When globalization, as a term, first entered common parlance in the early 80s, economists often spoke of the “global village.” The picture that came to mind was one where the whole world lived and interacted harmoniously. While this vision is true to an extent, ask any logistics professional, and they will tell you that routing and scheduling goods in this interconnected world has grown increasingly complex. 

No longer can goods be transferred from the source to the destination in a straight, sleek line. Instead, we find the route circuitous—more akin to a complex web. The fact that we are all linked to the good and the ugly of the complex supply chain was brought home in 2011 when the Slavery Footprint website went viral, asking people one stark question, “How many slaves work for you?” The survey results were a chilling reminder of the underbelly of globalization. 

The California Transparency in Supply Chains Act of 2010 became binding in 2015, making it essential for companies in the US to assume responsibility for their supply chains. Large conglomerates are now responsible for the abuse that happens downstream in the murky sweatshops of developing countries. Increasingly, the general public too has begun to demand that their goods be ethically sourced, leading to a boom in fair trade organizations. 

The need to increase supply chain transparency is becoming more widely recognized, but how exactly can this be done? Geospatial analytics, we believe, can play a leading role in magnifying these rudimentary efforts and making the global supply chain more sustainable and ethical.


What is Geospatial Analytics?

Geospatial data describes any data associated with a particular place on the earth’s surface. It contains position information (earth coordinates), attribute information (qualities of the item, event, or phenomenon), and temporal information (the time or life span at which the location and attributes exist). It is extracted from various sources—satellite imaging, aerial photography, AIS (ship transponders), mobile phone pings, IoT data, and SAR data (Synthetic-aperture radar). By visualizing all these pieces of information, one can easily identify the trends and nuances within a business.

Managing massive geographic data sets involves numerous obstacles. Due to this, many organizations fail to maximize their benefits. First is the sheer quantity of geospatial data. It is anticipated that 100 terabytes of weather-related data are generated every day. Consequently, even though 96 % of those who were surveyed claim to incorporate weather data into their organization’s operational planning, firms cannot guarantee that weather events and climate risk will not impact their continuity. 

Geospatial analytics closes the gap by providing contextual information to help companies make impactful decisions without contextual analytics. As geospatial technology merges with machine learning and AI, experts expect advanced decision-supporting models.


Understanding Sustainability

Sustainability is not merely environmentalism. Instead, it is the knowledge that economic growth at the expense of social equity and ecological health does not provide “sustainable” or long-lasting consequences. In the words of the Brundtland Commission, sustainability is all about meeting our needs without compromising the ability of future generations to meet their needs. A more holistic approach to development, sustainability considers ecological, social, and economic dimensions in pursuing profits.

A landmark global effort to achieve sustainability comes from the United Nations General Assembly, which, in 2015, set up the Sustainability Development Goals. A collection of seventeen interlinked global goals, the SDGs are considered a “blueprint to achieve a better and more sustainable future for all.” Making supply chains more “sustainable” would necessitate supply chain traceability—something geospatial tools can help facilitate.


Using Geospatial Data to Engender Supply Chain Visibility

Human rights violations downstream can still cause damage to more prominent brands through associated reputational costs, fines for failing to meet reporting obligations, and other ESG-related issues. Companies are under constant pressure from customers, authorities, non-governmental organizations (NGOs), and other stakeholders to reveal more information about their supply chains. A business may not fully grasp its Tier 2 and Tier 3 supplier connections. 

Geospatial tools can provide details on climate change, the environment, and transport-related issues. However, embracing a data-driven approach is only the first step. Organizations should begin leveraging this information to see visible change. Previously, on-prem infrastructure and upfront investment were significant barriers to organizations wanting to scale their geospatial technology. However, as cloud technology and cloud-native approaches become more pervasive, organizations with global supply chains can accelerate and become advanced users of geospatial data.

As sustainability continues to evolve as one of the vital corporate pillars, it’s essential to go beyond required certifications and verify and analyze activities on the ground. First-mile visibility has always been a barrier, but combining GPS data, satellite images, drone data, proprietary AI algorithms, and scalable data science can create a robust traceability platform. For instance, analyzing aggregated and anonymized GPS data helps spot traffic patterns and identify the areas with consistent traffic flow between an area of land and a mill. Transparency becomes more plausible by showcasing this “potential link” between the mills and the farms or plantations.


Geospatial Tools for Fostering Sustainability

In 2016, Google Maps and UN agency FAO (Food and Agricultural Organization) agreed to work together, under a three-year partnership, to make geospatial tracking and mapping products more accessible. It was anticipated that the high technology would assist countries in tackling climate change and provide much greater capacity to experts for developing forest and land-use policies.

Geospatial information systems also have the potential to tackle a wide range of environmental hazards, from climate change to poaching and deforestation. For instance, animals can be followed to understand their migration patterns, habitat suitability models will help conservationists determine when and where to implement protective measures, and endangered species can be fitted with tracking devices before being released into the wild.

In 2014, a landmark study used GIS technology to identify indicators of sex trafficking in online ads and track their movement patterns. The online ads were followed for six weeks and evaluated for indicators, with movement being observed by monitoring the advertised phone number. The GIS data was thus used to identify “prominent hubs and circuits.”

These are only a few instances of how geospatial data and analytics can be used for good in the supply chain. A similar approach can also help companies establish healthier practices and reduce cases of spoilage for perishable goods, track suppliers who are failing to adhere to regulations, and so much more.


How Can Geospatial Data Help You?

IoT, blockchain, and big data applications are viewed as aiding in real-time or near-real-time monitoring of supply chains. Rapid data capture followed by analysis through AI can help identify supply chain disruptions that may cause large-scale problems without relying on information sent by a single company or individual. 

Get in touch to find out how you can leverage data to improve supply chain sustainability.

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