Our society produces a lot of waste. We throw away huge amounts of electronics, packaging, food, clothing and other items every year. We also tend not to use our resources in the most efficient ways possible. Both of these forms of waste take a big toll on our environment. However, big data can play a role in solving these problems in many areas of our daily lives. Here’s how.
We waste about 30 percent of the food we produce globally every year, which requires significant amounts of water, land, fuel and other resources to grow. Meanwhile, millions of people go hungry. The problem isn’t that we don’t produce enough food. The problem is logistical, and big data can help with that.
Although consumers also discard large amounts of food, 75 percent of waste happens during production and distribution. Food providers can use data to reduce this waste.
One way data can prevent food waste is by analyzing consumer demand to determine optimal inventory levels. Any organization that provides large amounts of food, from grocery stores to restaurants to school cafeterias, could potentially do this.
Sensors can also track food items throughout the supply chain, helping to prevent them from being forgotten and sitting in one location for too long. These sensors can also monitor information that is vital to maintaining food freshness, such as temperatures and moisture levels.
The U.S. electric grid is surprisingly inefficient. In 2017, according to federal data, around two-thirds of the energy produced in the U.S. was wasted due to heat loss and other factors. This loss means we have to produce a lot more energy than we really need, much of which comes from fossil fuel plants.
By collecting and analyzing more data about where our power goes, we can reduce this waste and lower greenhouse gas emissions from power plants.
By tracking energy usage through smart meters, smart appliances, and other connected devices, customers can spot wasteful patterns in their energy usage and eliminate them. Utilities can also use big data to better predict energy demand.
An improved understanding of energy demand could also help utilities deploy more renewable energy. Distributed resources, such as rooftop solar panels, add to the complexity of the grid. Big data helps grid operators track the power these resources produce and direct it optimally, further reducing emissions.
Shipping is a logistics-heavy sector, and companies that handle everything from shipping small parcels to large freight can benefit from data analytics. Moving goods from place to place also produces substantial greenhouse gas emissions. Maritime shipping emits the equivalent of approximately 1,000 million metric tons of carbon dioxide every year, while medium- and heavy-duty trucks emit about 415 million.
By tracking packaging and considering where items need to go, shipping companies can optimize delivery routes to reduce wasting fuel and time. Additionally, by monitoring customer demand trends, companies can better ensure their inventories will remain at optimal levels.
Even small savings can add up to make a big difference. For UPS, cutting one mile off the daily routes of all its drivers could result in annual savings of as much as $50 million.
Manufacturers are always seeking ways to improve the efficiency of their operations. Big data can help them accomplish this and reduce resource waste as well.
By analyzing data related to inventory, customer demand, and supply chain management, manufacturers can better predict the amounts of resources they need and time shipments accordingly. This helps prevent an excess of resources that may end up going to waste.
Big companies like Dell are also using data analytics to track and reduce their energy usage. Sensors affixed to manufacturing equipment can even track the energy usage of individual pieces of equipment.
The more information we can collect and analyze, the better we can understand where our resources are going and how efficiently we’re using them. Big data can make a significant contribution to reducing waste and improving efficiency across various industries.