Digital Business Model Innovation for Manufacturing MSMEs Using the Business Model Canvas Approach - Risqi Windu Harjono; Eddy Soeryanto Soegoto; Maripova Nodira Xamidovna (International Journal of Research and Applied Technology (INJURATECH), 2026)
CV. Jaya Logam is a ship component manufacturing company in Bogor experiencing consistent sales growth from 310 units in 2021 to 384 units in 2025, yet all core operational processes including customer ordering, raw material procurement, and transaction recording remain entirely manual, creating a serious gap between market potential and operational capacity. This study analyzes the existing business model and designs a new digital business model using the Business Model Canvas (BMC) framework. A qualitative descriptive case study approach was employed, involving in-depth interviews with four informant categories and direct observation across three main operational areas. Data analysis followed three sequential stages: As-Is BMC mapping, SWOT analysis per BMC block to identify digital weaknesses, and To-Be BMC design as the proposed future transformation model. The results point to four BMC blocks (Channels, Customer Relationships, Key Activities and Key Resources) with critical digital deficiencies, which create an interdependent vulnerability cycle that makes the current business model unscalable. The proposed redesign encompasses six of the nine BMC blocks, with key transformations including a WhatsApp Business API-based ordering system, digital CRM for proactive customer retention, revenue diversification through consulting and maintenance services, formal recognition of digital data as a strategic asset, an integrated digital workflow replacing manual recording across order intake, inventory tracking, and production scheduling, and digitalized supplier coordination through structured procurement communication. This study contributes a practical digital transformation roadmap for CV. Jaya Logam and serves as an academic reference for Indonesian MSMEs facing similar operational challenges