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## Main Question or Discussion Point

I'm trying to understand this problem and could do with some help.

A small business is trying to measure their delivery performance in terms of "on-time, in-full & error-free".

It sent out product to 4 customers (A,B,C,D) and notes down what the performance was: 0 = not ok, 1 = ok.

(Apologies for not being able to do a table)

__________A_B_C_D

on time____1_0_1_1

in full______1_1_1_0

error free___0_1_1_1

Overall_____0_0_1_0

It is clear that only 1 out of 4 (25%) actually received goods on-time, in-full & error-free.

But then, a customer calls Sales and asks "What are the chances of my order being on-time in full and error-free?

The Sales guy thinks to himself:

Well, 3 out 4 (75%) were on time, 75% were in full & 75% were error-free so the chances are:

0.75 x 0.75 x 0.75 = 0.42

and tells the customer "There is a 42% chance your order will be on-time, in-full & error-free"

Can anybody explain why there is such a difference between the actual performance and the probability?

Thanks in advance.

A small business is trying to measure their delivery performance in terms of "on-time, in-full & error-free".

It sent out product to 4 customers (A,B,C,D) and notes down what the performance was: 0 = not ok, 1 = ok.

(Apologies for not being able to do a table)

__________A_B_C_D

on time____1_0_1_1

in full______1_1_1_0

error free___0_1_1_1

Overall_____0_0_1_0

It is clear that only 1 out of 4 (25%) actually received goods on-time, in-full & error-free.

But then, a customer calls Sales and asks "What are the chances of my order being on-time in full and error-free?

The Sales guy thinks to himself:

Well, 3 out 4 (75%) were on time, 75% were in full & 75% were error-free so the chances are:

0.75 x 0.75 x 0.75 = 0.42

and tells the customer "There is a 42% chance your order will be on-time, in-full & error-free"

Can anybody explain why there is such a difference between the actual performance and the probability?

Thanks in advance.