With many shelf-keeping units (SKUs) being offered to the market, management must decide whether Time Series Forecasting can be done. The simple moving average technique is not often used in todays market, but the Weighted Moving Average (WMA) methodology is often employed.

Consider the historical sales data of a hair product offered in a supermarket in the table below, then formulate the forecast for periods 9 and 10 using the WMA technique. Use weighting of .5, .3 and .2. To be awarded full marks, show all calculations in tabular form.

Once the calculations are done, write a short motivation to management about your findings, the methodology used, and how the risk of market

fluctuation can be minimised.

\begin{tabular}{|l|c|c|} \hline \multicolumn{1}{|c|}{ Month } & Period & Actual sales in units \\ \hline January & 1 & 1500 \\ \hline February & 2 & 2000 \\ \hline March & 3 & 1750 \\ \hline April & 4 & 1000 \\ \hline May & 5 & 2500 \\ \hline June & 6 & 1500 \\ \hline July & 7 & 3200 \\ \hline August & 8 & 3150 \\ \hline September & 9 & \\ \hline October & 10 & \\ \hline \end{tabular}