During the pandemic, supply chains became very unhealthy, but problems often result in rapid development and adoption of solutions. Those plagued supply chains brought new approaches to resilience and efficiency development, and shippers realized they needed to take greater control rather than be at their supply chains' whims.

Chief Supply Chain Officers (CSCOs) have realized the answer is technology, with 40% planning to implement data solutions to enable real-time supply chain data exchange by 2025. They’ve dedicated themselves to being at the forefront of developing supply chain resilience.

Cutting-edge data strategies are fast becoming the norm in the transportation industry, making it time to take a closer look at the data revolution.

What is Supply Chain Data?

The pre-data supply chain left shippers in the dark. A lack of visibility had them calling supply chain partners, responding too late to exceptions, and needing to reach out to stakeholders to relay information. There was poor communication and an inability to respond promptly.

Without data, shippers didn’t have the information needed to improve their future operations. There was no ability to create accurate carrier scorecards or know how well they met their KPIs.

The Definition of Supply Chain Data

Supply chain data is the data collected throughout each step of the supply chain process. When properly compiled, it provides the insights needed for decision-making, optimization, and collaboration across the entire ecosystem.

Overview of the Different Types of Supply Chain Data Analytics

Supply chains generate massive amounts of data. Just imagine how many milestones could happen for just a single shipment.

Supply chain analytics break the data down to make sense, allowing the shipper to gain new insights and discover once-hidden patterns.

The main types of supply chain analytics are:

• Descriptive analytics: Visibility and a supply chain single source of truth are the results of descriptive analytics.
• Predictive analytics: When a shipper needs to predict the most likely outcomes or model future scenarios and their implications, they use predictive analytics. This form of analytics learns from the past to help make predictions and mitigate risks and exceptions.
• Prescriptive analytics: Prescriptive analytics is all about problem-solving and collaboration. Improving collaboration with supply chain partners tremendously reduces the effort and time typically expended to minimize disruptions.
• Cognitive analytics: Complex questions are never resolved if answered in complex ways, and cognitive analytics put the resolution into simple and natural language. Companies are empowered to take a complex issue and think through it in easy terms, making its resolution easier.

Three Ways Supply Chain Data is Revolutionizing the Transportation Industry

Using the different types of analytics in concert, shippers are simplifying their models and taking control back from the high variability of the supply chain.

Improved Visibility Leads to Unprecedented Collaboration

Many issues and variations plagued the supply chain during the pandemic, often leaving shippers and their partners flying blind. When a shipper could discover the problem and got an updated ETA, they had to contact supply chain stakeholders and communicate what was happening.

Visibility, the ability to know where the cargo is in its journey, what is happening with it, and have an ETA, has changed the game. Shippers and their partners can access instant, real-time data as needed. The time and effort spent finding the necessary information and then communicating it is now spent on value add activities.

Efficiency from the Ground-Up

Efficient supply chains are essential to meeting the needs of demanding customers, and shippers cannot realize that efficiency without knowing how well they meet their KPIs. 

When supply chains are efficient, they save shippers money on operational spend and get goods where they need to be on time. Furthermore, they promote sustainability by enabling multimodal transportation, reducing deadhead miles, and eliminating other forms of waste.

When shippers are empowered to see real-time happenings, minimize needless communication, and use analytics to improve operations, they develop supply chain resiliency. 

Never before has supply chain efficiency been more critical.

A Proactive Approach for Resilient Supply Chains

The ever-expanding onslaught of challenges has left the global supply chain needing to shift from a reactive approach and the constant need to play catch up to a proactive approach. People need the ability to think ahead, which results from data-driven operations.

Big data analytics in supply chain management tell supply chain professionals what to look for, how to overcome potential challenges, and ensures they get the maximum value from their analytics. Using data from the past, shippers are prepared for the future and cultivate supply chain resilience.

Due to these key and now essential advantages, supply chain professionals are turning to tech-enabled solutions to take supply control.

What are the Key Features of Supply Chain Data Management Software?

Supply chain management software is no longer an option for shippers. In fact, the market is growing tremendously, with a CAGR of 10.9% to an expected value of $75.6 billion by 2032.

This boom in supply chain management has cultivated more options than ever for reliable data partners. Knowing what to look for, supply chain professionals can ensure they get the optimal impact from their supply chain data.

Scalable Integration

A software solution must be able to seamlessly scale, integrate, and aggregate data from various sources within the supply chain, including suppliers, manufacturers, logistics providers, and customers. With this capability, the data management system grows alongside businesses instead of constraining that growth.

The solution needs to integrate with enterprise resource planning (ERP) systems, transportation management systems (TMS), and warehouse management systems (WMS) to ensure smooth data flow across the supply chain ecosystem.

Real-Time Tracking Throughout Operations

Real-time visibility into supply chain activities is crucial to effective management solutions, allowing stakeholders to track shipments, monitor inventory levels, and access the needed up-to-date information on order statuses and delivery times.

Actionable Analytics and Reporting

The software must offer robust analytics capabilities, enabling users to analyze supply chain data, identify patterns, forecast trends, and see their performance metrics. For truly data-driven decision-making, customizable reporting features need to be present.

Without these data options, developing and monitoring accurate KPIs isn’t possible. Without knowing the company’s KPIs, constant improvement opportunities are missed.

For Unparalleled Supply Chain Data, The Transportation Industry Chooses VIZION API

There is no doubt that supply chain data will continue its meteoric growth to meet the needs of supply chain professionals in a demanding environment. 

The pandemic showed how easily supply chains break down, resulting in extreme variability. Professionals that take control of their supply chains with data build resiliency and position themselves to move into the future. They leverage descriptive, predictive, prescriptive, and cognitive data to save money, meet customer needs, see their KPIs, and communicate efficiently.

Efficient supply chains result from quality data.

VIZION API seamlessly integrates with a shipper’s existing tech stack, providing them with true end-to-end real-time visibility and robust analytics. Shippers gain access to intermodal transportation options with tracking across all modes, even rail.

Book a demo with VIZION API today to see how to revolutionize your supply chain.

‍