The automotive manufacturing supply chain has become almost too massive to manage, leaving manufacturers and suppliers with the challenge of finding qualified workers with the skills to identify and prevent quality risks.
With distributed plants and locations increasing in number, it has become difficult to gauge defects, whether isolated or spanning the supply chain, among the more than 20,000 moving parts that go into a vehicle. To ensure optimum efficiency, productivity and profitability across the supply chain, manufacturers and suppliers consider it critical to find the right employee with the right skill set for the job at hand.
Unfortunately, automotive manufacturers have traditionally struggled with access to a qualified workforce, but technological solutions do exist. Predictive analytics and machine learning are used for a wide range of business processes today, so why not deploy them for efficient employee recruitment and placement in the automotive manufacturing industry? Such processes can eliminate the guesswork in finding the most qualified individual for the job in a timely manner. This approach, coupled with the capability of the gig economy, can save manufacturers and suppliers valuable energy and resources, streamline logistics, and ultimately increase profitability.
The gig economy utilizes a temporary workforce for short-term engagements. The concept that can be scaled to meet the needs of most businesses today. Currently, more than a third of U.S. employees are gig workers, which amounts to nearly 57 million Americans. The high cost of health care and other benefits for full-time employees, constant fluctuation in demand for products and services, and increased overhead costs are driving this growth.
The automotive industry is no stranger to these issues, making it a strong candidate for leveraging gig economy principles to fill workforce gaps. Couple this with technological solution sets that enable digital workforce creation, and manufacturers and suppliers managers can identify the most qualified candidates, fill open positions based on geography and demographics, and monitor the employee training process and on-the-job performance through automated systems.
Operations and workforce management can be streamlined through two avenues:
Predictive analytics. By examining the performance metrics of their existing workforce, auto manufacturers and suppliers can assess which employee factors impact productivity most. This type of data-driven decision-making helps target and hire gig workers who possess the necessary experience and skills. Companies that provide and screen large talent pools of freelance workers for manufacturers can use predictive analytics to identify the candidates most likely to excel at the unique demands of each manufacturing plant.
The ability to find the right employee for the right job at the right time is invaluable. Looking beyond the traditional talent pools that are no longer yielding enough workers with the right skills, automotive manufacturers can leverage the gig economy to locate employees with the analytical, technological and problem-solving skills required for high-demand jobs. Reviewing key performance metrics can also determine the number of freelance workers needed to meet production goals.
Quality digital platforms. To maximize workforce operations and refine logistics, auto manufacturers should utilize a digital technology platform that aggregates all data and logistics, supports two-way employer-employee communication, and provides employees with the training, continued education and worksite information they need to be successful. The ability to select, screen and place employees through a platform that utilizes predictive analytics allows manufacturers and suppliers to match the most qualified candidates with the jobs that best fit their skill set.
Once employed, gig workers are best engaged through mobile. These apps can include a training component that enables freelance employees to arrive on the job with a solid comprehension of their tasks and job safety knowledge. Mobile technology can also provide employers with real-time analytics such as tenure, attendance, performance reviews, and issue identification across the supply chain to inform workforce needs. Integrating these elements into one cohesive platform is key to optimizing operations, from placement to production and beyond.
Auto manufacturers that capitalize on the power of the gig economy, paired with innovative predictive analytics and mobile platforms, will be well positioned to improve productivity, better meet customer demand and increase earnings. Complete workforce solutions that enable manufacturers and suppliers to align their business and operational frameworks with access to qualified, agile workforces will not only drive supply-chain success, but create a real-time communication network with a qualified workforce. In today’s increasingly competitive and complex workforce landscape, the gig economy provides manufacturers and suppliers with a scalable solution to combat the workforce shortage and propel their businesses.
Dave Kmita is executive vice president of operations at MS Companies, a provider of workforce technology to manufacturers and suppliers.