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  • The Owl Solutions

How Data Analytics Can Improve Your Supply Chain

Updated: Oct 16

Why Data Analytics is Important

Data analytics is the process of examining and analyzing large sets of data to uncover insights and trends. They can help supply chains improve end-to-end supply chain visibility, reduce costs and mitigate risks. It can help users spot challenges in their supply chain early, leaving them with more time to find a solution or pivot. Here are a few examples of where data analytics can help improve supply chains:

  • Forecasting Demand: by analyzing customer orders from the past, forecasts that were made in the past and forecasts based on statistical trends as The Owl does in our demand forecasting module, companies can better plan for inventory levels and avoid stockouts or overstocking which can result in an increased bottom line or unhappy customers.

  • Tracking Inventory: Data analytics can help companies better track inventory levels and identify potential bottlenecks in the supply chain, allowing them to adjust operations as needed to avoid stockouts or waste.

  • Improved supplier performance: by analyzing data on supplier performance, companies can identify areas for improvement and negotiate better terms with their suppliers. The Owl also launched a suppliers portal where both manufacturers and suppliers can collaborate through open communication online – making it easier to track performance, collaborate and align on expectations and business outcomes.

  • Identifying cost savings opportunities: by analyzing data on costs throughout the supply chain, companies can identify opportunities to reduce expenses and improve margins.

Overall, data analytics can help supply chains become more efficient, responsive, and profitable. By leveraging data to make better decisions, companies can gain a competitive advantage in the marketplace and better meet the needs of customers.

When Data Analytics is Used

Companies may start considering the use of data analytics in their supply chain at different stages of their development, depending on their industry, size, and level of digitalization. Here are some common scenarios where companies might start to consider using data analytics in their supply chain:

  1. Rapid growth: Companies that are experiencing rapid growth may struggle to keep up with demand and manage their supply chain effectively. By using data analytics, these companies can gain greater visibility into their supply chain operations, identify bottlenecks and inefficiencies, and make data-driven decisions to optimize their supply chain.

  2. Competition: In highly competitive industries, companies may turn to data analytics to gain a competitive edge. By analyzing data on their supply chain operations, companies can identify opportunities to reduce costs, improve efficiency, and enhance customer satisfaction, which can help them stand out from their competitors.

  3. Increasing complexity: As supply chains become more complex, companies may need to turn to data analytics to manage the growing amount of data and gain insights into their operations. With data analytics, companies can gain a holistic view of their supply chain, from supplier performance to logistics and transportation, and identify areas for improvement.

  4. Regulatory Compliance: In industries with strict regulatory requirements, companies may need to use data analytics to ensure compliance with regulations. For example, in the food industry, companies may need to track and trace products from farm to table to ensure food safety. By using data analytics, companies can ensure compliance with regulations, reduce the risk of recalls, and enhance customer trust.

  5. Digital Transformation: As companies undergo digital transformation initiatives, they may start to consider using data analytics to optimize their supply chain operations. By integrating data analytics into their supply chain management systems, companies can gain real-time visibility into their operations, make data-driven decisions, and improve their overall efficiency and effectiveness.

In summary, there are several scenarios where companies may start considering the use of data analytics in their supply chain. Whether it's due to rapid growth, competition, increasing complexity, regulatory compliance, or digital transformation, data analytics can help companies gain greater visibility into their operations, optimize their supply chain, and enhance their overall performance and reduce costs.

At The Owl, we help manufacturing companies and distributors get the most out of their supply chain with our supply chain performance platform. Our team leverages data, insights and actions to track and align key supply chain KPIs with projected business outcomes.

The Owl is a platform made by supply chain professionals, for supply chain professionals - so you know that we know our stuff! To see how our solution works, click the link below.

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