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Working with AI to Optimize Your Supply Chain



Artificial intelligence isn't just for science fiction anymore. More and more companies in a variety of industries are beginning to adopt AI in their operations to improve efficiency. Predictive algorithms are an increasingly common AI tool used in the logistics industry, as they can help to optimize inventory, prices, and even warehouse organization. However, these algorithms are still fairly new to the industry, and many people are still learning how to make the most of them. Here is some useful information for interacting with AI algorithms to optimize the use of these tools.

First, it is important that people learn to trust these algorithms. People naturally believe that we know best, so it makes sense that we're inclined to override the decisions an algorithm makes when we don't necessarily agree with it. However, statistics demonstrate that these algorithms tend to make better decisions than humans can, especially in the long run. Learning to trust, rather than fear, the decisions these algorithms make will help to increase the efficiency of the algorithms.

Another important aspect of interacting with predictive algorithms is to understand what the algorithm is able to consider. This data will be the most relevant for the day-to-day decisions in the area in which the algorithm is designed to improve. For example, if an algorithm is designed to predict if your neighbor is taking a road trip next weekend, it will likely consider important data such as the weather, holidays or days off work, season or time of the year, as well as events which may be going on in nearby areas. It can also be essential to understand what data the algorithm isn't designed to consider. While this data is unlikely to impact the day-to-day decisions your algorithm, there are rare situations in which this data may be important. In our previous example, the algorithm is likely to be much better at predicting your neighbor's road trips than you are. However, if you know they recently got into a car accident and their car was severely damaged (data which the algorithm cannot consider) this information may alter the prediction. Learning when it is appropriate to override the algorithm's decision will also help to improve the efficiency of the algorithm's decisions.

Knowing how to best interact with these AI algorithms to make the best use of them is essential to utilizing artificial intelligence tools to optimize your business. Effective use of predictive algorithms can significantly help to improve your logistics operations.

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