Data Driven Decision Making for Manufacturing
Manufacturing is all about numbers and measurements. Without both of those factors, a manufactured piece would not come out correctly and quotas would not be met. Numbers and measurements are also at the heart of Data-Driven Decision Making, and it is a method more American manufacturers can, and should, easily embrace.
Data-Driven Decision Making (DDDM) is simply the process of making operational decisions based on information that can be backed up via tangible data. Many of the big companies live the DDDM philosophy, and when you use data to make decisions about HR, logistics, marketing, and territories to expand into – why not use it for the manufacturing process?
“Big data, small data, internal, external, experimental, observational — everywhere we look, information is being captured, quantified, and used to make business decisions,” says Walter Frick of the Harvard Business Review.
“Data can come from all manner of sources, including customer surveys, business intelligence software, and third party research,” Walter continues. “One of the most important distinctions to make is between analytics and experiments. The former provides data on what is happening in a business, the latter actively tests out different approaches with different consumer or employee segments and measures the difference in response.”
Data driven manufacturing through machine monitoring is the best way to gather analytics on the performance of your shop floor, and then that shop can alter their machine utilization, schedule maintenance, and perform other administrative actions, to compensate for any measured loss in OEE.