Concepedia

Concept

operations analytics

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481

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27.2K

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1.4K

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590

Institutions

End-to-End Operations Analytics

2016 - 2021

During 2016–2021, operations analytics matured into end-to-end, big data-enabled decision making across procurement, production, and logistics through IoT data, scalable architectures, and real-time dashboards. The era also prioritized analytics capability development and workforce readiness, emphasizing data literacy, curriculum adaptation, and strong industry–academic alignment to sustain analytics talent. Proactive maintenance analytics and reliability dashboards advanced risk management, ensuring descriptive insights translate into prescriptive actions in BIM and broader operations.

• End-to-end analytics integration in operations and supply chains leveraging big data analytics architectures, strategies, dashboards, and IoT-driven data for decision-making across procurement, production, and logistics [1], [5], [13], [14], [10].

• Analytics capability development and workforce readiness in operations analytics, focusing on talent pipelines, curricula adaptation, data literacy, and industry–academic alignment [4], [7], [11], [12], [16].

• Operational excellence and risk management via Big Data Analytics, including maintenance analytics and reliability dashboards, enabling proactive decision-making [6], [9], [15], [18].

• Knowledge-to-insight transformation and decision-support frameworks in operations analytics, through descriptive to prescriptive analytics and data-driven decision making in BIM and broader contexts [13], [14], [17], [19].

• Forecasting and demand analytics in supply chains leveraging big data, including conceptual design-science frameworks for BDA-enabled forecasts [3], [5], [10].