Successful organizations are also those who are able to make relatively accurate forecasts about the future needs (inventory, facilities, capacity, manufacturing, manpower) for the products produced or the services delivered.
Forecasting is an uncertain science since it calls for predictions but current theoretical and mathematical models (quantitative and qualitative) make it possible for organizations to predict with an acceptable margin of error. Think about it this way; without forecasting organizations would always be responding rather than acting.
1. Select one industry from the list below:
Bank, restaurant, health clinic/hospital, airline, or university.
2. What specific variables would be needed by that organization in order to forecast? Be sure you explain "why" you selected each variable and why it is important to forecasting).
3. Which variables are used for short-range forecasting, long-range forecasting or for both. Make sure you support your selections.
In a health clinic, there are many supplies and some stock medications, like over the counter type products that an office should keep on hand for treatment.
Variables needed to forecast would be:
Quantitative methods: using moving average (time series)
1. How many patients are seen each day, week, month, for nutrition counseling, assuming these are the patients who receive vitamins? How many patients are seen for minor muscle strains/sprains, on ...
The analysis considers the various methods used for forecasting in the health care organization setting. It discusses both qualitative and quantitative methods of gathering data and the purpose for obtaining both types, as well as the practical application of data gathered by both approaches.