Automated Timers for Client-Server Production Event Costing
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Solution Overview
Problem
Traditional costing methods, including time-driven activity-based costing, fail to accurately account for the complex and variable nature of production processes in enterprises, particularly in healthcare, leading to inaccurate cost information and suboptimal decision-making.
Innovation Solution
Implement a system and method for time-feature-driven activity-based costing (TFDABC) that utilizes automated timers and Bayesian sampling to identify distinct clusters within business processes, establishing regression models to determine the quantitative relationship between resource features, cost drivers, and activity drivers, thereby optimizing cost accounting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional time-driven activity-based costing methods are used, then cost accounting is simplified, but measurement precision and accuracy of cost information deteriorate
Solution Approach 1:
The patent segments the business process into distinct clusters or groups based on measured data patterns. By dividing the continuous process into discrete segments with similar characteristics, the system achieves both simplicity (through manageable segments) and precision (through targeted measurement of each segment's specific cost drivers and relationships).
Solution Approach 2:
The patent changes the parameters of cost accounting by moving from fixed, predetermined cost rates to dynamic, data-driven cost models. The system measures actual time and resource consumption, then uses regression analysis to establish quantitative relationships between cost drivers and actual costs, allowing cost parameters to adapt to real-world variations.
2Measurement precision
If detailed automated timer measurements are implemented across all client systems, then measurement precision improves, but device complexity and data processing requirements increase
Solution Approach 1:
The patent implements a universal timer system that runs across multiple client applications and server systems using common infrastructure (HP Vertica database, standardized data collection protocols). This multi-functional approach allows the same measurement mechanism to serve numerous different business processes simultaneously, reducing overall system complexity while maintaining high measurement precision across all applications.
Solution Approach 2:
The timer system operates autonomously, automatically measuring time consumption without requiring manual intervention or complex configuration for each measurement event. The system self-collections data, self-stores measurements in the database, and self-processes the information through automated regression analysis, minimizing the operational complexity burden on users.
3Measurement precision
If regression models are built for each distinct cluster, then cost forecasting accuracy improves, but device complexity and computational requirements increase
Solution Approach 1:
The patent segments the overall cost modeling problem into multiple smaller, cluster-specific regression models. Instead of building one complex model for all data, the system divides the data into distinct clusters with similar characteristics and builds simplified regression models for each cluster. This segmentation reduces the complexity of individual models while improving their accuracy for their specific segments.
Solution Approach 2:
The patent applies local quality by creating specialized regression models tailored to each cluster's specific characteristics rather than using a single uniform model. Each cluster receives a customized model that reflects its unique cost driver relationships, improving local accuracy (for that specific cluster) while the overall system manages complexity through the modular, distributed nature of these local models.
Data Source
AI summary
The activities performed by an organization are conventionally identified using activity analysis. This involves determining what activities are done within the department, how many people and of which skills perform the activities, how much time they spend performing the activities, what resources are required to perform the activities, what operational data best reflect the performance of the activities, and the value of the activities to the organization. Historically, these determinations involved extensive interviewing and time-and-motion data gathering. However, some embodiments provided herein facilitate using an automated response time measurement system for measuring and characterizing activities for presentation on a user interface using online data that accrue as a byproduct of the performance of the activities.