Marketing 0

FIGURE 7.2
The Knowledge Management Hierarchy
Human judgment in filtering the noises is vital. In some instances,
insights can be found by discovering anomalies, in other words, the
outlier data. Many market researchers or ethnographers frequently
discover meaningful insights while watching unorthodox customer

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behaviors. They also often purposely observe extreme users at both
ends of the normal distribution to find ideas out of the norms. Due to
their rare occurrence, these unusual observations are usually deemed
to have no statistical significance. The qualitative aspect of finding
insights, beyond well-established knowledge, is best suited to
humans’ instinctive nature.
At the top of the hierarchy, there is wisdom, which is perhaps the
most challenging virtue for machines to imitate from humans. It
helps us make the right decisions with a mix of unbiased views, good
judgment, and ethical considerations. No one knows exactly how we
develop wisdom throughout our lives. But most people would agree
that wisdom comes from a wealth of practical—not theoretical—
experiences. In other words, humans learn from both the positive
and negative implications of their past decisions, and over time their
wisdom sharpens. Unlike in narrow machine learning, the process is
very broad, covering all aspects of human lives.
In the area of market research, computers will help marketers to
process information and create market simulation models. But at the
end of the day, marketers need to use their wisdom to draw
actionable insights and make the right call. Often, humans are
required to override AI-recommended decisions.
A case in point is the airline incident involving David Dao, who was
forcibly removed from a United flight in 2017. Four passengers had
to leave to make room for airline personnel who urgently needed to
board the aircraft. A revenue-maximization algorithm identified Dao
as one of the passengers to get bumped due to his “least valuable”
customer status—evaluated based on frequent flyer tier and fare
class. A significant fact that the computer failed to recognize is that
Dao is a doctor who needed to see his patient the following day.
Carelessly following the computer bias without using empathy would
often lead to the wrong decision. The rough handling of the situation
also undermined the importance of human touch in CX.