In recent decades, the number of global airline passengers has increased by nearly 400%, resulting in a rapid expansion in airline operators as well as air travel routes. Born from the need for a one-stop shop for consumers to explore the best available routes and most cost effective options, a number of internet-based providers consolidated this information (think Expedia or Kayak), and launched platforms which allowed passengers to access and filter the data, and ultimately find flights that best meet their needs.
At i2i we are exploring whether a similar tool can assist when designing demand-side surveys (DSS) for financial inclusion.
We’ve seen significant growth and development in the number and type of DSS to collect information on the financial services behaviour of adults in developing and emerging markets. Over this period, different variations of DSS have emerged, which have been tailored to the needs and context of where they are implemented. For example, the FinScope survey has been implemented more than 40 times, across 21 countries, with each questionnaire slightly different than the previous. The challenge for most survey designers is which questions will be most relevant for their specific needs.
For example, consider the following two questions [sample answers]:
- “On which of these do you rely to get most of your money from?”
[Salaries/wages; trading; piece work; state/government pension; money from family; money from friends; money from household member]
- “Which of these, if any, best describes your personal working status?”
[Work full-time; work part-time; student; housewife; pensioner; unemployed]
The first question (asked in FinScope Zambia 2015) will provide you answers on the broader topic of income and miss out on primary employment status; whereas the second (asked in South Africa FinScope 2015) will provide answers specifically on the status of employment and miss out on the full view of how income is derived.
Whilst this may seem like a trivial issue for many in financial inclusion, the variations to questions can have a measured impact on the relevance of responses. It would be like purchasing a flight from an airline without clarifying your preferred destination, ending up at the wrong destination and, ultimately, paying for your mistake.
Given the high cost of DSS and the critical role they play in getting information on invisible markets, it is important that the survey questions you choose provide reliable and relevant answers. Similar to the time before the emergence of Expedia-like tools for the travel industry, there is currently no one-stop shop where DSS designers can view and compare questions across different variations to identify which works best for their survey needs.
The tool we are exploring would consolidate multiple financial inclusion DSS, capturing the questions and answers verbatim in a very simple database and classifying questions in a consistent way. The reference system will provide a structure to help survey designers find the question-answer combinations that best meet their needs. It’s rudimentary, but it’s a start!
Once all the questions across the surveys have been collated, the information will be put into a searchable database. We are thinking about creating a fairly exhaustive keyword or question-generated association navigation system that would allow users to search and find what they are looking for in an intuitive manner. This will help questionnaire designers to assess:
- Has this question been asked before?
- If it has, what is the best way to ask this question?
- Are there other questions that you have not considered that would provide relevant answers for you survey?
Our initial focus is on a group of surveys with the broadest applicability in financial inclusion: Findex, FII and FinScope. Often these three surveys tackle the same concepts in different ways using different methodologies. Understanding the most appropriate use of these questions for different needs and contexts is a great starting point to develop such a referencing tool.
The tool will then feed into an implementation guide of DSS along with guidance on recent innovations and best practices in data collection, sample and survey design.