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This article is part of an ongoing series on the uses for artificial intelligence (AI) in manufacturing, starting with our article introducing machine learning and AI, and their relevance to manufacturing and supply chain operations. 

If you have been keeping up with this series, or read only one or a handful of our articles in Machine Learning for Manufacturers, you will know that artificial intelligence is frequently employed for prediction-based solutions. Calculating the likelihood of employee or customer churn (the chances either an employee or customer stops doing business with your company) is one such prediction-based solution that AI excels at. 

Baby Come Back 

Some things are harder to predict than others, and in manufacturing, customer and employee churn can be difficult to predict at times. 

Sometimes the writing is on the wall, and you can prepare accordingly, but other times it comes out of nowhere. 

Since even just one customer can account for a significant portion of a manufacturer’s overall revenue, or a well-trained and highly-skilled employee’s sudden resignation can threaten the efficiency you have worked so hard to achieve in your process. 

Such pitfalls can range from annoyingly costly to financially devastating, and so if you are not sufficiently well-prepared for a coming pitfall, you could face some serious setbacks to staying afloat in a competitive industry. 

An artificial intelligence prediction platform, such as those offered by Findability Sciences, can be instrumental in preparing for, or perhaps even preventing, customer or employee churn within the world of manufacturing. 

To find out how AI plays a role in this, read on. 

Predicting Churn Made Easy

To the layman, the word “churn” is associated with churning butter, an activity which nowadays has largely been left to robots rather than sturdy humans. For business owners, the word has quite different connotations. 

Churn refers to the rate of employees or customers that you can expect to part ways with your company. As mentioned earlier, the stakes are higher in manufacturing because one specific customer or certain employee can throw a pretty big wrench in your operations. 

So, the prospect of implementing a solution that brings you a highly accurate prediction of whether a customer will stay or leave. You can find such a solution in Findability Sciences’ Predict+ platform

Findability’s prediction platform analyses historical and present, constantly incoming company data to measure three crucial areas of customer satisfaction: proactive contact, ease of doing business, and problem resolution. 

Your level of satisfiability in these areas is measured, and connected to your dealings with certain clients, so that predictions about which of your customers are more likely to churn can be made. 

Of course, you are not expected to just sit there and mourn at this data, but to get proactive about rectifying your predicted level of satisfiability. More customer outreach, and follow-ups, perhaps even offering a discount on the next order, can all be methods for helping lessen the rate of customer churn.

Additionally, you will also know which specific customers you should be targeting, and which are happy customers. 

As hinted before, this service can also be extended to your employees as well. Company data from your HR department can be a goldmine here, and can let you know which employees are more likely to leave. Other data, such as work performance, which can luckily be easily measured in manufacturing since so much of the process is monitored, can also provide signs of dissatisfaction among employees. 


Churn can be devastating for a manufacturer, so having a highly-accurate AI prediction platform that specializes in measuring your satisfiability with customers and employees alike can be crucial to accurately predicting and preventing churn in the future. 

For more AI-based manufacturing solutions, reach out to Findability Sciences.

Read other informative articles in our ongoing Machine Learning for Manufacturers series: