Abstract
Amid increasing production complexity and growing uncertainty, effective inventory management has become critical for ensuring the financial sustainability of industrial enterprises. Conventional approaches, largely based on normative calculations and retrospective control, are increasingly inadequate, highlighting the need to integrate management accounting techniques with lean manufacturing tools (Lean). This study develops and empirically substantiates an inventory forecasting and management framework grounded in management accounting data and supported by lean principles and predictive analytics. The empirical analysis is based on data from a machine-building assembly enterprise in the Republic of Kazakhstan for the period 2021–2025. The information base comprises trial balance statements for account 1300 “Inventories” and its sub-accounts, along with cost of goods sold indicators reported in the financial statements. The research includes a comprehensive assessment of inventory dynamics, structure, and flow formation. Particular attention is given to turnover ratios, inventory intensity, imbalances between material inflows and outflows, and time lags between operational scale adjustments and inventory levels. The findings indicate that inventory management practices remain predominantly reactive and are characterized by shifts in inventory control regimes – from the accumulation of work in progress to excessive stockpiling of components and materials. Based on the empirical results, a target inventory level model is proposed. The model defines an optimal inventory range and enables quantitative evaluation of the management gap between actual and target inventory levels. The practical contribution lies in the model’s applicability for bottleneck diagnostics and evidence-based managerial decision-making within the inventory management system of a machine-building assembly enterprise.