- A Mobile App for Enumerators (Android)
- A WhatsApp Chat Bot for Self-Survey
- Policy Recommendation Dashboard
- Socio-Economic Index Creation
- Enumerator Management Dashboard
- Conducting first ever survey of unorganized sectors for the Government of UP
- Studying the ground status of Central/ State Government schemes/ initiatives benefits for these sectors and its utilization
- Policy making survey & report for unorganized sector of the economy and to study the socio-economic conditions of unregulated labours in unorganized sector
- Bringing unorganized sector in the mainstream and thereby, enhancing the economy of the state and the country
- Expected Increase in GDP of one district of the state by around 20% within a year despite COVID (based on the recommended policy plan for one district)
- Advanced level of discussion with the Govt. of Telangana
The technology platform required for this study shall utilize a number of apparatuses that talk to each other through a common database and the use of APIs wherever required. The apparatuses that shall be utilized are as follows
ENUMERATOR APP
A mobile application that surveyors can use to collect data and push it for analytics in real time, thus allowing better audit and higher quality of data collection.
The app also has an optional section to allow secondary research data to help fill the primary data.
React Native is used for building the mobile application that works on Android.
SAMPLING AND EXTRAPOLATION TOOLS
Combination of mathematical models that are used to extrapolate data in order to get collective information across various parameters, particularly for the purpose of knowing overall awareness and gaps.
These tools are built using Python.
STATISTICAL DATA ANALYTICS TOOLS
Tools that uses various hybrid econometric and statistical models to find critical variables that impact the related variables and help us identify key problem areas with respect to the publicity of the schemes, as well as key drivers that lead to low awareness of schemes.
All analytics tools are built on Python.
DATA NORMALIZATION ALGORITHMS
Data cleaning and normalization shall be needed to improve the quality of the collected data and such normalization is a function of various secondary and primary variables, thus being able to weed out false data and correct certain data.
Most of these algorithms are already in use for various surveys and are built on Python. Some of these algorithms are also available in Macro on Excel.
MEASUREMENT TOOLS
Various outputs can be combined to create various measurement indices or scores that can be used to understand the RoIe of schemes as well as the level of quality of benefits across demographics and regions. Such tools need to be developed specifically for the purpose of this study and can be built upon previous tools that have been used to measure scores such as financial status, social status, and socio-economic satisfaction status.
All of them are built in Python or R or Excel as the need be.
RECOMMENDATION ENGINE
Recommendations for course corrections for various schemes can be provided through a recommendation engine that follows the following steps
- Identification of Key Areas of Concerns that need correction through use of statistical models such as MLE (Maximum Likelihood Estimation) and Multi-collinearity across variables.
- Mapping of areas of concerns with a bank of recommendation statements for the same.
- Manual Evaluation of recommendations (wherever applicable).
- Use of Feedback Loops to see probability of recommendations leading to course corrections (using machine learning models such as KNN)- use of such loops shall depend on the extent of data collected for the same.
- Further improvement in recommendations based on the same.
DATA ANALYTICS DASHBOARD
A dashboard that provides filters of various demographics, regions, and urban/rural divisions and can display processed and analyzed reports across the entire state, using intelligent interfaces of graphs and diagrams, along with Heat Maps.
- The Heat Maps are shown on proprietary 2D GIS maps.
- The visuals are created keeping in sync with analytical outputs, aimed at providing the right messaging to the viewers.
A dashboard that provides filters of various demographics, regions, and urban/rural divisions and can display processed and analyzed
reports across the entire state, using intelligent interfaces of graphs and diagrams, along with Heat Maps.
LICENSES
All licenses of the above-mentioned tools, including the sub-tools such as the GIS Map of the entire state belongs to Sapio Analytics, our partner in the project.
Sapio Analytics is also a preferred technology partner of Amazon Web Services (AWS) and AWS is proposed to be the cloud infrastructure and cloud security partner for the project.
Moreover, the data architecture used by us is designed in a way that it can scale up to a much larger dataset in future keeping in mind the possibilities of going beyond sample data set for seeing the impact of this study later.