In November during a moment of fantastic-yet-uninformed self-reflection, Volkswagen’s Chief Executive Officer (CEO), Thomas Schaefer, announced Volkswagen was “no longer competitive as the Volkswagen brand” due to its “… preexisting structures, processes and high costs ….” This blunt declaration precedes intended staff and cost reductions intended to reduce VW’s expenses by 10 billion Euros (roughly $10.9M USD), which its Human Resources board member, Gunnar Kilian, states will be achieved through agreements on early or partial retirements over the next few years by “… taking advantage of the ‘demographic curve.” Days later, Stellantis offered buyouts to approximately half of its U.S. salaried workforce, GM will slash 1,300 employees and 24% of its struggling Cruise business and now Ford is rumored to be offering buyouts this month.

However, what is competitive, efficient or strategic is not well-understood by most of these executives. The typical, kneejerk answer is to cut resources, travel and spending, but research specifically focused on the automotive industry has shown that the size of the company has “… a statistically significant effect on efficiency, with smaller companies generally having lower efficiency ratings.” But the industry continues to cut in general ignorance, with strategic mistakes such as divesting electronics and software divisions only to have to rebuild software capability years later.

Therein, there are three efficiency measures where automotive executives will need to better understand the impacts in 2024 to truly be competitive: the adjusted throughput, the globalization lags and the green of green.

The Adjusted Throughput

In the 2011 classic “Moneyball”, Peter Brand (played by Jonah Hill) explains how baseball executives have been analyzing talent entirely wrong. “There is an epidemic failure within the game to understand what is really happening. And this leads people … to mismanage their team.” That same soliloquy could have been discussing how engineers are evaluated.

“Assessing an engineer’s productivity in relation to their colleagues is key to objectively determining who delivers a greater return on investment,” explains Adrian Balfour, founder of Envorso, a consultancy specializing in talent management and strategy for automotive software development organizations. “However, it’s crucial to consider the quality of work in this evaluation. Merely producing a high volume of code is not sufficient; the real question is, is the code of high quality?”

The traditional problem, though, is that typically it isn’t as easy as lines of code or number of widgets. “It isn’t possible to measure white-collar outputs or inputs fully,” argues Bruce Chew in the Harvard Business Review, “but this fact doesn’t mean that only blue-collar productivity can or should be measured. It does mean, however, that managers must be creative and open to new ways of thinking about an operation.”

The Globalization Lags

Soon after the turn of the century, several high-profile studies were produced from high-priced consultancies about the cost savings of offshoring from first-world countries. They garnered millions of media impressions, political debates and resulting business strategies. Soon thereafter, Josh Bivens published “Truth And Consequences Of Offshoring” in the Economic Policy Institute, stating “Recent studies overstate the benefits and ignore the costs …” Nevertheless, that bell could not be unrung.

Can development teams be efficient globally? Certainly, however few corporations have quantified the effects while making layoff decisions. For instance, the automotive industry absolutely understands the cost of delays at production facilities is upwards of $2M USD per hour, but few if any have quantified the known lags from globalization as delineated by Andy Nguyen nearly 20 years ago: time zone differences, cultural/language barriers, quality control issues, security and Intellectual Property (IP) issues, etc.

The Green of Green

A 2011 Urban Institute study found that for “… workers employed for the same amount of time … men aged 50 to 61 were ‘significantly more likely to become displaced from their jobs’ then men between the ages of 25 and 34.” Additionally, the National Bureau of Economic Research found that legitimate “age-related [discriminatory] firing … charges rise by 3.3% … for each percentage point increase in a state-industry’s monthly unemployment.” In other words, the kneejerk reaction of employers is to offload the larger salaries of older folks.

The underlying assumption: we get less productive as we get older, and in some measurements like inventive capabilities the peak is as early as 39 years old. However, some cognitive abilities such as vocabulary and crystallized intelligence are at their highest from ages 60 to 70 years old.

Additionally, the financial impacts of losing corporate knowledge cannot be ignored. In 2019, SciLo reported that “Conservative estimates indicate that at least 31.5 billion dollars are lost each year by [automotive] companies as a result of ineffective knowledge sharing.”

So when deciding whether to keep the green employee or the only that gets paid more green stuff, it once again requires more analysis and understanding.

Author’s Note

I’ve previously discussed how the Sixth Age of Efficiency may be the “… application of Artificial Intelligence (AI) to various parts of the product development instead of just to the product itself.” And that might happen.

But nothing in the aforementioned news clippings about layoffs and [in]voluntary retirements packages mentions the use of AI as a strategic tool to afford or inform such efficiencies. Just as pre-Moneyball assessments of baseball players without data analytics seems Jurassic compared to today’s sports evaluations, selecting engineers and programmers without the use of today’s tools and data seems archaic.

Maybe those employees who successfully ride the “demographic curve” will better understand that going forward.

Originally published on Forbes.com by Steve Tengler on 10-January-2024.