IndustryWeek July 25, 2017

For more information on SMT’s manufacturing skill solutions, please click on the links below.

• Company Overview Presentation
• Partial Client List
• Client Testimonials
• 46 year chart of Manufacturing Skill Assessment data
• Training Grid: Outlining targeted skill training based on assessment data
• Six-Page Capabilities Review Assessments & Training

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Any type of workforce skills gap is often the result of many forces that have evolved slowly over time, intertwining to create a complex social, political and economic problem.  Therefore, constructing arguments based on survey data (realistically, only a snapshot based entirely on perception) can be unreliable.  Both sides of the manufacturing skills gap argument have used survey data to frame their conclusions.

In the article, one of the authors even states this himself, “The claims and the data sets that are out there often don’t involve the direct measurement of skills, so people are looking at vacancy rates across the entire economy or all manufacturers,” he said. “There’s very little data in which people go in at the plant level and measure what skills U.S. workers need to have.”

How do you make conclusions about the hard skills of the US manufacturing workforce without actual skill data from US workers?

Since 1971, Scientific Management Techniques has been measuring and recording hard skill data using our Manufacturing Skills Assessment Programs across many manufacturing industries and geographical areas.   SMT’s assessments have been delivered millions of times over the course of this time period.  These programs utilize Validated, Hands-On, Performance-Based Assessment Machines that identify the most skilled, most capable, and most trainable candidates and incumbents.  In other words, our assessment programs directly quantify the hard skill levels of the manufacturing workforce.

From our decades of data, we have seen a sharp decline in overall assessment performance in the last 15 years.  We consistently hear about the struggles of manufacturers to find the right talent, and that is why they come to us for a solution.  Our manufacturing clients (such as Unilever, Colgate-Palmolive, Pfizer, Honda) deploy our Skills Assessment and Training Solutions because they know that without them, the impact of the skills gap to their bottom line would be significant enough to stifle productivity and profitability goals.

Clearly, we can assume the skills required by the manufacturing industry has not declined, and with the acceleration of technology and automation, they have in many areas increased.   With labor skills declining and the required skills increasing, a skills gap has developed.

This is not a judgement on the worthiness of the US workforce as one author states in the article.  This is the result of many socio-economic and political forces aligning against the manufacturing industry and the skills needed to see it thrive through the next century.

Of course, the solution required is multi-faceted, and certainly, coordinating supply with demand is at the heart of the issue. Outside of industry, SMT regularly partners with community colleges and workforce development initiatives to align their offerings to this goal.

If you are interested in more information about our Manufacturing Skill Programs or want to discuss skill data for your region or state, please contact me at ebarksdale@scientific-management.com.

The post Manufacturing Skills Gap Doesn’t Exist? It does, and here’s how. appeared first on Scientific Management Techniques, Inc..

Gregg Gordon describes Lean Labor Practices in this article on Manufacturing.net.

He states, “It is important for manufacturers to increase productivity, control costs and optimize labor resources and align them to the most important project or goal. Conceptually, all of this sounds good, but for many manufacturers, the question remains: How?”

Manufacturers often find themselves with incumbent skill sets that have been formed to a particular process or processes over time.  This allows them to operate effectively in a static environment with a predictable set of obstacles.  However, inefficiencies are exposed when change is implemented.  Sure, some of this is unavoidable, but hiring and training the right skills sets will allow greater flexibility when adapting to market changes in demand.

Scientific Management Techniques’ skill assessment and training programs allow manufacturers to acquire/develop the skill sets needed to implement a lean labor practice.

SMT’s Validated, Hands-On Selection-Evaluation program, using portable assessment machines and a non-written, non-verbal, task-oriented methodology, identifies the most skilled, most capable, and most trainable candidates and incumbents. It solves the question of who needs what training, eliminating wasted time and cost.

Here are some of the ways in which the assessment program can be used:

• In the hiring process; to identify and measure the skills required to operate, maintain, and troubleshoot a manufacturing facility.
• For promotions; using the assessment program ensures you promote the most skilled incumbent.
• To identify skill gaps/training needs. When you assess your workforce you identify the “specific” training needs of all employees. With this data you can deliver highly targeted training.
• To measure the effectiveness of training delivered.

SMT’s Industrial Skills Training curriculum is a 100% demand-driven program. It is highly customizable to fit only the specific needs of the client utilizing well over 200 training aids. This curriculum has been built by and for industrial operations professionals over the last 40 years.

Gordon summarizes, “While it is true that it is extremely tough to compete in the manufacturing industry today, Lean Labor can help. With Lean Labor, manufacturers gain a proven way to gain new efficiencies, reduce and control costs, and increase overall productivity. In turn, this allows them to focus on revenue-generating activities, strengthen the bottom line, and increase their overall competitive advantage.”

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