Automated Supplier Risk Data Retrieval in E-Procurement

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Solution Overview

Problem

Inefficient and error-prone manual processes for entering and managing supplier information in e-procurement systems hinder the completion of digital transactions, as buyers must manually communicate with suppliers to gather necessary data for supplier onboarding and risk assessment.

Innovation Solution

Automated data exchange is achieved through intelligent mappings of supplier risk scores to information request identifiers, generating custom data forms that are transmitted to suppliers, reducing the need for manual intervention and improving workflow efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual communication methods (email, phone calls) are used to request supplier data, then buyers can obtain supplier information, but the process becomes inefficient and error-prone

Engineering Contradiction:
Improveaccuracy of supplier information retrievalVSAvoidefficiency of supplier onboarding process
Core Design Contradiction:
ReliabilityVSProductivity

Solution Approach 1:

The system enables suppliers to self-serve by automatically receiving customized data request forms based on their risk scores and independently submitting required information through the e-procurement platform, eliminating the need for manual buyer-supplier communication while improving both accuracy and efficiency

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system performs preliminary actions by automatically generating customized data request forms before suppliers submit information, using pre-defined mappings between risk score values and information request identifiers to prepare targeted questions based on the supplier's specific risk profile

Inventive Principle:
Principle #10Preliminary action

2Measurement precision

If comprehensive supplier data collection is implemented to improve risk assessment accuracy, then better risk scores are achieved, but the complexity of data management increases

Engineering Contradiction:
Improveprecision of supplier risk scoringVSAvoidcomplexity of information management system
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the comprehensive supplier data collection process into distinct components: risk score calculation based on multiple factors (financial stability, delivery performance, quality metrics), mapping risk scores to specific information requests, and generating customized forms with only relevant questions, thereby managing complexity while maintaining precision

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system applies local quality by tailoring data collection requirements to each supplier's specific risk profile, generating customized forms that request only the specific information relevant to that supplier's risk assessment rather than requiring all suppliers to provide identical comprehensive data sets

Inventive Principle:
Principle #3Local quality

3Ease of operation

If automated form generation based on risk scores is implemented, then manual effort is reduced, but system complexity increases

Engineering Contradiction:
Improveease of supplier onboardingVSAvoidcomplexity of automated system
Core Design Contradiction:
Ease of operationVSDevice complexity

Solution Approach 1:

The system introduces an intermediary layer consisting of pre-configured mapping tables that connect risk score values to information request identifiers and form templates, allowing the complex automated form generation logic to be managed through standardized intermediaries rather than direct complex programming

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The system achieves universality by creating a multi-functional automated form generation mechanism that can handle multiple risk score values, map to various information request types, and generate different customized forms all through a single integrated process, reducing manual effort across diverse scenarios

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentUS11157850B2Automated information retrieval based on supplier risk
Publication Date: 2021.10.26 COUPA SOFTWARE INC
  • US11157850B2 patent drawing
  • US11157850B2 patent drawing
  • US11157850B2 patent drawing

AI summary

Techniques are provided for automated information retrieval based on supplier risk. In an embodiment, a selection of a supplier identifier value that identifies a supplier during a supplier onboarding process in an e-procurement system is received. A digital data repository of the e-procurement system is queried to seek a data record matching the selected supplier identifier value. In response to determining that the data repository has a record matching the selected supplier identifier value, a risk score value associated with the selected supplier identifier value is identified from a dataset of risk score values that is stored in the data repository. A unique mapping table is generated that maps each supplier risk score value of one or more supplier risk score values to one or more information request identifiers, the one or more supplier risk score values including the risk score value associated with the selected supplier identifier value. A custom digital data entry form is generated that comprises one or more information request fields that are mapped to the risk score value associated with the selected supplier identifier value. The custom data entry form is transmitted to a computer associated with the supplier corresponding to the selected supplier identifier value, the custom data form prompting the supplier to take action, respond, or contribute information back to the server computer.