Data-driven decision making has certainly improved upon the original model that relied solely on human intuition: The vast amount of unconscious cognitive biases in the human brain can influence decisions that are neither accurate nor optimal for an organization. Still, the typical data-driven workflow still relies on human judgment to make the final decision based on the generated spreadsheets and analytics, meaning some bias can still creep in.
To completely eliminate bias and also enable the processing of even larger quantities of data, then, “we need to evolve further, and bring AI into the workflow as a primary processor of data,” according to HBR. AI’s consistency and objectivity will not only make stronger organizational decisions, but will also improve efficiency and open doors for new analytical capabilities.
This streamlined workflow will not completely remove humans from the equation — especially in cases in which more subjective factors such as an organization’s strategy, values and culture must be taken into account. Instead, per HBR, “the key is that humans are not interfacing directly with data but rather with the possibilities produced by AI’s processing of the data.”
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