Challenge

I work for a government agency whose primary responsibilities are industry development and  investment promotion. In a nutshell, we encourage local and foreign investments to come into the  country by providing tax incentives and help priority industries grow by creating a conducive business  environment through policy.

Much of the agency’s operations have yet to be digitized and the primary pain point that is always  identified by upper leadership is our lack of robust data analytics to drive the development and  crafting of evidence-based policies. We were recently offered a data lake developed by one of the top  IT companies in the country; however, we were not fully ready to implement it out right.

Selection

Upon going through a design thinking process to understand how the data lake could be used best for  the agency, a multi-disciplinary team was formed in order to implement a learning launch. The team  sought to develop a proof-of-concept (POC) that would push quality real-time data into the data lake  for use in analytics. The learning launch was a crucial step in the project because, for the agency, this  was uncharted territory. The learning launch would provide the needed feedback so that the platform  could be implemented at a larger scale once all the kinks were worked out.

Application

The learning launch designed revolved around getting on-the-ground data to assess the supply of rice  across the country. By doing so, the necessary interventions could be put in place to create a more  efficient distribution system and avoid a shortage. To gather real-time data, a mobile application was  quickly developed where rice farmers could enter their information. The learning launch was confined  to a small geographic area that had a good amount of rice farmers that could be on-boarded into the  process. A group of volunteers was tapped to facilitate the on-boarding process and teach the rice  farmers how to properly use the mobile application. For the learning launch, there were five (5) small  groups that went out to on-board farmers and gather data.

Insight

The video lectures highlighted the importance of diversity in order to fill informational gaps and  reduce biases. Although the learning launch team was comprised of brilliant people from various  fields, we did not have anyone that was an expert in the local area. Locals were part of the  implementation phase, but not the planning phase, which led to a number of missteps during the  learning launch.

First, to use the mobile application, the rice farmer needed to have a smart phone. The majority of  the farmers were relatively old and/or part of the marginalized sector and, thus, could not afford a  smart phone. To address this, a small number of phones were loaned out, at least for the duration of  the learning launch.

Second, the mobile application had to be downloaded and installed onto the smartphone. Being a  rural area, some areas did not have cellular reception, mobile data, or wired internet connectivity.  Farmers had to be transported to the nearest town with connectivity in order to first get the  application and actually input information.

The learning launch was still a success; but instead of identifying what worked, it became clear what  didn’t work and that there was a need to rethink the concept and develop an alternative solution.

Approach

Due to the (un)successful learning launch, it would be best for the team to return to brainstorming  and integrate a member of the local community to get their inputs. This was a crucial missing factor  in the previous learning launch. With more diversity in the team and with a broader perspective in  terms of inputs, a more robust concept could be developed and eventually explored.


Challenge I work for a government agency whose primary responsibilities are industry development and investment promotion . In a nutshell , we encourage local and foreign investments to come into the country by providing tax incentives and help priority industries grow by creating a conducive business environment through policy . Much of the agency ’s operations have yet to be digitized and the primary pain point that is always identified by upper leadership is our lack of robust data analytics to drive the development and crafting of evidence - based policies . We were recently offered a data lake developed by one of the top IT companies in the country ; however , we were not fully ready to implement it out right . Selection Upon going through a design thinking process to understand how the data lake could be used best for the agency , a multi - disciplinary team was formed in order to implement a learning launch . The team sought to develop a proof - of - concept ( POC ) that would push quality real - time data into the data lake for use in analytics . The learning launch was a crucial step in the project because , for the agency , this was uncharted territory . The learning launch would provide the needed feedback so that the platform could be implemented at a larger scale once all the kinks were worked out . Application The learning launch designed revolved around getting on - the - ground data to assess the supply of rice across the country . By doing so , the necessary interventions could be put in place to create a more efficient distribution system and avoid a shortage . To gather real - time data , a mobile application was quickly developed where rice farmers could enter their information . The learning launch was confined to a small geographic area that had a good amount of rice farmers that could be on - boarded into the process . A group of volunteers was tapped to facilitate the on - boarding process and teach the rice farmers how to properly use the mobile application . For the learning launch , there were five ( 5 ) small groups that went out to on - board farmers and gather data . Insight The video lectures highlighted the importance of diversity in order to fill informational gaps and reduce biases . Although the learning launch team was comprised of brilliant people from various fields , we did not have anyone that was an expert in the local area . Locals were part of the implementation phase , but not the planning phase , which led to a number of missteps during the learning launch . First , to use the mobile application , the rice farmer needed to have a smart phone . The majority of the farmers were relatively old and/or part of the marginalized sector and , thus , could not afford a smart phone . To address this , a small number of phones were loaned out , at least for the duration of the learning launch . Second , the mobile application had to be downloaded and installed onto the smartphone . Being a rural area , some areas did not have cellular reception , mobile data , or wired internet connectivity . Farmers had to be transported to the nearest town with connectivity in order to first get the application and actually input information . The learning launch was still a success ; but instead of identifying what worked , it became clear what did n’t work and that there was a need to rethink the concept and develop an alternative solution . Approach Due to the ( un)successful learning launch , it would be best for the team to return to brainstorming and integrate a member of the local community to get their inputs . This was a crucial missing factor in the previous learning launch . With more diversity in the team and with a broader perspective in terms of inputs , a more robust concept could be developed and eventually explored .