The resource geography of today's global megabanks shows a dispersion of resources that clearly reflects the impact of the migratory patterns toward low-wage areas of the past few years: 40 percent of technology personnel and 35 percent of operations personnel are located in the Asia-Pacific region, while 33 percent and 35 percent, respectively, are based in North America.
Perhaps we are now witnessing a phenomenon that is driven by the principle that efficiency follows wages, and hence the continued movement toward low-wage geographies in Asia (and the not-so-visible build up in Latin America and the Caribbean). But, while it may be true that efficiency follows wages if one measures efficiency as cost per labor hour, if you shift the metric to throughput or output per labor hour or per unit of labor cost, the results may be quite different.
This begs the question, what does the global landscape look like in terms of productivity and quality as measured from an output perspective versus a labor (input) perspective? In addition, it is likely that technology - and technology economics - are key drivers of workforce performance. So a second question has to do with the interplay of global technology economics and global labor performance.
Choosing the Right Metric
Little is known about such dynamics, and results vary depending on the chosen metrics. If you use annual gross domestic product (GDP$) per worker as the measure of national productivity, the United States comes out at No. 1, at $63,885, which is 14 percent above the second-highest nation. If you shift the measure to GDP$ per worker hour, however, the U.S. slips down because, in general, U.S. workers work more hours than workers in other countries.
Interestingly enough, if you narrow in on technology competitiveness, The Economist recently ranked the U.S. as No. 1 overall. On a scale that measures worker output in terms of hardware and software goods produced per worker annually, however, the U.S. ($154,173) drops to seventh. (Taiwan assumes the top spot, at $386,713.) But this still is four times higher than India ($39,033). So is a worker in India earning one-third of a fully loaded U.S. wage really a good economic choice?
The Rubin Worldwide Research Database (www.rubinworldwide.com) shows that the spread in technology work hourly wages between developed nations and low-wage nations is on the order of 4.1 to 1. But consider that there is also another set of forces at work: labor productivity and quality. Shifting to yet another metric reveals the impact of these additional forces.
This metric is a "cost of goods/cost of service" metric - what is the cost per contact center contact or per payment processed? Intuitively, such measures seem to be a more effective way to assess true economic efficiency from an output view versus wage information, which is truly an input view.
Some sample data reveals that for a contact center, the cost per contact in Costa Rica is $8.53 versus Manila at $5.71, China at $7.24 and Budapest at $11.25. Of this set, hourly wage is lowest in China, yet unit cost per contact is far higher there than in Manila.
Cost per payment for an accounts payable function is equally revealing. Costa Rica is $1.26, Brazil is $2.86, Manila is $2.14 and China is $1.98. Again conventional wisdom would likely have placed the bet on China or Manila, not Costa Rica.
You Get What You Pay For?
Clearly economic efficiency does not follow wages. Other drivers that must be given consideration include worker hours per year, worker productivity, quality, and of course, a whole set of policy and risk issues.
Yet this list of considerations, in itself, is incomplete and insufficient because even as it is being written, its underpinnings are changing rapidly. Global technology economic data shows that nations around the world are making substantial investments in the technologies necessary to make their workforces competitive and differentiated. The global "steeplechase" shows nations such as the Ukraine increasing their investment per worker by as much as 77 percent over the next two years. As nations invest in their people to drive performance, wage levels will become even a poorer indicator of economic efficiency.
Furthermore, to fully compete on a global scale, nations are investing in their educational infrastructure to develop the critical talent that will be needed in the future. Again, technology and information access play a pivotal role.
Developing and executing an effective location strategy requires far more than focusing on labor rates and labor arbitrage. It requires mapping the new geography of our technology economy, and it requires new measures and transparency into workforce performance and outcomes.