beulen, ErikBashanfer, Hamza2023-06-122023-06-122022-09https://hdl.handle.net/20.500.14154/68347Supply chain management (SCM) and operation management (OM) have always triggered the need to establish a seamless system of information flow to achieve efficiency and accuracy. While the human resources have remained a significant aspect of the SCM and OM decisions, they have been found to be vulnerable to cognitive bias and heuristics which often affect how they execute critical supply chain needs. This dissertation sought to examine how I4.0 technologies can be used to mitigate the decision-making flaws expected from the human aspect of supply chain management. The study applied a qualitative study design and used purposive sampling to select nine primary and secondary sources of data. Textual analysis was applied to analyse the findings. The key findings of the study was that I4.0 technologies can be used to reduce cognitive bias and heuristics in SCM and OM decision-making because provide data used to justify the decisions reached. Unlike the human aspect of decision-making, I4.0 technologies such as big data corroborates crucial SCM and OM needs and aligns them with the desired outcomes. However, the study also established that it was impossible and not advisable to ignore the human aspect when making key decisions. The study demonstrated a key link between technology and how it can produce automated and reliable answers to key SCM and OM issues.39enOperationSupply ChainTechnology 4.0Thesis