MOB Forecasting Flashcards
What is forecasting?
Forecasting is the use of past and present data to make predictions
What are the two categories in forecasting?
Quantitative and qualitative
What is Quantitative forecasting?
Quantitative forecasting refers to the utilization of historical data and mathematical models to make predictions.
What is Qualitative forecasting?
Qualitative forecasting relies on subjective assessments, opinions, and expert judgment to make predictions.
What is time series analysis?
Time series analysis refers to the sequence of data points that occur in a successive order over a period of time and uses information regarding historical values and associated patterns to make predictions.
What are the components of the time series analysis?
Trend, seasonality, cyclicality, and irregularity.
What does the “Trend” component of time series analysis refer to?
The trend component states that there are no fixed intervals, and any divergence in the dataset is a continuous time line. The trend can either be a null, negative, or positive time line.
What does the “Seasonality” component of time series analysis refer to?
The seasonality component states that the normal or fixed interval shifts within the dataset in a continuous line. The line is a bull curve or saw tooth.
What does the “Cyclical” component of the time series analysis refer to?
The cyclical component states that there is no fixed interval but uncertainty in the movement and pattern.
What does the “Irregularity” component of the time series analysis refer to?
The irregularity component states unexpected situations, events, or scenarios that spike in a short period of time.
Why is time series analysis useful?
The time series analysis is useful as it shows how a given asset, security, or economic value changes over time. It can also be used with comparisons of chosen data to shifts in other variables over the same period of time.
What are the benefits of time series analysis?
- Analyzing historical datasets and its patterns.
- Understanding and matching the current situation with patterns derived from the previous stage.
- Understanding the factors or factors influencing variables in different periods.
What are the limitations of time series analysis?
- The data points must be linear in their relationship.
- Data transformations are mandatory, so it’s a little expensive.
- The missing values are not supported by the time series analysis.
What is the Sales-force composite method of forecasting?
The sales force composite method refers to where sales agents forecast sales in their respective territories, which is then integrated with branch/region/area level. The aggregate of all these factors are then consolidated to develop the company’s sales forecast. It is referred to as the bottom-up approach.
Why is the sales force composite method useful?
The sales force composite method is useful as the sales force is the closest to the customers and can give a more accurate prediction on the basis of their direct experience with customers.