Grant Brooke Twiga Finding Impact

FIP 30: Disrupting Markets with Grant Brooke

I was introduced to Grant through Christie Peacock (Episode 6). When I later met with him in a Nairobi lunch spot, he came across as an unassuming guy just minding his own business. A little into the conversation, I was struck by his immense curiosity – which is a hint at the qualities that have led him on this path of pitching to VCs with an Amazon-like business model. Grant spent a good chunk of his time in academia before settling on business, so understood economic theory and how well functioning markets should work. As you’ll hear in this episode, this deep knowledge in his subject matter paired with true authenticity, has undeniably led him and his co-founders to create such a disruptive business model.

On this episode you’ll learn:

  • How Grant spent 2-3 months on the road asking co-ops, county governments, farmers asking tons of questions, before realising the opportunity for business in the domestic market.
  • As a simple early stage pilot, they bought a couple of tuk-tuks (small three wheeler vehicles) and hired a small warehouse, to see what would happen if took products from the farm directly to retail.
  • They found that there can be up to seven trades between farm and final retail.
  • 2-3 months after starting their first banana pilot, they participated in a VC pitch competition, and received considerable interest from investors.
  • After sketching out what size the company could become and the many small sellers putting in small orders for produce, they soon realised that this would become a technology company because a traditional business could not cope with that many transactions.
  • In order to reach cash flow positive, they were drawn to higher margin products. But in focusing on scale, they realised they needed to chase the products with the biggest demand.
  • Before they take on a new product, they figure out the tipping point for how many customers they need to reach in a single day, which they build out first, which helps reduce wastage / maximise margins.
  • Their hub and spoke model allows a truck carrying 10,000 kgs of bananas to reach thousands of vendors around the city who only need 20-30 kgs every 2-3 days.
  • Twiga’s end game is that sub-saharan africa doesn’t need large scale wholesale markets or commodities markets. They need hundreds of thousands of small vendors on the end of their mobile phone ordering their stock. controlling pricing dynamically, with produce delivered to their shop, and we can let big data and predicative analytics pull purchasing power back to farmers.


Connect with Grant:


Nicole Van Der Tuin Finding Impact Podcast

FIP 016: Credit Scoring for Under-Served Populations with Nicole Van Der Tuin

For nearly ten years, Nicole has been working to get capital to places where it is scarce. She believes the cost of capital is central barrier to economic growth and development and she’s been focusing on ways to bring that cost down. In 2010 she set up First Access, a business that offers a credit scoring platform for lending institutions in emerging markets. In this episode, Nicole talks us through credit scoring for under-served populations and how this applies to any social entrepreneur taking on some level of risk with a lending product, such as asset financing or loans to customers.

Some of the things you’ll learn on this podcast include:

  • Ways to build up the “record of proof” for customers living in the informal economy, such as what you have earned, owned, spent.
  • How the emergence of mobile phones and the requirement to link SIM cards to people through some form of ID, has created the first mass of data, recording formal transactions for the majority of the world’s population.
  • How micro-finance institutions have been using a very labor intensive process for so long to offer small loans for people, creating a high cost per loan.
  • Also, how micro-finance institutions for too long have been non-digital and so leveraging the data they have on their customers has been hard.
  • The First Access analytics platform enables staff to act on patterns they’re seeing in the data of their customers.
  • The platform eliminates bias and ensures their decisions are made on the context of their country or region.
  • How using data analytics can reduce average customer acquisition costs dramatically, just by, for example, instantly approving any customer whose credit score comes within the top 5% of loan applicants.
  • Hiring a credit analyst would be a good move for any enterprise taking on some form of risk with a lending product.
  • A good first step for any social enterprise could be to simply start building up their data set to enable credit scoring faster at a later time. First Access can help organizations do this through a simpler, entry-level subscription which excludes the data analytics but ensures robust data collection using best practices.
  • We discuss distinctions between the lending products out there. One is small business micro-enterprise loans done through a customer evaluation process where you collect info about the customer before you lend them the money. This category is where you’re giving a borrower an asset that requires a down payment to ensure buy-in from that customer which predicts how likely they will pay and use the product.
  • Collecting data at the point of sale is good for your business, not just for potential credit scoring applications and assessing risk, but to know more about your customers which will make your sales and marketing more effective.
  • Email to request more info about credit scoring algorithms and other basic information to help improve your learning about this area.


Connect with Nicole: