It’s no secret that logistics has a lot of unutilized data.
“Data is the new oil” has become a common refrain. But like any quest for oil, it takes educated drilling before a well of valuable information is revealed.
The enormous growth of available data makes searching for meaningful information quite complex, especially if you need to process it rapidly.
Data overload leads to stress
If you ever spent a minute inside the delivery operations room, you know it’s hectic.
Logistics professionals must process a massive inflow of data when monitoring the delivery process, especially in the last mile. In addition to monitoring, they also need to understand what is happening very quickly.
On the other hand, our brains aren’t designed to handle the ever-increasing volumes of data we attempt to process. This leads to increased levels of the stress hormone cortisol, which can lead to confusion, memory loss, and a state of restlessness.
And it doesn’t stop there.
The environment in which they operate requires fast decision-making where they need to get a complete overview of both historical and real-time data and turn it into action.
This is where data visualization comes into play.
Introduction to data visualization
Data visualization is the practice of translating information and data into a visual context, such as graphs and maps, to make it easier to understand.
Visual data is designed to tell a story. The brain’s capacity to process large and complicated information in a significantly shorter time is the primary benefit of adopting data visualization. It’s all about the way the human brain processes and understands information – it’s all psychological.
Let’s look at a few examples of what this means in practice.
Most people are unaware that Uber leverages data visualization to understand better how cities move. Last-mile delivery companies can do the same to comprehend how parcels move and, most importantly, derive insights from them. This effort to showcase the importance of location data by providing visual context is called geospatial data visualization.
Furthermore, data visualization can be a key to uncovering trends and outliers. Shifting perspectives, from a set of bar charts to a map, can help find anomalies such as the most critical or underserved delivery areas.
Moreover, one of the best ways to visualize delivery data is a heat map. A heat map uses colors or shades to represent different values or value ranges. This is probably one of the most used data visualization tools for maps, and it is especially useful for the logistics industry. Among other things, it can be used to understand how to distribute the workload more efficiently. This leads to not only better business results, but also less operation room drama, and happier and more productive couriers.
Information has become a new frontier of competitive differentiation. Companies across industries are working to replace intuition with reliable data-driven insights to make thoughtful business decisions.
Data visualization bridges the gap between “what information do we have?” and “how can this information help us become more efficient?”. Furthermore, the speed of comprehending data summaries in order to act timely is critical. As Cassie Kozyrkov, Chief Decision Scientist at Google, points out: the analytics game is all about optimizing inspiration-per-minute.
If you want to learn more about how the Mily Tech platform helps last-mile delivery professionals become more efficient through various geodata visualizations, make sure to follow us or request a demo.