Financial Inclusion by Design: AppLab Money Incubator Case Study
Many criticize financial service providers for not being demand driven, especially in the developing world. Most of the products they offer are not tweaked to suit local needs, and look remarkably similar to those in more developed markets. This lack of customization leads to a devastating outcome—a problem of financial inclusion that makes three quarters of the world’s poor invisible to the formal financial sector.
But the stark reality is that the industry is changing. Technological breakthroughs like M-PESA are bringing a slew of new and aggressive players—from start-ups to middleware and white-label solution providers—into this space. And existing market leaders are reacting.
Earlier this year, Safaricom announced plans to appoint a head of innovation and a board to build relationships between Safaricom and the thriving Silicon Savannah tech community in Kenya. Safaricom will select prime ideas, test them in an incubation center, and prepare them for commercialization. They further committed nearly $240,000 (20 million Kshs) to Strathmore University in Kenya to set-up and run an incubation facility called @ilabAfrica to identify talent, encourage creativity and support innovation.
This is the beginning of an interesting trend in the industry—players are waking up to the opportunities, creating structures of innovation within their firms, and focusing on becoming more adept at delivering both efficiency and innovation to their customers.
In the same vein, Grameen Foundation, MTN and CGAP launched the AppLab Money Incubator a year ago, in part, to develop a human-centered design process that shows players with an appetite to go down-market that innovation can be cost-effective and impactful and can also lead to new areas of growth. Unlike most organizations that actively choose to innovate, we have had the luxury of time, money and a very talented team that focuses exclusively on creating and scaling powerful products that are ripe for adoption by poor customers. Although we are still engaging in this process, we wanted to share the first part of our story in a case study.
It recounts two key phases of the Incubator—the set-up, and research and ideation—and includes our key insights, with an emphasis on our fast and fruitful failures. This story is a must-read for anyone who works in the industry and wants to stay afloat as it evolves. Below is a sneak-peak of some lessons:
- Hire a team with the right skillsets: Innovation requires a strong team with complementary skills—from service designers, to business developers and data analysts. With a diverse cross-functional team, you will see magic start to happen when they sit in a room and come up with breakthrough product ideas. Do not rely on marketing or technology departments alone to develop breakthrough products.
- Be nimble and flexible in your approach to innovation: Do not fix yourself to one approach. Instead, develop a practice that works for your business. Give yourself the flexibility to change direction quickly, and focus on testing the process as much as the resulting ideas. Ensure that you identify the methodologies that yield the most powerful insights.
- Synthesize your results, and test ideas early with customers: Step away from the field often to synthesize data and package it in a clear and actionable manner. Run sessions with key team members to convert these insights into product ideas, and ensure that these ideas are put in front of customers as early as possible. Fail fast, and allow weak ideas to die early but put ample energy into refining the most promising.
- Know the value of different research techniques and data sources: Survey data or data mined from a company’s database facilitates generalizations of customer needs, wants and behaviors, which is valuable for segmentation. But only the qualitative data collected through progressive research techniques can get at why customers behave in the way they do. Such insights are vital for product development and, combined with the generalized data, can lead to products that make sense for the masses.
- Find innovative ways to slice and dice your market: Segmentation is part art, part science, and demands the right skillset to create meaningful and actionable market segments. Find organizations that know how to do this properly, using innovative ways to slice and dice your market. Test your ideas within each segment to identify differences in usage patterns and cultivate more tailored marketing approaches.
In the coming weeks, we will describe these insights in more detail on this blog. We encourage you to review our case study and send us your comments, especially if your views differ from our conclusions. We hope to use this material to encourage organizations to not only think about, but also engage in, more innovative approaches for giving the poor the services they need and deserve. In this changing industry, we believe, planning and testing methods for understanding down-market customers is both possible and critical to success.
Photo Courtesy of Grameen AppLab
Great approach to move the financial institutions beyond payments and also to think about innovation. I have been in the banking industry for years in the UK. The problem that you point out is global and not unique only to poor countries. Let's hope that there is a change in this approach in the coming years.
You are spot on when it comes to qualitative data and progressive research. I believe lack of reliable data is the main reason financial experts have got products wrong despite many years of experience. Getting useful qualitative data requires time, and progression. A subject will not always give actual insights in normal planned interaction (interview) time. Maybe it is human nature, or the fact that the 'environment' changes during formally organised sessions and because of this research misses out on useful qualitative data.
One of the methods I have used to get useful qualitative data is listening in to conversations on the subject of research 'unobserved' and asking questions to clarify later. That could happen in a public place or over a radio program (with people calling in). I have also experimented with getting useful data while riding on boda boda (motorcycle taxis) - taking care not to divert the attention of the cyclist off the road.
Does it work? Sometimes yes. Is it easy? No. What I know is that the reward is worth the effort.