Mrs. Fields is an iconic brand of home baked joy. The real Mrs. Fields was also a pioneer in what would become the future of business—connections between individual locations. You see, when Mrs. Fields continued to grow her cookie empire, she realized that she needed a way to better manage her list of 14-and-growing stores, as shared by “The Food That Built America.” Her husband, a tech-driven software developer, introduced a revolutionary idea that would help to better understand demand across her cookie empire and take the world by storm.
Bringing technology to share data between locations in the 1980’s—the intranet, a predecessor to the internet—was complex by even the most advanced standards. However, the premise was simple. Use a connection between locations to share data and act on that data. It was the beginning where shared data analytics and basing future decisions on its insights could make an impact in various functions. This is the foundation of modern business intelligence, and with time, a new type of connection—a RESTful API—took root. These advanced APIs have given rise to a more efficient and effective way to stay informed. Let’s take a closer look.
1. Analytics software value is only as strong as the data quality of the source
The first and most obvious use of big data analytics in logistics management typically surrounds route optimization. Route optimization is based on analyzing trends within current demand to reduce empty backhauls, aka deadhead, to effectively lower the total distance the trucks travel, and thus the emissions, by eliminating subsequent trips. In other words, driving with a load each time on both the headhaul and backhaul reduces the emissions associated with a single shipment or multiple in the case of LTL.
However, seeing these opportunities can be troublesome at best. Analytics make it easier to see when and where a backhaul might exist.
Analytics are a series of algorithms that identify trends and correlations within datasets. The ability to comb through different datasets also means that the datasets need a like structure. Now, while that feature may be evolving with the advent of AI-based tools to restructure data instantly, the data itself is technically meaningless numbers. However, if we think about what Mrs. Fields did with pre-packing ingredients for her recipe, guarding it as trusted intellectual property (IP), the output (the finished cookie itself) is dependent on her ability to prepack those ingredients in the exact volumes needed.
The same is true for data that powers analytics. The data quality needs to be absolutely the best it can be. That’s the only way to ensure the output tastes…err means something valuable. In turn, the insights made possible through its analysis can be applied to unlock logistics optimization opportunities. But let’s imagine a different scenario.
Say that Mrs. Fields hadn’t had this revelation with packing ingredients. Let’s assume she “eye-balled” it when training each store manager. Over time, the recipe changes even if no one intentionally changed it. No matter what she did, she’d always be behind and unable to scale. In the field of data analytics, it's this rich analysis that means you aren’t eye-balling the next best action for each shipment. And an API ensures that it’s the same recipe every time by pulling data in real-time or near-real-time to power insights.
2. Security risks are present with more traditional integration capabilities
Older connection capabilities worked fine…until they didn’t. With time, hackers and cyber-attacks have made it to where we have to change our passwords monthly (if not more often), and the traditional ability to share information, which is extremely advanced via SSL, is resource-intense.
So why does anyone really care where APIs are concerned?
The beauty is in their simplicity.
APIs rely on an advanced API key—a value of 20-128 characters, to share data. This, combined with a series of different calls, results in more data security around your data. Also, as a RESTful API, the programmed query fetches the data from the database. Since the data is dynamic, it’s able to derive more actionable insights into your supply chain. Further, this flexibility allows for a single API to be more easily integrated into your existing ERP systems and simultaneously connect without some fancy middleware.
Yes, it’s an open-standard architecture for the win, and at the end of the day, the data is then sent via API to the IL2000 TMS and back to your systems. You get a way to better understand what’s happening and how you can make meaningful improvements within your supply chain.
3. API-based freight analytics software requires less grunt work to implement
Okay, so we’ve already hinted at the surprise chocolate chip of using a RESTful API to share data, but let’s dig a bit deeper. A RESTful API-based analytics solution literally requires less work to implement. But the implementation is only half the battle.
Some traditional systems, i.e., legacy ERP software, are still subject to future updates. These updates could cause a potential delay in connection to SOAP APIs, but with a RESTful solution, these changes can be more easily accommodated by third-party platforms, such as a freight audit and payment solution, a TMS or any other RESTful API connection.
See. It’s not just ensuring you get the recipe right at the beginning, you have to be able to accommodate changes, like the same way two ovens, built almost identically, could differ with age. A RESTful solution doesn’t age in the same way that an oven does. And it also means that APIs have lower implementation and maintenance costs than traditional connection capabilities.
Improve your access to advanced freight analytics solutions with IL2000
Not every cookie tastes the same—unless you do something ground-breaking like Mrs. Fields—redefining the standards of what you thought you knew and how you’d approach the problem. You have to think outside of the box, and you have to recognize that sometimes, another person, even if you’re married to that person, could have a solution that you hadn’t considered in the past. IL2000 can be your other supply chain person; it’s who we are and why we value ourselves as supply chain consultants who bring an advanced tech suite to the table. So, are you ready to get back to baking while letting someone else worry, or are you going to keep trying to go it alone?
I think you know the answer. Talk to an IL2000 consulting engagement executive to get started today.