Pivotal’s nature intelligence helps companies — especially those that rely on commodity supply chains — understand the real condition of the ecosystems they depend on. As ecosystems degrade, supply chain stability and resilience are increasingly at risk. We integrate data from ground-based sensors, satellites, and other sources to generate high-resolution insights into species, habitats, and overall ecosystem health. This gives our customers the truth about ecosystem condition, enabling them to take smarter, faster, and more targeted action to reduce the financial risks of disruption and build long-term competitive advantage.

Our mission is to drive better decisions for nature. By pinpointing where ecosystems are healthy or under pressure — and tracking the impact of efforts to restore them — we aim to transform how people value, protect, and invest in the planet’s natural systems.

This kind of impact is only possible at scale. As we measure more ecosystems, our nature intelligence becomes more powerful, helping decision-makers act with greater precision and urgency. But to do that, we need a lot of data. Only broad, deep biodiversity datasets from ground-based data capture can generate the trustworthy intelligence needed to achieve our mission.

This article explores how we’re scaling the essential data collection that underpins our mission — by training local partners all over the world, from land managers to community groups, to gather the high-quality, on-the-ground data that fuels our analytics.

Why does digital data capture require training?

All of Pivotal’s data sources are digital, which means ground-level data is collected using sensors. So why is training necessary? Isn’t it just a matter of using a smartphone or deploying a sensor? Doesn’t data quality matter less than data volume?

In fact, the quality of any data analysis — including our nature intelligence — depends entirely on the quality of the input data. If that data is biased, skewed, insufficient, or inconsistent, the results probably can’t be trusted.

It’s true that one of our key safeguards is working only with digital data. Digital sensors are easy to deploy, can be calibrated for consistency, and remain in the field far longer than people, capturing more robust and continuous data. Machines are also less prone to bias in what they sense and record. And we run automated quality checks to ensure only reliable data enters our pipeline.

But that doesn’t mean digital data can be collected in just any way. Human error and bias still play a role. A sensor might be deployed with incorrect settings, or placed where someone thinks there are interesting species rather than according to a scientifically rigorous sampling design. That’s why training remains essential.

For example, one of our core indicators is the measured completeness of species composition and abundances across a range of taxa — in other words, what proportion of expected species are present, and in what relative abundances? Inconsistent or incomplete ground data can lead to false results, such as assuming a species has disappeared when it simply wasn’t recorded.

Everything about our approach is grounded in rigorous science. From designing statistically driven sampling plans to calibrating sensors, every step is based on ecological science and years of testing. Through our world-first training programme and field app, we enable people to collect data that meets these scientific standards.

Scaling Data Collection Through Training and Technology

We make it possible for customers and partners to gather top-quality data through digital, on-demand learning tools that are accessible, practical, and detailed. These tools empower people to collect the data that global nature decisions increasingly depend on.

On-demand Learning Management System

Our remote, online training platform is the first of its kind. It enables anyone, anywhere, to learn how to collect biodiversity data in line with our protocols. The course is divided into flexible modules made up of instructional videos, visuals, and written guides. Learners can go at their own pace, in any order.

The online course works both as a standalone tool and in combination with in-person, hands-on training. It’s available on desktop or mobile devices, can be translated into most major languages, and includes downloadable checklists and offline manuals for field reference.

The Pivotal Field App

To make third-party data collection as easy and foolproof as possible, we developed a free smartphone app that guides users in the field. Before collection begins, our software exports a map to the app, showing the scientifically determined sample locations and the sensors needed at each one. Users navigate to each location using the app, which then provides step-by-step guidance. The app tracks progress, so users can see what’s been completed. It also works offline, making it usable even in remote areas without network coverage.

In-person Training

While the online course and field app provide everything needed for high-quality data collection, some people prefer hands-on instruction. In these cases, one or two of our experienced Field Surveyors deliver practical, train-the-trainer sessions in the field, equipping our partners to train others in turn.

To learn more, we spoke with William Jones, a Pivotal Field Surveyor who leads nature data collection and trains organisations and communities around the world. Here’s a behind-the-scenes look at his work and how he helps scale data collection globally.

Interview with William Jones, Pivotal Field Technician

What does a typical in-person training session involve?

My first job as a trainer is to reassure people that our protocols really are as straightforward as we say. It’s common for people to feel overwhelmed when they first see the equipment, but it’s incredible how quickly they pick it up.

I start with an overview of our protocols, why data quality matters, and how our approach makes collection easy and fast. Then we head into the field, where I demonstrate the equipment, and we run live trials together.

What do you enjoy about teaching others?

I’ve trained everyone from professional ecologists and land managers to local communities and people who’ve never used a camera trap before. It brings me real joy to see someone go from novice to confident data collector in just a few hours.

I also love how we’re disrupting the old-school approach to biodiversity data collection. We don’t need teams of ecology PhDs in the field for months. With our digital technologies, optimised sampling plans and easy-to-follow training materials, anyone can collect vast, multi-taxa, auditable primary datasets, quickly and accurately. It’s accessible and inclusive.

The methods are so scalable that a small field team can collect data across large areas very quickly. While a 20,000-hectare site will take longer than a 20-hectare one, the difference isn’t huge, and our methods are so scalable that for a field technician, the logistics and execution are very similar, however large the site.

Sometimes Pivotal collects data directly. What does that involve?  

While we’re scaling up third-party data collection globally, there are times when we need or choose to do it ourselves. So a big part of my role involves travelling to deploy sensors and collect data myself.

How do you prepare for a data collection mission?

My role starts long before I set foot in the field. Each data collection campaign is planned in detail. We use algorithms to generate a scientifically validated sampling plan that identifies the precise number and location of data sampling points required to provide actionable intelligence, balancing data needs with feasibility and cost.

Once that plan is drafted, I assess whether it’s workable given the habitat, season, and time available. This is when I begin working with customers and their local partners, who can share useful on-the-ground insights.

Then comes the logistics. I like to think of this stage as a game of Tetris. I work to fit all the pieces together so that once I’m in the field, I can focus solely on data collection. That means arranging permits, like access to field sites or drone permissions, and researching any local cultural sensitivities that might be relevant. Local context is essential for a successful mission.

What happens during data collection?

I use the Pivotal Field App to guide me to sample points and tell me what to deploy at each one. I use an array of tools—camera traps, acoustic sensors, drones, high-resolution cameras, eDNA kits, and more—to capture biodiversity data across multiple taxa, including birds, bats, mammals, frogs, plants, and trees, and on the health and structure of habitats.

And after the data is collected?

I run initial quality checks before uploading the data to our cloud for analysis. For instance, I check that enough acoustic devices recorded correctly and that photos aren’t blurred. This is done quickly and simply, using an automated tool developed by our engineering team, resulting in high-quality primary data inputs from the very beginning.

I feel very privileged in my role as a field surveyor. I get to see both what the conditions are like on the ground and the final results, post-analysis, on our data visualisation platform. When I see the list of bird species that we have detected matches so completely with what I saw and heard myself, it makes me so confident in our approach! It’s not just fieldwork—it’s the foundation of a smarter, more data-driven approach to nature intelligence that’s easy, scalable, and affordable for anyone—from corporations looking to measure their impact and their supply-chain resilience to conservationists trying to protect critical habitats.

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Want to join Will and collect data around the world? We are currently recruiting for Field Techinicans based in Brazil. Please apply to join by clicking here. ‍

If you'd like to secure real, auditable evidence of on-the-ground ecosystem health to support critical operational decisions across your supply chain, contact us on info@pivotal.earth.