How Manufacturing Analytics Improve Productivity

As a world with seemingly limitless processes, manufacturing is the ideal use case for data analytics. But how can manufacturing analytics improve productivity, and ultimately, the bottom line? Here are a few of the top ways manufacturers can effectively incorporate analytics into their operations.

Get Answers in Real Time

Time is money in the world of manufacturing. Since so many processes can be automated, and it’s no problem to operate close to around the clock, manufacturers can’t afford to shut down in order to perform routine analysis. Fortunately, real-time analytics allows enterprises to get a clearer idea of what’s actually going on with operations without the need to pull the plug on productivity.

In the past, it would have been incredibly challenging to diagnose issues while still in production—especially if there were potential safety or regulatory concerns involved. Thanks to real-time analytics, however, manufacturers can analyze the flow of data as it’s created. This leads to a situation where issues can be rectified before they become so problematic it requires a full shutdown. When manufacturers have this added boost of speed and agility, they’re able to stay ahead of the curve and outperform competitors.

Better Forecasting

Manufacturing is a game of supply and demand. Creating too much or too little of a product versus the actual demand can lead to an organization losing efficiencies of scale—or worse, ending up with far too much inventory that isn’t moving. By harnessing the power of analytics, however, it’s possible for manufacturers to do a far better job of forecasting demand.

These improved capabilities can permeate throughout the entire organization. For example, utilizing sales analytics can paint a clearer picture of true demand across the product line, which can give manufacturers a better idea of what goods are worth prioritizing at any given time to maximize growth. 

Create a Data-Driven Culture

The idea of a data-driven culture might sound silly to some; but it’s actually becoming one of the biggest ideas in the world of analytics today. This is because an organization that fosters a data culture is more likely to base the majority of decisions on real information, not the hunches of a few people who don’t really know the answer.

Over time, the compounding effects of an enterprise operating in this way can make it completely indistinguishable from the way it was before moving toward a data culture. There are clear strategic advantages to any organization that’s willing to make the necessary changes to head this direction.

Greater Customization Capabilities

When most people think of manufacturing, they often consider it as building the same widget over and over in massive supply. While this is certainly the case for many kinds of manufacturing, it’s not the only way things work in this world.

In fact, customization of products is one area that can allow some manufacturers to stand out from their competition. By finding ways to incorporate various customizable elements, enterprises can both attract a more diverse customer base, while also improving operating margins. This, however, isn’t an easy thing t accomplish. Allowing data analytics to lead the way can help manufacturers get a better understanding of how to approach customization in the most cost-effective way.

Reduce Downtime and Inefficiencies

In manufacturing, it’s all about creating processes and protocols that maximize time and material efficiency. There are tons of variables that play a role in this—some of which can be hard to identify without the assistance of analytics. With advanced analytics powered by artificial intelligence and other technologies, it’s possible for manufacturers to take a deeper look at problems than ever before—understanding issues from their true source.

For instance, manufacturers can use analytics to do a better job of understanding what causes machinery to break down. According to McKinsey, “Predictive maintenance typically reduces machine downtime by 30 to 50 percent and increases machine life by 20 to 40 percent.” Those are massive improvements that will have a very noticeable effect on the bottom line.

Manufacturing is one of the most obvious fields for implementing data analytics. Enterprises that do this best will have a strategic leg up over those that slack on this front.