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, value is driven by comprehensive data integration. To have a supply chain that outperforms your competition, you need lower costs, less risk of disruption, and better customer service.

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

To help you with these, we’ve defined the Five Vs of supply chain big data below to clearly 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. 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? 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. A system is more powerful when this information is extended to display this information on an order or item level for better context.

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 of supply chain big data. Quickly, you are alerted to a disruption or exception, so you can implement a solution and lower your costs. As the Supply Chain Shaman says, data should flow at the speed of business.

Veracity

Veracity speaks to data quality and has two elements: conformity and accuracy. This V speaks to how the data is standardized, enabling 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. The non-integrated data is uncleansed and leads to misinformation. 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 on big data analytics from Supply Chain Quarterly confirmed this is why many companies were dissatisfied their results.

To extract real value from your supply chain big data, you’ll need a strategy built on accurate data that is easily integrated from and into your other systems. Integration prevents information from getting lost in translation from one separate supply chain system to another. More value is extracted from big data when it works together.

Please send us an email to discuss how big data can drive value through your supply chain.