BY: PRIYANKAR BHUNIA
PUBLISHED: 7 FEB 2018
“The team understands the importance of getting the foundations in place and is working towards it. In parallel, the team is exploring advanced applications, such as machine learning and predictive analytics.”
Mr. Kruger discussed a few examples. TAC is using machine learning or predictive applications to create client profiles for qualifying them for pre-approved medical services. This eliminates the need for any additional approvals and makes it easier to meet clients’ needs.
Another trial project Mr. Kruger talked about is the TAC Sofihub Smart Home where data insights are being used to enable more effective long-term care of the patients.
“A lot of our long-term support clients either live in accommodations supplied by us and many of them require 24/7 support and people to look after them. One of the things that we’re trying at the moment is the SOFIHUB Smart Home, where there are sensors in the house, for example, sound sensors, vibration sensors to see if a client has fallen and can’t get up or have taken their medication etc. The idea is that it will utilise AI to understand what the person’s normal patterns are, when they need to be alerted to take their medication or alert the client or caretaker if there are long periods of inactivity,” he explained.
With AI support, clients can manage their daily lives without having a person present 24/7. This project is still in a trial phase and privacy concerns are being examined.
Projects such as the ones discussed above demonstrate the benefits that can be derived from data to business and to the senior management. They help get buy-in.
Mr. Kruger said, “So, we get the best of both worlds. The fact that we have problems with data quality and we are having to get all the other things in place, does not stop us from doing these applications because we have to explore the mechanisms of doing those. And hopefully it will be incorporated into the newer architecture and platforms”.
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