In recent years, there has been a focus on measurement across all types of organizations working to improve the lives of people living at the ‘bottom of the pyramid’. Particularly for organizations that operate with a business model, this focus has turned from measurement not just for reporting to management and stakeholders, but for obtaining valuable information that can help manage the company’s social performance. Acumen’s Lean Data initiative has helped pave the way for social enterprises to shift mindsets and access data that can create value for the company and its customers.
The Progress out of Poverty Index® (PPI®) is a lean data tool. It helps an entrepreneur or investor understand a business by helping them understand the poverty level of the customers. Initially the PPI was used by organizations to measure and report on how well they were reaching poor customers. This was great, but it didn’t yet fully leverage the information that the PPI provides. As noted in an article on the Power of Lean Data, “few investors or entrepreneurs seek to understand, in a deep way, how customers experience the goods or services that an enterprise provides. Nor do people in the field give much attention to demographic factors such as the income levels or the gender make-up of customers.” But PPI users realized early on that there is value in the tool’s data beyond simply reporting.
A few examples of what companies have learned from PPI have been pretty well circulated by now. There’s the case of Ziqitza, the Indian ambulance service that learned that its poorest customers were female patients, and SolarNow which learned that its efforts to make its products more affordable was supporting the demand for them amongst poor customers. I wrote about Samasource for the Practitioner Hub a few years ago.
Combining demographic or other customer data with their poverty likelihood from the PPI creates a much more complex portrait of a business’s customers. This can help validate a social enterprise’s business model or help it to see where the model or marketing may need to be modified to reach and better serve the intended customers. Below are a few other examples of social enterprises who have come to better understand their businesses with poverty data via the PPI.
Rags2Riches is a social enterprise in the Philippines that empowers local artisans to create fashion and home goods out of upcycled or overstock materials. When they first utilized the PPI to understand the poverty level of their artisans, they realized that it also helped them understand the overall poverty profiles of the communities in which they were working. This raised opportunity for insights about whether or not their business model could actually work in poorer communities. Were poorer artisans as productive as others? Were they able to comply with requirements of the program? Were the poorer artisans driving their high program drop-out rate? Did the business need to create a different approach for these artisans?
When Vision Spring first started using the PPI, they didn’t have any window into their clients or how to best service them. This social enterprise, a provider of affordable eyeglasses and eye exams to the poor, regularly collects customer demographic info, customer satisfaction, and poverty level at the time of sale. Their customers’ PPI results have helped to validate that their marketing, services and products are effectively reaching the poor, and at a significantly higher rate than the national poverty rate. Through analysis of this poverty data with other client demographic data like gender and location, Vision Spring has answered important business questions like whether or not they are effectively targeting poor women as well as men and if their stores are situated in the right areas to reach the poor.
iDE is an international non-profit that helps farmers in the developing world through market-driven solutions. In their work with businesses serving the poor, they keep track of the socioeconomic characteristics of the clients in order to better understand their markets and the business models that are serving them. In one instance, management found that its clientele had slightly higher poverty than expected. They also found that the clients were in need of credit and savings services. iDE then partnered with rural banks, savings groups, and microfinance institutions to give the clients access to such services. This discovery and the subsequent improvement in strategy were made possible by combining the PPI’s objective poverty results with other important data points that they were regularly collecting from their customers.
Many businesses that intend to serve the poor are running their businesses with big blind spots. Some may already have basic data in hand, but without knowing how to ask about customers’ poverty status, they won’t know if they’re accomplishing what they set out to do or if they need to make a course correction. Adding a simple poverty measure like the PPI onto existing customer profiles can let management know if they are having the social reach they intended. The multiplicative effects of combining poverty data with other things a social enterprise knows about its clients can remove those blind spots, providing the insights needed to multiply the business’s social impact.
This blog is a part of the February 2017 series on Customer intelligence revolutionising business at the Base of the Pyramid in partnership with Acumen Lean Data. Access the series for interviews with social enterprises Dr.Consulta and D.light, as well as blogs from Business Call to Action, Social Value International and many more.