Analyze the Time Series of the Available Inputs over the October to June Period. Provide Key Observations When Browsing Across the 10 Skus
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Group : Firework Supply Chain : Question 1 & 21. Analyze the time series of the available inputs over the October to June period. Provide key observations when browsing across the 10 SKUs (using the slider). a) In October they focused on a 17% SKU of the total volume. The inventory is higher than forecast and demand, which means the inventory costs are also high. They count on a growing demand in order to be able to respond with the stocks they have. They do not want to take risk to be out of stock (stock out is very low on the graphic). Further, the general trend is volatile. We can see demand and forecast is growing. They stayed low for a long time, which is quite rare. The further fluctuations are reality and this is normal. They were not always able to respond quickly on these fluctuations. There are different situations on the graphic. For example, the 3 stock outs: week 8, week 24, week 35. The forecasts are often low and stable because of this lack of reaction: overall trend. A quick reaction is highly recommendable. The percentage of error if it is positive it means we have an excess of inventory so a low demand. We can see such a high percentage of error between 11-15 (right graphic).b) We can see again the big peak occurring on the second graphic between 11-13. It is shorter than in the period A. This means at this stage they were already reacting faster and they start adapting their strategy. They tried to decrease the excess of inventory in order to reduce their costs. But on the contrast, at the end we can see a very high demand peak. Here they cannot follow anymore and their stock out increased so at the end they were not able to control the “unexpected” demands. The stock out has never been so high up till now (they have been overwhelmed).c) As we can see the 1% of SKU of the total volume means they tried to reduce inventory and anticipate much faster with a greater forecast analysis. But they overstated (they were a little wrong) with the forecast during the period 7-15. This is good for the customer but not good for the company because there will be more total costs. All operations will function more slowly and this will affect the whole supply chain strategy. This is an improvement. Again, the same peak occurs at the end. Demand is extremely high and excesses the stock out and inventory. Here again, it was very hard to control the situation.
d) Obviously, there is big peak between 35-37. Demand is extremely high and above stock out. Inventory is lower than the demand. As discussed above, they were again not able to react on certain fluctuations and variability’s. The 18% of total volume represents a high inventory, which means inventory costs are increasing in order to follow up the bigger demand. The inventory is even increasing but then the demand has decreased. So it is never easy to forecast in a good and efficient way on demand fluctuations. e) The high inventory level is a fact. They try to forecast more and more on past experiences. The forecast is excessing the demand level. So we can see they are organizing and trying to plan their supply chain strategy (bigger reaction). At the end, the same issue occurs as explained earlier in the situations above. Stock out does stay low, which is positive. F) The forecast trend is almost the same as the demand trend. They are at the same level.  The inventory level decreased to 15% again, so they reacted on a decreasing demand based on the forecasts (which they did in a good way).G) Inventory level is extremely high in period 7 and decreasing at the end. They over forecasted and demand is fluctuating. Their reaction is not optimal even if they have a good forecast. But at the end the forecast level is decreasing. The situation is very bad and there is no good reaction at all.H) Demand fluctuations are obvious again. Forecast is not so good. They cannot react on unexpected fluctuations. I & J) Inventory changes a lot. They could not prevent peaks (25) so this means a strong forecast error. Overall, at the end they only have 3% and 1% of SKU of the total volume (they overreacted).