Shipping Analytics Challenges and How to Overcome Them

Shipping Analytics Challenges and How to Overcome Them

Advancements within shipping analytics platforms, including artificial intelligence, parcel and freight analytics, data management, and machine learning, are reshaping the supply chain. According to Industry Week, “The supply chain is a great place to use analytic tools to look for a competitive advantage, because of its complexity and also because of the prominent role supply chain plays in a company’s cost structure and profitability. Supply chains can appear simple compared to other parts of a business, even though they are not. If we keep an open mind, we can always do better by digging deeper into data as well as by thinking about a predictive instead of reactive view of the data.”  The promised results from advancements within shipping analytics are still subject to significant challenges. And those challenges are not necessarily problems within the capabilities of analytics and business intelligence. Instead, these challenges trackback to issues within the supply chain and are amplified during peak season. Regardless, challenges remain harbingers of potential disruption throughout the year, and freight managers need to know what they are and how to overcome them.

1. Disparate Systems Limit the Scope of Actionability and Impact

A leading shipping analytics challenge rests within disparate systems. Remember those disparate systems lack connectivity and remain disjointed, making it more difficult to capture and normalize data coming from various systems. As a result, it becomes more challenging to gain meaningful insight as you are unable to collect all data and get accurate actionable insights. 

What to do about it: companies need to connect their supply chain tech stack to an overarching analytics platform that collects, cleanses, normalizes, and analyzes the data. 

2. Visibility Challenges Continue to Undermine the Value of Actionable Insights

Disparate systems lead to the next business intelligence weakness: lack of visibility. Everyone wants increased visibility. The first step in having an effective freight business intelligence platform is to gain visibility into all data. Many data flows into various systems simply stay in those systems, not collected or used. Supply chain managers and freight professionals need to capture the data and bring it into one platform to view the data in its entirety.

What to do about it: companies need to leverage collection of data through file parsing, EDI, modern APIs and other web hooks to aggregate data into the analytics platform.

3. Limited Connectivity Between Analytics Platforms and Management Resources Contribute to Outdated Insights

Speaking about outdated visibility, that is the next shipping analytics weakness. As data ages, it begins to lose value. Making decisions on obsolete data could be more devastating than merely operating at the status quo.

What to do about it: connect all existing systems within the supply chain’s tech stack via EDI, API, or some other integration method to gain the most effective and comprehensive insights in near to real time.

4. Trouble Getting Data from Partners

Another problem exists when companies limit their view of data. Think about it. The supply chain is a network, and it relies on working parts across multiple companies. If an organization limits its view of data to only the operations and processes occurring within the individually owned facilities and assets, they miss a larger share of the picture. 

What to do about it: supply chains need to connect with systems outside their own walls, bringing in outside data, such as market or economic data via many methods including EDI, API, or via files. 

5. An Inability to Execute on Insights Reduces the Ability Manage by Exception

When a company lacks the end-to-end supply chain critical to making break-neck decisions that drive the most desired results, they fall into the trap of traditional management. What is traditional management? Traditional management is comparable to micromanaging every aspect of freight management. Yes, that is a slightly confusing explanation. However, it is the truth. With advancements in freight technology, managers should be able to manage by exception. In other words, redundancy should occur at the execution level and only require intervention when a problem cannot be rectified through a digital, clear, and concise process.

What to do about it: managers need to have clear direction on the next steps and actions to take based on shipping analytics. 

Recognize the Common Denominator—Actionability and Connectivity of Shipping Analytics in the Supply Chain—to Thrive

The commonality among these challenges is a lack of flexibility and sub-par autonomous logistics that manage data-driven insights. It’s that simple. The best way to overcome it is to advance the business intelligence resources through a connected, optimized, and continuously growing platform, such as Intelligent Audit. Remember that peak season shipping is now the standard and will remain that way for the foreseeable future. Visit Intelligent Audit online today to learn more about how your company can put the power of business intelligence to work.

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