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Valuable Business Knowledge Asset Discovery by Processing Unstructured Data

Author

Listed:
  • Maria-Isabel Sanchez-Segura

    (Computer Science and Engineering Department, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28011 Leganés, Spain)

  • Roxana González-Cruz

    (Project Management Department, Telefónica España, Ronda de la Comunicación s/n, 28050 Madrid, Spain)

  • Fuensanta Medina-Dominguez

    (Computer Science and Engineering Department, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28011 Leganés, Spain)

  • German-Lenin Dugarte-Peña

    (Higher Polytechnic School, Universidad Francisco de Vitoria, Carretera Pozuelo a Majadahonda, Km 1.800, 28223 Madrid, Spain)

Abstract

Modern organizations are challenged to enact a digital transformation and improve their competitiveness while contributing to the ninth Sustainable Development Goal (SGD), “Build resilient infrastructure, promote sustainable industrialization and foster innovation”. The discovery of hidden process data’s knowledge assets may help to digitalize processes. Working on a valuable knowledge asset discovery process, we found a major challenge in that organizational data and knowledge are likely to be unstructured and undigitized, constraining the power of today’s process mining methodologies (PMM). Whereas it has been proved in digitally mature companies, the scope of PMM becomes wider with the complement proposed in this paper, embracing organizations in the process of improving their digital maturity based on available data. We propose the C4PM method, which integrates agile principles, systems thinking and natural language processing techniques to analyze the behavioral patterns of organizational semi-structured or unstructured data from a holistic perspective to discover valuable hidden information and uncover the related knowledge assets aligned with the organization strategic or business goals. Those assets are the key to pointing out potential processes susceptible to be handled using PMM, empowering a sustainable organizational digital transformation. A case study analysis from a dataset containing information on employees’ emails in a multinational company was conducted.

Suggested Citation

  • Maria-Isabel Sanchez-Segura & Roxana González-Cruz & Fuensanta Medina-Dominguez & German-Lenin Dugarte-Peña, 2022. "Valuable Business Knowledge Asset Discovery by Processing Unstructured Data," Sustainability, MDPI, vol. 14(20), pages 1-24, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:12971-:d:938730
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    References listed on IDEAS

    as
    1. Nihel Chabrak & Nabyla Daidj, 2007. "Enron: widespread myopia," Post-Print halshs-00171687, HAL.
    2. repec:dau:papers:123456789/481 is not listed on IDEAS
    3. Xin Long Xu & Jianping Li & Dengsheng Wu & Xi Zhang, 2021. "The intellectual capital efficiency and corporate sustainable growth nexus: comparison from agriculture, tourism and renewable energy sector," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16038-16056, November.
    4. Zerbino, Pierluigi & Stefanini, Alessandro & Aloini, Davide, 2021. "Process Science in Action: A Literature Review on Process Mining in Business Management," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    Full references (including those not matched with items on IDEAS)

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