Purpose-Built AI Helps Futureproof CPG Manufacturing: Study

Workforce constraints/upskilling and capacity constraints tied for the first top picks among almost half of all consumer packaged goods (CPG) respondents, according to results shred by Augury.

Kaikoro Adobe Stock 245853295
Kaikoro AdobeStock_245853295

Workforce constraints/upskilling and capacity constraints tied for the first top picks among almost half of all consumer packaged goods (CPG) respondents, according to results shred by Augury. Forecasting production and scheduling came in just under those.

“The manufacturing environment is changing fast, across all verticals, and leveraging purpose-built AI is not just a nice-to-have–it’s an essential component for a competitive company. With more efficient processes and machines, organizational resilience, and an intelligent, well-armed workforce, CPG organizations will not just survive, but thrive, while also impressing consumers with higher quality, fairly priced, and innovative products,” according to Augury.

 

Key takeaways:

  •  By comparison, manufacturers as a whole across all nine surveyed verticals listed the high cost of materials/energy, capacity constraints, and quality/yield/throughput issues as their Top 3 challenges.
  • When asked to name the primary factor that could limit their ability to meet production targets and business objectives over the next 18 months, staffing constraints topped the list with nearly 42%, considerably higher than any other vertical in the survey.
  • CPG leaders tagged increasing competition and knowledge transfer as their thorniest workforce obstacles; interestingly, lack of technology came in third. 
  • More than two-thirds (69%) of CPG manufacturers said they planned to increase artificial intelligence (AI) investments over the last year (second only to food and beverage manufacturers at 74%). And they have high hopes for those investments: when asked which production goals they believe AI can help them achieve, CPG leaders listed workforce, capacity, and yield/throughput issues.

 

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