A commercial bakery has recorded sales (in dozens) for three products, as shown below:

a Based on the Plot for each data set, predict orders for the following day for each of

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the products using an appropriate naive method.

b. What should the use of *sales* data instead of *demand* imply?

## Answer & Explanation

~ From the figure i, Blueberry muffins sales data shows that the sale of muffins is stable, use simple naive forecast method.

Forecast units of Blueberry muffins on 16^{th} day = units sold on 15^{th} day

Forecast units of Blueberry muffins on 16^{th} day = 33 dozens

Cinnamon Buns sales data shows that increasing trend in sales. Apply trend-adjusted naive method. The difference of the last two daily sales data is obtained and then difference is added to previous sales data to forecast the next period demand.

Forecast units of Cinnamon Buns on 16^{th} day = Sales on 15^{th} day (sales on 15^{th} – sales on 14^{th})

Forecast units of Cinnamon Buns on 16^{th} day = 33 + (33 – 31) = 35 dozens

Cupcakes shows seasonal pattern in sales data, the cycle repeats after five days, as shown below:

Apply seasonal-adjusted naive forecasting method. The forecast value for period in next seasonal cycle is equal to the actual sales of corresponding period in recent seasonal cycle. Corresponding day 16 in cycle 4 is Day 11.

Forecast units of Cupcakes on 16^{th} day = sales in Day 11

Forecast units of Cupcakes on 16^{th} day = 47 dozens

.b.. The use of sales data instead of demand implies that Sales adequately reflects demand. We are assuming that no stock-outs occurred because demand equals sales if there are no shortages.

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