No sooner ordered than delivered
Bought yesterday, delivered tomorrow – it wasn’t so long ago that online retailers were able to set themselves apart from the competition by delivering orders within 48 hours. Yet ever since next-day delivery has been the phrase on everyone’s lips and the first sellers have even begun delivering goods on the same day, extremely fast delivery times are not only normal for many customers, but also explicitly required.
Delivery times used to be subject to natural limits that could only be pushed with a great deal of technical complexity. Besides establishing an extensive network of decentralized warehouses and expanding the transport fleet, forward-looking logistics also represents a key approach to optimization.
The development of forward-looking logistics is once again being driven by the e-commerce pioneer Amazon. This is hardly surprising since the company is able to draw on an infinite wealth of data. That’s because every product viewed, every page visited, and every click on one of the Amazon websites is registered. And it is precisely this information that provides the fodder for the algorithms that educe the probability that a prospective customer may turn into a buyer from the longer length of time they spend browsing a product or repeatedly viewing a particular page. The analysis method is constantly learning from the newly acquired data, allowing it to continuously increase the precision of its predictions. As such, given a certain level of precision it makes perfect sense for Amazon to prioritize downstream logistical processes such as retrieval, order picking, and preparation for shipping. If the customer ultimately clicks on the “Buy” button, then the package is already ready and only needs to be given an address label before it is sent on its way.
Yet the technology – for which Amazon has applied for a patent – goes one step further, because it moves away from the individual buyer and further concentrates on entire customer groups with the help of the probability calculations. As such, assumptions are made about the buying habits of entire regions. One example could perhaps be a sporting event in a city. Work would begin on preparing the shirts of the teams involved for shipping in a nearby warehouse one week beforehand. Address labels featuring the recipient’s city or zip code area would be attached to the packages. The item would then be transported there and possibly held in the truck or a local buffer storage location until the forecast orders are actually received. All that follows is the completion of the shipping label. Then the truck hits the road and delivers the required shirt shortly after the order is received.
Forward-looking storage logistics
Whether the items are stored in a central warehouse or a local buffer storage location, a smooth order picking process is essential for fast shipping. Highly efficient logistics solutions are needed here, because the time gained should not be wasted due to delayed retrieval. And this is precisely where smaller online retailers have the opportunity to go up against the giant from Seattle in terms of speed.
Here, too, the process is managed in a forward-looking way. For example, the control software allocates follow-up orders using the work schedules assigned to the transport systems or order pickers if they are near to the storage location of another item that has to be picked. Attached position indicators such as RFID chips or GPS devices could serve as further selection criteria. The self-driving robots anticipate the control process by communicating with one another autonomously and deciding among themselves which module is in the best position to fetch the item based on their current location or planned route.
Ultimately, whether software-controlled or autonomous, forward-looking planning helps to efficiently coordinate routes in the warehouse. Where not so long ago items were still stored on conventional shelving, from where they were manually retrieved and transported across long distances for shipping or production, in many companies storage processes now take place fully automatically and in parallel.
Compact storage units with high retrieval performance that can be positioned close to the picking stations are needed for this automated logistics process. Due to their small dimensions and high order-picking performance, vertical buffer storage systems could represent one solution here.
Transporting goods to the customer
Yet what good are all the algorithms, decentralized warehouse locations, and ultra-fast order picking if the packages are stuck in traffic on the way to the customer? Technology in the form of big data can also help here: Traffic flows are constantly monitored and drivers are always shown the optimal route. Researchers at the Hasso Plattner Institute have recently gone one step further by developing a system that links internal information with relevant online traffic data in real time. Logistics companies can get precise traffic flow forecasts with this solution. The latest information about the user’s own freight fleet is linked to current traffic data and evaluated using the system. This means that they can immediately find out whether one of their own trucks is stuck in traffic, where it is located, how long it has been there, and the extent to which it is delayed.
However, the system can do even more. It is able to forecast traffic problems before they actually occur. If GPS data indicates an increasing amount of vehicles traveling on a freeway, for instance, it can be deduced that there is congestion ahead. Information on weather conditions can also be used to predict ferry or plane departure times. With the help of this information, the planned routes can be optimized at an early stage so that the customer can actually hold the goods in their hands after barely having ordered them online.
Once again, the online giant from the USA may have an alternative in the form of delivery drones, with which it wants to serve the market at least in the medium term. From the company’s perspective, transporting goods by drone is certainly a good opportunity to optimize its Prime Now service. Traffic jams, congested roads, or a lack of parking space for delivery vehicles would no longer stand in the way of fast delivery.
Managers at the company are already calling for special air corridors for the unmanned aerial vehicles (UAVs). This would allow delivery drones to operate at heights of between 60 and 120 meters where they cannot interfere with aviation traffic. Transporting goods by drone is technically possible without big problems. The UAVs are already being tested in Canada, among other countries. The necessary authorization from the authorities remains problematic at present, but if this issue is resolved, then Prime Air, which delivers goods within 30 to 60 minutes of the order being placed, would no longer be just a pipe dream. The question is which customers would be prepared to pay the not inconsiderable extra price for this service, but Amazon is sure to already have an answer with its algorithms.