Future of the Technician Workforce Study

Summary of Key Findings: Cross Industry Sector Competency Requirements

Stakeholders identified relevant skill-sets, abilities, competencies, and tools that future technicians will be required to use for competitive jobs in Industry 4.0 fields. The following list summarizes cross-sector competencies that apply to multiple industry sectors and technology areas.  Soft Skills : In addition to technical skills, Finger Lakes regional businesses indicated a need to hire more technicians with complementary soft skills including communications, teamwork, leadership, problem-solving, and project management. Several stakeholders noted that soft skills are less quantifiable, more difficult to define, and lacking among science and engineering program graduates.  Data collection, analysis, and visualization : Regional business place significant value in technicians with experience and knowledge of advanced data analysis and mathematical skills. This includes abilities to collect data from multiple sensors (data fusion), visually present information, transform raw datasets, apply pattern recognition methods, and use software for machine learning and other AI-based suites.  Coding and programming : Industry 4.0 technologies require technicians with proficiencies in programming, coding, and design software suites for industrial automation and application development.  Systems integration : All industry sectors emphasize the need for technicians with systems knowledge to connect different administrative levels of organizations in a coordinated or unified manner. This also includes the ability to set up and troubleshoot IIoT-connected systems such as networks of manufacturing equipment as well as integration with broader supply chain networks to increase productivity and quality of services.  Testing, Inspection, and Quality Checks : Measurement, testing, and characterization are cornerstone functions of the technician workforce. Future technicians must automate and manage sensor-based quality control techniques to en- able high quality data acquisition as needed for advanced data-driven analytics and business-intelligence capabilities.  Cybersecurity : The proliferation of IIoT technologies and services compels businesses to place greater value in data security to ensure the protection of data and information for consumers. Across all industries, technicians are needed to help secure and manage cloud- and edge-based platforms and other IIoT devices and frameworks.

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