Author: Anne Konertz

  • How to 20x climate reporting

    How to 20x climate reporting

    Imagine traveling from Boston to New York City in the 18th Century. The long and uncomfortable journey takes 20 hours in a horse-drawn carriage. Now fast forward to today, where you can reach it in under an hour by plane.

    Recently, Seaspray Labs got the opportunity to re-design a greenhouse gas inventory and reporting tool. Compilers use the tool to estimate yearly national emissions for agriculture and report these to the UN. By transforming an old tool into a modern, user-friendly web app, we shortened the time it takes to create an inventory from 20 hours to one.

    How did we do it? Instead of just rearranging components of the existing tool, we decided to start from scratch. We interviewed inventory compilers and trainers to understand how they work, what data they have, and what their goals are. The tool is based on very technical and complex guidelines from the UN. It took a long time to study the guidelines and understand how the inventory process works for each emission source.

    Next, we designed a mock-up of the inventory process. We reviewed and co-designed our mockups regularly with a group of climate scientists. The number of iterations we went through was grueling. On the bright side, we could tell with each iteration that the product was getting better and better.

    We designed a responsive and adaptive experience. Inventory compilers can enter their datasets, from basic numbers to complex data collections. For each source they can choose what estimation method they’d like to use. Once the mock-up was more polished, we added instructions and help text so even unexperienced users would be able to create inventories.

    And then came the moment of truth. As soon as the livestock module, the first of three modules, was implemented, we tested it with end users. For the old tool, a one-day training was needed to learn how to navigate the tool. On a second day, compilers would enter their livestock data with the help of a trainer.

    When we tested the new app, users were able to complete the livestock inventory in under an hour, without any assistance. The app guides users through the process, and it is so intuitive that users know how to navigate by themselves. What a success!

    Starting from scratch, studying extremely technical guidelines, and going though countless iterations paid off: The inventory process is transparent and clear. It can be done without any assistance, and it takes only 5% of the original time. Funding climate reporting apps leads to better climate intelligence. It can also lead to increased productivity and massive cost savings.

  • How to make climate reporting fun

    How to make climate reporting fun

    As part of the Paris agreement each country is estimating the amount of greenhouse gases released into the atmosphere. The emissions are then reported to the UN. Think of it like tax time for emissions. The idea is to track and reduce emissions over time. How do countries estimate yearly emissions? Today, a mix of sensor data, survey results, and expert options are used to create an inventory. For the agriculture, forest, and land use sector there are tools to help with this process.

    One of these tools has been developed by climate scientists. It is very well thought out, has incredible features, and allows for maximum flexibility. The catch? It is very hard to use. So we started an experiment: What if we added a user experience expert to the mix and redesigned this as a modern, web-based app?

    To make apps user friendly we start by learning from end users: Who are our users? What data do they have? What are their biggest roadblocks? The wealth of information we get from end users is always humbling. We summarized our insights into three lessons:

    Lesson 1: Guidance: Often inventory teams don’t have enough time and resources to read the complex guidelines provided by the UN.

    How do we guide our users? In depth familiarity with the guidelines is great but not necessary to use our app. It guides compilers through the inventory process and points to specific sections in the guidelines to learn more.

    Lesson 2: Flexible usage. Some teams estimate just one source, while others estimate all sources.

    How do we design for flexibility? We let users choose what they want to do and adapt the experience to their needs. Part of this is approach is to only ask for data if and when they are needed. An advantage is that we are avoiding bottlenecks by not asking for data they might not have.

    Lesson 3: Adjusting complexity. Some compilers have basic datasets with gaps, others have very complex datasets.

    How do we design for different inputs and estimation methods? We ask users what kind of data they have and then tailor the experience to their personal needs. Rather than a static interface, this app guides the compiler through the process. Users view personalized pages based on the complexity of their dataset.

    Screenshot

    How do we make sure this is what users need?

    We started with high level prototypes and constantly iterated to make them better and more accurate. Weekly expert reviews and collaborative design sessions helped with constant improvements. Once the developers had created a working app, we tested it with users. The results were mind blowing:

    • Intuitive: Our test users completed the emission estimation on their own, without any training or help.
    • Easy to use: Our test users entered simple datasets as well as for complex datasets. They navigated the app easily and compared results for the different methods.
    • Fun: This is maybe not the first word that comes to mind when thinking of compiling an inventory, but our test users had fun! They enjoyed seeing graphs, playing with real-time emission results, and tweaking inputs to study the results.

    Where do we go from here? The app is still in development, and we hope to overcome obstacles along the way. Our goal is to roll this out to make climate reporting easier, faster and more accurate.

  • Top 3 challenges for livestock emission calculators

    Top 3 challenges for livestock emission calculators

    Seaspray Labs is currently designing and developing livestock emission calculators. But let’s step back. Why do we need to quantify livestock emissions? Most countries have agreed to reduce greenhouse gas emissions. Now we need reliable ways to measure and track emissions to see where we stand. There are several greenhouse gasses that are emitted from livestock farming. For example ruminants, such as cattle, emit methane, a potent greenhouse gas. The good news? There are many things we can do to reduce emissions, from eating a more plant-rich diet to feed adjustments for cattle. How can we quantify and measure current emissions and future reductions? We are designing a calculator for livestock emissions and here are our top three challenges.

    Challenge 1: Different experience levels. Who are our end users? We have expert users, who know all the details of climate science for livestock. One the other side we have absolute beginners, who have been tasked with creating an inventory for livestock emissions without having prior experience in this field. How can we explain and simplify this extremely complex process and at the same time allow experts to quickly enter data and navigate results?

    Challenge 2: Limited data. Inventory compilers enter or import activity data to then estimate emissions. For livestock this means data such as how many animals, at what temperature are animals being kept, and what manure management systems are being used. Some users have extremely limited data sets. How can we allow these users to plug in the data they have and generate comparable emission estimations with the help of default values?

    Challenge 3: Complex datasets. On the other hand, there are inventory compilers with extremely complex datasets. Their livestock species are divided into populations and subcategories. For each subcategory they have different temperature and manure management system usage data. While this is great for reducing uncertainty, it poses other challenges. How can we provide estimations that are transparent and easy to manipulate?

    Design thinking is about solving problems and tackling challenges. Let’s hope we can solve these challenges and address the different user needs. Our goal is to make emission estimation easier, more user friendly, and more transparent. Seaspray Labs works to quantify emissions and hopefully bring us closer to a low carbon future.

  • How can we make climate reporting easier?

    How can we make climate reporting easier?

    This story starts in Japan, where the United Nations body for climate reporting, the TFI, is based. Countries all over the world report yearly emissions to the UN. It’s like a financial report but for greenhouse gases. Countries determine their emissions and removals of greenhouse gases and send the final balance sheet to the UN.

    This sounds easy and straightforward, but in fact it’s a highly complicated process. There are tools to help, but most are old. While an enormous amount of experience and thought went into the development of existing tools, they haven’t been designed with end users in mind.

    This is where Seaspray Labs comes into play. We are currently working on a web-based app for greenhouse gas inventories. Like most inventory tools it is based on the guidelines developed by the TFI. Here are our design questions:

    • How can we simplify the inventory process?
    • How can we help and guide users through the process?

    Here are three steps we are taking to tackle this:

    Step 1: Understand the inventory process. When designing interfaces, this step is often skipped, even though it’s so important. How can designers simplify a process if they don’t have an in-depth understanding of it? This step includes user research to see how current users are using existing tools. During user interviews we learned how inventory compilers approach their inventories, and we heard about their struggles with existing tools. In the context of a greenhouse gas inventory, this step also includes understanding climate science and the guidelines for climate reporting from the TFI.

    Step 2: Design a simplified workflow. The majority of our users are newcomers. How can we make the user interface straightforward for them? We identify the actions for a simple inventory every step of the way and hide all other functions. This way, we don’t overload newcomers with information that doesn’t apply to them.

    Step 3: Architect the tool with flexibility. While the majority of our users are newcomers, we also have many expert users. They have more complex datasets and need more sophisticated estimation methods. We need to allow for flexibility. Functions and actions for expert users, such as importing massive data sets, are part of the design to address user needs from basic to extremely sophisticated.

    What do I like most about designing tools for climate reporting? There are existing tools out there. They are not easy to use, but a lot of experience and thought went into their development. It’s a fun challenge to transform them into intuitive, easy to use apps. And hopefully they can help to make climate reporting easier and more accurate.

  • Can an API Make Rice Farming More Climate Friendly?

    Can an API Make Rice Farming More Climate Friendly?

    This story brings us to Vietnam where I presented at a webinar, organized by the IFC, the International Finance Corporation. Thankfully highly skilled translators were able to translate in realtime to and from Vietnamese to allow meaningful discussions across the globe. The topic was ”Digital Disruption in Agriculture Vietnam – GHG Emissions Measurement and Reporting Tools”. My talk covered a joint project from Seaspray Labs and Irri, the International Rice Research Institute.

    In other posts I already talked about the climate impact of rice and how different farming practices can drastically cut emissions. To cut emissions, we need to measure existing emissions and then make ongoing assessments to monitor and reduce emissions. IRRI’s scientists have developed highly accurate rice emission calculators over many years. These were originally Excel based and Seaspray Labs partnered with Irri to develop web-based versions of the calculators. Now we are going one step further and developing an API. It will allow partner organizations to access IRRI’s calculator in their own apps and services. This is how it works:

    This is how the API works for a fictional carbon credit app for rice farmers. The app gets rice farming information from its end user. These are the inputs the API needs to calculate emissions. The API then sends the results back to the app and the app can present these results meaningfully to its end user.

    This is one example I showed in my talk. A second example showed a very different app for a very different user group. I mocked up a regional planning app. Vietnam wants to reduce methane emissions by 30% by 2030 and moving to low-carbon rice production will play a major role. My mockup shows how a planner can adjust the percentage of low farming practices and traditional farming practices to explore emission reductions of entire regions by 2030.

    These are just two examples. The API is currently in development and I’m excited to see what other ideas IRRI’s partners will come up with. Hopefully these apps and services can translate into climate action for rice farmers, agriculture organizations, food companies, and consumers to reduce our carbon footprint.