Valuable Business Knowledge Asset Discovery by Processing Unstructured Data

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 d...

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Bibliographic Details
Published in:Sustainability 2022-10, Vol.14 (20), p.12971
Main Authors: Sanchez-Segura, Maria-Isabel, González-Cruz, Roxana, Medina-Dominguez, Fuensanta, Dugarte-Peña, German-Lenin
Format: Article
Language:English
Subjects:
Business
Business intelligence software
Competition
Competitive advantage
Competitiveness
Computational linguistics
Computer organization
Data security
Digital economy
Electronic data processing
Evaluation
Gas transmission industry
Identification
Innovations
Intellectual capital
International business enterprises
Knowledge
Language processing
Methods
Natural language interfaces
Natural language processing
Organizations
Small & medium sized enterprises-SME
Sustainability
Sustainable development
Unstructured data
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Summary: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.
ISSN:2071-1050
2071-1050
DOI:10.3390/su142012971