Improving decision making in the digital era: Human and Machine

Abstract

In an increasingly digital world, companies are subject to constant and fast changes that require prompt responses and strategic decisions. The technological advances that contribute to business pressures can also be a source of competitive advantage. For this, organisations need to improve the way they make decisions, supported by evidence and making good use of both human expertise and data. How can we optimise decisions in such an environment? This thesis brings to the business world academic research results that often take a long time to be incorporated in work practices. Furthermore, it bridges the gap between the human study and technology, two integral components of decision making generally discussed in isolation. It addresses the question of how to improve decision making, taking into consideration flaws and potential of both humans and machines. We take a look at human cognition, analysing how humans make decisions. Some limitations are derived from our senses or memories, others come from our cognitive processes and we act as if we had two brains, an impulsive one, affected by heuristics and biases, and a rational one. Combined with the powerful effect of emotions, we constantly deviate from rational models of decision makers. But we also excel at some intuitive decisions. Some of our shortcomings can be overcome by training and evidence-based decisions, nowadays, possibly driven by data. We describe artificial intelligence from the business perspective, how it can help make better decisions, but also has its faults. Both humans and machines will have to work together, augmenting each other’s capabilities.