Tech-Driven Operations: Achieving Operational Excellence through Digital Transformation

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@article{1716544,
      author = {Omotoso Olumide},
      title = {Tech-Driven Operations: Achieving Operational Excellence through Digital Transformation},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {2543-2549},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1716544.pdf},
      abstract = {Digital transformation has become one of the most important sources of operational efficiency and competitive advantage in modern organisations. The technological developments in artificial intelligence (AI), big data analytics, cloud computing, and robotic process automation are inherently transforming the way operations are conducted in industries. This paper discusses the strategic implementation of digital technologies as a means of operational excellence through increased efficiency, decision-making, and organisational agility. Based on the recent literature on the digital transformation, the operational management, and technological innovation, the study constructs a conceptual framework that elucidates the role of technology-based operational systems in enhancing performance outcomes. The paper combines these findings to demonstrate how organisations can transform their conventional operational models into digitally integrated systems. The results indicate that the companies, which strategically align the digital technologies to the operational processes, are more productive, have better decision accuracy, and have a sustainable competitive advantage. The paper concludes with a discussion of the managerial implications of applying tech-driven operations and future research opportunities in the field of digital operations management.},
      keywords = {Digital Transformation, Operational Excellence, Artificial Intelligence, Industry 4.0, Data-Driven Decision-Making, Automation, Digital Leadership},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1716544}
  }