Using Data to Make Smarter Environmental Decisions

Jake Carrington • May 14, 2025
Using Data to Make Smarter Environmental Decisions 

In the era of climate urgency and environmental accountability, the convergence of big data and sustainability is creating new opportunities for impact. With the vast volume of information available today, from energy usage metrics and logistics data to real-time climate patterns, data is no longer just a business intelligence tool. It's a critical asset for making smarter, greener decisions that drive both environmental and economic value. 

Organisations that effectively harness data can uncover insights that inform more sustainable operations across the board. Whether it's cutting waste in production processes, forecasting renewable energy needs, or reducing emissions in global supply chains, data can reveal what’s working, what’s not, and where the biggest opportunities for change lie. 


From Carbon Footprints to Greener Logistics: Real-World Data in Action 

Data is already transforming how companies address their sustainability goals. In supply chains, for instance, businesses are using advanced analytics to map out routes that minimise fuel consumption and optimise loads, dramatically cutting transport-related emissions. Retail giants like Walmart and Amazon have invested heavily in data platforms to streamline logistics and reduce environmental impact. 

In manufacturing, predictive maintenance powered by sensor data helps reduce energy waste and prevent equipment failures, both of which have significant environmental benefits. Even in agriculture, data analytics is enabling precision farming, where data on weather, soil, and crop health leads to more efficient use of water, fertilisers, and pesticides. 

Cities, too, are becoming smarter and greener. From managing traffic patterns to optimising energy grids and improving air quality, urban planners are increasingly relying on data to inform sustainable development policies. 

For many organisations, they are motivated by compliance to ensure their climate data is accurate and up to date. Whether a business is a large corporate or a part of their supply chain, energy audits are happening, and it is vitally important to stay compliant. Companies are using data tools to ensure they are not left vulnerable. 


The Tools Behind Smarter Sustainability Strategies 

To drive these insights, organisations are turning to a suite of data tools and platforms designed for sustainability. Technologies like IoT (Internet of Things) devices collect real-time environmental data, while cloud-based analytics platforms process and visualise the findings. Tools such as Microsoft Cloud for Sustainability, Google Earth Engine, and IBM’s Environmental Intelligence Suite are empowering businesses to track, report, and act on sustainability metrics. 

Data visualisation tools like Tableau and Power BI make it easier to communicate sustainability insights with stakeholders, driving better decision-making and accountability. Additionally, ESG data platforms such as EcoVadis and 51toCarbonZero help organisations measure and benchmark their sustainability performance against global standards. 



The intersection of data and sustainability is more than a trend; it’s a fundamental shift in how organisations approach environmental responsibility. By embedding data into the heart of sustainability strategies, companies can achieve measurable impact, drive innovation, and build a more resilient, responsible future. Top 10 Big Data Platforms and Tools 


Ready to leverage big data for a greener future? 🌍 

Discover how your organisation can use data-driven insights to make smarter environmental decisions and build a more sustainable future. Explore real-world examples and powerful tools that are already driving change in sustainability practices. 


Take action today – Get in touch with Jake Carrington at Eden Smith to start your journey toward integrating big data into your sustainability strategy! 


By Christa Swain December 3, 2025
Executive Summary: AI, Ethics, and Human-Centred Design Our recent Leaders Advisory Board event - designed in partnership with Corndel - featured three engaging sessions that explored how AI impacts human cognition, customer experience, and fairness. Here's what we learnt: 1. Think or Sink – Are We Using AI to Enhance or Reduce Cognitive Ability? Speaker: Rosanne Werner , CEO at XcelerateIQ & ex Transformation Lead at Coca-Cola Roseanne opened the day with an interactive and thought-provoking session, firmly positioning AI: “AI should be your sparring partner, not your substitute for thinking.” Her research revealed a striking insight: 83% of people using LLMs couldn’t recall what they wrote, compared to just 11% using traditional search . The message? It’s not about avoiding AI, but using it in ways that strengthen thinking , not outsource it. Roseanne explained how our brains form engrams - memory footprints that enable creativity and critical thinking. Over-reliance on AI risks weakening these pathways, reducing retention and problem-solving ability. She introduced the Mind Over Machine Toolkit , six strategies to use AI as a thinking partner: Provide Context First – Frame the problem before asking AI. Use AI as a Challenger – Stress-test ideas and uncover blind spots. Iterative Co-Creation – Collaborate, refine, and evaluate. Document Your Thinking – Keep reasoning visible. Reflective Prompts – Support reflection, not replace judgment. Sparring Partner – Test assumptions and explore risks. Roseanne summed it up with a simple rule: use Sink for low-value, repetitive tasks, and Think for strategic, creative decisions. 2. Designing Chatbots with Human-Centred AI Speaker: Sarah Schlobohm , Fractional Chief AI Officer Sarah brought a practical perspective, drawing on experience implementing AI across sectors - from banking and cybersecurity to rail innovation. She began with a relatable question: “Who’s been frustrated by a chatbot recently?” Almost every hand went up. Through a real-world example (redacted out of politeness), Sarah illustrated how chatbots can fail when designed with the wrong priorities. The chatbot optimised for deflection and containment , but lacked escape routes , sentiment detection, and escalation paths - turning a simple purchase into a multi-day ordeal. “Don’t measure success by how well the chatbot performs for the bot—measure it by how well it performs for the human.” Sarah introduced principles for better chatbot design: Human-Centred Design – Focus on user needs and emotional impact. Systems Thinking – Consider the entire process, not just chatbot metrics. Escalation Triggers – Negative sentiment, repeated failures, high-value intents. Context Awareness – Detect when a task moves from routine to complex and route accordingly. The takeaway? Automation should remove friction from the whole system - not push it onto the customer. 3. Responsible AI and Bias in Large Language Models Speaker: Sarah Wyer , Professional Development Expert in AI Ethics at Corndel “When we create AI, we embed our values within it.” She shared her journey tackling gender bias in large language models , from GPT-2 through to GPT-5, and highlighted why responsible AI matters. AI systems reflect human choices - what data we use, how we define success, and who decides what is fair. Real-world examples brought this to life: facial recognition systems failing to recognise darker skin tones, credit decisions disadvantaging women, and risk assessment tools perpetuating racial bias. Even today, LinkedIn engagement patterns show gender bias! Sarah made the point that simple actions - like testing prompts such as “Women can…” or “Men can…” - can reveal hidden disparities and spark vital conversations. To address these issues, Sarah introduced the D.R.I.F.T framework , a practical guide for organisations: D – Diversity : Build diverse teams to challenge bias. R – Representative Data : Ensure datasets reflect all user groups. I – Independent/Internal Audit : Test outputs regularly. F – Freedom : Create a culture where employees can challenge AI decisions. T – Transparency : Share processes without exposing proprietary code. Wrapping up the final session - before we opened the floor to panel questions and debate - Sarah created the opportunity to discuss how we address AI bias within our organisations by stepping through the DRIFT framework. Shared Themes Across All Sessions AI is powerful, but context matters . Human oversight and ethical design are critical . Use AI to augment thinking , not replace it. Measure success by human outcomes , not just automation metrics. We've had such great feedback from this event series - especially around the quality of speakers and the opportunity to have meaningful conversation and debate outside of functions. Definitely more in the events plan for 2026! If you'd like to be part of the conversation please navigate to our LAB events page to register your interest .
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