In 2014, Indian PM Modi declared to have “100 Smart Cities” and allocated funds in the national budget of March 2016 to achieve this objective. TATA Telecom Ltd. (TTL), one of India’s largest Telecom provider and part of the TATA conglomerate, decided to bid for these government projects. As part of educating their senior management and stakeholders, they invited us to do a 4-day hands-on workshop on IoT and Analytics in September 2016.

TTL was going to approach geographically, Chief Ministers of all the 29 states and their corresponding members of parliament in the state’s districts. Their sales staff organization were also distributed into geographical regions.

To educate the audience, we wondered if there are any open datasets available that we could show the power of Analytics to help TTL in their bid for smart city initiatives.
In this talk, I will explain our journey of finding citizen-survey open datasets to suggest an alternative approach to bidding for government initiatives in the smart city/IoT space. The survey data, in effect, became “human sensor data” or “voice of the customer” to define “similar clusters” of citizens importance and priorities of issues faced by them. Hence, this alternative approach would have the sales staff target cluster-wise “similar districts”, instead of a geographical approach.

During the talk, I will explain the model development lifecycle phases, and some of the data quality challenges encountered, along with assumptions and constraints in building the models from open datasets. Finally, I will show the applicability of the approach to any initiative which desires to be “customer-focused”, and the importance of including them in designing solutions that fit their needs.