Valuable Business Knowledge Asset Discovery by Processing Unstructured Data

doi:10.3390/su142012971

2022-10-11

Marı́a-Isabel Sánchez-Segura *

Roxana González-Cruz

Fuensanta Medina‐Domínguez

Germán-Lenin Dugarte-Peña

DOI：10.3390/su142012971

原文链接

原文求助

摘要

En 中文

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.

Keyword:

intangible assets

process mining

natural language processing

knowledge management

digital transformation

sustainability

design science