At Dayrize, Ryan Collins leverages his expertise in Business Analytics to transform data into actionable insights, driving sustainability focused, data-driven decision-making for our clients. In this interview, we delve into Ryan’s perspective on AI in data analysis, explore the evolving role of sustainability analytics in business, and gain first-hand insights into the latest updates to our dashboards.
Can you share what inspired your journey into Business Analytics and how your career evolved to your current role as Head of Business Analytics at Dayrize?
Before joining Dayrize, I had two distinct career paths. The first half of my career was in the nonprofit humanitarian aid space, focusing on refugee camp management and disaster response, primarily in Africa. During this time, I helped with sustainability initiatives, such as bringing renewable energy into refugee camp healthcare settings.
The second half of my career was in corporate strategy in the U.S., helping large corporations better plan and execute their strategies. Dayrize represented a natural middle ground between these two worlds, allowing me to return to impact-driven sustainability work while applying the strategic skills I had developed in the corporate sector.
Business analytics has been a core skill across both career paths. Whether advising local governments, NGOs, or corporate stakeholders, the process of making data understandable, telling stories with it, and making it relatable to different audiences has remained the same. This shared approach has allowed me to bridge the gap between sectors, and my role at Dayrize brings together all of these experiences into one cohesive path.
In your view, how is AI shaping the future of Data Analytics, and what opportunities or challenges do you foresee in this space?
AI is solving a long-standing challenge in data analytics. We’ve been living in the era of big data for a while now, with datasets in the billions becoming commonplace. For years, organizations have been amassing data without a clear plan for how to use it — unless you were one of the largest tech companies with dedicated teams to mine it for insights. AI changes that by making it possible for smaller, less resourced teams to analyze vast datasets. Instead of conducting deep analysis on a thousand products, AI allows us to analyze millions, opening new possibilities for businesses of all sizes.
In sustainability, AI plays an especially critical role. Global supply chains weren’t designed with sustainability in mind, and the traditional data points we have — like cost, delivery time, and inventory — aren’t enough to measure sustainability. The key product data we actually need, like material sourcing and production methods, hasn’t been systematically collected because it wasn’t seen as a priority. AI offers a chance to bridge that gap, allowing sustainability teams to shift from being “data accountants” to being true decision-makers. By automating data collection and analysis, teams can focus on strategy rather than manual tracking.
That said, there are challenges, especially around transparency and reliability. In sustainability, you can’t simply ask an AI tool to tell you the carbon emissions of a product and expect it to be instantly accurate. Consumers, regulators, and other stakeholders want clear, credible data. It’s essential to understand where AI is pulling its data from and how reliable those sources are. The challenge is finding a balance — using AI to speed up processes while maintaining scientific rigor and traceability in the data. Bridging that gap will be essential to fully realizing AI’s potential in data analytics and sustainability.
Could you walk us through the upcoming update to the Dayrize platform, the new dashboards?
The new dashboards go beyond product-level insights to give users a full view of their impact at the portfolio, brand, supplier, and category levels. Instead of just seeing the impact of one product, users can now see the combined impact of all products and dive deeper into specific areas like suppliers or product categories.
What are the standout features and improvements users can expect in the updated dashboards?
There are several new features that make these dashboards much more powerful:
- Portfolio Impact Analysis: See the total impact of every product in your portfolio, with breakdowns by brand, supplier, or category.
- Product Comparisons: You can now compare products, brands, and suppliers to determine which have the highest impact and how they rank against each other.
- Data Quality Insights: View and understand the strength of your data—know which areas are backed by high-quality data and where improvement is needed.
- History-Tracking: Instead of viewing a single snapshot of impact, you can monitor changes in impact over time. For example, changes in impact scores as you add more data or receive more details from suppliers or if you change the design of the product itself.
- Drill-Down Capabilities: Start with a company-wide view of your impact and drill down step-by-step to specific brands, categories, or individual products, making it easier to pinpoint impact drivers and take action.
How do you see our dashboards enabling businesses to achieve their sustainability goals more effectively?
The dashboards make it easier for businesses to see how every product decision impacts their big sustainability goals. Most companies set company-wide goals, like reducing total emissions by a certain percentage. But those goals are driven by individual products, suppliers, and materials. With these dashboards, you can see how product-level actions contribute to company-wide goals.
What trends and innovations do you believe will define the future of sustainability analytics in business?
Right now, sustainability analytics is primarily focused on understanding the present state — getting a clear, reliable picture of a company’s current impact. This has been driven by corporate reporting requirements and regulatory pressures. Businesses have been focused on ensuring their impact data is credible, defendable, and reliable. But the future of sustainability analytics is about moving beyond reporting. The next big shift will be using analytics not just to track today’s impact but to drive strategies for reduction. Analytics will increasingly be used to inform strategy, prioritize actions, and guide investment decisions. Instead of just reporting on emissions, companies will use analytics to figure out how to lower them. The future of sustainability analytics will be about moving from passive measurement to active reduction, giving businesses the tools to not only understand their impact but to actively reduce it and move toward regenerative practices.
What advice would you give to companies struggling to scale their sustainability initiatives?
The best advice I can give is simple — just start. It’s easy to feel overwhelmed, especially for smaller companies that are new to sustainability. I’ve spoken with many businesses in this position, and the common thread is being overwhelmed. They see all these regulatory requirements they don’t fully understand, they worry their data isn’t good enough, and they feel like they need a perfect plan before they begin. You won’t create a perfect sustainability strategy on your first try — and that’s okay. Start small, build momentum, get your team involved, and refine as you go. Your data will get better. Your strategy will get sharper. Your goals will become more defined. The most important thing is to get moving. It will still be challenging, but once you take the first few steps, the path becomes clearer. Don’t panic. Don’t wait. Just get started.
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