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Edisoft: Leading the Way to More Efficient Trading

Established in 1995 Edisoft is a one of a kind company that specializes in supply chain performance. Headquartered in Toronto, Canada the team at Edisoft is continually striving to improve the efficiency of the trading experience for small and medium sized businesses. Edisoft achieves this through a variety of outlets.

One way in which Edisoft aims to manifest a more streamlined method of trading between small and medium sized companies is through the implementation of supply chain performance. By tracking all aspects of shipping and trading supplies, individual companies are better able to make more informed decisions. Edisoft is known for their high quality work in supply chain performance.

Edisoft executes supply chain performance by looking at a large spread of data considered to be vital when trading between small and medium businesses. Analysis of this data better allows a company to understand where improvements could be administered as part of their business trading process. With this in mind, the field of supply chain performance has made many strides over the years.

Recently, a discussion regarding the appropriate utilization of large sets of data as a way to fine tune supply chain performance has erupted (LinkedIn). As part of the debate, it is suggested that companies begin leveraging big data as a way to more efficiently tweak areas in need of improvement across the supply chain performance. This becomes particularly helpful to companies, large and small when there are multiple trading partners involved in a shipment. While this may occur with domestic shipments, it is most common to see many trading partners in global shipments. As such, when there is an increased number of trading partners present within a single shipment there is an escalated likelihood of greater variance in factors such as the shipment being delivered in a timely manner. Despite the example provided in this article it is important to remember that numerous components are considered when analyzing a supply chain performance.

In conclusion, the use of large data sets provides a more effective method for determining which aspects of shipment between trading partners could be improved.

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