Estimated reading time: 2 minutes, 12 seconds

Big Data from EDI Can Make Predictions

Big-data-by-luckey sunEDI is a significant source of big data. Of course that's no shock to anyone dealing with data storage or a VAN bill, but when you consider the volume of transactions and the number or companies involved, it would seem that there is a wealth of data in those transactions. The data now covers (depending on the trading partners) every aspect of the order process, from initial P.O. to final payment, with plenty of status updates along the way. So, what can be learned from all the data? It turns out that when looked at as an aggregate and put through the right analytical processes, there's plenty to be learned - and predicted.


EDI software/service providers/VANs that act as collecting points for EDI data are in a great position to help leverage this data because all the transactions they transfer between trading partners pass through their servers. At some point these transactions are stored on their servers, and some of the providers maintain those transactions for historical purposes. The newest trend that these providers are offering is to leverage those transactions by applying business intelligence techniques to them. What emerges from these advanced calculations takes on many forms, but in general they paint a picture of what has happened, and what is likely to happen in the future.

EDI service providers prove various forms of data collection and analytical tools to their customers. One of the main areas of concern addressed by this and other services is the category referred to as 'order performance.' Companies are increasingly looking for the 'perfect order,' an order that matches the P.O. and the delivery exactly. By looking at the aggregated data, a manufacturer can see how they are doing with their trading partners in terms of delivering the perfect order. They are able to spot trends and identify patterns that may point out difficulties they are having with particular customers, locations, carriers, or products.
 
Being able to use the data created by both the supplier and customer to understand the sales cycle can be a great advantage to both companies who are looking to make the most of their resources in an increasingly competitive environment. The addition of CPFR (Cooperative Planning, Forecasting, and Replenishment) can go a long way to maximizing margins and minimizing mistakes. 

The key word here is 'Cooperative' but the tools that make this process possible, if not easy to implement are already available because of the collection of data that makes up the EDI transactions that till recently, have moved through the supply chain with little analysis.
Read 14652 times
Rate this item
(0 votes)
Scott Koegler

Scott Koegler is Executive Editor for PMG360. He is a technology writer and editor with 20+ years experience delivering high value content to readers and publishers. 

Find his portfolio here and his personal bio here

Visit other PMG Sites:

PMG360 is committed to protecting the privacy of the personal data we collect from our subscribers/agents/customers/exhibitors and sponsors. On May 25th, the European's GDPR policy will be enforced. Nothing is changing about your current settings or how your information is processed, however, we have made a few changes. We have updated our Privacy Policy and Cookie Policy to make it easier for you to understand what information we collect, how and why we collect it.