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What Are the Top Supply Chain Analytics Problems?

Two warehouse managers discussing and wondering What are the top supply chain analytics problems? Today’s businesses rely on data collection and analysis for an edge over their competition. Data analysis plays an important role in realizing the benefits of EDI, as it enables companies to gain a deeper understanding of their supply chain’s dynamics and complexities. Analytics can help improve decision-making, uncover inefficiencies and problems, and identify areas for optimization. However, there are a number of different issues that can adversely affect data analytics. In this blog, we’ll examine the top supply chain and EDI analytics problems as well as the challenges in supply chain management.

Key Issues in Supply Chain Analytics

There are several top problems that can complicate supply chain analytics, including incomplete or inaccurate data, a lack of visibility into EDI transactions, inefficient processes, poor coordination between supply and demand, long lead times, high costs, stockouts and other disruptions. These challenges must be addressed in order to optimize the performance of a company’s supply chain and EDI processes.

A range of analytics tools and supply chain analytics solutions can be used to address these challenges effectively. These can include predictive modeling, forecasting, optimization, data visualization, and simulation. For example, developing predictive models for demand or supply, using optimization techniques to streamline processes and reduce costs, implementing data visualizations to gain a clear picture of the entire supply chain, and simulating different scenarios to test various response plans. There are so many use cases for deploying a comprehensive EDI dashboard, between the pharma company who realized a 300% ROI based on the manual time it took their client services team to resolve customer order to cash issues to the ubiquitous food conglomerate that leveraged the Exceptions and Notifications feature to understand when ASNs are not delivered by the Expected Ship Date to either expedite shipments or divert supply from other parts of their network to keep product on the shelf.

Ultimately, the goal is to use data-driven insights to make more informed decisions about how to manage and improve the performance of the supply chain.

Problems and Challenges in Supply Chain Management

Supply chain management is a complex and dynamic process, involving many players, activities, and factors that must be coordinated in order to achieve optimal performance. However, the following factors pose challenges to effective management.

Globalization

One of the major challenges in supply chain management is dealing with the effects of globalization, which makes it difficult to coordinate supply and demand across different regions or countries. 

Data analytics tools and techniques are often used to help address this by incorporating real-time data from different sources and using advanced analytics methods like predictive modeling and simulation to more accurately forecast demand, optimize processes and resource allocation, mitigate supply risks, and respond to disruptions. 

Additionally, by leveraging big data technologies such as cloud computing, machine learning, and the Internet of Things (IoT), it is possible to gain much greater visibility into the end-to-end supply chain, which can help further improve coordination and decision-making.

Fast-changing Markets

Staying current with fast-changing markets and trends is also a key challenge in supply chain management. This can be particularly difficult due to the high levels of uncertainty that are often present in these environments, as well as the many moving parts and stakeholders involved in managing a supply chain. To effectively address this challenge, it is important to have robust analytical tools and techniques in place, as well as an understanding of how to interpret the data that these tools generate.

Maintaining ongoing communication and collaboration among all supply chain stakeholders can also help to ensure decisions are being made based on the most current information available. 

Quality and Compliance

Quality and compliance are often major challenges in supply chain management, as they can affect every aspect of a company’s operations, from production to distribution and beyond. Issues related to quality and compliance can arise due to poor product design or manufacturing processes, regulatory requirements that are not properly understood or followed, lack of oversight and accountability, or many other factors.

The effective use of data analytics tools can help organizations gain visibility into quality and compliance issues in their supply chains. These tools, such as vendor scorecards and order lifecycle reconciliation, can also help identify where areas need improvement. This ultimately helps companies achieve better overall performance, reduce costs, minimize risks, and improve customer satisfaction. One large Fortune 50 retailer reports, “Never before have we been able to implement a successful ASN Compliance Program.”

Major Risks Supply Chain Leaders Face

There are several risks that supply chain leaders face, including the risk of disruptions to the supply chain, the risk of poor coordination between different parts of the supply chain, suppliers going out of business, high costs, and the continued impacts of the COVID-19 pandemic. 

These risks can have a major impact on a company’s bottom line, and it is important for supply chain leaders to have a plan in place to mitigate these risks.

One way to do this is to use analytics to improve decision-making and reduce the likelihood of these risks occurring. Another way to mitigate these risks is to have contingency plans in place so that if one part of the supply chain is disrupted, the rest of the supply chain can continue to operate smoothly. Additionally, it is important for supply chain leaders to stay up to date on industry trends and best practices in order to effectively mitigate these risks and maintain an optimal supply chain performance. 

Key Takeaways

While supply chain challenges will always exist, analytics can help identify and mitigate many of the risks associated with them. By improving risk management practices and making better-informed decisions, supply chain leaders can improve their bottom line and ensure that their business functions as efficiently as possible. As you’re thinking through what the top problems for your supply chain analytics may be, you need a partner who truly understands data. Contact us today to speak to an expert. 

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