In transition economies, digitalization has become one of the main forces behind innovation and competitiveness among manufacturing firms, yet managers rarely have analytical tools to confirm whether their digital investments actually translate into better products and processes. This paper addresses that gap by building an IT-enabled analytics framework for evaluating technological innovation outcomes in manufacturing enterprises, situating the discussion within the wider digital economy and business analytics literature. Rather than treating information technologies purely as engineering infrastructure, the study frames them as enablers of data-driven decision-making and organizational change. Combining the resource-based view with dynamic capabilities theory, the paper develops an analytical model that connects manufacturing digitalization to product and process innovation through the capabilities of sensing, seizing, and reconfiguring. The empirical analysis draws on survey responses collected from manufacturing firms across Uzbekistan’s major industrial regions, with Structural Equation Modeling (SEM) applied as the business-analytics tool for testing both direct and mediated relationships among the constructs. The results show that digitalization has a substantial positive effect on technological innovation overall; dynamic capabilities fully mediate its effect on product innovation and partially mediate its effect on process innovation. In practical terms, this means digital tools alone are not enough, since firms also need the organizational and analytical capacity to put them to use. By demonstrating how IT-enabled analytics can support innovation-driven industrial development, the study contributes new evidence on the digital economy from an emerging-market setting.