Valuable Business Knowledge Asset Discovery by Processing Unstructured Data

Maria-Isabel Sanchez-Segura (), Roxana González-Cruz, Fuensanta Medina-Dominguez and German-Lenin Dugarte-Peña
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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

Sustainability, 2022, vol. 14, issue 20, 1-24

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.

Keywords: intangible assets; process mining; natural language processing; knowledge management; digital transformation; sustainability; design science (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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