Key to managing data requires dedicated system in supply chain

By: | at 08:00 PM | Logistics  

Focus on contextual data presentation must have coordinated purpose in mind

Simon Clark, Business Development Manager - Europe, Middle East & Africa for CargoWise’ edi, a leading provider of integrated international supply chain logistics management systems, says that while IT systems today provide extensive data, or raw facts, many businesses are missing out on critical operating and financial opportunities because they try to manage data with multiple software systems that are unable to provide useful, knowledge-based information.

“The global supply chain environment today is a very competitive market where knowledge is power,” says Clark, “and knowledge is based on information that is relevant to a given situation. Despite the surplus of data that is readily available throughout the freight forwarding industry today, many companies fail to properly convert the data into information that can be used to improve operating efficiencies. Too often this occurs because discordant data is gathered from many different sources and software systems and is largely useless as it is not compiled in a universal fashion with a thoughtful purpose in mind.”

Clark points out that the Oxford Dictionary defines information as “knowledge gained through study.” He reminds us that individual bits of information, by themselves, are useless without context. For instance, he says that awareness of shipment status such as dates and times is commendable data; but only when put into a context does it help provide a relevant knowledge-based decision making process. Another example is looking for the gross margin on a job. Data could reveal a gross margin figure of 10%; but without perspective, this is just unrelated data. Knowing that you have established a target gross margin of seven% for your business, however, provides the necessary point of view to recognize that particular job is indeed profitable.

“The historic use of data processing systems tried admirably to assist in establishing this context,” says Clark, “but as technological evolution took place, data processing gave way to information systems, which focus on presenting the data without an explicit purpose in mind. Many businesses today still operate on these data processing style systems and do not possess the ability to convert the data in their database into useful information. Further, this data is often presented by multiple, disparate reporting systems and presented to the wrong people in the wrong format, at the wrong time. The result, far too often, is data mis-management and decision-making chaos.”

To avoid data disaster, Clark suggests the solution to properly managing data lies in having one central enterprise system capable of presenting all pertinent facts in a consistent and cohesive format throughout the organization. “Having all the shipment data in a central software system is the answer,” he says. “Only with a common, central software application and database can various bits of data be disseminated as useful and purpose-driven, and fully used by all appropriate personnel in a completely comprehensive manner that reflects a companywide rationale for analyzing data.”

Clark emphasizes that each department within a company has its own use for the data collected, but without a common purpose, raw facts can be fragmented and not easily converted to relevant information used for decision making.

“For operators this data might be the balance on an account; but the truly useful information is the balance on the account, along with a periodic analysis and update of data, with information about credit issues and collection calls, disputes and reasons,” he says. “Only when all of that information is considered together can the operators make qualified decisions.

“Managers require a broader scope of studied information, or knowledge, for decision making. A CRM process may provide individual analysis on pipeline status, field sales activity and trade lanes; but unless all of this unrelated data is culled together from a central data repositor


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