I find it interesting to listen to economists talk about U.S. productivity growth – or the lack thereof. It has been a source of much fretting over the years. The 3+%/year labor productivity growth rates of the 1950s and 1960s slowed to under 2% in the 1970s and then to 1.5% in the 1980-1995 period. There was a heartening rally between 1996 and 2004, when growth returned to its 1950s/1960s levels of 3% — a performance almost universally attributed to the efficiency gains from information technology.

But just as the economists and IT enthusiasts were completing their victory lap, productivity growth headed into the doldrums for a decade — growing at an anemic 1.4%/year from 2005-2014, with the slowdown starting well before the global financial crisis. When the first quarter of 2015 revealed a 3.1% decline on the back of a flat 2013 and +0.7% 2014, it precipitated much wailing and gnashing of teeth. Thankfully, the just-released revisions to the second quarter 2015 growth of 3.3% wiped out the first quarter decline and helped economists breathe a collective sigh of relief that we aren’t necessarily going into a hell in a productivity hand basket.

As I read all the productivity analyses and commentary, including the recent one on these pages by the clever folks at the OECD, I am struck that in trying to understand productivity, economists exclusively look at only one half of the productivity equation — literally not figuratively. That impedes their ability to understand what is really going on with productivity in the modern economy.

Most people instinctively think of productivity as a quotient: a physical output (e.g., a ton of coal) divided by a physical input (e.g., labor hours). They wouldn’t be wrong; that is where productivity measurement started.

But to say something useful about the comparative productivity of different kinds of enterprises, you can’t compare the output “one ton of coal” with “one automobile” to judge the one that used fewer labor hours to be “more productive”. It is, of course, apples and oranges. To make the comparison you need to convert the numerator from a physical measure to a financial one — conventionally the dollar value added (essentially a product’s selling price less purchased inputs), which is also how economists measure a country’s Gross Domestic Product. Once you have a dollar figure for the numerator you can compare the productivity of labor across industries and jurisdictions in terms of dollar value-added created per hour worked.

So far, so reasonable, but when figuring out how to improve productivity, researchers almost always focus on the direct determinants of the denominator — they think about how to use technology, training, re-engineering of work processes, and automation in order to reduce the number of labor hours required to produce a given product or service.

The numerator is entirely ignored as if the value of the output was fixed and immutable. However, as any student of strategy knows very well, the dollar value-added that a firm generates is directly proportional to what it can charge in the marketplace for its products or services. And that price is, in turn, highly sensitive to the competitive dynamics of the firm’s industry and the strategic decisions it makes. Given the basic dynamics of a quotient, changes to the numerator are equally important to results as changes to the denominator.

An example of the impact of changes in competitive dynamics can be seen from our experience with globalization. After China joined the WTO in 1997, the effect of its exports on many U.S. markets was to systematically reduce prevailing price levels. While ignored by economists, this has created massive downwards pressure on U.S. labor productivity as Chinese exporting ramped up after 2000. Many US firms in many U.S. industries had no chance to reduce their denominator (labor hours) as fast as the market-driven numerator (prevailing price levels) fell. While on a physical basis, many were reducing the labor hours per unit (of whatever they were producing), their efforts were swamped by the reduction in the value those units generated. That shows up in an economy-wide reduction in the pace of productivity growth in the past decade.

That notwithstanding, there is little discussion among economists of the mixed impact of globalization on US productivity growth numbers. Most consider globalization an unalloyed good for productivity — because it reduces denominators. While it almost certainly increases the efficiency of the economy, there is no reason to expect that it will result in an observed increase in productivity.

Economists do try to account for this kind of effect by making what they call “hedonic adjustments.” Literally, they take the price of a good (let’s say a PC) and adjust it (in this case upward because over time the consumer has gotten more for less in their PCs) to take into account quality changes. But I struggle to take seriously the notion that any economist can accurately or even usefully re-price goods across the entire economy based on their “true value” rather than their prevailing price.

What about the second factor: strategic decisions? These also have a direct impact on the numerator. If, thanks to choices around, say, product design, brand-building or selection of distribution channels, your product or service is hugely attractive to customers, you will automatically have high productivity, almost regardless of what you do to the denominator.

Take Apple. An iPhone 6, with largely the same physical properties, sells for two times a HTC Desire because Apple has created a user experience and brand that causes consumers to pay whatever it decides to charge. As a result, Apple has sky-high productivity versus HTC — which is struggling to make ends meet in the smartphone business. It is simply and clearly a function of a strategic choices influencing the numerator, not the size of the denominator.

Yet the impact of these kinds of decisions seems to be almost completely ignored by productivity economists. It is a shame. All of the economists and policy wonks obsessing about low U.S. productivity growth focus, at best, on half the problem, which is like going into a fist-fight with one arm tied behind your back. When productivity recommendations are made, they never point out the need for smarter strategic decisions on the part of U.S. company executives — except for smarter decisions on adoption of labor-saving technologies.