Big data and LTL analysis create business opportunities

Embracing new and sometimes unfamiliar technology is a requirement in today’s business environment. There is where the problems – and the opportunities – arise. Technology has reduced much of the simple, mundane and manual activities to efficient processes that are both quick and accurate. Technological disruptors are shaking up the supply chain, but also offer opportunity for those who can exploit these new tools.

Many supply chain stakeholders have LTL analysis systems in place that increase the speed, accuracy and reporting of day-to-day transactions, reducing cost while providing excellent customer service. Large companies likely still have legacy systems that have been in place for years and have been supplemented by updates and patches. New technologies have come on board that legacy systems never anticipated.

It is easy to see that data technology is often singular in its purpose. Operations, vehicle diagnostics, scheduled vehicle maintenance, revenue accounting, human resources, payroll and benefits have their functions and resultant databases. This is the foundation of data silos; the data exist and fulfill an intended purpose but are not mined or utilized in conjunction with other data within the organization. As technology expands, the amount of information captured and maintained expands exponentially.

Rising alongside the concept of big data (Forbes just declared “space data” the new big data) is the job title of data scientist. This role combines the business and data analyst function and moves it to a broadened level of focus. Many of the traits of the analyst are needed; their formal training encompasses a solid foundation in computer science with emphasis in transportation analysis, math, modeling and statistics. While the data scientist must have commanding expertise in the field of analytics, his or her true value is the ability to communicate astute business findings to company leadership. Once a problem is identified and corrected, proper follow up will close the informational loop and quantify its ultimate success or failure.

From a corporate standpoint, this approach is a major change in mindset. The data scientist will utilize the data and LTL analysis from multiple internal sources, spanning many areas of executive responsibility while questioning existing assumptions and processes. The goal is to find trends, previously hidden relationships and redundant processes; the data scientist works to improve awareness of the company’s activities with an eye towards problem solving. These activities, coupled with providing “what if” analysis, will create completive advantages in the marketplace.

SMC³ utilizes the expertise of data scientists in every product released through the SMC³ Platform. To learn more about the company, watch a profile of SMC³ shown during an episode of “Innovations with Ed Begley, Jr.”

Categories: Data, Technology
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