Why These Analysts Believe Robotic Automation Could Save Footwear, Apparel Industries

Labor costs on average represent 20 to 30 percent of manufacturing costs throughout Asia and are growing at an "unsustainable" double digit-rate, according to Laurent Vasilescu of Macquarie Capital.

According to Vasilescu, the hike in labor costs is putting "pressure" on apparel and footwear companies' gross margins – and moving production to cheaper labor areas isn't necessarily a solution.

Wage Hikes

Vasilescu continued that the average hourly compensation costs for manufacturing employees in China has grown at a 16 percent compounded annual growth rate from 2002 to 2009, a trend that has likely continued in the subsequent six years.

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Several apparel and footwear companies have shifted production within inland China or to Vietnam, but these regions are also showing "unsustainable" double-digit growth in hourly wages as their respective middle classes emerge.

To combat the rising wage rates, companies like Nike Inc (NYSE: NKE) would need to raise their average selling prices by at least 5 percent annually (above inflation) to maintain its gross margins if labor costs continue to rise in the double digits.

Is There A Solution?

The answer, according to Vasilescu, is robotic automation. This solution will "likely save the footwear and apparel industries."

Nike's ambitions within automation are well known. In 2013, the company announced it has acquired a minority stake in Grabit, an industrial automation and materials handling solutions company.

Vasilescu noted that VF Corp (NYSE: VFC) may also be working on "creating efficiencies around production."

Concurrent with Vasilescu's report, Corinne Jian, Macquarie's Taiwan-based analyst, commented that textile and footwear suppliers she met with "mostly see automation as an inevitable trend," especially for the footwear industry.

The analyst also pointed out that many footwear brands have already changed their product designs (such as no-sew, bonding and fabrics) to increase the amount of automation within the production process.

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