Solaris Pte Ltd is a manufacturer of solar panels used by many organisations in solar farms to produce electricity in Singapore. The last few years had been tough. The COVID19 pandemic had shutdown many economic activities leading to poor sales in solar panels. In more recent times, with many countries in the world embracing endemic COVID and opening up their borders, economic activities are restarting. The CEO of Solaris is optimistic even though there are other challenges like sharp spikes in oil and gas prices, war in Ukraine and frequent supply chain disruptionsTable 4 shows the past quarterly sales data of solar panels sold by Solaris in terms of units per quarter for the last three years. Sales data are only available right up to the second quarter of 2022. The CEO would like its sales manager to forecast sales for the next 4 quarters ahead from 2022 Q3 to 2023 Q2. Suppose you are the Sales Manager at Solaris. Using the Weighted Moving Average (WMA) method, develop a quarterly sales forecast for the solar panels.(i) What is your sales forecast for 2022Q3 through 2023Q2? You may assume that the weights are 2:3:1 where weight 2 is for the oldest data point and weight 1 is for the most recent data. What is the Mean Absolute Deviation (MAD) of your forecast? (Note: you need to show how the first two (2) values of your WMA, Absolute Error and final MAD are computed.) (ii) Comment on your new forecasts in terms of its reliability for business planning. (Hint: consider plotting a graph of your new forecast for analysis.)Do provide all equations, tables, graphs and working Table 4. Solar Panel SalesPeriod2019 Q12019 Q22019 Q32019 Q42020 Q12020 Q22020 Q32020 Q42021 Q12021 Q22021 Q32021 Q42022 Q12022 Q22022 Q32022 Q42023 Q12023 Q2Units SoldActual25,00022,50017,50012,50010,50010,75012,50017,50021,25023,75025,00027,50060,82557,500????

Question

Solaris Pte Ltd is a manufacturer of solar panels used by many organisations in solar farms to  produce electricity in Singapore. The last few years had been tough. The COVID19 pandemic  had shutdown many economic activities leading to poor sales in solar panels. In more recent  times, with many countries in the world embracing endemic COVID and opening up their  borders, economic activities are restarting. The CEO of Solaris is optimistic even though there  are other challenges like sharp spikes in oil and gas prices, war in Ukraine and frequent supply  chain disruptionsTable 4 shows the past quarterly sales data of solar panels sold by Solaris in terms of units per  quarter for the last three years. Sales data are only available right up to the second quarter of  2022. The CEO would like its sales manager to forecast sales for the next 4 quarters ahead  from 2022 Q3 to 2023 Q2. Suppose you are the Sales Manager at Solaris. Using the Weighted Moving Average (WMA)  method, develop a quarterly sales forecast for the solar panels.(i) What is your sales forecast for 2022Q3 through 2023Q2? You may assume that the weights  are 2:3:1 where weight 2 is for the oldest data point and weight 1 is for the most recent  data. What is the Mean Absolute Deviation (MAD) of your forecast? (Note: you need to  show how the first two (2) values of your WMA, Absolute Error and final MAD are  computed.)  (ii) Comment on your new forecasts in terms of its reliability for business planning. (Hint: consider plotting a graph of your new forecast for analysis.)Do provide all equations, tables, graphs and working Table 4. Solar Panel SalesPeriod2019 Q12019 Q22019 Q32019 Q42020 Q12020 Q22020 Q32020 Q42021 Q12021 Q22021 Q32021 Q42022 Q12022 Q22022 Q32022 Q42023 Q12023 Q2Units SoldActual25,00022,50017,50012,50010,50010,75012,50017,50021,25023,75025,00027,50060,82557,500????

Accepted Answer

The sales forecast for the 2022 Q3 to 2023 Q2 is computed by using linear regression method.Let y =…