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Enabling user-inclusive innovation in African agriculture

Ignitia has developed a disruptive technology that allows smallholder farmers in West Africa to access accurate weather predictions. Engaging with local partners and initiating reliable impact measurements were key factors to gain trust and scale-up the business.  

Within ICT there are a few successful examples of technically advanced solutions that radically change opportunities in underserved markets, such as mobile payment solution M-Pesa. However, there is a lack of similar successful examples by small and medium-sized enterprises (SMEs) or new ventures. Many companies manage to do a promising pilot, but to execute a scale-up has proven very complex. The reasons are still not well researched and current literature for scaling strategies in underserved markets are simply not proving to prepare or guide entrepreneurs well enough, with exception of a few hands-on business accelerators such as Dasra (India), the Unreasonable Institute (US) and Villgro (Bangladesh).

One longitudinal study of the Royal Institute of Technology in Sweden focuses on how innovative entrepreneurs could scale-up while engaging with end-users who are poor, live in rural areas and often are low-literate. The study includes the company Ignitia, with its headquarter in Sweden and subsidiaries in Ghana and Nigeria. It all started with the realisation of a young meteorologist that there were no accurate weather forecasting models specifically developed for tropical Africa. Existing forecasts provided information that was more often wrong than correct, leaving farmers trying to predict changes in weather based on observing nature. The basic need for accurate forecasts is to get a good estimate of whether it will rain or not, sufficient for sowing and applying fertilisers, and to plan the harvesting. Few farmers in Western Africa have irrigation and low productivity effects the economic risk of buying high-quality inputs that may go to waste if the farmer has little idea whether the coming month will be wetter or drier than normal.

Finding local partners

A team of young entrepreneurs decided to set up the operations of Ignitia in Accra and developed an enhanced weather forecasting model. The idea was to deliver 2-day forecasts in such simple format that the simplest phone could be used and to the lowest possible cost for the user. Still, the forecast had to be very accurate, not just for a district, but at the location of each user’s farm.

One of the first practical challenges was the frequent power cuts, which led the team to put the supercomputers that are critical in processing the huge amounts of satellite data and run the algorithms that the team developed, in Sweden instead of Ghana. It took two years (and a total of 15 man years) to research and develop the high-resolution tropical forecast model before the service was piloted with farmers in Northern Ghana.

During the pilot phase the business model was tested. First of all, how to engage with local partners such as farmer cooperatives and NGOs to make farmers aware of the service and to train them. If these partner organisations see the service as a productivity-enhancing tool, they may be willing to pay for it on behalf of the associated farmers. Therefore, Ignitia first researched and networked its way among local farmer associations and international development communities to find the right local partners. In parallel to this, the company researched farming practices, so that it would understand better how farmers would use weather information depending on type of crop and different farming methods.

The local partners became important actors that provided the company also with feedback on how the service was perceived in terms of accuracy over time and to evaluate whether the service influenced farmer’s behaviour. Once these factors have been validated and impact measured, Ignitia is better equipped to approach more partners, which are essential to reach out to the poorest and the most remote farmers in Western Africa and for the business model as local partner organisations pay for the forecasts on behalf of the farmers. The other important channel to market the service is offering the tool through a mobile operator via short code so that any person can subscribe to the service. The users are charged just a few cents per day from their mobile credits.

Learning from the illiterate users

Symbols for clouds, rain and sunshine would help low-literate and illiterate users to understand the forecast, the team initially thought. In addition to the symbols, these messages also included the number 1, 2, and 3 to indicate how certain the forecast was. However, the number indication caused a lot of confusion. The decision was made to train farmers on this rather than taking it out of the message, as the message could be misinterpreted that the company is dictating the weather rather than predicting it. And when international staff in one of the NGO projects pointed out a problem with the symbols, they were changed into words. The users may be illiterate but they have proven perfectly capable of recognising the few words that are used in the forecast.

A start-up has to deal with the many mixed feedback messages that it receives from end-users and clients. This should certainly not be interpreted that decisions to change things are not necessary, but must be inspirational for further development of the ICT service and business decisions. Today, the company has a marketing team that includes competence in anthropology and have introduced a rapid-prototyping process to test marketing ideas. Getting to know markets and end-users, whose preferences vary a great deal across such diverse countries as in West Africa, is expected to take time and require testing of different approaches. Observations of what people do and the influence on behaviour changes as they interact with ICT based services, rather than interviewing, would sometimes be more effective to overcome language barriers and biased responses. For a small enterprise with very scarce resources this is rarely feasible.

Impact measurements

In the case of Ignitia there were some external studies that gave the company indications that its ICT tool was helpful for smallholder farmers to increase their productivity, which in turn may lead to increased economic status and poverty reduction. Any business that produces a type of decision tool for a farmer, needs to be careful with impact measurements as it has to measure changes in behaviour of farmers and then try tracking what the effect of this changed behaviour could be. For example, a willingness to chose higher quality inputs and more fertilisers, because they are more confident about when rain is coming by using the ICT tool, which then may in turn lead to higher yields. A study done by students at Yale has given Ignitia preliminary results that their service indeed does influence farmers’ behaviour and that the forecast is often shared among neighbours.

The Ignitia entrepreneurs have also been subject of questioning and outright suspicion from international meteorology institutions, due to their claims of achieving higher accuracy than other, more established organisations. Part of the controversy is not about the science and what the company has managed to develop, but comes down to the start-up being a private company, which is selling its services in low-income markets. A start-up that is disrupting a traditional sector, is not welcomed by all with open arms.

Related links

Official website of Ignitia

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