PolarisG7

Polaris Case Study – Team G7 APICS Northeast District Conference 2015 – Student Case Competition

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Executive Summary Polaris, a leading manufacturer of high-performance motorsport products, is well-positioned in the

industry, claiming almost a fifth of the ten-billion-dollar power sports market. With demand growing and revenues expected to increase, Polaris must determine its strategy for meeting this demand and maintaining its position as an industry leader. A key decision is where to locate its manufacturing, and Polaris’s management has narrowed its options down to its top choices: keeping production in the US, opening a factory in China, or opening a factory in Mexico.

Based on careful analysis of Polaris’s goals, strategy, strengths, and culture, we recommend that Polaris open a manufacturing facility in Monterrey, Mexico to help meet expected high demand in the Southwestern US and increasing demand overseas. We also make additional recommendations about actions Polaris can take to support this decision in the context of its overall strategy.

Quantitative Analysis Polaris has multiple options for locating its manufacturing facilities, including manufacturing in the US,

offshoring, and near-shoring. There are benefits and costs to each option, but analysis of the most viable alternatives reveals that near-shoring to Mexico is the best option for Polaris in 2010. Exhibit A contains detailed calculations demonstrating that, while cost figures vary slightly based on changes in labor and exchange rates, opening a plant in Mexico is less expensive than either opening a plant in China or keeping manufacturing in the US. Because there are one-time costs associated with relocating some manufacturing, continuing to produce in the US is the cheapest option for the first two to three years, but over time moving some production to Mexico emerges as the cheapest alternative in the longer term savings of $10,633,778 in the worst case, and $14,275,481 in the best case (Exhibit A).

Qualitative Analysis Moving some manufacturing from Roseau, Minnesota to Monterrey, Mexico is the lowest-cost option

from a quantitative standpoint, but it is also a good idea based on qualitative analysis. First, skilled labor is more abundant in Mexico than in the US, so Polaris’s concerns about the manufacturing talent gap would be addressed close to home. While opening a factory in China or another location would also provide access to skilled labor, opening one in Mexico not only allows Polaris to take advantage of cheap labor rates, but also does so in a country where wage growth has stabilized (Exhibit A), making for a low growth rate and reducing uncertainty about the wages Polaris will pay. In addition, Monterrey’s geographical proximity has other benefits.

Because Monterrey is just over the border rather than in the Midwest near Polaris’s other facilities, it is closer to the US markets in which more Side-by-Sides are sold: the southern US, mainly Texas and California. In addition, most of Polaris’s near-term growth is expected to be from the Southwest, so a plant in Monterrey will be well-positioned to meet demand there. Long-term sales growth is expected to come from overseas, especially emerging markets. One of these is Latin America, where Polaris has been investing heavily in marketing and brand awareness; a manufacturing facility in Mexico is also more convenient for selling to that market. This efficiency is the second benefit of opening a factory in Mexico.

A third benefit is that it would also make collaboration between management, design engineers, and the production staff at the plant much easier than opening a plant in another part of the world. While it would not be quite as simple as if Polaris kept its manufacturing in Roseau, management will be able to communicate easily with the production staff, and will be able to arrange in-person visits whenever necessary. Unlike if a plant were opened in China, there would be no time difference between the Midwest and Mexico facilities, and crossing the border would be less complicated. In addition, the greater degree of cultural familiarity between the US and Mexico compared to the US and China would make integrating the Mexican workers into Polaris’s operations relatively easy (


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Exhibit B). Lead times for transportation from Mexico are variable, but Polaris can take some steps to reduce the

impact of this variation. Trucking companies claim they can deliver products across the border in two days, although it sometimes takes them up to seven. While this can cause some problems for Polaris’s supply chain, both lead time and variability are lower for transportation from Mexico than for transportation from China (Exhibit A).

Polaris has multiple options for dealing with this lead time variability. One option is vertical integration—if it acquired a trucking company or purchased vehicles, it could handle its own transportation, with more control over lead time and reliability. This, however, would require up-front investment in trucks as well as hiring drivers, which might not be worth the cost since Polaris is only moving a portion of its manufacturing to Mexico. Another option is to compensate for lead time variability with efficient inventory management. Rather than simply padding inventory models to allow for longer or more variable lead times, Polaris can use techniques such as cross-docking or postponement that will increase efficiency. In addition, it will benefit from the fact that the factory in Mexico would be located closer to customers: the reorder point for distribution would decrease, which would reduce cumulative ordering cost since fewer orders would have to be placed.

Investment Strategy In order to open a new factory in Mexico, Polaris must decide how to obtain the factory and how to

finance the transition. It has several options for its factory, including building a new plant, buying an existing one, acquiring a small manufacturing company, or outsourcing manufacturing. It also has several options for financing, including issuing debt or equity, bank loans, or partnering with another company.

While owning and operating its factory would give Polaris more control over aspects such as manufacturing processes and quality management, it would also require much more capital expenditure on land and facilities, compared to outsourcing. Also, Polaris is considering moving approximately 60 jobs to the new plant. While it will lay off workers from its factory in Roseau, it will not close the Roseau plant. Outsourcing would give Polaris the option to increase capacity if necessary without additional investment in plant, property, and equipment. In keeping with its overall strategy is to maintain most of the facilities it currently has in the Midwest, it makes sense for Polaris to outsource to Mexico rather than absorbing the costs of buying or constructing an entire factory and operating it with only 60 workers. This would help offset the fixed costs of transitioning some manufacturing to Monterrey.

In order to meet the costs of manufacturing in Mexico, Polaris has several alternatives. Based on its weighted average cost of capital, any rate of return greater than 8.68% would be an acceptable way to finance the transition (Exhibit C). Given that requirement, one option would be any investment at the current market rate or higher. Another option would be to partner with another company. This could mean either pooling resources with a firm manufacturing in Mexico or working with another firm to finance its move.

Additional Recommendations If Polaris does relocate some of its manufacturing to Mexico, it can also make other changes to support

its strategy. Two that are closely aligned with opening the Monterrey factory are warehousing in China and expanding its facility in Los Angeles.

If Polaris opens a plant in Mexico and does not in China, it would not have the same advantages in China, where it has spent heavily on advertisement. However, while demand is expected to grow in emerging markets like China, Polaris does not yet have the strong presence there that it does in areas close to Mexico. Therefore, it could open a warehouse in China to better serve that market, without making the significant up-front investment to open a factory there. After operating the warehouse for a few years, Polaris would be better informed about whether demand in China increased as expected, and about the costs and benefits of locating more of its operations there. It could then decide whether to open a plant in China, maintain its warehousing


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approach, or to withdraw from China to some degree. It is a reasonable long-term plan to open a factory in China to meet demand if sales increase as expected. Outsourcing in Mexico, as described above, would leave more capital available if Polaris eventually does invest in manufacturing in China.

To integrate the warehouse in China with manufacturing in Mexico and other operations in the US, Polaris could expand its distribution center in Los Angeles, CA. This site is small relative to some of Polaris’s other distribution centers, but if it were expanded, it could serve as a major hub (Exhibit D). Side-by-Sides and other products shipped to Los Angeles could be distributed to China via shipment to Shanghai. They could be stored in a warehouse located inland from Shanghai, such as in Hubei, where costs would be lower but location would be convenient to a major port and for distribution to the rest of the country. Using Los Angeles as a hub would also reduce lead time for distribution to China, because instead of transporting Side-by-Sides from the Monterrey when an order was placed, orders could be filled from Los Angeles (Exhibit E).

Making Los Angeles a hub would also work well with Polaris’s domestic operations. For example, ATVs and other products manufactured in Minnesota could be shipped to Los Angeles as normal, and the vehicles could take Side-by-Sides back to Minnesota on their return journeys. This would make transportation more efficient by reducing the time trucks travel empty. With an expanded Los Angeles facility, Polaris would have the option to close or reduce the size of smaller distribution centers on the west coast, such as the one it operates in Washington, for greater efficiency.

Because Los Angeles would serve a larger area, there would be other opportunities as well. Risk pooling would reduce the variability in demand at Los Angeles, since demand from Asia, the west coast, and nearby areas would be aggregated there. Postponement would also be highly beneficial. With 25 types of Side-by-Sides, Polaris could distribute base models and subassemblies for last-minute differentiation, allowing for more flexibility in meeting demand. A similar implementation could be used for its other products.

Conclusion While Polaris has many viable options for locating its manufacturing facilities, moving some production

to a new factory in Monterrey, Mexico is its best course of action based on cost-benefit analysis, examination of qualitative effects, and alignment with its corporate strategy. Locating some manufacturing in Mexico can be integrated with Polaris’s overall strategy with additional practical considerations, including culture, outsourcing, and its long-term plans for overseas markets. Based on culture and relationships, it will be easier to integrate a factory in Mexico than one in a location such as China. It will also be most practical to outsource, and to take steps to account for lead time variability, such as more efficient inventory management. In addition, Polaris can support its long-term strategy with an expanded facility in Los Angeles, California and a warehouse in China, giving it the opportunity to take advantage of risk pooling with a hub-and-spoke model, and the option of further expansion abroad.


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References

Distances and Time. (n.d.). Retrieved February 20, 2015, from http://www.searates.com/reference/portdistance/

The Hofstede Centre. (n.d.). Retrieved February 20, 2015, from http://geert-hofstede.com/china.html

The Hofstede Centre. (n.d.). Retrieved February 20, 2015, from http://geert-hofstede.com/mexico.html

POLARIS INDUSTRIES INC. 2010 ANNUAL REPORT. (2011, January 1). Retrieved February 20, 2015, from http://ir.polaris.com/files/doc_financials/annual_reports/PII_2010_AR.pdf

POLARIS INDUSTRIES INC. 2011 ANNUAL REPORT. (2012, January 1). Retrieved February 20, 2015, from https://www.proxydocs.com/edocs/request?paction=doc&action=showdoc&iindex=1&page=main&docid=509397&cid=962155&iclass=large&broker=0&se=0


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Exhibit A Calculations and Scenario Analysis

Figure 1: Overall Cost Comparisons for Three Manufacturing Strategies

Figure 2: Scenario Analysis of Wage Growth


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Figure 3: Scenario Analysis of Currency Exchange Rates

Table 1: Production, Transportation, and Other Costs

Table 2: Distances and Demand for Distribution Centers


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Table 3: Lead Time Variability by Location


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Exhibit B Cultural Comparison Based on Hofstede’s Dimensions

Figure 4: Comparison of Hofstede Dimensions for US and Mexico

Figure 5: Comparison of Hofstede Dimensions for US and China


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Exhibit C Weighted Average Cost of Capital Debt: $100,000,000 Equity: $370,991,000 Cost of Debt: .65% Tax Rate: 35% Market Rate of Return: 11% Risk free rate: 2.5% Beta: .99 Re = 2.5% + .99 (11% - 2.5%) = 10.91% WACC = *Assumes Beta and Market Rate of Return based on current industry data due to lack of historical data for Polaris; all other data taken from 2010 Polaris Industries Annual Report


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Exhibit D Facility Types and Sizes

Table 4: Polaris Facility Types and Sizes


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Exhibit E Proposed Delivery Route to China

Figure 6: Proposed Shipping Route to China


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Exhibit F Calculations

China Mexico US China Mexico US

7,651,304.64 7,512,008.93 11,221,862.12 18,851,304.64 18,212,008.93 11,221,862.127,832,940.87 7,361,177.67 11,221,862.12 26,684,245.51 25,573,186.61 22,443,724.238,059,097.75 7,509,559.23 11,221,862.12 34,743,343.26 33,082,745.83 33,665,586.358,313,986.22 7,667,080.98 11,221,862.12 43,057,329.48 40,749,826.81 44,887,448.468,603,782.20 7,834,584.10 11,221,862.12 51,661,111.68 48,584,410.91 56,109,310.588,936,371.39 8,013,025.04 11,221,862.12 60,597,483.07 56,597,435.95 67,331,172.69 10,733,736.75


7,650,932.75 7,523,079.13 11,221,862.12 18,850,932.75 18,223,079.13 11,221,862.127,830,159.69 7,376,024.84 11,221,862.12 26,681,092.44 25,599,103.97 22,443,724.238,051,243.37 7,526,904.22 11,221,862.12 34,732,335.81 33,126,008.20 33,665,586.358,297,018.60 7,685,979.65 11,221,862.12 43,029,354.41 40,811,987.85 44,887,448.468,571,693.70 7,853,923.47 11,221,862.12 51,601,048.11 48,665,911.32 56,109,310.588,880,357.77 8,031,482.94 11,221,862.12 60,481,405.88 56,697,394.26 67,331,172.69 10,633,778.43


7,646,593.97 7,509,812.80 11,221,862.12 18,846,593.97 18,209,812.80 11,221,862.127,820,350.39 7,354,726.29 11,221,862.12 26,666,944.36 25,564,539.09 22,443,724.238,032,364.92 7,495,114.86 11,221,862.12 34,699,309.28 33,059,653.95 33,665,586.358,264,040.75 7,641,784.04 11,221,862.12 42,963,350.03 40,701,437.99 44,887,448.468,517,672.19 7,795,274.55 11,221,862.12 51,481,022.22 48,496,712.54 56,109,310.588,795,839.58 7,956,201.59 11,221,862.12 60,276,861.80 56,452,914.13 67,331,172.69 10,878,258.56

CALCULATIONS-‐-‐WORST-‐CASE Conversion Worst Case labor

CALCULATIONS-‐-‐WORST-‐CASE Conversion-‐-‐ Base Case labor

CALCULATIONS-‐-‐WORST-‐CASE Conversion-‐-‐Best Case laborTotal Annual Costs Cumulative Annual Costs

Total Annual Costs Cumulative Annual Costs

Cumulative Annual CostsTotal Annual Costs


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7,651,304.64 7,512,008.93 11,221,862.12 18,851,304.64 18,212,008.93 11,221,862.127,700,632.90 7,515,918.84 11,221,862.12 26,551,937.54 25,727,927.77 22,443,724.237,759,838.02 7,522,141.17 11,221,862.12 34,311,775.57 33,250,068.95 33,665,586.357,831,129.35 7,529,664.16 11,221,862.12 42,142,904.92 40,779,733.10 44,887,448.467,917,256.02 7,538,583.06 11,221,862.12 50,060,160.93 48,318,316.16 56,109,310.588,021,648.84 7,549,013.36 11,221,862.12 58,081,809.77 55,867,329.53 67,331,172.69 11,463,843.17


7,650,932.75 7,523,079.13 11,221,862.12 18,850,932.75 18,223,079.13 11,221,862.127,697,926.20 7,531,180.30 11,221,862.12 26,548,858.96 25,754,259.43 22,443,724.237,752,438.61 7,539,524.49 11,221,862.12 34,301,297.57 33,293,783.92 33,665,586.357,815,673.00 7,548,119.02 11,221,862.12 42,116,970.56 40,841,902.94 44,887,448.467,889,024.89 7,556,971.37 11,221,862.12 50,005,995.45 48,398,874.31 56,109,310.587,974,113.08 7,566,089.30 11,221,862.12 57,980,108.53 55,964,963.62 67,331,172.69 11,366,209.08


7,646,593.97 7,509,812.80 11,221,862.12 18,846,593.97 18,209,812.80 11,221,862.127,688,379.62 7,509,287.44 11,221,862.12 26,534,973.59 25,719,100.24 22,443,724.237,734,653.69 7,507,664.89 11,221,862.12 34,269,627.28 33,226,765.13 33,665,586.357,785,632.41 7,504,961.28 11,221,862.12 42,055,259.68 40,731,726.41 44,887,448.467,841,497.33 7,501,206.66 11,221,862.12 49,896,757.02 48,232,933.07 56,109,310.587,902,387.00 7,496,444.34 11,221,862.12 57,799,144.01 55,729,377.41 67,331,172.69 11,601,795.28

CALCULATIONS-‐-‐BASE CONVERSION SCENARIO-‐-‐BEST LABOR

CALCULATIONS-‐-‐BASE CONVERSION SCENARIO-‐-‐BASE LABOR

CALCULATIONS-‐-‐BASE CONVERSION SCENARIO-‐-‐WORST LABORCumulative Annual CostsTotal Annual Costs




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7,651,304.64 7,512,008.93 11,221,862.12 18,851,304.64 18,212,008.93 11,221,862.127,679,757.23 7,225,938.93 11,221,862.12 26,531,061.87 25,437,947.87 22,443,724.237,592,962.80 7,102,904.38 11,221,862.12 34,124,024.67 32,540,852.24 33,665,586.357,522,567.67 6,986,768.60 11,221,862.12 41,646,592.34 39,527,620.84 44,887,448.467,469,680.40 6,877,145.56 11,221,862.12 49,116,272.74 46,404,766.40 56,109,310.587,435,891.07 6,773,700.99 11,221,862.12 56,552,163.81 53,178,467.39 67,331,172.69 14,152,705.30


7,650,932.75 7,523,079.13 11,221,862.12 18,850,932.75 18,223,079.13 11,221,862.127,677,062.29 7,240,424.03 11,221,862.12 26,527,995.04 25,463,503.16 22,443,724.237,585,817.08 7,119,010.63 11,221,862.12 34,113,812.12 32,582,513.79 33,665,586.357,508,077.06 7,003,470.07 11,221,862.12 41,621,889.19 39,585,983.87 44,887,448.467,443,964.06 6,893,408.65 11,221,862.12 49,065,853.25 46,479,392.52 56,109,310.587,393,784.24 6,788,467.83 11,221,862.12 56,459,637.49 53,267,860.35 67,331,172.69 14,063,312.35


7,646,593.97 7,509,812.80 11,221,862.12 18,846,593.97 18,209,812.80 11,221,862.127,667,557.15 7,219,644.88 11,221,862.12 26,514,151.12 25,429,457.68 22,443,724.237,568,641.95 7,089,491.59 11,221,862.12 34,082,793.07 32,518,949.27 33,665,586.357,479,913.48 6,964,412.73 11,221,862.12 41,562,706.55 39,483,362.00 44,887,448.467,400,670.19 6,844,088.91 11,221,862.12 48,963,376.74 46,327,450.91 56,109,310.587,330,249.80 6,728,240.65 11,221,862.12 56,293,626.54 53,055,691.56 67,331,172.69 14,275,481.13

CALCULATIONS-‐-‐BEST CASE CONVERSION-‐-‐WORST WAGE

CALCULATIONS-‐-‐BEST CASE CONVERSION-‐-‐BASE WAGE

CALCULATIONS-‐-‐BEST CASE CONVERSION-‐-‐BEST WAGE




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