Have you ever imagined industrial machines talking to one another or “smart” factories taking production and budget decisions without involving any human interaction?
You might still think that computers, the internet, and automation (Industry 3.0) will continue to be the remarkable trends of the future. But, in fact, they no longer resemble a technological breakthrough! Everything has changed since the term “Industry 4.0” was revived in the 2011 Hanover Fair in Germany.
Without human interaction, Industry 4.0 enables machines and cyber-physical systems in factories, for example, to communicate via the Internet of Services and cooperate with each other to make better production decisions considering resources of time, effort, and cost.
To make it clear, let us take an example of a simple manufacturing process from a traditional chocolate factory that produces your favourite chocolate bars, which you buy from stores. Let us suppose that once the company receives a shipment of cocoa beans at its processing plant, the process starts with beans being roasted (maybe at different temperatures and stages). Later, beans are refined, moulded, cooled, checked for quality, packaged and then ready for distribution. At every stage of the production process, we have a production line that operates on its own but with the supervision of a worker, who is responsible for spotting any errors, reporting issues, and maybe turning the machines on or off. If, for any reason, a failure within the system occurred or ingredients were questioned, the plant manager might stop production, operate the machines at a different pace or add an extra worker for quality check. Were the company to experience an excess of supply, the CEO would need to ask the plant manager to decrease production volumes to adapt to the market. If consumer consumption were to lean more towards dark chocolate, you might require some changes in the process and value chain. Your supply chain expert or business/process analyst will work for hours to optimize a new process. But what if these responsibilities of spotting errors and maintenance as well as decisions of decreasing/increasing production, or stopping machines due to crisis, were to be handled by the very same machines and systems?
This is the core of Industry 4.0. Not only machines and systems, but whole factories will be able to communicate with each other through the internet and analyse complex market data to drive decisions related to running production, and will be coping with change with no human interaction. These factories and systems will be able to work in holidays, tailor production to consumer preferences, and most importantly reach just-in time maintenance that results in near-zero downtime for systems and machines.
While this outstanding revolution will bring many advantages to the economy in future, the sociological impact will be harsh. As most decisions and machine behaviour will be determined by cyber-physical systems that monitor physical processes and utilize big data to drive decision-making, human presence in manufacturing will no longer be necessary. In better terms, it will be costly and inefficient. A recent report of the World Economic Forum revealed that 7.1 million jobs will be replaced by Artificial Intelligence systems and machines in 2020. Most of these jobs are those associated with blue-collar workers.
These figures along with other studies on the impact of Industry 4.0 applications on the human workforce raise concerns with regards to future unemployment rates and the employment skills composition. Replacing most blue-collar, administrative, and low-skilled jobs will mean that many people will lose their jobs and the labour market will no longer demand such occupations.
Although the change will be gradual across the world, there are no guarantees that generation X workers in these occupations will have any method to escape this transition. The reason is simple: jobs performed by this workforce group require by their virtue fewer skills, education and problem-solving skills. Although education rates have been growing in the last decade, Millennials and Generation Z might end up with the same fate of not being able to match the demand of the future labour market.
If our educational institutions’ learning methods and outcomes continue to be the same, we will experience not only a skill gap, but a whole misalignment between educational outputs and demands of work. Educational Institutions should be more focused on providing new generations with skills that are needed for the future of work.
What skills? Simply those that cannot be yet done and those concerned with operating machines and robots.
Data Analysis, Problem Solving, Critical Thinking, Emotional Intelligence and Machine Learning should soon be essential components of our educational systems, while instructors and teachers should focus more on Industry 4.0 outcomes and digitalization rather than reinventing the wheel with tons of theories and unrelated skills.
The new generation of workers should start soon thinking in terms of data, learn to solve problems, and criticize what is given, rather than accept it. We need to start learning more about HR analytics than about HR, Marketing Analytics instead of only Marketing, Econometrics when learning Finance and Economics, and Engineering Analytics as a tool for future engineers.
With this fast pace of technological change, skills need to be developed to match the future needs of work, those impacted by Industry 4.0. Unfortunately, failure to adapt and learn will not only result in losing our jobs but will impact the economy severely, with large numbers of the population unequipped to participate in the workforce.
Written by Sahim Kasht