Requisition Rejection Prediction Scoring Unit
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Solution Overview
Problem
In computer-based procurement systems, users face inefficiencies due to the lack of real-time prediction of requisition approval or rejection, leading to time-consuming revisions and resource consumption, as they cannot anticipate whether a requisition will be accepted or rejected until submission, and subsequent rejections require repetitive resubmissions.
Innovation Solution
A computer-implemented method that predicts the likelihood of requisition rejection by analyzing electronic requisition data using a scoring unit, incorporating factors like vendor information, product metadata, user profiles, and enterprise rules, and displays this probability to users in real-time, allowing for proactive revisions before submission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users submit requisitions without real-time prediction of approval or rejection, then the procurement system can process all submissions, but users experience time-consuming revisions and repeated submissions
Solution Approach 1:
The system performs preliminary evaluation of requisitions before formal submission by providing real-time predictions of approval or rejection. This allows users to anticipate outcomes and make necessary revisions beforehand, eliminating the need for time-consuming repeated submissions after initial rejection.
Solution Approach 2:
The system provides immediate feedback to users in the form of prediction results before requisition submission. This feedback mechanism enables users to understand potential rejection reasons and adjust their requisitions accordingly, reducing the iterative cycle of submission-rejection-resubmission.
2Reliability
If users repeatedly resubmit rejected requisitions, then they can eventually achieve approval, but computer resources and network bandwidth are unnecessarily consumed
Solution Approach 1:
The system evaluates requisitions in advance and provides prediction results before formal submission. This preliminary action filters out potentially rejected requisitions before they enter the formal processing pipeline, preventing unnecessary consumption of computer resources and network bandwidth that would otherwise be spent on repeated submissions.
3Ease of operation
If the system provides real-time prediction of requisition rejection likelihood, then users can proactively revise and improve approval chances, but the system complexity increases
Solution Approach 1:
The system introduces an intermediary prediction module that sits between the requisition submission interface and the formal approval process. This intermediary layer evaluates requisitions in real-time and provides predictions to users, enabling proactive revisions without fundamentally altering the core approval workflow or requiring excessive system complexity.
Data Source
AI summary
In an embodiment, an automated computer-based method for improving a computer system to be able to predict rejections of requisitions submitted to the computer system, the method comprising receiving a requisition from a client device; determining, at a scoring unit of a computer system, a probability value indicating a likelihood that the requisition would be rejected if the requisition is submitted to a requisition approval chain; transmitting the probability value from the computer system to the client device to be displayed on a display of the client device.