How Can Manufacturers Use Machine Learning Today?
Machine learning, which is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed, is part of nearly every aspect of our day-to-day lives. Think of things like your Facebook photo album or your credit card’s fraud alert. Whenever you post a new picture on Facebook, the social media network recommends who to tag based on facial recognition. Or, if a suspicious transaction is made on your credit card, the credit company immediately puts a hold on the account.
There is more data available now than ever before, but business practices haven’t quite caught up to handle this influx of information. Luckily, adjusting business practices, plus the right investments in technology, can help companies adapt to these changing demands.
Manufacturers specifically have been slow to incorporate machine learning into their daily practices. However, there are several areas, particularly in after-sales service, where machine learning could positively impact manufacturers’ bottom line and the overall customer experience.
Below, I outline three areas where manufacturers can incorporate machine learning today and start seeing immediate results.
Efficient demand forecasting, which predicts future demand for products and parts based on past events and prevailing trends, is a key component to after-sales service success. An accurate picture of demand allows manufacturers to improve service after the initial sale of a product without increasing costs.
In after-sales service organizations, it’s all too common for service parts planners to lack visibility into supply or demand between different stocking locations, leading to forecast accuracy issues and problems maintaining a balanced inventory, and most notably, increased costs. Oftentimes, this is a result of manual processes, as well as outdated technologies and business practices.
Investing in technologies that incorporate machine learning gives manufacturers greater control and visibility, as well as an effective service parts inventory redistribution process. Cloud-based inventory management solutions eliminate overstocking and enable warehouses to work with each other – as opposed to each operating in its own silo – to meet demand.
