Data stuffing to data exploration! That’s how data analytics have changed in the recent years.
The catch here is not just about collating a bewildering amount of real-time data, but how to pick the relevant ones for analysis to further use them for improving operational efficiency, enhancing product/service, and ensuring great customer experience.
Here a question that may naturally crop up is how a fragmented sector like logistics incorporates effective data analytics so that loopholes can be fixed to make efficiency and cost move inversely? Well, the world of logistics has already got the answer in the form of big data, only its implementation is changing based on market competitiveness and customer expectations.
Organizations across the world have been using the big data technology effectively to re-assess and grow their business and keep the costs under control. A survey carried out by Gartner in June 2016 shows that 48 percent companies made investments in big data in that year, which was up by 3 percent from 2015.
Companies like United Parcel Service or UPS, the largest package-shipping company in the world, has been using big data for quite some time. The company invests a whopping sum of $1 billion every year on big data. By using this technology, UPS captures every possible data to reduce the impact of various environments on their business.
Using big data UPS collects information related to engine performance, mileage, speed, stoppages, miles for gallon and others. In addition, the company also gathers data on drivers’ behavioural pattern and safety habits. It happens through the sensors installed in the vehicles that provide data feed on emissions and fuel consumptions.
Logistics companies have initiated various project prototypes to exploit big data analysis, and some of those projects will be part of our daily lives soon. One such project is real-time analysis to assess large volumes of data stored on registers’ logs, database, or Excel. Here, we would discuss the functions of big data and how logistics companies can use this to their advantage.
How Do Big Data Work?
Let’s start with the basics first. What is big data? It is a collection of various data management technologies and practices that support in multiple data analysis processes. The analyses are more specific through which organizations try to find out specific business issues rather than having vague notions. The success of big data depends on a holistic approach, data, infrastructure, and skilled manpower.
Simply put, organizations these days are making efforts to get accurate data-driven insights for effective business decision making. Regardless of the business matters such as anticipated sales volumes, customers’ expectations/preferences, or optimized work schedules, they can help businesses succeed.
Also, in the current era companies are dealing with an unprecedented amount of real-time data that comes through mobile devices, particularly in the logistics industry. There are new data sources such as sensors and radio frequency (RF) tags in trailers, RF readers in distribution centres, Electronic On-Board Recorders (EOBRs) in trucks, and a huge number of handheld devices such as smartphones and tablet PCs. Big data helps manage assets more efficiently, and in the process gain more visibility and control over supply chains, and leverage communication anywhere at any time.
Usefulness of Big Data for E-commerce Logistics
Industries like e-commerce can get immense benefits from the advanced and integrated technologies of big data. These days logistics service providers manage large consignments that create vast data sets. For thousands of shipments every day with various shape, size, content, weight, and destinations, they need a robust delivery network. On top of it, these companies also require an effective tool to detect the grey areas that bring down efficiency and cause cost spike. This is why there would be excellent benefits of integrating supply chain data streams as this could eliminate the existing market fragmentation. Here are the four major usages of big data in the e-commerce logistics:
1. Analyzing Volume
Forecasting the volume of parcels in a week, month or on a particular day has always been a difficult task for logistic companies that are seeking a solution for optimizing resource allocation and budget. An increasing number of logistics companies are investing to sort out this area to identify the patterns that will help them predict peak volumes, and big data can do that quite well.
2. Smart Management
Logistics management is a complex process that involves risk analysis and finding solutions based on that. For example, if there is a roadblock or political unrest in a particular area or even during vehicle breakdowns, the authorities can have a clear understanding of these risks through data analysis and be ready with potential remedies.
3. Cost-effective Routing
Real-time data processing can help logistics service providers to predict and handle crises even before they happen. The ability of big data technology to analyze data from various sources enables them to predict events and alternates. Logistics firm that has better infrastructure, routing, transparency and cost efficiency will have the edge over their competitors. Some of the leading companies are doing it by using big data analysis to study huge amounts of parcel data to predict the most reliable, fastest, and cost-effective routes.
4. Web Analytics
Many logistics companies are using big data for analyzing their web traffic. For example, a top-tier logistic company in Germany is carrying out big data analysis to provide personalized services and better customer experience to online visitors. In addition, the entire shipping process can be made highly efficient based on a real-time data analysis location, traffic, volume, and others.
The massive amount of data that gets generated these days is far beyond the managing capacity of conventional data analysis systems. This is where big data comes in to do things that were never thought possible earlier. Equipped with spark and a real-time transactional database such as MongoDB, Cassandra, and NOSQL, the transformation is happening at a fast pace. Simply put, big data makes “Predictive Analytics” possible, which is likely to set the future roadmap.
Implementation of big data is one of the most revolutionary technological shifts in the recent times when it comes to data analysis. However, despite endless innovations that have bolstered the logistics sector over recent years, the final phase of the process or the “last mile” is still causing trouble for the companies. After all, products still need to be moved into the hands of consumers. Keeping this mind, some of the logistics providers have come up with innovative click-and-collect solutions like parcel lockers to eliminate the last mile woes, and of course reduce a significant amount of cost. It also means consumers don’t have to sit around waiting for the courier personnel to show up but can collect at their convenience. Overall, such a step can greatly improve the operational efficiency of e-commerce businesses.
You may or may not have opted for big data just yet for your business; however, you need a permanent solution to end the persistent last mile issue. In your effort, we can assist you to streamline your logistics through our truly impactful solution. To learn more, call us right away at +91-8882-760-760 or send an email to email@example.com, for consultation. Try us; it can transform your business for better.