The climate is changing in the tropics, as with the rest of the world. Changing rainfall patterns and seasons mean many tropical areas are now significantly wetter or drier than they were a century ago. 

Until recently models for predicting weather failed to provide accurate forecasts for the tropics, home to 40% of the world’s population and 80% of whom are smallholder farmers. Reliable weather forecasts can minimise risk and maximise yields at every stage of the farming cycle, and can help to double the income for small scale farmers.

After studying physics and meteorology in Sweden, Liisa Petrykowska, 31, thought it was about time to develop a weather forecast for tropical regions, and in 2009 gathered a research team in physics & meteorology from different renowned universities and research institutions such as NASA. Together they spent four years developing new technology that increases the accuracy of tropical weather forecast and started Ignitia - the world’s first highly-accurate tropical weather forecasting company. The company’s model is built on disruptive technology and creates GPS-specific forecasts that are twice as accurate as existing models to help take the guess work out of small scale farming.

Based in West Africa, Ignitia partners with local telecoms providers to send 48 hour forecasts plus monthly and seasonal outlooks to farmers via SMS. The low-cost subscription-based service is paid for through a micro-payment scheme to help farmers avoid adverse impacts of an ever changing climate.
Since the first trial, Ignitia has grown fast. Recently, it started its third company based in Lagos, Nigeria. Ignitia's technology (ISKA) is currently accessible to 12 million subscribers in West Africa.

Iperium caught up with Liisa Petrykowska to discuss the social enterprise and the challenges the company faces while scaling up its business model.

IP: How many farmers currently use your service?
Since our first trial in 2013, which offered 3,400 small scale farmers daily forecasts, we have grown to around 100,000 to 110,000 subscribers. Our subscriber base is growing rapidly so if you ask me next week I may have a completely different number. Since we have implemented partnerships with telecommunications companies our numbers have grown significantly. Last year we also entered three new countries in Africa, Mali, Senegal and Burkina Farso.

IP: How does the technology work?
Most rural farmers are using basic mobile phones which can be used to access different services from operators. Therefore, we use Unstructured Supplementary Service Data (USSD) [sometimes referred to as quick codes or feature codes] which can communicate with service provider's computers. Farmers can enter a short code into a phone, such as *445#, and a menu will appear where they can choose to subscribe to certain services. The forecasts are then delivered via a text message.

IP: How important is it for farmers to accurately predict rainfall?
Every action a farmer needs to take out in the field is dependent on the weather. The main reason is that they don’t have any kind of irrigation possibilities so decisions on when to plant, harvest or apply fertilizers are directly connected to the weather and if they time these actions wrong then their seeds or crops will die. For example, if a farmer applies a fertilizer on his or her land and it rains later that evening it will be washed away and their most expensive investment is down the ditch.

IP: How much does the service cost and how does it compare to a farmer’s overall investment?
The current cost of the service is around four cents per message. In total it’s around 1% to 2% of a farmer’s yearly investment.

IP: What steps took your idea from conception to commercilisation?
The initial thought came out of frustration followed by an idea in 2009. At the time I was working with one of NASA’s satellites called Calypso and I didn’t have any data for a particular region, so I gathered a team of scientists with expertise in specific fields who were also curious about looking into the problem. In those early years we started just with research funding so was pretty tough at times and some days we only ate pesto and pasta! From the outset we faced research-based challenges with certain things not going to plan, such as trying 100 different ways of slightly improving the forecast but it still not working. At the same time we needed to raise funds while figuring out exactly who would gain the most from receiving our forecast information and working out how we were going to sell the service. All these questions felt so fictional when we didn’t have a product, yet thankfully three years of research led us to a pretty reliable forecast which is currently around 84% accurate, yet differs a little country by country. During the process we also spent time learning about the markets we were entering and took time to set up the offices before commercialisation happened in 2013. It is challenging to start something new and especially an innovation that is very high risk and built on technology that doesn’t exist. It’s certainly not suited for everyone.

IP: What was your roll-out strategy?
Our plan was to make a mass market product for the wider population, yet prior to our launch we were frequently told that farmers didn’t have the willingness or the money to pay for the service, and especially not for information. We are now active in five countries in West Africa and I think that 2018 will be the year where we decide where to go next. As our product is aimed at regions with tropical weather conditions the alternatives are India or South East Asia. In both of these locations there are many farmers in need of our product.

IP: Any notable success stories?
I know one farmer who had been using our service and received a forecast saying that the rainy season was going to be much drier than usual. Based on this information he decided not to plant rice like everybody else in the village and chose eggplant instead. One day when everyone in the village started fertilizing, his forecast told him that it would rain heavily that evening so he waited until the day after instead. As predicted, heavy rain arrived that evening and the villagers’ fertilizer ran off the fields. A dry season followed and most of the rice that the other farmers had planted didn’t grow, yet when it was his time to harvest he had so much crop that he shared it with the rest of the village. The others didn’t grow a grain of rice that year so he was deemed a saviour.