Today, the consumer-packaged goods (CPG) sector faces many environmental sustainability imperatives – waste management, supply chain transparency, decarbonization, responsible sourcing, promoting a circular economy, etc. To achieve these goals, looking at the entire value chain is crucial—from where materials are sourced, and products made to how they are distributed and used.
Within this landscape, CPG companies confronting the sustainability challenge with a data-driven lens are accelerating the path to environment-friendly value chains in the current purpose-led, sustainability-focused, low-carbon economy. Harnessing the untapped data produced across different touchpoints in a CPG value chain, companies can generate actionable insights and decision intelligence that can guide their sustainability-related efforts, helping them reach their net-zero goals and drive positive change.
Data in Action: How CPG Companies are Embracing Environmental Change
According to a BCG report, the agri-food supply chain, in which CPG companies are heavily involved, accounts for 31% of annual greenhouse gas emissions – highlighting the potential of CPG companies to contribute to the decarbonization effort. The good news is that CPG companies have already started to leverage data-driven approaches as an advanced measure to boost their sustainability efforts and decarbonize this emission-intensive industry.
Take, for instance, Nestle’s AI and ML project in collaboration with the Emissions Capture Company (ECCO), which leverages ECCO’s WhiteBox machine learning technology to capture scope carbon dioxide (CO2) emissions and recycle industrial wastewater. The novel approach converts CO2 into eco-friendly products that find application across various industries, such as consumer goods, food, cosmetics, etc.
Global retailer Walmart is another example, as it supported the development of Plastic IQ, a data-based planning tool developed by the Recycling Partnership and sustainability-focused company SYSTEMIQ, that enables companies to prioritize actions to address plastic packaging waste and promote a circular economy. The tool utilizes user data to assess the circularity of plastic packaging throughout its lifecycle – from creation and use to disposal. It guides companies through practical steps, enabling them to decrease plastic usage and optimize packaging.
Procter & Gamble (P&G) also utilizes scalable predictive models that leverage data and AI to anticipate production needs, enabling streamlined processes and reduced waste. It further employs tracking dashboards that provide real-time insights and data visualization across its operations, such as resource usage, energy consumption, waste generation, and emissions, to improve manufacturing sustainability.
While these examples underscore that the CPG sector is already leveraging data to boost sustainable operations, they represent only a fraction of what companies can accomplish today. The possibilities are abundant when data is harnessed effectively.
Exploring the Full Potential of Data for CPG Sustainability
The advancements in technology and the availability of resources have converged to create an environment where taking impactful actions is feasible and achievable. Combining the data collected across various value chain stages with next-gen technologies such as AI, ML, Big Data, Predictive Analytics, Digital Twin, Computer Vision, etc., provides CPG companies with holistic visibility across their entire value chain. It also empowers them to overcome the common challenges associated with sustainability, such as growing carbon footprint, irresponsible sourcing, supply chain disruptions, etc., and accelerate their decarbonization efforts. Let’s take a look.
Gain real-time supply chain visibility
CPG companies can gain real-time supply chain visibility by integrating and analyzing various data sources. Utilizing historical and real-time data, predictive analytics can accurately predict supply chain disruptions (natural disasters, supplier issues, transportation delays, quality control concerns, etc.) and forecast consumer demand. Furthermore, by sharing supply chain data with suppliers, CPG companies can drive CPG-supplier collaboration – identifying efficiency areas, innovating sustainable solutions, and tracking progress on sustainability. This approach refines warehouse operations and decision-making, fostering a responsive, transparent supply chain.
Moreover, CPG companies can implement digital twin technology to create a virtual version of their real supply chain. This virtual model combines real-time data from different IoT devices with AI and machine learning. This can enable them to test different scenarios, evaluate risks, model different nodes, and modify parameters in the supply chain to see how they affect operations. As a result, CPG companies can fine-tune their strategies for optimizing energy usage, managing logistics, and minimizing environmental impact.
Implement sustainable sourcing and procurement
Today, companies have remarkable capabilities at their disposal. ML-driven image recognition algorithms, for instance, can play a crucial role in tracking a product’s origin and evaluating its sustainability. For specific industries like agriculture or forestry, satellite or drone imagery can help track the growth and origin of products in fields and forests. For instance, these algorithms can scrutinize satellite images to spot potential deforestation signs. If identified, alerts can be triggered, prompting investigations to ensure the accuracy of sustainability claims.
Moreover, supplier scorecards act as a data-driven, objective approach to assess supplier performance, labor practices, and regulatory compliance, painting a holistic picture of a supplier’s contributions to a value chain. These scorecards delve into ethical sourcing methods, resource efficiency, emissions footprints, and alignment with environmental standards. This ensures sourcing aligns with sustainable goals and consumer demands. Similarly, AI and ML and strategic insights from Predictive Analytics can help companies optimize inventory, ensure stock availability, and align supply with demand fluctuations. This enhances customer satisfaction and optimizes resource planning, thereby contributing to the overarching goal of decarbonization.
Address scope 3 emissions (looking beyond scope 1 and 2)
Scope 3 emissions come from activities outside an organization’s control but are influenced by its value chain — from extraction and transportation to distribution and disposal. Scope 3 emissions comprise the largest portion of a company’s carbon footprint and are the toughest to evaluate.
Some studies show CPG companies harnessing the power of Machine Learning can gather and create a complete dataset from multiple sources for quantifying scope 3 emissions. Compared to traditional linear regression models and naïve mean models currently applied within the industry, ML algorithms are a cost-effective solution to improving the prediction accuracy of scope 3 emissions across different sources by understanding the complex relationships between input data and predicted targets. Another great resource that CPG companies must leverage is life cycle assessment (LCA) to quantify the environmental impacts of producing the product or service at different stages (raw material extraction, manufacturing, packaging, transportation, use, and disposal). This helps understand the changes that must be made at distinct stages to guide emission reduction strategies and decisions around product design, materials used, etc.
Leverage consumer Insights for sustainable product development
Consumers produce extensive data daily – opening emails, clicking on links, making purchases, etc. By 2025, a staggering 463 exabytes of data will be generated globally each day, which equates to around 212,765,957 DVDs’ worth of data. Within each piece of this data lies valuable information that can provide insights into consumer intentions and behaviors. Businesses can extract insights into consumer trends and sentiments about sustainability by analyzing purchasing behavior, social media engagement, surveys, and feedback. CPG companies can achieve deeper insights into the reasons behind the preference for eco-friendly products, the readiness to pay more for sustainability, preferred sustainable features, etc. These insights are a compass for designing products that connect with environmentally conscious consumers. They also enable CPG companies to shape their offerings in line with consumer wishes, fostering a product landscape that’s both sustainable and socially responsible.
Boost waste reduction & recycling
Real-time data monitoring empowers CPG companies to track waste generation throughout their operations efficiently. Through waste composition analysis, materials that contribute to waste and the environmental impact of packaging choices become clear. This enables companies with the ability to spot chances for integrating more sustainable materials into their packaging, effectively shrinking their ecological footprint and minimizing packaging waste.
Through data-powered insights, companies can optimize their recycling initiatives. By analyzing metrics like material collection quantities, contamination levels in collected materials, and the overall success of recycling projects, recycling programs can be fine-tuned, resulting in heightened material recycling rates. Additionally, the integration of Computer Vision technology brings a new dimension. It boosts quality control, real-time monitoring, and process optimization along the production line. This amplifies product consistency and reliability and reduces material wastage and energy use, cultivating a more sustainable production environment.
Manage carbon footprint
CPG companies utilizing predictive modeling have the power to seamlessly predict carbon emissions across diverse scenarios — from seasonal shifts and shifts in energy sources to alterations in packaging and production volume. This foresight guides the adoption of energy-efficient strategies, novel packaging materials, and the integration of alternative energy. Furthermore, they can pinpoint emission “hotspots” within their value chain, as predictive models highlight areas where emissions are particularly high or there’s a high likelihood of emissions exceeding a certain threshold. This helps CPG companies prioritize efforts where emission reduction would yield the greatest impact.
More possibilities can be unlocked by leveraging supply chain mapping. The work involves gathering and visualizing data encompassing various stages and elements of the supply chain, including the origins of raw materials and components. This analysis can help understand the carbon impact of different suppliers and regions.
The combination of data and sustainability is a powerful force. By harnessing advanced data-driven techniques and cutting-edge technologies, CPG companies can strategically navigate the complexities of the modern environmental landscape, paving the path toward optimized operations and, ultimately, a more ecologically conscious future.
