Research shows that between 4.8 to 12.7 million tons of plastic end up in the ocean every year—giving us massive artificial land masses such as the Great Pacific Garbage Patch and the North Atlantic garbage patch.

Still, it is not too late to save the world’s oceans. However, it’s not merely a case of scooping plastics out of the water and preventing more from coming in. Addressing this problem requires seeing the larger picture and finding sustainable long-term solutions.

Here’s how data analytics helps in the fight against the accumulating ocean plastic.

Made possible by modern technology such as artificial intelligence (AI) and machine learning, data analytics allows us to manage large volumes of raw data and extract meaningful information. This field of intelligence has been used in various industries, from finance to entertainment—and it can be used for environmental protection too.

In the ongoing global effort against marine pollution, one research effort tapped massive amounts of data from various sources. The data collection involved the National Oceanic and Atmospheric Administration’s (NOAA) Global Drifter Program, which used floating buoys to gather data across the ocean.

The raw data were first processed using the publicly-available Quantum Geographic Information System. This open-source platform converted the data into shapefiles, geospatial data containing location and item specifics such as plastic volume and surface current data.

Laying out the shapefiles in a custom user interface creates an intuitive visualization of the problem. The research outlines how sorting and processing raw data helps us visualize the ocean plastic problem—the great garbage patches in the Pacific and the Atlantic were also identified, and are monitored, using similar tools and technologies.

Seeing where the plastics aggregate is only one part of a larger, multilayered issue. The problem with ocean plastics is indicative of a lot of other problems, which return to harm natural life as well as human communities.

Most plastics that end up in the ocean are returned to land when beaches and coasts are hit by a storm surge to shore. Large waves carry debris back, creating a disproportionate effect on coastal communities instead of inland urban centers.

With access to a wide variety of data, it’s also possible to identify potential connections between factors that seem disparate or irrelevant at first. A case in point is Our World in Data, which reveals the grim data-driven conclusion that no plastic collection program is enough to keep up with the volume of waste we generate—with the ocean plastic expected to triple by 2050.

However, one curious relationship explored in the study is that of the volume of mismanaged plastic waste generated per capita versus the Gross Domestic Product (GDP) per capita. The “inverse U-curve pattern” between the two factors means that the least and the most developed nations have lower average mismanaged waste compared to nations whose GDP sits in the middle.

Insights like this help identify underlying problems that further contribute to the ocean plastic problem. In the above example, it’s highly possible that developing countries in the GDP mid-range generate large amounts of industrial wastes and plastics, but without access to sufficient technologies to offset or manage these wastes effectively.

By finding root causes, intra- and intergovernmental units can focus their efforts better, which leads us to the following:

In the context of environmental conservation, data analytics is not only used to track the flow of plastic waste. Modern intelligence tools can facilitate targeted solutions and data-driven decisions on other aspects that, in return, contribute to the management of ocean plastic.

From a macro management perspective, organizations such as The Ocean Cleanup managed to deploy plastic collection stations. These are floating barriers placed at critical locations to optimize the amount of plastic they can capture.

Data analytics can also be leveraged in a lot of other contexts, from government policymaking to waste management initiatives for private companies. Modern business analytics tools allow decision-makers to access relevant information regarding budget, financial impact, and even employee and customer response—often with streamlined navigation capabilities.

For example, a manufacturing firm can accelerate its research and development phase for alternative production strategies. Similarly, big data collected from various aspects of the organization can help identify opportunities for plastic waste reduction.

Not only does it positively affect waste generation, but an environmentally responsible business makes for an attractive proposition for both business partners and clients.

We all need to play our part in protecting the environment. Not only is it the right thing to do, but it is also critical in the sustainability of our businesses. The first step is knowing where you stand. To do this, you need to gather the data so that you can understand your impact, and then you can make a plan to address the impact of your operations on the environment and track your progress.

Tools like Syft allow you to understand and analyze financial and non-financial information and a combination of these. With this tool you can analyze your impact on, say, plastic management or carbon emissions and then track how this impacts your costs and profits. You can include it as numbers and even visually as graphs and then include in reports.

More than improving customer experience and arming businesses with a competitive edge, data analytics can be used to address environmental challenges such as the growing volume of plastic waste in the world’s oceans.

By providing a more comprehensive view of the problem, identifying the underlying issues involved, and finding impactful opportunities, it’s still possible to mitigate the flow, or perhaps completely reverse, the accumulation of ocean plastic.

Bash Sarmiento is a writer and an educator from Manila. He writes laconic pieces in the education, lifestyle, and health realms, and is a frequent contributor to the Syft blog. His academic background and extensive experience in teaching, textbook evaluation, business management, and traveling are translated into his works.

You can also read some of the other articles he has written for us here, including blogs about payroll automation in the delivery service industry, how understanding financial statements facilitates business growth, and top tips on maintaining a work-life balance when working from home.