Control Tower Platform With Unified RPA for Value Chain Data Complexity
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Solution Overview
Problem
Organizations face challenges in managing complex and voluminous data from smart devices and IoT systems, leading to overwhelming complexity and missed insights, necessitating systems that convert data into actionable insights and timely decisions for efficient operations.
Innovation Solution
A cloud-based management platform with a micro-services architecture, incorporating interfaces, network connectivity, adaptive intelligence, data storage, and monitoring facilities, along with robotic process automation systems, to manage value chain network entities from origin to customer use, facilitating coordinated automation among supply chain and demand management applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If organizations implement multiple data collection systems (IoT sensors, wearables, CRM, ERP), then the quantity and variety of available data increases, but the complexity of managing and processing this data increases
Solution Approach 1:
The patent combines multiple separate data collection systems (IoT sensors, wearables, CRM, ERP) into a unified data management platform. This consolidation reduces the number of separate systems organizations must manage while maintaining access to diverse data sources, directly addressing the complexity issue while preserving data quantity.
Solution Approach 2:
The control tower platform serves multiple functions: data collection, data processing, analytics, and decision support. This multi-functional approach eliminates the need for separate specialized systems for each function, reducing overall system complexity while handling large volumes of diverse data.
2Loss of information
If organizations collect and store large amounts of data from multiple sources, then the potential for insights increases, but the difficulty of converting data into actionable insights increases
Solution Approach 1:
The control tower acts as an intermediary layer between raw data sources and decision-makers. It processes, analyzes, and translates complex multi-source data into actionable insights, reducing the difficulty of insight extraction while maintaining information quality.
Solution Approach 2:
The patent replaces manual data analysis processes with automated analytics systems and AI/ML algorithms. This substitution transforms the mechanical process of converting data to insights, reducing difficulty while preserving insight quality.
3Ease of operation
If organizations use traditional linear supply chain management, then operational simplicity is maintained, but responsiveness to changing demand and market conditions deteriorates
Solution Approach 1:
The control tower enables dynamic supply chain management by continuously monitoring data from multiple sources and automatically adjusting operations in response to changing conditions. This maintains adaptability while using standardized processes to preserve operational simplicity.
Solution Approach 2:
The system implements continuous feedback loops where data from IoT sensors, market conditions, and operational metrics are constantly monitored and fed back to adjust supply chain decisions. This enhances responsiveness while using automated feedback mechanisms to maintain operational simplicity.
4Device complexity
If manual processes are used for supply chain and demand management, then system complexity is reduced, but productivity and timeliness of decisions deteriorate
Solution Approach 1:
The control tower enables self-service automation where the system automatically collects data, analyzes insights, and executes decisions without extensive human intervention. This increases productivity while using standardized automated processes to manage system complexity.
Solution Approach 2:
The patent changes the operational parameters from manual processing speeds to automated processing speeds. This dramatically increases productivity while the modular architecture of the automation system keeps complexity manageable.
Data Source
AI summary
An information technology system generally including a cloud-based management platform with a micro-services architecture having a unified set of robotic process automation systems that provide coordinated automation among at least two types of applications from among a set of demand management applications, a set of supply chain applications, a set of intelligent product applications, and a set of enterprise resource management applications for a category of goods with respect to the value chain network entities of the platform.