A Heuristic and Algorithmic
Viability drives Sustainable Development and Long term Value Creation
Explanation of the Model
By following an initial algorithmic classification with a heuristic analysis of the properties of a complex adaptive system the model revolutionized the measurement and monitoring of the business-related risks to the dynamics of organizations that drive viability and predict the behaviour of a company to give unique strategic intelligence for investment and resource allocation decisions. Predictive data analytics and system science are combined in one consistent, integrated approach to design forward-looking KPIs that support sustainable investment decisions and monitor real-time operating performance during the life-cycle of an investment.
Below you see a visualization of the model. The pictures are blurred to protect intellectual property. You can contact us if you are interested to use the model.
To summarize, the model combines macro and micro business elements as they are interdependent and cannot be assessed separately as in a complex system, small events might have high impact consequences. The power of the model (as manifested in the forward-looking KPIs that it generates) is that it combines qualitative and quantitative data. It transfers qualitative data (e.g., viability and stress) into quantitative data by seeing a company as a complex adaptive system. Therefore, it discounts the expert factor and takes out the human element or bias, which makes it more reliable than qualitative models and more effective than a quantitative model.
“Resource allocation is one of the most difficult challenges for a company and maybe the most important role of a Board. The model gives valuable information on how to pro-active allocate resources to drive long-term sustainable value creation”