Filling the Cloud with High-Quality Data
The millions of dollars spent on supply chain software are squandered if data flowing through it lacks integrity. An attractive, feature-laden application is like a Ferrari—it only runs well when the right fuel flows through the engine. In this case, data is the fuel that powers this impressive vehicle. Without it, only the glitzy exterior remains. After decades of trial and failure, technology has emerged that finally gives companies an efficient, economic way to leverage data across global supply chains—by plugging into a collaborative trading network, hosted in the cloud.
Supply chains can span continents, and trading communities are not always speaking the same IT language. It is more compelling than ever to deal with this complexity by ensuring data is mapped properly, updated instantly across a network, and used to make smart logistical decisions.
Traditionally, setting up partners to receive and send data involves expensive software and electronic data interchange (EDI) networks set up through a long, tedious implementation. An enterprise resource planning (ERP) system must reconcile a variety of standards, formats, and communication channels, while keeping up with an evolving global supply chain. This approach has three major limitations:
- The more partners there are, the harder it is to connect. Traditional software requires dedicating IT resources to build connections. First, IT infrastructure must be built out to create the data "pipes" that connect partners. This involves reaching out to EDI contacts at data providers, and agreeing on a communications protocol and EDI message format. As the number of partners increases, so does the complexity of connecting them. Often, by the time connections are established, the addition of new partners demands another round of implementation.
- "Apples-to-apples" can be difficult to achieve. Companies must standardize data across their trading network if they intend to derive meaningful conclusions from it. Discrepancies such as varied spellings of a particular location, currency, or organization name can skew data and lead to poor supply chain decisions. Again, the more partners involved in a supply chain, the higher the odds of bad data comparison.
- Managing data quality is a full-time commitment. Once connections are built, monitoring them requires a dedicated IT staff—on call 24/7 to respond in the case of data failures. In traditional systems, dedicating these resources is expensive, but necessary to ensure data accuracy, completeness, and timeliness. This key aspect to data quality management is often overlooked, with the intense focus during the implementation phase tapering off once the solution is live. If the next IT project steals the spotlight, data quality begins to decay.
It's Different in the Cloud
The better path to achieving high data quality lies in cloud-based supply chain networks. These collaborative platforms allow for real-time data sharing among companies—something traditional software was never designed to do.
Connecting with trading partners is easier in the cloud. Because data sharing is permission-based, companies retain control over their information while easily bringing any number of partners on board. Adding new connections is simple, and only needs to be done once.
When data resides in the cloud, it is standardized across a single platform, across an industry-wide community of major shippers and service providers. Many companies will find their partners already connected and accessible; if not, the process of mapping data is much more efficient than with traditional ERP systems, because standards and milestones are already established and adopted.
A company connected in the cloud no longer needs to fund a full-time data management roster. The administrators of the network create and maintain all connections. As a bonus, data quality grows exponentially as more partners are plugged in.
The Network Effect
The cost benefits of this model lie in the network's power. Because a cloud-based trading platform has its own dedicated IT staff, all participants share in the cost of maintaining data integrity. Time-to-benefit is reduced, and risk to any single enterprise is cut. Any data-quality improvement made for one member benefits the others, and partners are encouraged by everyone on the network to contribute solid, real-time data. This is the "network effect" -- when the value of the network increases as each new participant joins.
Supply chain software can act as a powerful, well-oiled machine—provided it is powered by high-grade information. Companies must take it upon themselves to invest in technology that will maintain the highest quality standards by moving data to the cloud.