It's not challenging to see the large influence of technology and data in our daily lives. Everything from the availability of goods at your local grocery store, how cities move people with public transport, how energy companies control electricity demand spikes, and how you feel on a given day is controlled by the manipulation of data through algorithms.
Manufacturing is no exception to this influence of technology. Engineering marvels have long been about how large or grand a project was. The engineering marvels of tomorrow will be defined by the ability of a company to collect and utelize data.
The state of how manufacturing will and should be in the coming decades is a discussion for a separate post, but briefly, companies will increasingly devalue the human aspect of manufacturing. Arguably with good reasoning. As systems become more automated, human intervention just presents liability, higher costs, and inefficiencies. Even manager positions will become of little use. Fewer headcount operations require less guidance. Additionally, hiring managers will begin valuing employees who listen to machines and can follow their instruction.
Before you discredit this, think about what makes operations efficient. Repaceable components, maximum simplification of operator tasks, and little to no human intervention yield high efficiency processes. So what happens to the white collar worker in a world where there is no need to manage employees, monitor outputs, or meet deadlines?
Unfortunate as it may be, it has been proven time and time again. We've seen AI beat chess masters, win games of Jeopardy dominate online Esports competitions, and so much more. Any single task that you could ever think of, we could build a robot to do it better given enough time. But that's the aspect that cannot be replaced by AI.
We build robots to be very good at one or two very specific things. In a game of chess, a game or Jeopardy, we stand no chance. But in dynamic challenges in which there is no example to train upon, humans will always be required.
The Requirement of very smart individuals who can make sense of these automated systems will always be present in manufacturing facilities. Specifically, individuals who can understand all of the components of the given manufacturing business. Algorithms excel in specific use cases, therefore the individuals specialized into one role will struggle to compete.
The best way to preserve your role in advanced manufacturing facilities coming in the next decades, is to understand big pictures. The broader your knowledge and faster your ability to learn new specialities, the more value you'll provide to your employer. The integration of these specialized algorithms into complete systems will be one of the most in demand jobs in the near future.
The time of being guaranteed a job is over. The way I mean this, is that for a long time, even with little or no skills, just because of one's ability to be taught tasks, they were valuable to an employer. The risk of human error, financial waste, and human liability was worth the value they could get from your work. Production lines need to run and low skill individuals could be taught to do it. Medium skill individuals could be taught to look over the low skills individuals, therefore they were valued as well.
The Knowledge split in regards to manufacturing is coming. Only minimally skilled and extremely skilled employees will find work in manufacturing environments. Automation will remove the need for medium and low skilled employees.
Of course, this transition will not happen overnight and there is not much to worry about for those who are planning on ending their careers in the coming decades. This will be a problem that plagues middle and low skill workers down the road. This shortage in positions will likely further increase the wealth inequality in many capitalistic countries.
But what can we do to prepare? It is important to develop a working knowledge of all the components of your business. Understand the supply chain, ask questions to the quality department, understand the KPI's on the production floor. What separates you from an algorithm is the ability to piece together components to form that big picture. Don't let the algorithms win!
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