Feeling and Deciding
The primary advantage of statistical (or decision) models is that they are not subject to many of the biases, limitations, and inconsistencies in human judgment. While individuals display biases of perception and evaluation, models are less biased. Humans tend to be overconfident and easily influenced by organizational politics, while models are immune to social pressure. Humans get tired, bored, emotional, leading to inconsistent decision strategies, while models integrate evidence in a consistent manner.
On the other hand, there are some elements of the decision process where the human judgment is critical. For example, models know only what they are told by model developers. Experts must identify and measure the relevant information. Humans are also able to evaluate subjective judgment or information which is difficult to measure and quantify, while models are typically based on objectively measured information. Humans also have the ability to capitalize on new information and changing conditions in a dynamic decision environment.
Models and human intuition are typically integrated in two ways. Under what might be called objective or statistical synthesis, human judges and models make their calculations independently, and then a formal combination rule (for example, a 50-50 weighting for each) is used to integrate them into a final prediction. A more subjective or intuitive approach is to provide decision makers with the output from a model as a decision aid. There are several issues to consider here – it is important to consider the performance of the decision makers who are going to combine their intuition with the inputs of a model; how much of uncertainty is present in the business environment (typically in less uncertain business environments, models tend to perform better than humans; results for human and human-model are mixed in highly uncertain business environments), the type of contextual information that is made available to both the humans and the models, etc.
Models seem to be consistent, sometimes at the expense of being rigid. Humans have the ability to react to quickly to changing situations, but they tend to be too flexible and may overreact to new developments. The Human-Model approach seems to be on a continuum (human at one end and the model at the other end of the continuum) and the decision maker seems to slide between these two (hence subjectivity creeps in) trying to incorporate model consistency and managerial insight into a decision. The relative strengths and weaknesses of humans and models seem to be two sides of the same coin. Where one is weak, the other is strong. The human-model approach seems contradictory as it allows performing contrary actions at the same time.
From the above, the debate on how people make decisions seems still inconclusive (even after decades of research on this issue). What are your thoughts on the above (for example, take a stand on one or more of the three approaches and justify why so)? What are the implications of the above debate in organizations – this debate practically affects every area of the organization and beyond (for example, how can organizations ensure consistency in decision-making – the problems are magnified in multi-unit, multinational, etc. organizations as other variables such as culture, etc. also play a role)?
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