Data Analytics Optimizes Shipping through KPI Tracking
The shipping industry is being affected by big data analytics more than most pundits care to admit. It is clearly having a profound effect on shipping.
Big data is affecting every element of logistics in the economy. One facet of modern business that doesn’t get as much attention as it should is shipping, even though big data is having a profound impact on its future.
Last June, a paper prepared by Paterson Simmons showed that big data is a driving force behind the shipping industry. According to the paper, 81% of respondents recognized that big data was vital to the future of the shipping industry.
Big Data Makes it Easier to Track KPIs in Shipping Logistics
Almost every business tracks key performance indicators (KPIs) in specific areas to gauge their success. KPIs help them identify areas where improvement is needed. Measuring KPIs allows for improved goal setting by providing quantifiable evidence of the company’s performance.
KPIs can apply to all aspects of a business, but one area that is often overlooked is shipping. Shipping contributes to costs for both the shipper and the receiver. Tracking the most critical performance measures allows businesses to reduce those costs, while simultaneously increasing efficiency and customer satisfaction.
All of these variables can be tracked more easily with big data. Data analytics is ideal for monitoring performance across many metrics.
Although there are dozens of potential shipping metrics to track, there are a few that are especially vital. They focus on containing costs and improving the shipping process. As you focus on continuous improvement, these KPIs are critical to monitor.
Shipping Damage. On the surface, if 99 percent of your shipments arrive undamaged, it appears that you are doing well. But consider the actual monetary impact of that: 1 percent of $1,000,000 is $10,000. Now imagine that 5, 10, even 15 percent of your shipments have some type of damage, and the costs can quickly add up. Therefore, it’s important to measure the damages that occur to your shipments and seek ways to reduce them. This typically requires further analysis. For example, installing damage indicators can reveal specific routes or even trucks or drivers that have higher levels of damage and therefore require corrective action. A certain amount of damage to shipments is to be expected (after all, transportation can be unpredictable) but using KPIs can identify preventable situations and reduce losses due to damage.
Big data plays a very important role in tracking damage of packages during transit. This helps shipping companies minimize damages by finding the source of the problem.
Shipping Time. Looking at the shipment time is also a key metric for companies that ship. You need to determine how many deliveries are made in full (i.e., without any backordered or delayed items) and in what time frame, the average length of delays, and the causes of delays. The amount of time that it takes for a customer to place an order and receive it needs to be tracked, and trends in late deliveries need investigation. However, more than simply revealing how long it takes for your customers to get what they ordered, looking at shipping time metrics can reveal inefficiencies or issues within your own internal processes. For instance, how long does it take for orders to be picked and packed? Are there certain shifts or warehouses that outperform others? Comparing these key measurements will identify outliers as well as ongoing issues and provide insight that can improve processes.
Big data helps brands identify reasons that deliveries are failing to meet timetables. They can expedite shipping to ensure deliveries outpace competitors.
Accuracy of Orders and Inventory. They say no one is perfect, but when it comes to order accuracy, perfection is the goal. Incorrect orders not only waste time and money but can also hurt your brand. Therefore, you need to measure the number of orders that are picked, shipped, and delivered without any incidents. When orders are shipped correctly within the promised time frame and delivered undamaged almost 100 percent of the time, it reveals that your supply chain and delivery services are working as they should. The lower these numbers, the more problems you have.
Inventory accuracy is another KPI to track. If your inventory listing are incorrect, you risk not only disappointing customers with unnecessary back orders or order cancellations, but also having too much inventory that you end up taking a loss on. It’s not uncommon, for instance, for companies to order more inventory unnecessarily due to inaccuracies. Therefore, it’s important to measure your inventory accuracy levels, and identify areas that need improvement.
This is probably the most important area where big data can be of use. It allows brands to track reports and ensure customer satisfaction is in line with expectations.
Shipping Costs. Finally, monitoring shipping costs is vital to maintaining the bottom line. This includes looking at the costs of an order from beginning to end, including maintaining inventory, warehousing, and shipping. Breaking down your shipping costs into different stages allows you to see where you are spending too much money, and where you can make improvements. Monitoring shipping costs can also help you identify potential cost-savings measures. For example, by comparing the costs of different classes of service to the average delivery time of each service, you may find that you can use a different level of service without sacrificing delivery times.
Any company that ships orders needs to track these important metrics. Failing to do so could mean higher than normal costs, reduced productivity, and damage to your brand.
Big Data is the Key to Ensuring the Success of Modern Shipping
The shipping industry is being affected by big data more than most pundits care to admit. The role of new analytics solutions has somehow been overlooked by many experts in the big data community. However, it is clearly having a profound effect on shipping.
You must log in to post a comment.