Location, location, location: Helping FarmDrive break through the barriers of distance
In 2017, EWB fellows helped FarmDrive scale their mobile platform, which provides credit scores for smallholder farmers in Kenya so they can access credit to improve their farms. EWB Fellows Cale Ettenberg, Rasheeda Slater and Ross Edwards designed, tested and implemented a new algorithm on FarmDrive’s SMS platform that precisely determines a farmer’s location. Location informs a farmer’s credit score by specifying data on a farm’s local environmental conditions, which affect crop productivity.
Cale, Rasheeda, and Ross found a way to determine a farmer’s location through the use of text messaging on analog phones, no GPS required. Previously, the team was personally visiting each farm on the platform to determine their locations- a big limiting factor to the venture’s growth. Now, farmers can answer a series of text messages through the FarmDrive platform about their proximity to known locations of schools in Kenya as a way of positioning their farm.
This is a sustainable, scalable approach for determining a farmer’s location as it builds on how farmers were already using the platform. They submit other data about themselves and their farms to inform their credit score, such as their age, what kind of crop they grow, expenses, revenue and more. FarmDrive now has the potential to reach tens or even hundreds of thousands of registered farmers, delivering strong credit scores that ultimately help farmers apply for and secure loans.
With more precise information on farmer location and stronger credit scores that reflects local climate conditions in an area, FarmDrive also improves its services for their clients. They can help farmers using the platform better understand their local geography and increase their crop yield.
Through these efforts, Cale worked hard to ensure user-friendliness and good system design to collect accurate data for credit scoring and, ultimately, encourage loan repayment through SMS. Ross and Rasheeda, two university students turned start-up talent, helped test Cale’s multiple algorithm iterations to determine which was the most accurate within the local context visiting countless farmers across Kenya.
Read Ross’s blog about how the team worked to find FarmDrive’s farmers, here.