Industry 4 Company a 36493-SMA-A
Information and Decision Making
Lots of research done on how people make decisions
There is a school of thought that considers that management is all about decisions.
o Promotion, human resource, where do you invest stocks/bonds made on a regular basis
o Marketing, R&D investment
Two big researches: Robert Simon, Daniel Karaman (their theories)
The way information is presented can change everything
The economist selling strategy is as follows:
1) Internet subscription for US59$
2) Print subscription but no online access for 125$
3) Both the print and online version together for the same $125.
Out of a study of 100 students:
o Option 1 – 16 Student
o Option 2 – 0 students
o Option 3 – 84 Students
In a second study only containing Option 1 (Online Only) and Option 3 (Print and online version)
o Option 1 – 68 Students
o Option 2 – 32 Students
If you add a product at the same price range, consumers tend to drift to the higher price range
This is known as the decoy effect. Option 2 is merely there to influence you toward option 3.
o As previously said, the way you present information can change the consumer’s
Observing and recording data is the central aspect of management
Sometimes, the data at hand is not ideal Discrimination
US Berkeley in the fall of 1973
8,442 men and 4,321 women applied
44% of the men and 35% of the women were admitted
The quality of the applicants was the same
Is this discrimination?
Quality of applicants is the same.
2 twice as many men than woman applied.
Ideally, in a ratio of 2:1, 66.66% men should be admitted to 33.33% women
In fact, according to percentages, 2% more woman got into the university than is ideal, while
22% less men got into the university.
Things you need to look at include which program they are applying to. It is possible for example
for women to apply to programs where admission rate is very low.
o You need historical data. It is very possible historically they were admitting only 15% of
women, so you need the data to put things into perspective.
o Other needed data could be things like, how the data (applicants) where selected.
o One last aspect to consider is preferences. It could so happen that a lot of males may
have preference to this university, while females may not select this because it is not
their first choice
This is called “the Simpsons Paradox” –a paradox in which a trend that appears in different groups of
data disappears when these groups are combined, and the reverse trend appears for the aggregate
data. LOOK THIS UP. CLASS CASE – GENDER BIAS
“Berkeley gender bias case
One of the best known real life examples of Simpson's paradox occurred when the University of
California, Berkeley was sued for bias against women who had applied for admission to graduate schools
there. The admission figures for the fall of 1973 showed that men applying were more likely than
women to be admitted, and the difference was so large that it was unlikely to be due to chance.
Men 8442 44%
Women 4321 35%
But when examining the individual departments, it appeared that no department was significantly
biased against women. In fact, most departments had a "small but statistically significant bias in favor of
women." [1The data from the six largest departments are listed below.
Applicants Admitted Applicants Admitted
A 825 62% 108 82%
B 560 63% 25 68%
C 325 37% 593 34%
D 417 33% 375 35%
E 191 28% 393 24%
F 373 6% 341 7% Stock Predictions
One stock broker provides monthly predictions that correctly predicted 7 of the 9 downturns in
the economy over the past 3 years
Is he an expert?
Do you want to invest with this person?
Can Experts predict better?
A study conducted showed that experts cannot predict anything better than a person who is not
a professional in the stock market”
Another Case Study
A rat was placed in a T-Shaped maze
Food was kept randomly on either the right or the left transept of the T
Over the long run, food was kept 60% of the time on the left side and 40% of the right side.
Assuming that the rat cannot smell the food, and needs to make a decision to go left or go right. Neither
the students nor the rats were told these frequencies. The students were also to predict where the food
where it will appear.
Rats were right roughly 60% of the time – D, but a passing grade
Students scored 52% - F
Students created models of information and thought too much about the issue. Meanwhile, whenever
the rat picked a side it kept going there and got it right 60% of the time.
TRY TO MAKE MORE PREDICTIONS ABOUT THINGS. YOU WILL ADJUST YOURSELF AND PRED