Building Resiliency in Manufacturing with Automation and Advanced Analytics

Published: 
March 22, 2023

The manufacturing industry has been experiencing significant disruption in its supply chain due to various factors. These factors include geopolitical challenges, disruptions in freight and logistics, an impending global recession, weather events due to climate change, and other issues that may surface. In response to these challenges, the US Congress has passed legislation such as the Chips Act, which provides $39 billion in federal funds to companies in the semiconductor value chain to improve domestic production capabilities. This is an important step towards improving supply chain resiliency. However, it is worth exploring how we got here in the first place.

To begin with, let's define what supply chain management is. In business, supply chains allow manufacturers to produce the right amount of product at a competitive price point in response to market demand. The supply chain helps manage the total cost of product ownership by sourcing the right supplies/services at the lowest unit cost, the best legal and commercial terms, and, most importantly, leveraging the best technology to manage the overarching engagement. Supply chain teams focus on margins, processes, and scale/efficiency.

It's Time to Invest in Machine Learning and AI

Automation is the next logical, and necessary step. With the ever growing scale of the global supply chain, (and its current challenges) teams need to adopt AI/ML faster.  The space demands speed and agility to manage tasks and large datasets due to the real-time demands they face. Big data has become too robust for human hands and eyes to sift through. Thankfully, technology has evolved alongside us in this phase of our economy, and we will soon learn where it can take us.

As supply chain teams increasingly seek to gain efficiencies, optimize processes, and gain greater data insights, automation presents ripe investment opportunities. Automation, driven by AI/ML, will have a significant impact as autonomous tasks and decision criteria-based advancements become more prevalent. Gartner's 2022 Hype Cycle report stated that autonomous sourcing is at the forefront of innovation, and it is easy to understand why.

As teams strive to optimize processes, reduce risk, improve flexibility, and gain a competitive edge, they are beginning to realize the value of advanced technologies and big data. These technologies enable teams to scale and free up time to become trusted advisors to the business and provide actionable insights. The IoT and next-gen robotics will continue to be a focus of supply chain design as teams look to optimize scale and drive more efficient output.

Automation Improves Resiliency, Analytics Sustains It

Automation takes billions of data points, and presents them to human eyes in a way that makes sense, and improves decision making. Faster, real time data in sourcing, procurement, and spending is going to be a determining factor in system sustainability, and efficiency in resource management. Many companies are facing the challenges of practical integration of these technologies.

But let’s take it out of the hypothetical for a moment, and look at some real world examples. PCI Pharma Services is a leading pharmaceutical and biopharmaceutical global outsourcing solutions provider, with rapid growth through M&A. Acquiring three companies in two years, PCI Pharma Services partnered with Fairmarkit to substantially increase the number of MRO sourcing events they run across in the US with no need to onboard additional headcount. In the first year, PCI has identified over 20% savings on over $1M in sourcing events. The investment paid off, as it usually does in disruptive technologies. 

In summary, the manufacturing industry is currently facing significant supply chain disruptions. However, investment in automation, big data, and advanced analytics can offer opportunities for improvement. Supply chain resiliency and risk mitigation strategies will be crucial moving forward, and data should be treated as an asset to be leveraged for actionable insights and improved decision-making. By working to optimize processes, reduce risk, and gain a competitive edge, organizations can navigate the current challenges and emerge stronger and more resilient in the long run. Organizations can navigate the current challenges and emerge stronger and more resilient in the long run.

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