Organizational manageability is a crucial aspect of business management, requiring a combination of forecasting, planning, organizing, implementing, controlling and decision-making. Topological modular forms study the properties of objects that are invariant under certain types of transformations and the authors search for and identify a set of key factors that are essential to the organizational manageability (both stable and unstable) and create a framework that captures these factors. Organizational manageability is highly complex and multifaceted field that requires the integration of mentioned elements. In order to simplify incommensurable complexity, authors offer the hypothesis that differentiating the approach to manageability in the two distinct situations "steady and familiar condition" and "unsteady and with considerable uncertainty condition" is effective. Discrimination between those two situations is essential for business success and requires a deep understanding of market trends, customer needs, design of organization and usage of resources. By mastering the principles of organizational manageability based on mentioned classification of situations, businesses can improve their performance, increase their competitiveness and achieve their goals more effectively.

This paper aims to focus on identification and selection of the decision-making tools by planner using the ratio between known and unknown in sophisticated planning process. Decision situations in planning are multiplex (company objectives extrapolated through modelling in the future and mixed with uncertainty and risks), dynamic (dependent and independent events amalgamated in space and time and reflected in advanced analytics applications) and requires subjective thinking abilities from planner in the conditions of vague information, unvalidated data and tough deadlines. The objective of the research is to find the most appropriate tool in decision making for different planning situations through evaluating knowledge gradient for identified situation. Specific hypothesis of the study is usage of the knowledge gradient during decision-making under uncertainty that helps planner to easier the plan creation. The closest fields of application are planning in manufacturing transportation, logistics, delivery, supply chain management, organizational management.