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The Importance of Supply Chain Analytics in the Logistics Industry

Logistics Tech Outlook | Monday, June 20, 2022

Using the correct analytics to make data-driven decisions is the key to developing a successful, customer-centric supply chain while increasing operational efficiency.

FREMONT, CA: The global supply chain issues affected businesses across numerous industries during the COVID-19 Pandemic. Using data analytics to handle supply and demand challenges is one potentially successful method. Countless significant disruptions are now disrupting supply chains. These include the ongoing worldwide logistics disruptions caused by the COVID-19 Pandemic, which continue to impact businesses and consumers as the movement of commodities into critical markets is hampered by the closure of major global ports and airports. Major logistics interruptions produce a rippling effect across global supply chains, causing items to build up in storage.

Convert data into easily actionable insights

Most businesses have massive amounts of data saved in various systems and databases. Additional data sources supplied by extended partners such as outsourcing, logistics, and distribution activities have added complexity to supply chains. Many people struggle to produce valuable insights from this data beyond top-level indicators and descriptive statistics. Data analytics technologies can provide richer, actionable insights while improving accuracy. Ensure that internal and external data are brought together in an organized way; focus the conclusion of data projects on what actions need to be taken to move the performance needle, and ensure that the results are clear to grasp.

Concentrate analytics on places where it can make an impact

Data such as client orders, item information, equipment utilization, and ever-changing transportation costs are inundating supply chain firms. Organizations collect millions of rows of transactional data, allowing for extensive analysis of customer purchasing trends. Using this data to create a robust and analytical algorithm that drives inventory placement throughout the supply chain ensures that products are in the right location at the right time. Businesses should direct their analytical resources toward projecting demand patterns based on product category, sales channel, and geographic location.

To deal with disruptions, use real-time data

As the scale and complexity of global supply chains grow, it becomes exponentially more difficult to oversee and respond to swings throughout the supply chain. With data points changing so quickly, analysis and decision-making are frequently dependent on out-of-date information, exacerbated by the time required to examine the data thoroughly. To successfully navigate this, supply chain managers must create concurrent planning systems that optimize demand and supply by leveraging advanced analytics and real-time insight across the supply chain.

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