Question 2 25 p The following data represents number of customers arriving at Qu

Question

Question 2 25 p The following data represents number of customers arriving at Quick Lube for an oil change between 8 and 11 AM over the past 6 days Day 1 2 3 4 5 6 Customers 12 9 11 12 10 13 a) Using the Naïve Method, how many customers would you forecast for Day 7? b) Using 3 day Moving Average, how many customers would you forecast for Day 7? c) Using Exponential Smoothing with alpha 3, how many customers would you forecast for Day 7? (hint: use Actual Value for period 1 as period 2 forecast) d) If the actual # of customers for period 7 was 12, compute the MAD statistic for each method (parts a, b and c) using periods 4, 5, 6 and 7 as data points Compute MAD for all three Methods: Naive, 3-Day Moving Average, Exponential Smoothing e) Which method produces the best forecasts for Quick Lübe? Why? 12ptParagraph ompany's oining its president ntory ing a ale? 6 7 8 9 0 each rate irm

Explanation / Answer

a) Using naive method, the forecast would be 13 customers. In the naive method, last observation is your forecast i.e. sixth day had 13 customers

b) Moving average for 4th Day = (12+9+11)/3 = 10.66

Similarly, Moving average forecast for 7th Day (12+10+13)/3 = 11.66

c) Using exponential smoothing, forecast for 7th day = 0.3*13 + 0.7*10 = 10.9 ~11 cusomers

d) Mean of customers visiting if day 7 is 12 = 11.28

Note - we take absolute value in MAD equation irrespective of what is negative i.e. 11-11.28 = 0.28.

d ) The best method is exponential smoothing as it has the lowest MAD.

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