Requirement engineering continues to be document-centric and a heavily manual activity relying on the expertise of business analysts. Requirement specification documents contain details of product features, process flows, activities, rules, parameters, etc. Intricate knowledge of dependencies between these specification elements is necessary for carrying out the effective evolution of the product over time. Today, Business Analysts (BA) are forced to recourse to keyword-based search across multiple requirement specification documents which is a time-, effort- and intellect-intensive endeavor, and vulnerable to the errors of omission and commission. To overcome these lacunae, we propose DizSpec, an automated approach for digitalizing the requirement specification documents into a model form through automatic extraction of specification model elements and the various dependencies between them. Our approach creates a digital thread providing machine-processable traceability from product features to its specification elements. It also provides an easy natural language querying mechanism to generate traceability and impact analysis reports of interest. In this paper, we describe the application of this approach to two real-world products thus bringing out its efficacy as well as lessons learned from this transformation journey of the document-centric process to a model-centric and automated process. Though the findings are shared in the specific context of two industry products, we believe, researchers, practitioners, and tool vendors will find the takeaways from this approach and experience applicable in other contexts too.