Optimizing profitability through pricing and capacity decisions in solar simulation

Solar Simulation

Per the parameters given for this assignment, the author of this report ran the solar power economic simulation twice and tweaked the results along the way. The author of this report will describe the adjustments and changes that were made along the way and will also analyze the results that were offered by the website at the conclusion of each simulation. Inclusive of the analysis and work done for this assignment will include a discussion and analysis of key metrics that resulted from each decision, an analysis of key data that would demonstrate the differences between each data run, a common on the more aggressive pricing used by competitors, whether said aggressive pricing would have helped the author's company in the simulation and so forth. Finally, there will be a recitation of the recommendations the author of this report would make regarding this simulation and how to remain competitive in general.

Simulation One

The above are the results from the first simulation. As one can see, the author's company very much stayed with the pack when it came to revenue per year and was only slightly distinguished from the others when it came to net income per year. Indeed, the author initially kept in line with the other solar companies as the price was the precise same as the competitor and so was the investment in new capacity. Results were positive with that approach and that was indeed the tactic for the few years. However, the author then dropped the unit price of electricity down by one cent and also upped the investment in new capacity and this caused the profit, as a matter of percentage, to soar quite high. After initially being in the ten percent range, it got as high as thirty percent and more by slightly undercutting the bigger solar companies and increasing capabilities and capacity along the way. When the new entrants came into the picture, they undercut the prices of all of us even more. However, this clearly did not get the desired results as their metrics, while very close to the author of this report, were not better and the bigger solar industry blew away everyone else including the author. The overall metrics of the first run can be seen below:

A couple of metrics above jump out to the author of this report. Capacitiy utilization was the same for all three groups. Annual shipments were a little low as compared to the other groups. However, return on sales as a fraction of revenue was 0.43 for the author while it was 0.31 or below for both of the other groups. This puts the author's simulated amounts at nearly forty percent higher than either of the other two groups. Further, gross margin was 0.61 for the author which was nearly thirty percent higher than the closest competitor and more than that for the other group. Consumer net price and unit direct cost was the highest for the author and it was not close on the consumer net price part of things. Annual net income for the author was much higher than the big industry group as it was 31.47% for the big group and 41.12% for the author of this report.

Conclusion

As for what recommendations the author of this report would make, there would be two general ones. First, one cannot be complacent and casual when it comes to making business decisions. The author of this report was a fairly small fish in a big pond with a much bigger fish. Following the start, there were other smaller competitors that entered the fray. They were individually smaller than the author but collectively made up a fairly big piece by the end of each simulation. What has to be done is that there has to be a differentiation. The author focused on capabilities and attracting customers through price and that strategy seemed to work fairly well. Surely, that is not the only way to proceed but it paid fairly good dividends in this case (Help Scout, 2015). In short, the first recommendation is to find a niche (Heydt, 2014). The second recommendation is to not be too conservative. Sure, one cannot be too over-the-top and aggressive (SRPL, 2015). There are indeed risks. The author's first results were decent but there were no losses. The second time, there were some losses but the overall performance over time was better. There can be brash and aggressive decisions made but they need to be made with the long-term metrics in mind. Overall, the best way to proceed is to have a game-plan and strategy in mind in advance (Parinello, 2004). There could and should be adjustments along the way but a stark departure from the original plan should only be done as needed based on what happens to occur as time drags on (Christ, 2014).