PDA Simulation III: Pricing & R&D Strategy Analysis
This paper analyzes the third run of a PDA product portfolio simulation, evaluating pricing and R&D allocation decisions for three products — the X5, X6, and X7 — over a four-year period (2006–2009). The analysis examines how price elasticity of demand and R&D investment interact to drive unit sales and total profit. The simulation achieved $1.907 billion in total profit, a 5.2% improvement over the prior run. The paper identifies a misstep in raising the X6's price and the resulting impact on sales saturation, then proposes a revised strategy with a gradual price reduction for the X6 while maintaining the successful $137 price point for the X7.
- Simulation Strategy Overview: Rationale for X6 and X7 pricing decisions
- Year-by-Year Pricing and R&D Decisions (Sim III): Decision table for all products 2006–2009
- Results and Performance Analysis: Profit outcomes and identification of X6 pricing error
- Revised Strategy and Projected Outcomes: Lower X6 price path and projected profit gains
- Conclusion and Remaining Questions: Open questions on X7 optimality and X5 pricing
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What makes this paper effective
- The paper clearly connects each pricing decision to an underlying economic rationale — specifically, price elasticity of demand — making the logic traceable and transparent.
- It demonstrates self-correction: the author identifies that raising the X6 price was a mistake, explains why, and proposes a specific revised strategy with projected quantitative outcomes.
- Quantitative evidence is used throughout (e.g., 5.2% profit increase, 78% vs. 98% saturation, $7.755 million in projected additional profit), grounding the argument in simulation data rather than generalities.
Key academic technique demonstrated
This paper demonstrates iterative decision analysis — the process of running a simulation, measuring outcomes against expectations, diagnosing errors, and adjusting strategy for the next iteration. This approach mirrors real-world managerial decision-making under uncertainty and shows how analytical frameworks like price elasticity can be tested empirically and revised when evidence contradicts assumptions.
Structure breakdown
The paper opens with the strategic rationale for Sim III decisions, presents the year-by-year decision table, analyzes the results (distinguishing X7 success from X6 failure), and then proposes a revised decision table with a modified X6 pricing path. It closes by flagging unresolved questions — particularly about the X7's optimal price point and the X5's potential — setting up a future simulation run.
Simulation Strategy Overview
For this run of the simulation, the strategy revolved around two main dimensions. The first was that the price elasticity of demand for the X6 is relatively low. As a result, the price can be pushed higher. While this will decrease the number of units sold, it should increase total profit for the product. In this scenario, the upper bound was tested with a price increase to $450 for the first two years and to $460 in the following two years.
The X7 remains the key source of potential growth. Already, almost all R&D money has been shifted into this product. However, there is still room for growth above the $140 price point that was previously set. Assuming that price elasticity of demand is linear, the optimal price is close to that point, at $137. Any lower price will expand the customer base but will only serve to decrease overall profits associated with the product.
Year-by-Year Pricing and R&D Decisions (Sim III)
The decisions undertaken for this simulation are as follows:
X5: Price held at $250 for 2006–2008; R&D at 1% for those years, dropping to 0% in 2009. Discontinued in 2009.
X6: Price set at $450 for 2006–2007, rising to $460 for 2008–2009; R&D at 32% for 2006–2007, reduced to 1% for 2008–2009. Not discontinued.
X7: Price held at $137 for all four years; R&D at 67% for 2006–2007, rising to 98% in 2008 and 99% in 2009. Not discontinued.
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