June-July - 2018 9logisticstechoutlook.comof all their systems to ensure that data has common keys or attributes that allow this information to be mined in a meaningful manner. This may occur not just within the WMS (warehouse management system) or TMS (transportation management system), but also may include information from systems such as appointment scheduling, invoicing, pricing, and time reporting.From these systems, a wealth of information can be garnered about past performance and how it might impact future growth or behaviors, including opportunities for continual improvement efforts. Real world applications for this data already exist in the 3PL world now. With the data connectivity, there are opportunities for 3PL providers to help customers determine the best locations for future warehouses based on delivery times, along with transportation and labor rates. Other areas of application include determining short-term logistical needs based on natural disaster and emergency relief areas. These data modeling scenarios require a large amount of data with an array of information from transportation rates to hourly labor rates. However, this will only be successful if the data is meaningful.Meaningful data can only be achieved by the 3PL through examination of data quality or with data governance efforts already in place and enforced. For example, incorrect or partially filled out address information on orders may lead to incorrect mappings of orders on a heat map, which in turn could skew projecting future sales or growth for that area. Data governance should account for uniqueness, consistency, accuracy, timeliness, and completeness of that data to ensure that all aspects are addressed when considering data quality. In addition, significant effort must be made when modeling the data from various systems to ensure the integrity of the data or referential integrity is in place.Increased opportunities exist today for 3PL providers to mine the "Big Data" they are receiving from their customers. The days of providing basic metrics on performance are gone. 3PL's must have the right tools and processes in place, along with a data governance strategy in order to utilize this data effectively. They must look beyond the WMS and TMS systems to evaluate and connect systems that are likely cloud-based or on-premise. Customers are beginning to expect this "Big Data" mining and reporting from their providers, not as added value, but as a standard requirement. Increasing focus on efficiencies and predictability allows for data analytics to become the feature within the 3PL space of the future. Now is the time for 3PL providers to ensure they are harnessing all the data available at their fingertips so that they can provide exceptional service to their customers. Joe Johnson
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