How Statistics Are Used in Supply Chain Management

 

In 2021, the waves of the pandemic started to quickly unravel supply chains across the world. Manufacturing plants slowed or even closed, ports experienced unprecedented back-ups, and transportation costs and inflation raised prices dramatically. This situation was exacerbated by prevailing manufacturing practices. That is, before the pandemic, many large organizations were using “lean manufacturing," which means they had just enough staff, materials, and vehicles to fulfill average orders.

And at the same time that people became isolated in their homes, orders went up, but the ability to adequately fill those orders went down. And supply chain managers were tasked to solve these problems.

Supply chain managers are crucial to improving the efficiency and speed of supply-chain processes. Equipping them with new skills in data, analytics, and statistics can support digital acceleration efforts that may help mend the broken supply chain.

Professionals with a Master’s in Applied Statistics are able to leverage supply chain management statistics to automate outdated processes, track the supply chain, and provide data-driven business insights that improve operational efficiencies. Learn more about how statistics are used to optimize supply chain management and discover if a supply chain career could be right for you.

What is the Current State of Supply Chain Management?

In response to the pressures of the pandemic, burnout, and the collective “Great Resignation” sweeping across the United States, supply chain managers began leaving their jobs. As a result, the number of job openings for supply chain managers more than doubled between January 2020 and March 2022. Supply chain managers directly attributed their burn-out and stress to the use of outdated systems and processes in the supply chain.

Although data is essential to streamline processes, sources say that 60 percent to 70 percent of an analytics employee’s time is spent gathering data whereas only 30 percent to 40 percent is dedicated to analyzing the figures and providing insights.

In other words, the current state of supply chain management relies too heavily on manual, labor-intensive operations while lacking the data, talent, and skills needed to modernize platforms and processes. Therefore, the global supply chain still needs experts in supply chain statistics who can lead in data-driven decision-making.

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