An Integrated Business Management and Analytics Platform for Optimized Workflow and Real-Time Collaboration
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https://doi.org/10.37648/ijtbm.v14i01.015
Abstract
Modern organizations run on a patchwork of tools: ERP for transactions, spreadsheets for tracking, chat for decisions, ticketing for work, and dashboards for reporting. The problem is not that these tools are “bad”; it’s that work and data get separated. Decisions are made without context, approvals get stuck in inboxes, and analytics arrive late or can’t be trusted. This paper proposes an integrated business management and analytics platform that unifies (1) workflow orchestration, (2) real-time event-driven analytics, and (3) collaboration embedded directly inside business objects (orders, projects, cases). The proposed architecture combines BPM-driven process execution [1][2], process mining feedback loops for continuous improvement [3], real-time stream processing principles [4], a unified compute layer for batch + streaming analytics [5], and lakehouse-style ACID table storage for reliable “single source of truth” datasets [6]. For collaboration, the platform supports co-authoring and shared decision trails using proven consistency approaches (OT/CRDT) [14][15] and addresses well-known distance and coordination challenges in distributed work [13]. We also outline security, governance, and evaluation using established frameworks [8][9][10][11]. The contribution is a practical, reference architecture plus a measurement model that organizations can apply to reduce cycle time, improve cross-team alignment, and make analytics actionable in the moment rather than after the fact.
Keywords: Business process management; workflow optimization; real-time analytics; lakehouse; stream processing; collaboration systems; microservices; governance; zero trust
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