Example reflection – Learning Launch

Challenge

I am a lead data scientist in an elderly care project. The aim of this project is to provide an IOT  technology driven complementary healthcare system to assist the daily work of healthcare  providers, and improve the quality of life for elderly patients. There are three main stakeholders in  this project, namely the elderly patients and their family members, the healthcare providers (i.e. care managers of the patients), and IT technicians (i.e. software engineers, data scientists, IT architects).

The challenge of this  project is that there are lots of variations of the design of potential system,  from sensor selection, IT architecture design, data collection, analytic objectives, and results  display. Especially, if we rely on one set of system selection and go through the whole loop to  collect real data and test the system. The cost of failure could be huge and unrecoverable.

Selection

User experience is crucial for the success of the project. Therefore we decide to take a agile  approach to communication with stakeholders through frequent feedback delivery loops. We split  the IT system into three main components, i.e. sensor selection and deployment strategy, data  analysis pipeline, and results visualization. Based on our experience in relevant technique domains,  we proposed a set of sensor kit options, and data analysis prototypes, as well as data visualization  designs. We set learning launch targets at different stages of the project to collect user feedback to  test our hypothesis and adjust the system design.

Application

For our first learning launch, we aimed at narrowing down the sensor kit selections and result  visualization design, to understand the users’ preference and needs. We recruited 20 elderly patients  who are potential users of the system, and elderly who are simply curious. The end product has to  be a compromise between technique complexity and the usability (user interaction required, and the price). We grouped the selected sensor kits into different categories accordingly to the amount of  user interaction required, and their capabilities. We create result visualization interface based on  public dataset and mock data that we created. During this session, we have gain valuable  information in terms of sensor selection, and what information (result visualization) to feed to the  users.

Our second learning launch focused on testing several prototype IT structure, and data analysis  pipeline based on real data collected from volunteer patients. The aim is to get ready for a first hand user experience of the running system. During this session, we were able to communicate with users about how an edge based system could offer, and what we could achieve with a powerful cloud- based service, as well as what service is necessary for a real-time feedback, while another could  afford a delay.

We launched several more rounds of learning launch afterwards. At each round we tested hypothesis that were set beforehand. Through these launches, we were able to get closer and closer to a system  prototype that offers users the best experience, and a backend IT system that offers  robust and  seamless service to the elderly patients.

Insight

By applying the learning launch tool in an agile way, our team were able to efficiently communicate with the target users and narrow down the hypothesis of various technological tool kit options.  Additionally, the process has brought the stack holders in a closer healthy relationship, by taking  care of users’ feedback in the design loop, which has largely increased the confidence of the elderly  patients into using our system.

Approach

Given the success of applying the learning launch tool in this project, I would like to continue  practising it in future projects. However, various types of project may require different degrees of  efforts to launch from the technicians as well the end users. Therefore, carefully set hypothesis,  goals, and reasonable time line is very crucial to a successful project, as well as to build a healthy  relationship among stakeholders. I would like to pay extra attention in these factors in the future.


Example reflection – Learning Launch Challenge I am a lead data scientist in an elderly care project . The aim of this project is to provide an IOT technology driven complementary healthcare system to assist the daily work of healthcare providers , and improve the quality of life for elderly patients . There are three main stakeholders in this project , namely the elderly patients and their family members , the healthcare providers ( i.e. care managers of the patients ) , and IT technicians ( i.e. software engineers , data scientists , IT architects ) . The challenge of this project is that there are lots of variations of the design of potential system , from sensor selection , IT architecture design , data collection , analytic objectives , and results display . Especially , if we rely on one set of system selection and go through the whole loop to collect real data and test the system . The cost of failure could be huge and unrecoverable . Selection User experience is crucial for the success of the project . Therefore we decide to take a agile approach to communication with stakeholders through frequent feedback delivery loops . We split the IT system into three main components , i.e. sensor selection and deployment strategy , data analysis pipeline , and results visualization . Based on our experience in relevant technique domains , we proposed a set of sensor kit options , and data analysis prototypes , as well as data visualization designs . We set learning launch targets at different stages of the project to collect user feedback to test our hypothesis and adjust the system design . Application For our first learning launch , we aimed at narrowing down the sensor kit selections and result visualization design , to understand the users ’ preference and needs . We recruited 20 elderly patients who are potential users of the system , and elderly who are simply curious . The end product has to be a compromise between technique complexity and the usability ( user interaction required , and the price ) . We grouped the selected sensor kits into different categories accordingly to the amount of user interaction required , and their capabilities . We create result visualization interface based on public dataset and mock data that we created . During this session , we have gain valuable information in terms of sensor selection , and what information ( result visualization ) to feed to the users . Our second learning launch focused on testing several prototype IT structure , and data analysis pipeline based on real data collected from volunteer patients . The aim is to get ready for a first hand user experience of the running system . During this session , we were able to communicate with users about how an edge based system could offer , and what we could achieve with a powerful cloud- based service , as well as what service is necessary for a real - time feedback , while another could afford a delay . We launched several more rounds of learning launch afterwards . At each round we tested hypothesis that were set beforehand . Through these launches , we were able to get closer and closer to a system prototype that offers users the best experience , and a backend IT system that offers robust and seamless service to the elderly patients . Insight By applying the learning launch tool in an agile way , our team were able to efficiently communicate with the target users and narrow down the hypothesis of various technological tool kit options . Additionally , the process has brought the stack holders in a closer healthy relationship , by taking care of users ’ feedback in the design loop , which has largely increased the confidence of the elderly patients into using our system . Approach Given the success of applying the learning launch tool in this project , I would like to continue practising it in future projects . However , various types of project may require different degrees of efforts to launch from the technicians as well the end users . Therefore , carefully set hypothesis , goals , and reasonable time line is very crucial to a successful project , as well as to build a healthy relationship among stakeholders . I would like to pay extra attention in these factors in the future .