Big Data gets Big in Logistics
Business is producing data – a lot of data. Many smart companies like Google, Facebook and Amazon thrive on it. However "Big Data" and "Business Intelligence" are not only important for IT-driven companies. Every company can profit from useful information and the knowledge that is gained from it. The subject is now naturally picked up by the logistics sector. Big Data was highlighted by a panel of specialists at the 31. Deutsche Logistik-Konferenz of BVL in Berlin and the logistics magazine DVZ regularly publishes articles on the matter. Big Data is largely coined as a buzz word for compiling the mass of information you have at your disposal. Be it logistics-, financial- or marketing-related, everything hides real monetary or efficiency-raising value. Or not…
It is true that activities of the transport sector generate a lot of information most of which could be used to optimize business – when analysed correctly. Transport time (and time loss), distance and fuel consumption are just a few of the relevant figures. Getting a real grip on your activities can have many benefits. You may identify inefficient processes, overlooked problems or missed out business opportunities. It can also help you regain control of every single step of your supply chain and strengthen the bond with your clients.
During the BVL-conference in Berlin, the actors issued several warnings against following the trend without proper preparation. The software for this kind of analysis evolved a lot in the last years - even real-time survey is possible- but managers shouldn’t just take all available data, compile it through dedicated software, and hope for a useful result. Before starting you need to ask the right questions. What do I want to achieve with this data analysis? What data should I use and which information can I discard?
Settle down your data
A lot of effort is usually wasted in data-gathering. This can go on indefinitely and should be under control or else you will never start analysing. “When you avoid useless information right at the beginning you win a lot of time”, says Dr Jozo Acksteiner, Manager Strategy & Analytics for Hewlett-Packard in Singapur. He is responsible for streamlining the support supply chain for HP. Too much information kills information and less is more. Therefore a classical logic-driven approach can narrow down the scope to a manageable level before starting the actual process.
The methodology is very important. Compiled wrong your data set might produce incomprehensible results, basically just wasting your time, or, even worse, spit out incorrect correlation which could lead to wrong decisions. Correct data analysis however can enhance profitability, highlight inefficiencies and streamline your production. Vlisco, for example, a fabric producer for the African market, was able to increase production efficiency by four in a decade. The correlation highlighted inefficiencies in production and supply chain that couldn't be grasped with classical data collection.
However this massive compilation of data can also be a risk for your company as it can attract hackers, warns Holger Junker, a specialist from the German Cybersecurity Office BSI. Often skilled and less-skilled hackers intrude servers with ease because security is neglected. This affects not only IT-providers but industrial companies as well. On a daily basis, companies are attacked by malicious hackers in order to gain any kind of data or disrupt production. The information can be sold to the competition or published; the harm done to the companies is real and can be costly. Therefore a constant effort should be put on security.
Big Data is only at its beginnings but it has created a strong buzz already. Knowing what you want out of this data is the key in order to derive useful information out of it. The specialist Prof. Dr. Jens Dittrich, Professor for Databanks of the Universitat des Saarlandes, CISPA, knows that if you simply jumble everything together, all you get is a mess.
