Execution Intelligence: Why Dashboards Are Dead

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@article{1718176,
      author = {Rohit Rajdev},
      title = {Execution Intelligence: Why Dashboards Are Dead},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {11},
      pages = {3203-3213},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1718176.pdf},
      abstract = {In today's hyper-velocity data environments, distributed cloud-native architectures and AI-driven decision automation, the traditional dashboard which has long been considered the hub of organisational intelligence is becoming more and more outmoded. This article proposes that as it is traditionally defined, a dashboard is a passive, retrospective tool that cannot be used to fulfill the needs of today's execution excellence. This paper, based on an analysis of the various literature of the fields of urban informatics, business intelligence (BI), real-time data platforms, cloud-native ETL systems and AI-driven automation, proposes a new concept: Execution Intelligence, which is an integrated paradigm that brings real-time intelligence into the organisational workflows, eliminating the gap between observing and deciding, typical in dashboard culture. The study illustrates how Execution Intelligence systems can cut decision latency up to 95%, boost actionability rates from 12% to more than 81% and deliver a significantly better strategy-execution alignment qualitatively. The results suggest that data infrastructure needs to be rethought as a self-serving execution layer, rather than a display layer for practitioners, data architects, and technology strategists. The impact of cloud transformation, inventory management, digital sustainability and AI governance are explored.},
      keywords = {Execution Intelligence, Business Intelligence, Dashboard, Real-Time Data, Cloud-Native Architecture, Ai Automation, Decision Latency, Digital Transformation, Data Warehousing},
      month = {May},
      doi = {https://doi.org/10.64388/IREV9I11-1718176}
  }