Given the segments in which we decided to compete, we focus our analysis on the Low-end, Traditional and High-end segments. Our analysis of the competition is mainly based on two dynamic parameters:
The degree of differentiation of our competitors in each segment
The degree of importance of a price war in each segment
The degree of differentiation may be evaluated as the distance from the current position of a product to its relative ideal spot inside a given segment. From that assumption, we can easily define what will from now on call the deviation D of a product through the following calculation, where Pi and Si are the relative performance and size of the ideal spot, and P and S are the relative current performance and size of a given product:
Hence the lower D is through every round, the higher is the degree of differentiation of the corresponding competitor, since it is investing in order to keep its products closer to the ideal spot. Oppositely, our products would have an increasing D since we let our products shift naturally given our product lifecycle focus.
The degree of importance of a price war may be assessed as the standard deviation σ of the whole industry’s price range for a given segment through each round. A low standard deviation indicated prices that are quite concentrated around a certain value. If this value is closes to the lower bound of the customer’s expectations, we can fairly say that a price war is ongoing in this segment.
We will use those two parameters as the inputs of our analysis in the following lines and try to form a conclusion over every team’s strategy.
As shown in annexure A, all competitors have had quite the same decreasing in their degrees of differentiation across the rounds until round 3, because this is from round 3 that the natural shift of the low end product takes him beyond its ideal spot, hence there is then a necessity of accommodating the product’s position across the following round if one wants to differentiate. As we can see, teams Digby and Chester have made the choice to let their low products keep drifting after round 3, indicating they did not plan to compete on differentiation in this segment.
Concerning the prices, we can see as shown in figure 1 below that there’s been a peak of the value of the standard deviation on round 1 since no one had any information on the other’s intended strategies. The prices stabilized from round 2 to 5 around an average of 0.50 with a final average price of $17.20. Given the price sensitivity of the low end customers, this result is quite surprising since it shows there hasn’t been a severe price war in this segment. Indeed none of the competitors suddenly decided to drop the prices down to $14 for instance, which encouraged prices to stay relatively high given the $12.50 final lower bound of customer’s expectations in round 5.
Our team was actually prepared to face such a price war. We anticipated the fact that none of the competitors would compete on differentiation in this segment (since spending money in R&D to devaluate a product seemed unconceivable) and thus decided to gain our competitive advantage from an early automation of our production lines, as shown in figure 2 below. However, this advantage was not sustainable and we were imitated by the other teams quite quickly during the following rounds. However it allowed us to ensure a higher margin on our low end product for more than half the game.
As shown in annexure B, differentiation in the traditional segment is quite uneven. Some competitors as Chester and Baldwin improved their products only every two rounds whereas Erie and Andrews clearly appear as differentiators in this segment. However, as Erie spent a lot of money on improving its traditional product, it got beaten on price almost every round since they had to maintain a higher margin to ensure profits. This leaded to a…