Automated Pricing is the Future of Supply Chain Management

As previously depicted by David Kiger, supply chain management has achieved wonders: today, it is perfectly possible to receive an Amazon Prime package within hours after placing the order. The question is, however, how is this possible? A sheer array of complex series of processes connects suppliers with manufacturers, wholesalers, retailers and, subsequently, with consumers. This whole process, as asserted in previous articles, is commonly referred to as supply chain management.

Within the whole chain, logistics is perhaps one of the most crucial components—it takes care of the movement of products and goods in general. E-Commerce businesses, especially E-Commerce mega corporations like Amazon have become logistics experts whilst finished and packaged products and goods specialists like Colgate-Palmolive seize the full scope of today’s supply chain management services.

Just like any other industry wherein data and information play a vital role, logistics and supply chain organization and companies are starting to invest (heavily) in artificial intelligence solutions—or transformational A.I solutions—to overcome and properly tackle those pain points and challenges that are commonly associated with this industry. Many companies, practically both large and small businesses are trying different types of innovations, ranging from simple software to robotics to intelligent machines.

A simple failure in the supply chain implies a total breakdown across the whole supply chain. Such scenario, or better said, such fact, is what encourages businesses and companies to seek out other ways to improve their current processes and enhance the way they manage stock, predict prices and carry out their operations. One of those ways is, of course, Artificial Intelligence. Let us consider the following example of how this has become key: in America, there is a myriad of freight companies. Many of these companies, however, seek out different ways to outsource their activities in hopes of cutting costs and overhead. Surprisingly, and given the fact that these are transportation companies, a vast majority owns zero vehicles. They use instead, a freight broker—an additional step in between the whole process that connects buyers who are looking forward to moving goods and freight and suppliers of trucks and vehicles capable of carrying out the task.

In fact, the suppliers pool is incredibly diverse: companies can find from the guy who owns a simple truck to a massive fleet of vehicles. These companies, the ones that outsource the transportation, have almost zero power to negotiate transportation prices: sometimes they are required to quote a price on the same day, or, worse, commit up to a year in the future.

How to predict prices?

Under the aforementioned circumstances, price prediction has become one of the today’s biggest and most daunting business challenges—prices vary depending on the season of the year: by day, by week, and even by time. And not every single route costs the same: it is not the same to take goods from Ohio to New York than from New York to Ohio. And be that as it may, since these challenges prevent many companies from thriving under this juncture, the vast majority of vendors and suppliers have incorporated high-tech logistics and supply chain software backed by a high degree of artificial intelligence to allow this process.

Now, it is possible to see companies that have migrated their pricing predictions from humans—whose expertise was based on experience and a deep knowledge of the market—to machines capable to predict prices based on tailored financial models, that, as a matter of fact, assess historical prices along with other variables such as weather conditions, traffic and economic and social challenges.

For what is worth, and although artificial intelligence does not always outsmart specialized market experts, both actors must coexist. Sometimes humans come up with better and more accurate prices. In that sense, the involvement of technology should be interpreted differently: as something good rather than something that prevents people from working in their fields. Thus, technology ought to be considered a tool that helps specialists interpret conditions and come up with accurate information—in this case, prices.

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Image courtesy of Pixabay at

The plethora of algorithms that have invaded the whole supply chain play a vital role, though: they enable a more reliable access to real-time information. Instead of just relying on a few hard-to-reach experts to provide accurate information, companies and employees, in general, can use artificial intelligence and machines to make sure they are doing the right thing with the right information, whether it is a quote or a prediction for the sales department. Thus, many other processes that also exist across the supply chain such as sales and procurement can work properly and in harmony with the rest of the company. This is, of course, vital, for today’s companies need to reach out to more and more customers all around the world, and without such synchronization and the use of technology to possess and subsequently use accurate information, every attempt to do so will be futile.

* Featured Image courtesy of Marco Verch at

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