26. Expected Value Computations & Learing Curve Analysis

Question 1

What is an expected value computation?

Answer 1

When there are multiple possible future outcomes, a manager can mathematically “combine” several outcomes to form an “expected value” based on all possible outcomes, weighted by their respective probabilities.

Question 2

What is the formula for the expected value of a set of possible outcomes?

Answer 2

The formula for the expected value of a set of possible outcomes is EV = ∑(rp) where r = result of the outcome and p = probability of the outcome.

Question 3

What are the benefits of expected value computations?

Answer 3

1. Expected value computations that incorporate multiple possibilities are generally more representative of an uncertain future.
2. The expected value computation reduces multiple outcomes to a single value, which is easily understood and can be entered into a budget plan.

Question 4

What are the shortcomings of expected value computations?

Answer 4

1. The underlying probabilities used in the expected value formula are usually based on subjective judgments.
2. The result of the EV formula is not the most likely outcome in the future. It is a weighted average of the possible results used in the computation.

Question 5

What is learning curve analysis?

Answer 5

As the organization’s workforce gains experience, the organization learns how to work better. Learning results in the biggest improvements in the beginning, with learning (and improvement) becoming smaller over time. Therefore, as output doubles, the cumulative average time or cost of the total output is reduced by a constant percentage.

Question 6

What is the formula for calculating the cumulative average?

Answer 6

Y = aXb

where Y = cumulative average per unit, a = time required for first unit, X = cumulative number of units, and b = ln learning curve % ÷ ln 2. (Note: ln indicates the natural log.)

Question 7

What are the benefits of learning curve analysis?

Answer 7

1. Learning curve analysis is anticipating movement in future costs by recognizing that the organization is learning and becoming more efficient with its processes.
2. By anticipating where costs are moving, organizations can establish more relevant budgets with appropriate stretch targets, as well as predict and set more aggressive market pricing based on expected learning curves.

Question 8

What are the shortcomings of learning curve analysis?

Answer 8

1. Learning curve analysis is focused on human learning and behavior and may not be relevant to more machine-intensive processes.
2. A fundamental assumption of learning curve analysis is that the learning rate is assumed to be constant. This may or may not be true.