Is your business prepared to win the race for top talent?

With over 60 years of talent acquisition experience, Acara is well-equipped to source and recruit candidates for our manufacturing and logistics clients. Our team of recruitment professionals is committed to implementing innovative people strategies that deliver results and empower the workforce. Through our suite of contingent and direct hire placement services, Acara has helped companies to hire candidates in the following job types:

• Assembly
• Inspection
• Machine Operation
• Maintenance
• Management
• Production
• Warehouse/Distribution

By leveraging Acara’s 2023 Manufacturing & Logistics Salary Guide, your organization will be well-positioned to attract qualified professionals with competitive hourly rates and annual salaries at your disposal.

Inside:

• Anticipated Industry Trends
• Job Outlook Growth
• Manufacturing and Logistics Salary Guide

All compensation figures within our enclosed salary guide were generated via Lightcast—a premier labor market data and analytics provider. An array of verified public and government sources underpins Lightcast’s sophisticated software. The tool drives in-depth industry analysis by delivering accurate summaries of the labor and compensation market.

Anticipated Industry Trends

Acara’s team of workforce experts anticipates these manufacturing and logistics trends becoming more prevalent in the future:

Addressing the manufacturing skills gap

While the world of technology is evolving rapidly, 22 percent of existing skilled manufacturing workers plan to retire by the end of 2025, resulting in 2 to 3.5 million unfilled manufacturing jobs by 2025, according to HBK. A report from Deloitte detailed the skills gap currently hindering these businesses. Companies must identify and analyze their skills needs against their current workforce’s skill sets. Organizations must rethink hiring procedures, provide proper training, and tap into existing overlooked talent pools to close these gaps.

A greater emphasis on sustainable practices

Within the manufacturing and logistics space, there is arguably no hotter topic than promoting workplace sustainability. Incorporating eco-friendly practices into manufacturing efforts can generate cost savings while enhancing the organization’s brand in the eyes of its target audience. Nearly 80 percent of U.S. consumers consider the sustainability of a product, the retailer, or the brand when making at least some of their purchases—highlighting the sheer importance of sustainable business practices.

Fostering local and regional strategic partnerships

Material lead times are unpredictable and supply is limited. 47 percent of leaders plan to expand their supplier network—to ensure they are not scrambling for a solution at the last minute. To help alleviate supply chain delays and disruptions, manufacturing organizations are placing more trust in their regional economies and fostering supplier relationships closer to home.

Implementing big data to improve decision-making

Manufacturing and logistics companies are constantly looking for ways to scale. By leveraging the power of big data, organizations can discover smarter ways to analyze and extract information from large, complex, and otherwise unwieldy data sets. Implementing these strategies can help improve forecasting, enhance production capabilities, and generate greater revenue.

Using artificial intelligence (AI) and machine learning (ML) to augment smaller labor pools

The steady emergence of concepts such as AI and ML will continue to change the manufacturing and logistics sector in the years ahead. Through AI, businesses scale production to become faster, standardized, and more efficient, all while effectively managing product inventory and upgrading product quality. Machine learning can help companies program automated tools or robots to better react to unexpected circumstances. Combining both of these concepts will enable manufacturing and logistics businesses to work smarter, with few resources, while innovating faster than ever before.