A Strategic Management System Based on Systemic Learning Algorithm

Abstract

The paper is devoted to the development of strategic management systems for companies and organizations to solve two problems that are typical for the current level of these systems: insufficient synchronization of strategic management systems with operational management systems and insufficient adaptability of strategic management systems to changes in external environment. To solve the first problem, for each category of objects in the operational management system is proposed to use a separate internal perspective in strategic management system. To solve the second problem, for each internal perspective is proposed to include in the system one additional external perspective reflecting the state of the environment. The problem of strategic management is formulated as the problem of Systemic Learning. To solve it, a combined active-passive algorithm of Systemic Learning is proposed. The presence of the passive component is due a lot of time between the individual decision making (month, quarter), during this time complex calculations can be performed. For a set of scenarios with a relatively high probability, all states and possible transitions between them will be calculated for entire depth of the forecasting period. To ensure high adaptation to changing of external conditions, the developed algorithm has an active component. After each step, information on trends, target values of indicators and probability of scenarios are updated, sets of initiatives may be changed. The architecture of the system’s prototype capable of implementing the proposed ideas contains two parallel running On-Premise instances of the strategic management solution as well as additional modules for Systemic Learning algorithm execution and scenario network’s maintenance.