Brand New PPI Features For TaroWorks

TaroWorks now enables you to see Progress out of Poverty Index (PPI) results with built-in reports and dashboards. In addition to accessing all PPI scorecard questions through TaroWorks’ survey library, organizations can now see aggregated results as surveys are submitted.

These new features were part of the TaroWorks 3.1 release – you can read more about some of the other features here. You can also get a step-by-step walkthrough of all the new features, including those related to PPI, in our webinar which you can register for at the top of the article.

Overview of PPI features

• Pre-built reports for comparing poverty rates: poverty rates for all poverty lines, poverty rates compared against national data, and poverty rates by mobile user
• Pre-built reports for seeing poverty rates by standard demographic categories: household size, gender, age, tenure as a client
• Customize the report templates to fit your needs
• On-device PPI score calculations – even when your field officers don’t have reception
• Automatically send anonymous PPI results back to Grameen Foundation for benchmarking purposes

How the new PPI features look

The first dashboard below is an example of an overview of PPI metrics for outreach and monitoring. This allows you to gain a sense of the economic situation of your respondents and the outreach your field force is having by user when collecting this data.

The second dashboard is an example of ways to analyze your PPI data with demographic information. In order to help you further slice and dice the poverty line probability data that you’re gathering with TaroWorks, we’ve worked with our PPI team to add some demographic questions to all the PPI templates, including information like the age and gender of the respondent. You can also compare the poverty data with other data you are collecting by adjusting these templates.

TaroWorks scoring allows you to assign numeric values to individual multiple choice responses to survey question in order to evaluate an otherwise qualitative response in a quantitative way. For example, an organization may say that, based on the responses to a series of questions, if the score is below 50, the respondent is eligible for the organization’s services; if above, they are not. Previously, field officers had to wait until their device had connectivity to the scores, but with the offline score calculation in 3.1, they will have instantaneous visibility. And they can use that information to carry on with their field work on TaroWorks or otherwise.