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[Concept/Idea Not Complete]: SoCon Malawi - Micro-financing Solar Energy - July 2018

by
Seif Zakri Stacey
Seif Zakri Stacey | Jul 6, 2018 | in Knowledge Base

Background: The energy team have identified that lighting and energy used to charge their phones are a major need of Malawians in rural areas. They spend up to 1,500 Kwacha a week on these amenities and the energy team seek to reduce this cost through the Solar energy battery they are distributing.

 

The problem: The energy team were uncertain how to finance their product, as most people couldn’t afford to purchase the battery outright. They also lacked a clear understanding of who their optimal customer type was. Financial education of people in rural areas is limited; they have a low propensity to save their money, and a lack of understanding of good debt/ bad debt and microfinancing. We in the social consulting team also lack an understanding of the environment we are selling our product in terms of finance (people's access to it and the systems currently in place), as well as our customer segment/ relationships.

 

Aim: to use the data we gather from the energy teams sales to identify potential key customers we can issue loans to, develop a customer database and eventually develop a customer archetype of who is most likely to want a microloan (in rural areas). To assess the financing environment in the rural areas of Blantyre (the potential risks and customer expectations of issuing loans) and how feasible maintaining microfinance is back in Australia.

 

Hypothesis: the people most likely target customers are divorced or widowed women with children seeking to start up a side enterprise (their main one being agriculture) which would most likely be some sort of retail business.

 

Variables:

Controlled:

  • The payment options

  • The product (Solar energy batteries)

Measured (dependent):

  • Customers that want to microfinance a product

Independent:

  • Deposit amount

  • Number of weeks of repayment

  • Area loan is issued (village)

  • Socio-economic status of customer

  • Gender of customer

  • Age of customer

 

Method

We began by developing an affordable payment plan for potential customers with variable down payment amounts and a discount rate (the larger the initial down payment the larger the discount). The idea behind this being it incentivizes the customer to make larger down payments and reduces the number of weeks it takes for them to repay their loan, thereby reducing our risk exposure.

We then developed security measures to further mitigate our risk exposure. This included things like asking for their national ID, their contact details and date of birth, the ID and

contact details of their guarantor, Geotagging the location of any sales, they need to have lived in the village for a minimum of 5 years and the recommendation of their village chief.

Our next step was utilising the questionnaire developed by William Lee. This will be the most direct and effective way of identifying what makes a good potential customer segment. After compiling our data we will need to select the criteria we think is most important to developing an optimum customer profile and do so.

 

Results

This might take time to gather but once we do and develop 3 major customer archetypes we can compare this to the customer profiles of other financial providers that have been successful in distributing capital in developing countries and those already operating in Malawi. If we have similar customer profiles then we know we are on the right track to narrowing down our target customer that we want to help finance.

 

Conclusion

The experiment is a work in progress but the more information gathered means the closer we are to identifying our customer segments.

edited on 5th September 2018, 23:09 by Justin Hakeem

Wade Tink Jul 6, 2018

The key consideration around this experiment is the learning specific to the financing of the energy asset. My thoughts is that the "Aim" doesn't hit the mark on this at all.
Learning can cover several areas of the Lean and BMC including:
- Solution
- Key partners
- Key resources
- Key activities
- Value Proposition
When it comes to the aim I would specify this done to particular components of validated learning. With measurement be more specific as to the thresholds of success and failure and be more specific about the methods you are using- security methods is a huge one through this.
Consider breaking this experiment down to several components.

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Wade Tink Jul 6, 2018

Status label added: Idea/Concept Not Complete

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