Navigate Tech Disruption in Semiconductor Industry with Agile Learning and Development Strategies

The constant evolution of advanced technology is disrupting the talent landscape, widening the skills gap at a concerning rate. As a result, up to 800 million jobs (about 1/5 of the global workforce) could be lost to automation. The semiconductor industry is no exception to this trend. With rapid technological advancements, companies must adopt agile learning and development (L&D) strategies to stay ahead of the curve. 

Disruptive Innovation in Semiconductor 

Constant technological disruption is making skills complex and creating demand for new-age skills at an unprecedented rate.  

By 2030, up to 14% of the global workforce will need to acquire new skills to fill the skill gap. Companies are already experiencing the impact, with skill gaps starting to occur within organizations.  

Semiconductor companies are facing significant job displacement due to the disruptive influence of the following innovations:  

• AI – The AI market size in the semiconductor industry is expected to be around $67 billion by 2025, indicating high user adoption. 
• Robotics and Automation – The robotics market size in the semiconductor industry is projected to have a CAGR of around 17.5% by 2030, indicating high demand. 
• Internet of Things – The IoT market size in the semiconductor industry is predicted to be around $694 billion by 2030, indicating higher usage. 
• Big Data – The big data market size in the semiconductor industry is expected to have a CAGR of around 8.6% by 2027, encouraging user engagement. 
• Blockchain – The global blockchain market is expected to have a growth rate of around 53.2% by 2026, providing solutions to the semiconductor industry. 

That’s not it; AR & VR, Advance Packaging, Digital Twin, Nano Technology, and Quantum computing are some emerging technologies that will continue to drive disruption in Semiconductor Industry. 

Disruptive innovation is also disrupting existing core roles while creating demand for new-age roles with emerging skills. The disruption of these job roles over time leads to no positive economic value as the skills become obsolete. Targeted L&D can result in a 53% increase in the economic value of employees to the organization.  

Agile and proactive Learning and Development strategies can help organizations fill skill gaps faster, saving considerable costs in the long run. L&D leaders can play a crucial role in navigating these disruptions. 

Learning and development strategy is critical for the productivity of the workforce 

To overcome the impact of Tech disruption and to bridge capability gaps, L&D has become critical for organizations.  

1,216 companies (87%) know they are either already experiencing a skills shortage or will experience one soon.  

Learning and Development strategies tailored to the specific needs of organization and its workforce are critical for productivity. 

Steps to create a Conscious Reskilling Program: 

1. Assess the current situation: Identify the existing skills gap, and evaluate the skills required to bridge the gap. 
2. Set SMART objectives: Create specific, measurable, achievable, relevant, and time-bound objectives that align with the organization’s goals. 
3. Develop a customized L&D program: Create a program tailored to the organization’s and its workforce’s specific needs. 
4. Deliver the L&D program: Implement the program and measure its effectiveness to ensure it achieves the desired outcomes. 

Steps for Continuous Upskilling: 

Continuous upskilling is an ongoing process that can help organizations stay competitive in a rapidly evolving industry. Here are the steps involved in continuous upskilling: 

1. Identify the skill gap: Determine the skills necessary for the workforce to remain relevant. 
2. Define learning objectives: Create clear objectives that align with the organization’s goals. 
3. Select learning methodology: Choose the most effective learning methodology for each skill. 
4. Develop targeted learning content: Create content tailored to the workforce’s needs. 
5. Evaluate effectiveness: Measure the upskilling program’s effectiveness to ensure it achieves the desired outcomes. 

Building a Modern Workforce: Impact and Cost of L&D in the Semiconductor Industry 

As the semiconductor industry undergoes disruption, many job roles and core workflows are evolving.  

For example, a design engineer’s workflow will become increasingly digitalized as AI and ML algorithms drive greater efficiency and productivity.  

Companies can save ~2/3 of the cost of hiring a new employee by reskilling an existing employee while improving retention rates and efficiency. 

Benefits of Reskilling for Semiconductor Companies 

Reskilling provides several benefits, including: 

1. Improved retention: Reskilling reduces attrition by providing viable career paths to disrupted job roles in demand. 
2. Improved efficiency: 69% of talent professionals believe reskilling can help improve diversity and inclusion (D&I). 
3. Reduced cost: The cost of reskilling an existing employee is approximately one-third the cost of hiring a new employee with the same skills. 

Cost Analysis of Reskilling vs. Hiring 

To analyze the cost savings associated with reskilling and hiring, let’s consider the case of a Design Engineer.  

By reskilling a Design Engineer with data analysis, machine learning, statistics, and artificial intelligence skills, the organization can transform them into an AI Engineer.  

The total cost savings of reskilling an existing employee to an AI Engineer is around $30,000 per FTE. For a team size of 40 FTE, the organization can save up to $1.2 million/year in the first year.  

The total cost of reskilling includes the base pay, salary hike, and reskilling cost, while the cost of hiring an AI Engineer includes the base pay and non-recurring costs. 

Cost Analysis of Upskilling vs. Hiring 

Let’s consider the case of a Data Scientist whose current skill set includes: 

• Analyzing complex data to identify patterns and trends 
• Developing insights to support business decisions 
• Communicating findings to stakeholders, and  
• Programming in Python, R, and SQL.  

To keep up with the evolving field of data science, Data Scientists need to upskill with new-age skills like AutoML, Explainable AI, Hugging Face, and Apache Beam. 

By upskilling Data Scientists with new-age skills, organizations can drive innovation and efficiency (up to 80%) and gain a competitive edge.  

Firms that provide upskilling training to their employees see a 12% increase in productivity, improved efficiency, and promoted innovation and creativity. 

While investing in upskilling programs may seem costly, the benefits outweigh the expenses in the long run. The total cost savings of upskilling a Data scientist is around $34,000 per FTE. 

Draup’s Reskilling Intelligence platform can help design targeted reskilling/upskilling programs for employees to acquire specific skills. The platform performs complex assessments around various critical reskilling and upskilling parameters between existing and desired roles to understand the skill gap and match it with relevant learning modules.