Elon Musk has been steadily gaining political influence since being named a” unique government staff” by President Donald Trump in January. Musk has pushed for widespread layoffs of government employees and made an effort to shut down the US Agency for International Development ( USAID), and he has been appointed to lead the newly established Department of Government Efficiency ( DOGE ).
Musk has excelled at Space X and Tesla with his relentless pursuit of productivity, but can the same strategy also be applied to state where the stakes are significantly higher and companies are more tightly tied to people’s lives?
Cuttings to government programs may disrupt vital services and have an impact on millions of people around the world, in contrast to the private sector, where people and investors are typically impacted by streamlining operations.
Governments are not tech companies.
Musk is unquestionably renowned for his innovative success; he has founded and taken companies from the beginning to unfathomable levels, frequently at the same time. He has been merciless in terms of performance in doing so.
In his biography of Musk, Walter Isaacson devotes several chapters to his method of creating effective process and systems, a subject that industrial and systems engineering covers.
Musk’s strategy is incredibly problematic. His default response when analyzing a set of tasks to accomplish a goal is to eliminate as many as possible, with an attempt to overcut by at least 10 %. Not enough tasks were eliminated in the first place if he doesn’t gain 10 % of the things to the process in the second half. No cutting sufficient tasks is a mistake that Musk’s “productivity algorithm” avoids.
Industrial and systems architecture is based on the idea that eliminating misuse is essential. It is a method that is frequently associated with the post-war Japan-inspired Lean Production theory. A basic tenet of Lean is that leaders should support employees in identifying waste and that workers should be supported in removing inefficient tasks. It’s designed to be a bottom-up strategy, unlike Musk’s top-down performance engine.
Musk developed his strategy for tech startups, where failing is expected, widespread, and generally unimportant for everyone but shareholders. If SpaceX doesn’t send people to Mars, it’s irrelevant for the majority of people. Choices does fill the void if Tesla, PayPal, or Twitter/X crash.
His default strategy is to eliminate as many [tasks ] as possible, with an emphasis on reducing the number by at least 10 %. Not enough tasks were eliminated in the first place if he doesn’t gain 10 % of the things to the process in the second half.
However, this design is difficult to transfer to government, where failing has more profound and profound effects on people’s lives.
People are never things.
The businesses he’s led have benefited greatly from Musk’s efficiency-driven technique. Soon after taking over Twitter/X, Musk switched from eliminating jobs to eliminating individuals. Musk fired around 80 % of Twitter’s team over the course of the course of a year.
New devices were required because identifying “wasteful” staff is more difficult than eliminating pointless tasks. Employees were given an ultimatum: those who didn’t settle in to remain at their jobs may be fired, putting the pressure on them to consider their commitment to keep. Software engineers were asked to submit script for evaluation, but this didn’t lead to significant cuts.
In February, the FBI employed a comparable strategy. Musk sent an email to federal employees outlining what they had done the previous year and outlining how non-responses may be treated as resignations. This was quashed in less than 48 days, and actions were made on a voluntary basis.
The National Nuclear Security Administration even struggled to understand this business ethos of “failing hard,” as a result of a recent round of firings that raised concerns that federal security was in jeopardy. Most of the layoffs were canceled within 48 days, and 322 of the 350 people who had been fired were reinstated.
Similar to how DOGE-led firings at USAID “accidentally” reduce Ebola protection during an outbreak in Uganda, a error that could have had disastrous effects.
Musk’s weak productivity algorithms
The notion that fired workers can always be rehired if necessary is one of the shortcomings of Musk’s efficiency algorithm. However, people are not things that can be discarded and replaced with for good without effect.
The National Nuclear Security Administration had a difficult time reaching the fired employees. One of the fired researchers at the US Food and Drug Administration questioned,” How are you going to be able to get good citizens when you’re not offering Silicon Valley property or pay and you’ve taken their balance.”
Although this approach does have worked in the fast-paced, high-rewarding world of tech startups, its use in state has been turbulent at best and risky at worst. Additionally, beginning studies reveal that investing is not being significantly affected by the cuts.
No luxuries of failure and prosecution
Lean manufacturing has frequently been credited with revolutionary effects that transformed troubled businesses into fiercely organized competitors, but Musk’s performance engineering fails to take into account long-term effects.
Yet Lean apostles would not label it destructive or adopt an overzealous” shoot first, ask questions later” mentality. Effectiveness is not associated with cut; instead, it should be put into practice with consideration, careful consideration of value creation, and consultation with the parties involved.
In contrast to Henry Ford, Joseph Juran, or Tim Cook, the man who pioneered real-world effectiveness in his approach to government, Musk’s so much seems more like the ruthless corporate downsizer George Clooney plays in Up in the Air.
Public employees are not jobs, public services don’t have the pleasure of trial and error when national security or public health are in the public’s interests, and government organizations don’t work like technology startups.
Peter Vanberkel is a teacher at Dalhousie University’s Department of Industrial Engineering.
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