Title of Case Study: Enhancing operational efficiency of knowledge-intensive businesses with (big) data science applications
Managing knowledge and big data present challenges for large scale organisations, where the capacity to make data-driven decisions and share knowledge has considerable implications for operational efficiency. Research undertaken by Lingnan University is leveraging big data analytics in a real-world setting for a knowledge-intensive business serving 12 international locations.
Fostering knowledge management
Lingnan’s research has informed the development of a new Knowledge Management System (KMS), which is making data-driven decisions in the organisation, improving operational efficiency and service quality. The organisation uses the KMS and the research underpinning it to identify opportunities for enhancing productivity and to promote a dynamic business culture to foster knowledge management.
The KMS uses the insights gained from text mining generated by the research of Prof Eric See-To and his collaborators, and the hidden cause discovery algorithms developed by Prof Wong Man-leung and his team, to provide functions that make it possible for the organisation’s staff to collect, store, share and search useful knowledge. The KMS has allowed the organisation to conduct centralised knowledge management more efficiently, share and reuse available knowledge, and extract data-driven insights about their operations. Managers use the information generated to identify opportunities for increasing productivity, to make data-driven decisions about operational efficiency and business service quality, to streamline the internal logistics of flow materials, and to promote learning.
Enhancing efficiency and productivity
Evaluation of the KMS system trial revealed multiple benefits for the organisation, including an enhanced technical knowledge of staff, which is expected to increase competitiveness. As well as the operational benefits, staff report that the new system has benefitted their work and practice as it creates business value, offers real-time support for employees, and provides information about existing and potential customers. In feedback collected after the final trial of the system, two-thirds of the staff reported that their operations were more efficient as a result of using it. The KMS has demonstrated a high potential to be developed, commercialised, and used by other similar industries in Hong Kong.