
The patent extracts the computational complexity from the user interface and places it in the central server backend. The user terminals present a simple interface for inputting availability and selecting from pre-generated candidate lists, while the complex optimization algorithms run on the server. This extraction maintains high precision in candidate selection while keeping the device complexity perceived by users minimal.
Solution Approach 2:
The patent uses copying by generating multiple candidate assignments based on the optimization algorithm and presenting these pre-computed options to users. Instead of requiring users to perform complex analysis themselves, the system creates copies of potential solutions and presents them in an easily comparable format. This maintains high selection precision while simplifying the user interface and reducing perceived system complexity.
Data Source
AI summary
Systems and methods for rearranging icons on a graphical user interface are disclosed herein. In an embodiment, the method includes arranging a plurality of icons corresponding to a plurality of candidates on the graphical user interface, receiving a selection of a first candidate of the plurality of candidates from a user using the graphical user interface, determining, by a processor, an availability of the first candidate over a predetermined time period, and automatically rearranging the plurality of icons on the graphical user interface for selection of a second candidate based at least in part of the availability of the first candidate.