Forecasting
Moving Average
Learning Objectives:
- Understand the advantages, disadvantages and applications of moving average forecasting technique.
We have Three Types forecasting methods that are appropriate for a time series with a horizontal pattern:
- Moving average
- Weighted moving averages
- Exponential smoothing
- A quantitative method of forecasting or smoothing a time series by averaging each successive group (no. of observations) of data values.
- Term MOVING is used because it is obtained by summing and averaging the values from a given no of periods, each time deleting the oldest value and adding a new value.
- For applying the method of moving averages the period of moving averages has to be selected . This period can be 3- yearly moving averages 5-yr moving averages 4-yr moving averages etc.
- If the moving average is an odd no of values e.g., 3 years, there is no problem of centring it. Because the moving total for 3 years average will be centred besides the 2nd year and for 5 years average be centred besides 3rd year.
- But if the moving average is an even no, e.g., 4 years moving average, then the average of 1st 4 figures will be placed between 2nd and 3rd year. This process is called centering of the averages. In case of even period of moving averages, the trend values are obtained after centering the averages a second time.
Joxemai, CC BY-SA 3.0, via Wikimedia Commons
Solved Example: 9047-01
The actual sales of a product in different months of a particular year are given below:
Sept : 180
Oct : 280
Nov : 250
Dec : 190
Jan : 240
A. 230
B. 240
C. 250
D. 260
Correct Answer: B
Solved Example: 9047-02
The time series forecasting method that gives equal weightage to each of the m most recent observations is:
A. Moving average method
B. Exponential smoothing with linear trend
C. Triple Exponential smoothing
D. Kalman Filter
Correct Answer: A
Exponential Smoothing
Learning Objectives:
- Understand the advantages, disadvantages and applications of Exponential Smoothing forecasting technique.
$\hat{d}_t$ = forecast for demand t
$\alpha$ = smoothing constant $0\leq \alpha \leq 1$
- Exponential smoothing is actually a way of “smoothing” out the data by eliminating much of the “noise” (random effects).
- The idea behind “smoothing” the data is to get a more realistic idea about what is “really going on”. – The value of the smoothing constant, $\alpha$, is selected by the modeler.
- Higher values of $\alpha$ allow the time series to be swayed quickly by the most recent observation.
- Lower values keep the smoothed time series “flatter” as not that much weight will be given to the most recent observation. – Usual values of $\alpha$ are between about .1 and .7
- The value (1-$\alpha$) is called the damping factor.
Solved Example: 9046-01
In exponential smoothening method, which one of the following is true?
A. 0 $\leq$ $\alpha$ $\leq$ 1 and high value of $\alpha$ is used for stable demand.
B. 0 $\leq$ $\alpha$ $\leq$ 1 and high value of $\alpha$ is used for unstable demand.
C. $\alpha$ >1 and high value of $\alpha$ is used for stable demand.
D. $\alpha$ $\leq$ 0 and high value of $\alpha$ is used for unstable demand.
Correct Answer: B
Solved Example: 9046-02
Which of the following forecasting methods takes a fraction of forecast error into account for the next period forecast?
A. Simple average method
B. Moving average method
C. Weighted moving average method
D. Exponential smoothening method
Correct Answer: D
Solved Example: 9046-03
The sale of cycles in a shop in four consecutive months are given as 70, 68, 82, 95. Exponentially smoothing average method with a smoothing factor of 0.4 is used in forecasting. The expected number of sales in the next month is:
A. 59
B. 73
C. 86
D. 136
Correct Answer: C
Solved Example: 9046-04
For a canteen, the actual demand for disposable cups was 500 units in January and 600 units in February. The forecast for the month of January was 400 units. The forecast for the month of March considering smoothing coefficient as 0.75 is:
A. 550
B. 560
C. 569
D. 588
Correct Answer: C
Solved Example: 9046-05
Which of the following is a technique used for forecasting?
A. PERT/CPM
B. Exponential smoothing
C. Gantt Chart
D. Control Chart
Correct Answer: B
Solved Example: 9046-06
The current period forecast becomes equal to last period forecast for the value of smoothing constant equal to:
A. 1
B. 2
C. 0
D. 0.5
Correct Answer: C
Solved Example: 9046-07
In simple exponential smoothing forecasting, to give higher weightage to recent demand information, the smoothing constant must be close to:
A. -1
B. 0
C. 0.5
D. 1
Correct Answer: D
Solved Example: 9046-08
In a calendar year, the demand forecast of motorbikes for the month of June is 200. The actual demand of motorbikes for the month of June and July are 300 and 350, respectively. If single exponential smoothing method with smoothing constant 0.7 is used, then the demand forecast for the month of August is:
A. 300
B. 315
C. 325
D. 326
Correct Answer: D
Solved Example: 9046-09
The forecast and the actual sale of a product for December 2020 were 35 and 30 respectively. If the exponential smoothing constant is taken as 0.2, what will be the forecast for January 2021?
A. 33
B. 32
C. 31
D. 34
Correct Answer: D
Tracking Signals
Learning Objectives:
- Explain the relationship between tracking signals and statistical process control (SPC) techniques, such as control charts and process capability analysis.
A tracking signal is an automatic warning when actual results differ from expectations in terms of sales, inventories, or any other aspect of an organization's future demand.
It keeps track of things and alerts users when results unexpectedly diverge from expectations.
Solved Example: 9048-01
Tracking signal is used in the context of:
A. Quality Management
B. Forecasting
C. Inventory Management
D. None of the above
Correct Answer: B
Solved Example: 9048-02
_________ has a fair to very good accuracy for short and long term forecasts.
A. Judgmental technique
B. Prior knowledge
C. Trend line technique
D. Delphi method
Correct Answer: D