Purchase Solution

Forecasting & Inventory Model

Not what you're looking for?

Ask Custom Question

1. The healthcare environment would be advised to use the MAD, MSE, and the MAPE as measures of forecasting accuracy. Describe how these techniques could aid managers in the projections of cost and assist in inventory control.

2. Summarize the factors involved with seasonal variations. Provide examples.

3. An essential part of cost control in any healthcare organization is staffing levels, maintaining the right mix of professional individuals at any given time. Inventory and production control models are designed for static environments. Would such models work in healthcare to adjust for staffing needs? Explain your rationale.

4. Our basis EOQ inventory model makes five assumptions. For each of these assumptions, explain the assumption, give an example of when the assumption is false, and describe what options are available when the assumption is false.

Purchase this Solution

Solution Summary

This posting provides answers to questions on forecasting including forecasting accuracy and seasonal indexes and inventory modeling questions on EOQ assumptions & Production control models.

Solution Preview

1. The healthcare environment would be advised to use the MAD, MSE, and the MAPE as measures of forecasting accuracy. Describe how these techniques could aid managers in the projections of cost and assist in inventory control.

Mean Absolute Deviation (MAD)
MAD = ∑ |At - Ft| / T
Where T = the number of time periods
MAD measures absolute error. It should be as small as possible. One problem with MAD is that there is no way of knowing if MAD is small or large in relation to the actual data.

Mean Absolute Percent Error (MAPE) Measure error as a percent of actual values
MAPE = 100 ∑ [ |At - Ft| / At ] / T

MAPE is same as MAD except that it measures deviation as a percentage of actual data.
MAPE and MAD are easy to interpret.

Mean Squared Error (MSE)
MSE = ∑ (At - Ft)2 / T

MSE measures error variance.
Recognizes that large errors are disproportionately more "expensive" than small errors

A low value of MAD/MAPE/MSE signifies that the errors made while making forecast about demand/inventory/cost is minimal and thus the forecast is accurate. This will help the managers in being confident about their forecast and thus facilitate in projections of cost and inventory.

2. Summarize the factors involved with seasonal variations. Provide examples.

The factors involved with seasonal variations are:
? Consumer Behavior: Consumer's preferences towards certain products are based on weather conditions.
o For example: Consumers prefer to have ice-cream ...

Purchase this Solution


Free BrainMass Quizzes
Know Your Statistical Concepts

Each question is a choice-summary multiple choice question that presents you with a statistical concept and then 4 numbered statements. You must decide which (if any) of the numbered statements is/are true as they relate to the statistical concept.

Terms and Definitions for Statistics

This quiz covers basic terms and definitions of statistics.

Measures of Central Tendency

This quiz evaluates the students understanding of the measures of central tendency seen in statistics. This quiz is specifically designed to incorporate the measures of central tendency as they relate to psychological research.

Measures of Central Tendency

Tests knowledge of the three main measures of central tendency, including some simple calculation questions.