First Of Its Kind Planning Professionals Assessment Quiz
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Planning Quotient Test checks your knowledge levels in quantitative and qualitative aspects of planning and forecasting process with set of objective questions.
Score above 50% and get extra 10% discount on our comprehensive planning and forecasting online course
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Categories

ARIMA
0%

Data Cleansing
0%

Error Measurement
0%

Exponential Smoothing Models
0%

Intermittent Demand Models
0%

New Product Forecasting
0%

Planning Basics
0%

Planning Process
0%

Simple Models
0%

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 40

Answered

Review

Question 1 of 40
1. Question
1 points
Category: Error Measurement
The BIAS Value ranges from





Question 2 of 40
2. Question
1 points
Category: New Product Forecasting
Which function’s input is most important in new product introductions?





Question 3 of 40
3. Question
1 points
Category: Exponential Smoothing Models
Which of the following is not a component of Exponential Family of Models?





Question 4 of 40
4. Question
1 points
Category: Exponential Smoothing Models
EXSM(LM) model is also called as





Question 5 of 40
5. Question
1 points
Category: New Product Forecasting
To forecast by analogy which product would you pick as a ‘looks like’





Question 6 of 40
6. Question
1 points
Category: New Product Forecasting
Honda is launching a new version of the Honda City petrol car. Which technique should it use to forecast the demand of the new model:





Question 7 of 40
7. Question
1 points
Category: Planning Basics
Which of the following is the correct sequence of the typical supply chain line?





Question 8 of 40
8. Question
1 points
Category: Exponential Smoothing Models
When the year on year growth of sales is proportional to the previous year which of the following models should be used?





Question 9 of 40
9. Question
1 points
Category: Planning Basics
At which point on the process is the forecast lag the greatest ?





Question 10 of 40
10. Question
1 points
Category: New Product Forecasting
Which of the following is new to the world product:





Question 11 of 40
11. Question
1 points
Category: Simple Models
The Same as Last Year Model always means copying demand values from the previous year



Question 12 of 40
12. Question
1 points
Category: ARIMA
ARIMA and Box Jenkins are both the names for the same forecasting model



Question 13 of 40
13. Question
1 points
Category: New Product Forecasting
Which of the following is improvement & revision to existing product:





Question 14 of 40
14. Question
1 points
Category: ARIMA
Which of the following is/are the drawbacks of ARIMA Models?





Question 15 of 40
15. Question
1 points
Category: Error Measurement
In which cases MAPE fails to give the true picture of Error





Question 16 of 40
16. Question
1 points
Category: Error Measurement
The best measure to assess the fit of the statistical model is




Question 17 of 40
17. Question
1 points
Category: ARIMA
The difference between ARIMA(p,d,q) and ARIMA(p,d,q)(P,D,Q) is





Question 18 of 40
18. Question
1 points
Category: Exponential Smoothing Models
If the EXSM(NA) {No Trend, Additive Seasonality} Model has level = 300 and seasonal value for the Month of Nov = 20 then forecast value of the next Nov will be?





Question 19 of 40
19. Question
1 points
Category: ARIMA
ARIMA (0,1,0) is read as





Question 20 of 40
20. Question
1 points
Category: Simple Models
If the product sales data is 100, 130, 110, 120, 115 and 135 in last six Months what will be the value of Simple Moving Average SMA(4)?





Question 21 of 40
21. Question
1 points
Category: Exponential Smoothing Models
The total number of Models in the Exponential Smoothing Family of models are





Question 22 of 40
22. Question
1 points
Category: Intermittent Demand Models
In which cases do we need to use the Intermittent Model ?





Question 23 of 40
23. Question
1 points
Category: Error Measurement
Which of the following error measurements is most suitable for lower volume data?





Question 24 of 40
24. Question
1 points
Category: ARIMA
ARIMA stands for





Question 25 of 40
25. Question
1 points
Category: Error Measurement
1. Which of the following is/are not the properties of MAPE?
i) High Negative MAPE indicates the Forecast is far higher than the Actuals
ii) High Negative MAPE indicates the Actuals is far higher than the Forecast
iii) MAPE is expressed in %
iv) Forecast Value is the Base for MAPE





Question 26 of 40
26. Question
1 points
Category: Intermittent Demand Models
Which of the following is/are the properties of Discrete Models?
i. The data follows no statistical distribution
ii. It is used for the products with sparse requirement
iii. It is used for the products with very high value
iv. The data has no trend and no seasonality





Question 27 of 40
27. Question
1 points
Category: ARIMA
1. Which of the following are assumptions for fitting ARIMA Model?
i. The model parameters are constant over time
ii. The data is stationary
iii. There are no level shifts
iv. There are no known/suspected predictor variables





Question 28 of 40
28. Question
1 points
Category: Simple Models
1. Why do we still use simple methods?
i) Easier to Compute
ii) More Accurate
iii) Data exhibits seasonality and trend
iv) History data available for very less period





Question 29 of 40
29. Question
1 points
Category: Intermittent Demand Models
1. Which of the following Model is/are not suitable for data with Seasonality?
i. EXSM(LA)
ii. Intermittent
iii. Discrete




Question 30 of 40
30. Question
1 points
Category: ARIMA
Which of the following statement is/are true with ARIMA Models
i) ARIMA works well for the data with history of more than 2 years
ii)ARIMA works well for the nonseasonal data series
iii)ARIMA works well for products where sales is dependent one or more independent variables





Question 31 of 40
31. Question
1 points
Category: Data Cleansing
Which of the following are examples of outlier event ?
i. Stock out situation
ii. Competition closure
iii. Higher sales in summer months, annually





Question 32 of 40
32. Question
1 points
Category: Error Measurement
Which of the following Bucket(s) need(s) High Attention
i. Low Value, High Error
ii. Low Value, Low Error
iii. High Value, Low Error
iv. High Value, High Error





Question 33 of 40
33. Question
1 points
Category: Exponential Smoothing Models
Which of the following is/are strengths of EXSM model?
i) Simple to Understand, develop and explain.
ii) Good at predicting natural demand
iii) Puts more weightage on recent history
iv) Easy to determine the optimal values for α, β, γ





Question 34 of 40
34. Question
1 points
Category: Exponential Smoothing Models
1. Which of the following is/are necessary to pick the right EXSM model?
i. Domain Knowledge
ii. Visual Inspection
iii. Chi – Squired test





Question 35 of 40
35. Question
1 points
Category: Data Cleansing
Statistical Outliers are found based on?





Question 36 of 40
36. Question
1 points
Category: Planning Process
Which one of the following is NOT a key objective of the planning process?





Question 37 of 40
37. Question
1 points
Category: Planning Process
One of the key skills of a planner is





Question 38 of 40
38. Question
1 points
Category: Planning Process
Objectives of the S&OP process is





Question 39 of 40
39. Question
1 points
Category: Planning Process
Which of the following function should always vouch the unconstrained demand?





Question 40 of 40
40. Question
1 points
Category: Planning Process
Which of the following is not a sign of a good consensus meeting?




Quizsummary
0 of 40 questions completed
Questions:
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 9
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 23
 24
 25
 26
 27
 28
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Information
Planning Quotient Test checks your knowledge levels in quantitative and qualitative aspects of planning and forecasting process with set of objective questions.
Score above 50% and get extra 10% discount on our comprehensive planning and forecasting online course
GET STARTED NOW
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Results
0 of 40 questions answered correctly
Your time:
Time has elapsed
You have reached 0 of 0 points, (0)
Average score 

Your score 

Categories
 ARIMA 0%
 Data Cleansing 0%
 Error Measurement 0%
 Exponential Smoothing Models 0%
 Intermittent Demand Models 0%
 New Product Forecasting 0%
 Planning Basics 0%
 Planning Process 0%
 Simple Models 0%

Thank you. Your results will be mailed to your above email id, shortly.
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 7
 8
 9
 10
 11
 12
 13
 14
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 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
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 38
 39
 40
 Answered
 Review

Question 1 of 40
1. Question
1 pointsCategory: Error MeasurementThe BIAS Value ranges from

Question 2 of 40
2. Question
1 pointsCategory: New Product ForecastingWhich function’s input is most important in new product introductions?

Question 3 of 40
3. Question
1 pointsCategory: Exponential Smoothing ModelsWhich of the following is not a component of Exponential Family of Models?

Question 4 of 40
4. Question
1 pointsCategory: Exponential Smoothing ModelsEXSM(LM) model is also called as

Question 5 of 40
5. Question
1 pointsCategory: New Product ForecastingTo forecast by analogy which product would you pick as a ‘looks like’

Question 6 of 40
6. Question
1 pointsCategory: New Product ForecastingHonda is launching a new version of the Honda City petrol car. Which technique should it use to forecast the demand of the new model:

Question 7 of 40
7. Question
1 pointsCategory: Planning BasicsWhich of the following is the correct sequence of the typical supply chain line?

Question 8 of 40
8. Question
1 pointsCategory: Exponential Smoothing ModelsWhen the year on year growth of sales is proportional to the previous year which of the following models should be used?

Question 9 of 40
9. Question
1 pointsCategory: Planning BasicsAt which point on the process is the forecast lag the greatest ?

Question 10 of 40
10. Question
1 pointsCategory: New Product ForecastingWhich of the following is new to the world product:

Question 11 of 40
11. Question
1 pointsCategory: Simple ModelsThe Same as Last Year Model always means copying demand values from the previous year

Question 12 of 40
12. Question
1 pointsCategory: ARIMAARIMA and Box Jenkins are both the names for the same forecasting model

Question 13 of 40
13. Question
1 pointsCategory: New Product ForecastingWhich of the following is improvement & revision to existing product:

Question 14 of 40
14. Question
1 pointsCategory: ARIMAWhich of the following is/are the drawbacks of ARIMA Models?

Question 15 of 40
15. Question
1 pointsCategory: Error MeasurementIn which cases MAPE fails to give the true picture of Error

Question 16 of 40
16. Question
1 pointsCategory: Error MeasurementThe best measure to assess the fit of the statistical model is

Question 17 of 40
17. Question
1 pointsCategory: ARIMAThe difference between ARIMA(p,d,q) and ARIMA(p,d,q)(P,D,Q) is

Question 18 of 40
18. Question
1 pointsCategory: Exponential Smoothing ModelsIf the EXSM(NA) {No Trend, Additive Seasonality} Model has level = 300 and seasonal value for the Month of Nov = 20 then forecast value of the next Nov will be?

Question 19 of 40
19. Question
1 pointsCategory: ARIMAARIMA (0,1,0) is read as

Question 20 of 40
20. Question
1 pointsCategory: Simple ModelsIf the product sales data is 100, 130, 110, 120, 115 and 135 in last six Months what will be the value of Simple Moving Average SMA(4)?

Question 21 of 40
21. Question
1 pointsCategory: Exponential Smoothing ModelsThe total number of Models in the Exponential Smoothing Family of models are

Question 22 of 40
22. Question
1 pointsCategory: Intermittent Demand ModelsIn which cases do we need to use the Intermittent Model ?

Question 23 of 40
23. Question
1 pointsCategory: Error MeasurementWhich of the following error measurements is most suitable for lower volume data?

Question 24 of 40
24. Question
1 pointsCategory: ARIMAARIMA stands for

Question 25 of 40
25. Question
1 pointsCategory: Error Measurement1. Which of the following is/are not the properties of MAPE?
i) High Negative MAPE indicates the Forecast is far higher than the Actuals
ii) High Negative MAPE indicates the Actuals is far higher than the Forecast
iii) MAPE is expressed in %
iv) Forecast Value is the Base for MAPE 
Question 26 of 40
26. Question
1 pointsCategory: Intermittent Demand ModelsWhich of the following is/are the properties of Discrete Models?
i. The data follows no statistical distribution
ii. It is used for the products with sparse requirement
iii. It is used for the products with very high value
iv. The data has no trend and no seasonality 
Question 27 of 40
27. Question
1 pointsCategory: ARIMA1. Which of the following are assumptions for fitting ARIMA Model?
i. The model parameters are constant over time
ii. The data is stationary
iii. There are no level shifts
iv. There are no known/suspected predictor variables 
Question 28 of 40
28. Question
1 pointsCategory: Simple Models1. Why do we still use simple methods?
i) Easier to Compute
ii) More Accurate
iii) Data exhibits seasonality and trend
iv) History data available for very less period 
Question 29 of 40
29. Question
1 pointsCategory: Intermittent Demand Models1. Which of the following Model is/are not suitable for data with Seasonality?
i. EXSM(LA)
ii. Intermittent
iii. Discrete 
Question 30 of 40
30. Question
1 pointsCategory: ARIMAWhich of the following statement is/are true with ARIMA Models
i) ARIMA works well for the data with history of more than 2 years
ii)ARIMA works well for the nonseasonal data series
iii)ARIMA works well for products where sales is dependent one or more independent variables 
Question 31 of 40
31. Question
1 pointsCategory: Data CleansingWhich of the following are examples of outlier event ?
i. Stock out situation
ii. Competition closure
iii. Higher sales in summer months, annually 
Question 32 of 40
32. Question
1 pointsCategory: Error MeasurementWhich of the following Bucket(s) need(s) High Attention
i. Low Value, High Error
ii. Low Value, Low Error
iii. High Value, Low Error
iv. High Value, High Error 
Question 33 of 40
33. Question
1 pointsCategory: Exponential Smoothing ModelsWhich of the following is/are strengths of EXSM model?
i) Simple to Understand, develop and explain.
ii) Good at predicting natural demand
iii) Puts more weightage on recent history
iv) Easy to determine the optimal values for α, β, γ 
Question 34 of 40
34. Question
1 pointsCategory: Exponential Smoothing Models1. Which of the following is/are necessary to pick the right EXSM model?
i. Domain Knowledge
ii. Visual Inspection
iii. Chi – Squired test 
Question 35 of 40
35. Question
1 pointsCategory: Data CleansingStatistical Outliers are found based on?

Question 36 of 40
36. Question
1 pointsCategory: Planning ProcessWhich one of the following is NOT a key objective of the planning process?

Question 37 of 40
37. Question
1 pointsCategory: Planning ProcessOne of the key skills of a planner is

Question 38 of 40
38. Question
1 pointsCategory: Planning ProcessObjectives of the S&OP process is

Question 39 of 40
39. Question
1 pointsCategory: Planning ProcessWhich of the following function should always vouch the unconstrained demand?

Question 40 of 40
40. Question
1 pointsCategory: Planning ProcessWhich of the following is not a sign of a good consensus meeting?