Conversational Business Analytics for Real-Time Supply Chain Insights
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Solution Overview
Problem
Business data related to supply chain management is complex and difficult to understand, with existing methods like paper reports, phone/email communication, and interactive dashboards being inflexible, time-consuming, or requiring specialized training, and failing to provide real-time, relevant insights.
Innovation Solution
A conversational business tool using Natural Language Processing (NLP) to interpret user queries, integrate with a business database, and deliver insights in a conversational manner, allowing real-time data access and collaboration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If paper reports are used to communicate aggregate business data, then data can be provided in a static format, but the reports are inflexible, require valuable time and financial resources to create, and do not provide real-time updates
Solution Approach 1:
The patent transforms static paper reports into dynamic, automatically updating digital reports that refresh in real-time without requiring manual recreation. The system continuously pulls data from connected sources and regenerates visualizations automatically, eliminating the time-consuming manual update process while maintaining data accuracy.
Solution Approach 2:
The patent creates digital copies of traditional reports that can be instantly replicated and distributed. These digital report copies maintain the same analytical value as original paper reports but can be generated and updated automatically through software, eliminating the need to recreate reports from scratch each time updates are needed.
2Quantity of substance
If paper reports include detailed data, then comprehensive information is provided, but irrelevant details obscure important aspects and insights
Solution Approach 1:
The patent extracts and highlights only the most relevant insights and key performance indicators from large datasets, separating critical information from irrelevant details. The system automatically identifies and surfaces the most important findings while allowing users to drill down into detailed data only when needed, improving readability without losing comprehensive information.
Solution Approach 2:
The patent applies different levels of detail and presentation quality to different parts of the report based on their importance. Critical insights receive prominent visualization and explanation, while secondary data is presented more concisely or aggregated, allowing the report to maintain both comprehensiveness and clarity through differentiated presentation quality.
3Adaptability or versatility
If interactive dashboards are used to display business metrics, then data can be filtered and modified, but the visualizations require even more training to comprehend and do not allow multitasking
Solution Approach 1:
The patent segments complex dashboard interfaces into simpler, focused modules that present one key insight or metric at a time. Each segment is self-contained and easy to understand independently, reducing the cognitive load required to comprehend the overall system while maintaining filtering and modification capabilities within each segment.
Solution Approach 2:
The patent introduces natural language processing and conversational interfaces as intermediaries between the user and complex data visualizations. Users can ask questions in plain language and receive targeted answers with relevant data, eliminating the need to navigate complex dashboard filters and visualizations while still providing access to filtered and modified data when needed.
4Loss of information
If visualizations and graphs are used to present business data, then data can be displayed graphically, but trained skills are required to interpret meaningful results
Solution Approach 1:
The patent incorporates automated insights and explanations that provide feedback alongside visualizations. The system analyzes the data and automatically generates narrative explanations, trend descriptions, and actionable recommendations that accompany graphical displays, eliminating the need for users to interpret visualizations without guidance while preserving comprehensive data visualization.
Data Source
AI summary
A business analytics conversational tool comprising: a device comprising a communication channel, a natural language processor (NLP), a fulfillment application program interface (F-API), a database application program interface (D-API), and a business management database; wherein: the NLP receives a user-input from a user through the communication channel; the NLP deduces an intent of the user-input; the NLP communicates the intent to the F-API; the F-API communicates a request for data associated with the intent to the database via the D-API; the D-API communicates the data associated with the intent to the F-API; the F-API converts the data associated with the intent to conversational form and sends the conversational form for voice output through the communication channel.