Every day it seems a new technology hits the market that has the potential to transform how we do business. This is particularly true for any supply chain business, where the sheer complexity of operations, diversity of activities, and volume of data make it a prime candidate to benefit from the whole array of emerging disruptive tech; but the technology that will probably make the biggest impact in the foreseeable future is artificial intelligence. Here are a few ways AI may change the way supply chain businesses operate:

1. Predictive demand forecasting 

“In 2015 the cost to companies of overstocking was around $470bn and of understocking $630bn worldwide”IHL Group

By applying machine learning to real-time production, stock and sales data, businesses can create predictive models to determine how many of a particular product they should be manufacturing at any given time. This means retailers will not be sitting on excess stock nor run out of stock, factories will have up to date visibility for better production planning and logistics operators will have a clearer understanding of future capacity requirements. All of this translates to massive efficiencies and cost savings in the supply chain.

2. Product development

Product development AI will be able to use historical sales data and real-time trend data to provide product developers with insights about what products they should be developing, what features those products should consist of, and in the case of retail, even what price-point a product should retail at. We may even imagine a future where AI develops new products they predict to have the highest chance of selling, and autonomously send the design files directly to manufacturers without the need for human intervention.

3. Product inspections 

Many factories are already using computer vision systems that can inspect products as they flow through an assembly line. These systems take multiple images of each product in a matter of milliseconds and scores them, in real-time, against quality control criteria. They detect potential flaws in the product based on shape, colour, size and temperature, among other attributes, and then output a quality score. Products that don’t pass the AI’s inspection are instantly dropped out of the assembly line.

 

In part 2 we’ll be looking at how AI can have an impact on logistics and manufacturing in the supply chain. You can read it here.