Forecasting, Prod-System Design, Process Select-Cap-Planning Flashcards
pertains to utilizing several different methods of estimating to determine possible future outcomes for the business. Planning for any of these potential future outcomes is the scope of the job pertaining to operations management.
Forecasting
may be Short range (e.g., an hour, day, week, or month), or
Long-range (e.g., the next six months, the next year, the next five
years, or the life of a product or service)
Forecasts
Groups of high-level executives will often assume responsibility for the forecast. They will collaborate to examine market data and look at future trends for the business. Often, they will use statistical models as well as market experts to arrive at a forecast.
Executive Judgement
(Top Down)
Techniques are subjective, based on the
opinion and judgment of consumers and experts; they are appropriate when past data are not available. They are usually applied to intermediate- or long-range decisions.
Qualitative Forecasting
are those persons most close to the customers. Their opinions are of high value. Often are asked to give their future projections for their area or territory. Once all of those are reviewed, they may be combined to form an overall forecast for the district or region.
Sales Force Opinions
(Bottom Up)
A group of experts are recruited to participate in a forecast. The
administrator of the forecast will send out a series of questionnaires and ask for inputs and justifications. These responses will be collated and sent out again to allow respondents to evaluate
and adjust their answers.
Delphi Method
Some organizations will employ market
research firms to solicit information
from consumers regarding opinions on
products and future purchasing plans.
Market Surveys
is the consistent upward or downward movement of the demand. This may be related to the product’s life cycle.
Trend
Models are used to forecast future data
as a function of past data. They are
appropriate to use when past numerical data is available and when it is reasonable to assume that some of the patterns in the data are expected to continue into the future
Quantitative Forecasting
is a pattern in the data that tends to last more than one year in duration. Often, they are related to events such as interest rates, the political climate, consumer confidence or other market factors.
Cycle
> Many products have a pattern, generally predictable changes in demand that are recurring every year.
Seasonal
are the unexplained variations in demand that remain after all other factors are considered. Often this is referred to as noise.
Random variations
> Often demand can be influenced by an event or series of events that are not expected to be repeated in the future.
Irregular Variations
use historical data as the basis of
estimating future outcomes. A time
series is a series of data points
indexed (or listed or graphed) in
time order.
> Time-series methods
> The simplest forecasting method. In this case, the forecast for the next period is set at the actual demand for the previous period. This method of forecasting may often be used as a benchmark in order to evaluate and compare other forecast methods.
Naïve Method
In this method, we take the average of the last “n” periods and use that as the forecast for the next period.
Simple Moving Average
> This method is the same as the simple moving average with the addition of weight for each
one of the last “n” periods. In practice, these weights need to be determined in a way to produce the most accurate forecast.
Weighted Moving Average
