Enterprise Value Optimization via Unified Data Platform
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Solution Overview
Problem
Conventional data management practices in new age organizations lead to complexity, silos, and inefficiencies, negatively impacting service delivery and ROI due to misaligned information and lack of visibility across co-dependent business units, making it challenging to measure the impact of changes on overall quality and service delivery.
Innovation Solution
An integrated system that processes and analyzes data from multiple sources to generate value graphs, providing actionable insights and optimizing key performance indicators (KPIs) across various processes and services, enabling stakeholders to make strategic decisions and improve value delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data is stored centrally or dispersed in spreadsheets by respective business units, then data management is simplified, but silos are created and visibility is reduced
Solution Approach 1:
The patent merges data from multiple dispersed business units into a unified data platform, eliminating silos while maintaining data accessibility. The integration layer combines data from different sources into a centralized repository that preserves the benefits of distributed data collection while achieving organization-wide visibility.
2Ease of manufacture
If conventional data management practices are used, then implementation is straightforward, but service delivery capabilities are negatively impacted
Solution Approach 1:
The system is segmented into distinct functional layers: data collection layer, integration layer, analytics layer, and application layer. This modular architecture maintains ease of implementation while significantly improving service delivery capabilities by enabling specialized processing at each layer.
Solution Approach 2:
An integration layer acts as an intermediary between dispersed data sources and business units, facilitating data flow and coordination without requiring complex point-to-point connections. This mediator enables improved service delivery while keeping the overall system implementation straightforward.
3Adaptability or versatility
If data is managed through disparate systems, then storage is distributed, but misaligned information leads to lower ROI
Solution Approach 1:
The unified data platform serves multiple functions simultaneously: it stores data from diverse sources, standardizes data formats, enables cross-unit analytics, and supports various business applications. This multi-functional approach maintains storage flexibility while ensuring information alignment across the organization.
Data Source
AI summary
A system and a method to optimize values delivered by an enterprise, are described. An integrated system may receive data from multiple data sources that may be processed by engines and/models. The engines and/or models may execute operations or functions, such as data processing, analysis based on rules, automated learning, machine learning and transforming the data to create value graphs associated with processes, tasks, and/or services in the enterprise. The value graphs may be generated that may provision continuous monitoring and insights to measure of KPIs and other influencing factors that may be associated with the processes, and services in the enterprise. The integrated system may generate visualizations that may be rendered via user interfaces. Further based on the value graphs, stakeholders may be able to identify opportunities associated with processes, tasks, and/or services that may be actioned to drive employee engagement, and value of the enterprise.