businessneutral
Banking in a Pandemic: Navigating Resources and Capabilities
IndonesiaWednesday, May 21, 2025
The proposed model includes seven key managerial decisions. These are probe, sense, structuring, bundling, building, leverage, and reconfiguring. The model uses fuzzy preference judgments as inputs, deep learning analytics for processing, and success rate predictions as outputs. In theory, this research improves dynamic capabilities using the cynefin framework. In practice, it gives the board of directors a tool to make better decisions about resources and capabilities during complex environmental changes.
The cynefin framework is a sense-making tool. It helps organizations navigate complex situations. By integrating this framework, the model can handle the uncertainty and complexity that banks face today. Deep learning analytics adds another layer of sophistication. It allows the model to predict outcomes based on vast amounts of data. This predictive power is crucial in a fast-changing environment like banking.
The model's success rate predictions are a game-changer. They provide a clear, data-driven way to evaluate decisions. This is especially important in banking, where the stakes are high. The board of directors can use these predictions to make informed decisions. They can allocate resources more effectively and adapt to changes more quickly. This is not just about surviving the pandemic. It is about thriving in a complex, ever-changing world.
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