COP26 – the largest gathering of world leaders in the history of our planet to discuss the future of our planet – concluded with much said and unsaid. Big commitments were made in the areas of fossil fuels, deforestation and finance, with specifics laid out about how these commitments can be achieved.

Agriculture also received its day, with nations agreeing to change farming policies and protect nature. The “how” component of these commitments is less certain.

What is clear is: Much will be expected of livestock farmers. More than 100 countries agreed to the Global Methane Pledge and its commitment to reduce methane emissions 30% by 2030. A smaller number of countries signed on to the Policy Action Agenda for a Just Transition to Sustainable Food. It provides a high-level roadmap for how a range of policy changes can support desired outcomes.

Even with these more aggressive targets and established commitments, though, some big questions remain: What on-farm changes will have the biggest impact? And what help will farmers be given in making those changes?

The Food and Agriculture Organization of the UN (FAO) provides a comprehensive list of 72 tactical recommendations to livestock farmers for how they can mitigate emissions. The recommendations span across land use change, herd management, manure management and regenerative practices. Farmers must then decide which strategic combination of the tactics is right for their farm.

Many of the tactics require measurement of various activities, soil lab samples, water and energy use. Data collection is manual and time-consuming. Outsourced consultants typically visit a farm, measure the activities and input measurements into complex models. Farms are then scored on their sustainability criteria. A year later, the consultant delivers a full report. This yearly cycle simply cannot scale to a higher frequency of data capture and analysis. If we continued with this approach, we would only have nine measurements before 2030. Eight cycles to transition to the new aggressive operating targets.

Technology can and must be part of the measurement solution. Whether this is through IoT-based solutions that capture and transmit data to a central hub for analysis, or satellite and drone-based systems, or more likely a combination of all three, technology can theoretically fulfill the need to measure what is happening on farms with much greater degrees of frequency and accuracy. It can, in theory, help us fix the problems we find and accelerate progress toward shared goals. This approach has worked for the technology sector. Transferring it to agriculture makes logical sense.

If only it were that simple.

The average U.S. dairy farm generates several thousand data points per week related to operations and animal behavior. Business metrics like milk price, labor availability and fuel costs are also constantly monitored and evaluated. Add the thousands of possible tactical combinations for a net-zero transition plan, and the decision-making matrix quickly becomes overwhelming.

Naturally, farmers look for assistance. A typical dairy works with several suppliers that provide recommendations on feed, cow health and genetics. And each farm typically sells raw milk to one major buyer. The power dynamics of this ecosystem are complex, but these suppliers are usually who farmers trust most. Much like a “leadership team” in a corporate environment, this advisory group is fully vested in strategic and operational decisions, and these relationships can go back decades.

As the animal agriculture sectors aim to achieve more aggressive emissions reduction targets, suppliers and advisers are ramping up to provide much-needed, more data-driven advice. C-suite leaders are scrambling to empower their field teams with tools that facilitate technology-based recommendations and collaboration.

But each member of the farm leadership team tends to have their own proprietary data, a different perspective on what will work and what won’t. For farmers, this compounds decision-making complexity. As any effective manager of complex systems knows, a disconnect in data, perspectives and interests will result in subpar outcomes at best or, worse, a failure to act.

In short – no matter how much data we can generate from a farm, if we cannot align stakeholders on a common data vocabulary and verifiable outcomes, any stepwise change in emissions reduction is unlikely.

But there is hope.

Initiatives like Danone’s Farming for Generations are bringing together industry leaders to test, measure and provide data-driven evidence that regenerative agriculture practices create positive outcomes. Coupled with advanced predictive analytics, these practices can be modeled to simulate outcomes and provide daily recommendations to a larger volume of farms.

Another example is Arla Foods’ Future 26 strategy, which provides guidance to farmers that combines financial impact with sustainability impact. And New Zealand’s Fonterra is incentivizing farmers to adopt specific, sustainable initiatives through its milk price.

All of these initiatives are leveraging data and collaboration and building trust with farmers to enable a transition toward lower-emission animal agriculture. We will need to lean on technology to scale up, ideally with a neutral technology platform that brings farmers and advisers together with high-quality insights with predictive capabilities.

This pathway is possible. By using technology to standardize data and give stakeholders a common vocabulary, we can accelerate progress. We can achieve our ambitions. The time to choose this path is now. Eight years will go quickly.