Causal Modelling


Causal modelling assists the top management and decision-makers in optimizing strategic management. Causal analyses constitute essential cornerstones of business intelligence (BI). As such, they help to:

  • secure investments (planned or done)
  • improve the workflow
  • increase efficiency and productivity and, thus,
  • boost competitiveness.

Clearly, causal analyses have an advantage over other analytical BI-tools such as SPSS Clementine® or Oracle's Balanced Scorecard®. Simply, this is because all factors in a causal model are analyzed simultaneously.

Today's corporate management bears many risks. However, strategic management errors can be reduced significantly by employing causal analyses based on our proprietory 4M Technology. Since causal analyses require 'hard' data, key management decisions can be made on a much more reliable and objective basis.

Consequently, causal analyses help to avoid malinvestment and, at the same time, allow for more effective HRD/HRM.

Causal modelling can be applied to nearly all business sectors and to a whole range of strategic management issues. Of course, causal analyses are no foolproof method to avoid management errors altogether. But they assist significantly to limit the possibility of making the wrong strategic decision.