Enterprise Communication Data Analysis System
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Solution Overview
Problem
Large enterprises face inefficiencies and risks due to the complexity of aggregating and analyzing employee communications data from various digital tools, which are often underutilized despite providing an unfiltered view into business processes.
Innovation Solution
A computer-implemented method and system that collects communications data from digital sources, synthesizes it into structured data, performs exploratory and confirmatory data analysis, and disambiguates findings to determine organizational risks and inefficiencies, generating business processes to mitigate these issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional methodologies (surveys, interviews) are used to gather employee information, then data collection is simple and manual review is feasible, but the process is overly time- and resource-intensive and infeasible for large-scale enterprises
Solution Approach 1:
The patent replaces manual mechanical processes (circulating surveys, conducting interviews, manual review) with an automated computer-based system that collects, stores, synthesizes, mines, and analyzes employee communication data automatically, eliminating the need for human reviewers to manually process information
Solution Approach 2:
The system enables self-service by automatically gathering data from digital communication tools, performing synthesis and analysis without human intervention, and generating insights that would otherwise require manual effort from reviewers
2Measurement precision
If employee digital communication data is collected and analyzed, then unfiltered and unbiased insights into actual business processes are obtained, but the data comes in large volumes from multiple sources in different formats and locations
Solution Approach 1:
The patent creates a universal system capable of handling multiple data types (emails, instant messages, collaborative platform data) from various digital communication tools, storing them in a unified database structure that can process and analyze diverse formats through common synthesis and analysis routines
Solution Approach 2:
The system introduces an intermediary database and processing layer that sits between the various digital communication tools and the analysis functions, standardizing and normalizing data from different sources before analysis, thereby simplifying the complexity of aggregating heterogeneous data
3Reliability
If comprehensive data analysis is performed to identify organizational risks and inefficiencies, then accurate business impacts are determined, but the amount of data processing and analysis required is substantial
Solution Approach 1:
The patent segments the data analysis process into distinct automated stages: data collection from multiple sources, storage in database, synthesis to create structured data, mining to generate exploratory data, and analysis to produce confirmatory data. This segmentation allows each stage to be optimized independently and processed efficiently by computer systems
Solution Approach 2:
The system performs preliminary actions by automatically collecting and storing communication data as it is generated, synthesizing it into structured formats in advance, and preparing it for analysis, so that when analysis is needed, the data is already organized and ready, reducing processing time
Data Source
AI summary
Systems and methods are provided for assessing risks and efficiencies based on enterprise communications information. A method for assessing risks and efficiencies based on enterprise communications information may include: collecting information from digital data tools over at least one computer network into a storage database in a computer memory; executing instructions on a computer processor to synthesize the employee communications data into structured data; mining the structured data to generate exploratory data; performing analytics on the structured data to generate confirmatory data; disambiguating the confirmatory data and exploratory data; determining a business impact based on the exploratory and confirmatory data; and implementing a business process based on a quantification of said business impact.