This paper reflects on a multi-round business simulation involving three products — X5, X6, and X7 — and the strategic decisions made to maximize profitability. The author applies contribution margin analysis, cost-volume-profit (CVP) frameworks, and price elasticity concepts to guide pricing and discontinuation decisions. The paper also examines how Porter's generic strategies should inform tactical alignment, and how behavioral factors such as risk aversion and strategic myopia can limit further optimization. Key lessons center on matching tactics to strategy, interpreting elasticity data, and the dangers of becoming overly cautious after initial success.
From this exercise, a number of important lessons emerged. The first step was to recognize the major areas where performance could be maximized. Several techniques were used to achieve this. The first was to conduct a contribution margin analysis. Through this analysis, for example, it was determined that the X7 had a very high contribution margin, which drove the notion that its price could be lowered. The contribution margin analysis was part of a broader financial review that revealed other important truths about the products. The X5 had fixed costs of $70 million — double the fixed costs of the other two products. This was understood to impact the profitability of that product, and indeed the base case run saw X5 profitability turn negative in 2009.
Cost-volume-profit (CVP) analysis, when combined with total potential market size and an analysis of fixed costs, led to the basic decisions for the first round of the simulation (Richards, 2010). It was determined that the X5 had high fixed costs that compromised its profitability beyond 2008. The number of unit sales required at the $250 price point for the X5 to turn a profit was in the range of 700,000 — a figure that could not be achieved with the remaining market share available in 2009. The product therefore had to be discontinued before 2009, since profitability in that year was going to be impossible given the high fixed costs and low level of remaining potential sales. A strategy was developed to maximize market penetration of this product in the first three years, with the understanding that it would be discontinued in the fourth year.
It was also noted that the X7 product not only had a high contribution margin but also offered the most potential sales at 15,000,000 units. As a result, a balance needed to be struck between sales volume and profit margin. Using price elasticity data from the first simulation run, a selling price of $137 was identified as the optimal point between market saturation and contribution margin. This tactic was not applied to the X5, which was believed to be largely maximized, nor to the X6, which was deemed largely price inelastic. This assessment proved faulty, however: there was still price elasticity in the X6, and when the price was increased to $460 in later years, demand fell considerably. The elasticity tactic used for the X7 should have been applied to the X6 as well — but with R&D expense as the key elasticity variable. It is believed that had this approach been adopted for the X6, total profit would have been higher.
The concept of price elasticity of demand was also central to the simulation. Elasticity refers to the degree to which a change in an independent variable — in this case either price or R&D expenditure — affects the dependent variable, in this case sales (QuickMBA.com, 2007). It was understood that different products would exhibit different degrees of elasticity with respect to different variables. That elasticity can be estimated and used to set the point at which profit is optimized. Profit is determined by the number of sales and the contribution margin at a given price point.
Two elasticity dimensions required consideration. The first related to price: it was established from the outset that X6 consumers were not price sensitive, while X7 consumers were. Both sets of consumers were sensitive to changes in product features, which were driven by R&D expenditure. A strategy was developed based on the idea that the first simulation run would provide data to estimate the price sensitivity of demand, especially for these two products.
The most useful concepts throughout the exercise were contribution margin (CVP analysis) and elasticity of demand. Understanding the cost structure of each product allowed for more informed pricing decisions. The price cut applied to the X7 was significant — a reduction of 25% from the base price in the initial run, extending to 31.5% of that base price in later runs. It was understood from the outset that such substantial price reductions were viable. The same analytical framework was used to determine that an increase in the price of the X6 would raise its total profit.
"Minor adjustments across three rounds improve total profit"
"Misaligned tactics undermine differentiation and cost leadership"
"Behavioral biases limit bold strategic moves and optimization"
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