Understanding the 5 Vs of big data is an essential aspect of supply chain management. But which elements are really driving value? In today’s competitive landscape, comprehensive data integration drives value. For a supply chain that outperforms your competition, you need lower costs, less risk of disruption, and better customer service.

Improving performance requires companies to have accurate data. To leverage the data, you’ll need a method to collect, analyze, and a process or tool to take action. Plus, you’ll need to store and integrate all your data to gain a complete picture of your supply chain.

To help, we’ve defined the Five Vs of supply chain big data below to explain how leveraging these concepts will power your competitive edge in supply chain management.

The Five Vs of Supply Chain Big Data

Volume

Volume is the amount of data that represents all aspects of your supply chain. But it doesn’t require a sophisticated supply chain to generate millions of data points and records. How are you going to store volumes of detailed freight data? For example, this includes TMS data, ERP/WMS order-  and item-level data, tracking data, and freight invoice data. You have a mountain of data to sift through, and need to collect all of it easily.

Variety

Variety refers to the types of data and is what makes data relevant. It is the combination of critical components from various data sources and specific attributes across different modes of freight. Capturing each package, their weights and dimensions for a small parcel shipment, is very different than capturing the total miles and cost of a truckload shipment.

Integrating this data with order- and item-level data to provide the proper context around your freight spend requires a system that understands all modes of transportation. When extended to display on an order or item level for better context, this information is powerful.

Velocity

Velocity refers to the speed of data. Capturing all of this data in real-time, and providing instant analytics with Key Performance Indicators (KPI’s) built to measure the health of the supply chain exemplifies the Velocity component. For example, a quick alert to a disruption or exception helps you implement a solution and lower your costs. As the Supply Chain Shaman says, data should flow at the speed of business.

Veracity

This V speaks to data quality and has two elements: conformity and accuracy. Veracity is how data is standardized. This allows you to process the data and make the right decisions. We talk with many companies that have tons of data but no useful information, commonly due to non-integrated data. You’ll need a method to integrate the data from disparate sources and formats. Then, you’ll need a way to cleanse the data to make it usable. These two mechanisms ensure your data accurately represents the health of your supply chain.

Value

The value of the data extracted is the most important, yet the most elusive, of the 5 Vs. Challenges with achieving value usually start with veracity. Data that is on-integrated is uncleansed and leads to misinformation. But data can be incomplete, late, or irrelevant.

Many companies may have captured volumes of a variety of data at velocity, but have a hard time extracting actionable intelligence. A recent study from Supply Chain Quarterly confirmed this is why many companies were dissatisfied with their results.

To extract real value from your supply chain big data, you need a strategy built on accurate data that integrates from and into your other systems. Integration prevents information from getting lost in translation from one separate supply chain system to another. When it works together, more value can be found in big data.