The
opening example in chapter 3 reminded me a bit of how marketing makes
eye-popping advertisements. We see it all the time: “GET FREE SHIPPING” or “GET
YOUR FREE ITEM TODAY”, the list goes on. When looking at these, we often times think
right off the back that that’s a great deal. Without thinking, many people
often go straight to the deal, only to realize later that they can qualify for the
promotion if they make a purchase of $40 or more. In chapter 3, Stephen Hoch
mentioned that this is a common mistake for many managers, and reminded us of
the importance of forward planning (2001).
Rather
than judging by the cover, Hoch suggests that leaders should examine a problem
more by identifying the probabilities of a decision. This not only includes
positive outcomes, but also the negative outcomes and penalties that could
occur. For the example in chapter 3, we have one distributor we worked with
that can reach 50 percent of all potential customers. The second choice is a
new firm that reached 25 percent last year, but is expected to reach 75 percent
with the investments. Right off the back, the new firm may be a better deal
because it has a chance of reaching an additional 25 percent compared to the
other firm. However, when considering the risks, the 75 percent is an expected amount, and therefore has a
chance of failing. While there’s no positive answer, the first firm we made
deals with in the past may be a better deal because they reach 50 percent.
After
reading through Hoch’s advice on optimal dynamic decision analysis, I was able
to draw some similarities to my own decision-making process. Personally, I am
naturally an “over-thinker” and constantly image what-ifs scenarios before
making any final decisions. For example, when an unusual and somewhat urgent
situation occurs with a student while my boss (campus director) is gone, I can
make two choices: make a decision on-the-spot with the information I currently
have, or tell the student to wait a day or two so I can double check with my
boss and other co-workers. Often times, students want an immediate answer, and
the first choice therefore may seem like a good choice. However, my knowledge
and authority is limited and I worry that the situation could get if provide
the wrong information. In addition, doing the job wrong can also put me at risk
in getting in trouble. While there’s a chance for the student to be
disappointed, the best choice may be to politely tell the student to wait to
ensure accuracy.
Since I
had previous practices of some of Hoch’s advice, I personally believe that my
decision-making process won’t change significantly. As previously mentioned, I
am naturally someone who over-thinks and image the possibilities before making
my final move. However, I really like the mathematical equation mentioned on
page 41. While I’m likely not going to implement the equation to my
decision-making, it reminded me of the classic “which is a better deal” trick questions
in math class. For example, you could be paid $5 for every mile you travel or
you can be paid $2 for every mile, but have an initial $10 bonus. Most people
might say the one with the bonus might be better because it’s eye-popping, but
once you reach a certain number of miles, the $5 per mile would be a better
deal. In conclusion, the mathematical example provided reminded us of how
things could be seen differently if examined further.
References:
Hoch, S. & Kunreuther, H. (2001). Wharton on Making Decisions. Hoboken, NJ: John Wiley & Sons
Inc.
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