Reducing Manufacturing Waste With Data: Inventory Insights

Manufacturing waste is a major environmental issue. Even as businesses shift to greener methods and materials, overproduction and poor inventory management pose a serious threat to long-term solvency and sustainability. Luckily, with the advent of new technology, particularly data-driven inventory management tools, manufacturers, and stores have the opportunity to cut back on excess at every level.

The Benefits of Sustainable Manufacturing

There are countless reasons why businesses are interested in adopting more sustainable manufacturing practices, but the leading factors include public pressure, tax incentives, regulatory compliance, and cost reduction.

While these factors play a role in changing manufacturing norms, it’s also important to remember that a greater number of these businesses are already equipped with analytics platforms. The same tools companies use for labour management and warehouse optimization can also be used for forecasting and inventory management.

Spotting Trouble Spots

Certain industries stand to benefit significantly more than others from identifying overproduction, poor distribution, and manufacturing excess. Grocery stores and food distributors, for example, have recently faced serious bad press due to high levels of food waste in the US. Many estimate that as much as 40% of food is wasted before it even reaches consumers.

By using inventory data to examine sales patterns at varying distribution points, suppliers can determine what stores produce the most waste. They can then optimize inventory levels for individual locations and adjust overall production levels for future distribution based on past patterns and data-driven forecasting.

Another industry experiencing manufacturing imbalances is the automotive industry. Though sales seem to be steady, car dealers are reporting more cars on-lot than they normally maintain. The issue seems to be on the manufacturing end, not on the sales end.

In order to stabilize inventory levels, manufacturers need to assess numerous buying trends, not just total cars required, since some are simply more popular than others and popularity varies by sales location. For example, as of this writing, the Lehigh Valley Hyundai has 74 Elantras in stock but only 3 Sonatas. Why the variation when the two are so similar? With data that sales teams can provide to manufacturers about what’s moving off the lot, when, and with what demographics, manufacturers can adjust what they’re making and where they’re marketing specific car models.

More Data, Less Waste

The more manufacturers know about their own internal processes, the more efficiently they can perform; this is vital to future production models that will reduce waste even further.

Most factories hope to switch to greater use of robotics in production, and without the need to maintain a steady workforce, they’ll be able to focus more on meeting up-to-the-minute demands. But what robotics-led manufacturing can also do is enable factories to shut down production entirely when supply needs are fulfilled.

Adidas, for example, is currently shifting to a Speedfactory model in Germany that relies heavily on automation. And since robotics-driven manufacturing is also more precise than human work, it has the potential to cut waste in numerous areas, not just in terms of overall supply.

Our current waste levels are unsustainable, but better manufacturing data can help reverse this trend. It’s time to reduce the burden of manufacturing on our environment and focus on placing what we do produce more intelligently.