18


Issue 5 2017 - FBJNA


///3PL


3PLs use data to make predictions


By Adina Solomon


For years, third-party logistics companies have collected troves of data. Now, they can put it to use. Big data, which refers to large


sets of information that require advanced software to analyze, is becoming an increasingly significant part of how 3PLs do business. If analyzed properly, big data offers answers to supply chain woes. “Supply chain management


and logistics both in the past have had issues primarily with predictability,” said Biju Kewalram, Agility’s vice


president for operational transformation. “Think of big data as obviously lots of unstructured data that you’ve got to basically try to make sense of and explain patterns.” The questions driving


logistics, such as where is the freight and when will it arrive, are data-related ones. “It’s almost like this question has been there forever, but the technology has never existed to be able to answer it,” Kewalram said. “We’re finally seeing a tipping point where the database technology and


the human awareness are both merging and converging so that we can actually utilize the insights we get from data.” Agility has a tool called


Insight that manages data from their own company and outside sources. One way that 3PLs use big


data is predictive analytics, which studies data to make forecasts about the future. “When you look at what


goes wrong within those businesses, it’s very rare that something new is wrong. The same mistakes happen across our industry every day


“Supply chain management and logistics both in the past have had


issues primarily with predictability.” -- Biju Kewalram, Agility


often they get involved in the supply chain to prevent an unwanted outcome. “It’s very important for


thousands of times,” said Marc Gross, SEKO Logistics’ chief commercial officer. “It’s using big data to try and understand what the actual cause of that is. Once you understand what the causes are, you can either help eradicate the cause or start understanding how you predict that something is going to happen.” Gross called this predictive


failure. For the past decade, logistics companies were judged on their reactive abilities. But going forward, people will look at 3PLs’ proactive abilities and how


3PLs to embrace it, but they also need to understand how they’re going to use it and what they’re actually looking for and that the data itself is clean – that they know the source of it and that it’s validated,” Gross said. “It’s a lot of work to get to that point.” To reach that point, DB


Schenker began hiring dedicated data scientists two years ago. In the past, the 3PL had data scientists focused on an individual product or customer level, but now, the scientists


collect data from


multiple internal and external sources. “That’s the focus change


really, so going from an isolated focus to now a data-linked and expanded focus,” said Richard Ebach,


CIO, DB Schenker


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