Business Model Optimization Engine for IT Scalability
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Solution Overview
Problem
Current methodologies for business transformation, such as balanced scorecard, COBIT, and ITIL, are expensive, ad-hoc, and fail to scale with the rapid changes in globally integrated enterprises, lacking an integrated framework for aligning business and IT strategies effectively.
Innovation Solution
A computer-based method for developing and managing business models using a business model tool that aligns business strategy, goals, and constraints, incorporating a model optimization engine to iteratively update and optimize business models based on performance benchmarks, enabling continuous improvement and strategic transformation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional methodologies (balanced scorecard, COBIT, ITIL) are used for business transformation, then structured frameworks are provided, but they are expensive, ad-hoc, and do not scale with rapid changes
Solution Approach 1:
The patent implements a dynamic business model that automatically adapts to changing conditions through continuous monitoring of performance parameters and iterative optimization. The system adjusts business models in real-time based on actual performance data, eliminating the need for static, ad-hoc methodologies while maintaining structured framework benefits.
Solution Approach 2:
The system incorporates continuous feedback loops where performance data from business operations is automatically collected, analyzed, and used to optimize business models. This feedback mechanism enables the system to learn from actual performance and automatically adjust, replacing manual ad-hoc adjustments with automated continuous improvement.
2Productivity
If business models are manually created and monitored, then customization is possible, but the process is time-consuming and lacks continuous optimization
Solution Approach 1:
The system performs self-optimization by automatically monitoring its own performance parameters, analyzing results, and adjusting business models without requiring manual intervention. The business model monitors itself, identifies areas for improvement, and implements optimizations autonomously, dramatically increasing productivity while eliminating time-consuming manual processes.
Solution Approach 2:
The system maintains continuous optimization operations through uninterrupted monitoring and iterative improvement cycles. Performance data is continuously collected and processed, enabling constant refinement of business models without the start-stop nature of manual review processes, thus maximizing productivity over time.
3Adaptability or versatility
If multiple business models are created to explore different strategies, then strategic options increase, but the complexity of managing and selecting optimal models increases
Solution Approach 1:
The system segments the business model management process into distinct components: multiple strategic models can be created and maintained separately, each optimized for different scenarios. The system then systematically evaluates these segmented models against actual performance data, making the management of strategic options more organized and less complex through structured decomposition.
Data Source
AI summary
A method and system for operating an enterprise via an optimized business model. An output benchmark value is generated. An initial benchmark value for a resource of an enterprise is updated based on the output benchmark value. The business model is updated. A process is iteratively performed based on the updated benchmark value and model, until the benchmark value is changed by less than a predetermined threshold to generate the optimized business model. The enterprise is operated in accordance with the optimized model which includes: generating performance measures of usage of a computer resource, dynamically displaying a dashboard of the performance measures, determining from the displayed performance measures that the computer resource is a current bottleneck or is likely to become a bottleneck in the near future, and optimizing the computer resource's usage using the displayed performance measures to reduce data throughput delay and increase throughput of bottleneck operations.