By Puneet Dhiman, CEO and Founder, chaabi.ai
In a rapidly evolving world where technology and data are transforming industries, organisations are facing an urgent need to upskill their workforces. The digital transformation has created an imperative for reskilling, not only for white-collar professionals but also for blue-collar workers who are increasingly interacting with technology and data.
According to the World Economic Forum’s 2022 Future of Jobs Report, 85 million jobs will be displaced by automation by 2025, while 97 million new jobs will be created. This means that workers in all industries, including blue-collar workers, will need to upskill to adapt to the changing work landscape.
The world of work is undergoing an epochal transition. As indicated in a recent McKinsey Global Institute report titled “Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation,” by 2030, as many as 375 million workers, roughly 14 percent of the global workforce, may need to switch occupational categories due to digitisation, automation, and advances in artificial intelligence disrupting the world of work. In response to these trends, many organisations are investing in upskilling programs for their blue-collar workers.
The Changing Landscape
The traditional blue-collar workforce, typically comprising individuals employed in industries like manufacturing, construction, agriculture, and logistics, is undergoing a significant transformation. These jobs, often associated with manual labour, are no longer immune to the influence of data-driven technologies and digital advancements. To stay relevant and competitive, blue-collar workers must embrace the digital revolution and equip themselves with the necessary skills to thrive in this evolving landscape.
Here are some compelling examples:
Precision Agriculture: In agriculture, data-driven technologies like GPS, remote sensing, and big data analytics are used to optimise planting, harvesting, and irrigation. Farm workers need to understand these technologies to operate equipment as sophisticated as drones effectively and maximise crop yields.
Manufacturing: The manufacturing industry is embracing automation, with Indian manufacturing companies currently preferring to adopt one standardised digital solution across plants compared to global companies that prefer one standardised digital solution with different functionalities or modules.
A 2022 study by IBM shows AI adoption continued at a stable pace in 2022, with more than a third of companies (35%) reporting the use of AI in their business, a four-point increase from 2021. A major driver of adoption was accessibility, making AI easier to implement across the organisation. Companies are also looking to AI to help them increase automation of tasks and reduce costs.
Construction: Building Information Modelling (BIM) is becoming the standard for construction projects, offering a 3D digital representation of building components. According to a 2023 report by Mordor Intelligence, 72% of construction firms are using BIM, and the market is expected to grow from USD 7.66 billion in 2023 to USD 14.68 billion by 2028, at a CAGR of 13.90% during the forecast period (2023-2028).
Logistics: In transportation and logistics, data-driven route optimisation, demand forecasting, and inventory management are crucial for cost savings and timely deliveries. Truck drivers and warehouse staff can benefit from data literacy to improve their job performance.
Empowering the blue-collar workforce with data-centric skills in addition to basic soft skills offers several advantages such as job security, career advancement, efficiency, quality, and safety.
Challenges and Solutions
Despite the benefits of upskilling, there are challenges in empowering the blue-collar workforce in a data-centric world. Some of these challenges include:
Access to Training: Providing training opportunities and access to resources may be limited in certain industries and regions. Governments, employers, and training institutions and platforms should collaborate to address this issue.
Digital Literacy: Many blue-collar workers may not have the digital literacy required for data-centric roles, but they are very well versed now with using a mobile phone. Tailored training programs and user-friendly tools can help bridge this gap.
Resistance to Change: Workers may be resistant to change, especially when they have been performing their jobs in a certain way for years. It is important to communicate the benefits of upskilling and provide incentives for learning new skills.
Costs: Upskilling programs can be expensive, and some employers may be hesitant to invest in their workforce. However, the long-term benefits in terms of productivity and retention can outweigh these costs.
In a data-centric world, the blue-collar workforce cannot afford to be left behind. Empowering these workers with data-related skills is crucial for their job security, career advancement, and the overall competitiveness of industries. By addressing the challenges and promoting upskilling, we can ensure that blue-collar workers are prepared to thrive in the evolving workforce and contribute to a more resilient and innovative economy.