CRITERIA FOR DIGITAL ANALYTICAL INFORMATION SUITABILITY IN MANAGERIAL DECISIONS

Abstract

The purpose of the article is to theoretically substantiate a system of criteria for assessing the suitability of digital analytical information for specific managerial decisions. The research employs comparative analysis of scientific approaches, conceptual modelling, logical deduction and scenario analysis using hypothetical numerical data. General data quality, information suitability for a task and managerial decision performance are distinguished. Information requirements are derived from the available courses of action, intended outcome, planning horizon, decision deadline, opportunities to revise the decision and losses associated with errors. Universal requirements for information transparency are separated from task-dependent criteria for information sufficiency. A matrix linking the criteria to four tasks is developed: inventory replenishment, marketing budget allocation, investment project selection and an operational response to supply disruption. The matrix specifies the required timeliness, granularity, scope, accuracy, explainability and stability of analytical conclusions. The scientific contribution consists in aligning these criteria with task characteristics and with a procedure for examining whether information limitations can reverse the preference between alternatives. A numerical example shows that highly accurate individual indicators do not necessarily justify a choice and that uncertainty does not always require postponing action. The example examines a rule that minimizes the maximum loss in expected benefit and identifies an upper bound on the potential benefit of obtaining more precise information. Information gaps are assessed in terms of their influence on the choice, the cost of obtaining additional information and the consequences of delaying the decision. The practical significance lies in using the matrix to prepare analytical assignments, review management reports and document the limitations of recommendations without developing a new software product. The study is theoretical; the calculations illustrate the logic of the approach and are not based on observations of enterprises. Conditions for revising information requirements following changes in objectives or available courses of action are specified. Future research should empirically examine agreement between evaluators in applying the criteria, measure information acquisition and decision delay costs, and investigate changes in choices under different characteristics of decision-support information.