Complexity-Based Forecasting, based on Quantitative Complexity Management and SDI (Stochastic Design Improvement, a Monte Carlo Simulation-based technique developed by Dr. J. Marczyk in late 1990s) is an advanced forecasting system developed for applications in Business, Finance and Economics. The system has been developed specifically for conditions of high uncertainty, interdependency and turbulence.

In addition to forecasting, the tool enables us to drive a given system to a specified target value of complexity and resilience. In practice, the system determines the parameters of a business process so that its complexity and resilience attain prescribed levels. The ability to actively drive the value of complexity and resilience of a given system sets new standards not only in management but also in design of processes and products.

The forecasting service is very simple:

You send us an array of M columns and N samples and we tell you what sample N+1 will be.

Applications of our forecasting service are numerous. A few example are:

• Estimate the performance of a corporation in the next quarter.
• Estimate the performance of a corporation in the next quarter under certain assumed conditions (e.g. price of oil). This is an example of the so-called "what-if?" analysis.
• Estimate the performance of stock portfolios.
• Estimate traffic volumes
• Estimate transaction volumes  
• Stress testing

Complexity-Based forecasting is an exclusive service aimed at large corporations. It produces results of immense strategic value. In a turbulent economy, in which unexpected and extreme events will be increasingly frequent and intense, conventional predictive analytics are of little use. It is necessary to resort to new science-based techniques which have been designed specifically to cope with highly uncertain and non-stationary regimes.

Write to us for more information.