Resumo

BISSCHOFF, R.A.D.P.  e  GROBBELAAR, S.. Evaluation of data-driven decision-making implementation in the mining industry. S. Afr. J. Ind. Eng. [online]. 2022, vol.33, n.3, pp.218-232. ISSN 2224-7890.  http://dx.doi.org/10.7166/33-3-2799.

The ability of organisations to collect and store vast amounts of data has become increasingly more accessible and affordable in recent decades thanks to the advancement of Industry 4.0. This ability is an enabler of data-driven decision-making (DDDM). However, converting data into knowledge that can inform decision-makers has proven challenging for many companies. The ability to perform DDDM effectively depends on a combination of capabilities that encompass the technological, analytical, and managerial aspects of a business. This research focuses on the mining industry, and used a scoping literature review to identify the different DDDM tools that are currently available, the potential benefits of DDDM, the key enablers of DDDM, and the lessons learnt from previous implementations. The objective of the paper is to assist mining industry organisations in developing a DDDM implementation framework.

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