share their thoughts and knowledge on the changing container freight and supply chain industry.
What is “Big Data in shipping?”
First, it's important to recognize the difference between 'lots of data' and 'big data.' Traditional technology has been serving organizations’ analytics needs for decades, allowing them to analyze large data sets from traditional sources such as warehousing and distribution systems. ‘Big data’ takes it to the next level, allowing companies to harness extremely large data volumes including non-traditional data types such as text, audio and video in conjunction with information from business systems in a much more economical fashion, in both batch and in real time modes. While the sheer volume of data available to a company today is daunting, the first step in leveraging 'big data' is deciding on the problem you want solved, or the issues you need addressed, and then finding the proper data necessary. It's more than just 'look-back information', of say how many TEUs you shipped in May from Shanghai to Rotterdam, but rather pulling the data necessary to ship them cheaper, faster, or to achieve whatever metric you need addressed.
This is just an expensive IT solution then?
No – it's not about IT at all; remember the term “Garbage In = Garbage Out? That's too-much data, not Big Data. A company needs to determine what they want to do...reduce costs? Increase revenue? Optimize transit times? These are all serious strategic issues for both a carrier and a shipper, whose implementation – or not – affects profitability on every voyage. The carrier needs to sit with a company like ours in order to figure out the questions that need to be asked in order affect positive outcomes, and determine what is the traditional and non-traditional data that goes into profitability.
What's traditional data vs. non-traditional data?
Traditional data is look-back data from ordinary business systems; fuel costs, transit times, wages, insurance, revenue per TEU. It's accounting data that's used to determine the profitability of a voyage. But non-traditional data is time-sensitive data – weather and traffic delays, port strikes, unexpected repairs. It’s also extremely large volumes of data being generated from sensors, GPS devices, RFID tags and traffic management systems. If Big Data can assist in helping forecast or avoid problems, the money saved goes straight to profitability.
And non-traditional data is quantifiable?
Some is, some isn't, but it's all related to issues that can be resolved or avoided. If a storm blows up, would you steam through it? Perhaps not, but you’d use a ‘big data’ solution to analyze GPS-type information to quickly determine the costs of other routes as opposed to not diverting. Or a 3PL might get a message from his GPS about a highway being closed, so instead of having the truck idling in traffic burning fuel and time; the driver would be re-routed. Preventive technology is a lifesaver for most forms of transportation from a container ship to a delivery truck; modern sensor technology enables the carrier to be warned of failures before they occur, which allows management to affect repairs prior and on a timely basis, instead of being stuck in port on demurrage or being towed off the motorway. Sensor information can be leveraged to predict a failure rather than waiting for it to occur.
This sort of information would be equally important for the shipper?
Absolutely; whether you’re shipping the goods as a vendor, or receiving them as the buyer; getting them to the final destination on time, undamaged, and in a cost-effective manner is important. Whether the data comes from the carrier, or is transmitted via RFID; it's data the shipper can use to quantify his shipping metrics and work on improvement.
Is big data alone all you need to make your logistics procurement business successful?
At Xeneta, we have the industry business and technical expertise needed to make sense of the ‘big data’ our platform aggregates and presents. We'll work with our customers to articulate and advise on their strategic direction and answer business-critical questions based on the facts we see coming from the data we hold: What problems are you trying to resolve? What direction do you want to go? What data do you need brought forward? While we’re IT people; we're business people first.
Is there a place for Big Data in Supply Chain Management?
Absolutely; in fact it's what makes advanced SCM possible. It's using Big Data to start replacement inventory moving before inventory is exhausted; it's taking look-back vendor reliability data and instead of just disqualifying those who missed shipments, rewarding those with good reliability as well as others who stepped up to cover for those vendors who failed. It’s bringing information together from multiple sources to make predictions and real-time decisions to keep the logistics pipeline flowing. Remember, Big Data is used to quantify what you, the customer, has determined is important to your business.
Final thoughts on the use of Big Data for shippers and carriers
It's important to remember that Big Data is used in assisting your company in achieving it's business objectives, whether reducing costs or improving efficiency, which is of obvious daily importance to carriers and shippers, or increasing sales, which is of interest to everyone. When properly used, Big Data will enable management to take a gut-feel decisions and quantify it, which lets them take that good idea and make it work.