While rest of the world confined itself to closed door, healthcare and life sciences organizations could never had the same luxury. With healthcare professionals continuing to operate at the forefront to cure people and life sciences professionals working extra hours to continue with the drugs research and making them available to the world, the need for finding digital solutions to contain the spread of pandemic remains a necessity.

Health insurance is a complex industry to navigate with myriads of hurdles in the form of processes tangled with regulations and age-old legacy systems. While automation has become the new normal in a world of digital business, health insurance has lagged behind. Even the technologically advanced payers are crippled with greater operational cost, poor customer experience, higher cycle time, and a tangled back office. It’s now time to run at the speed of new and evolving opportunities and fully embrace the power of intelligent automation.

The secular shift toward an accelerated adoption of cloud capabilities continues unabated. Yet. despite all the marketing noise around technology capabilities such as containerization and microservices, the journey toward cloud-native operations is more about culture, people, and processes than technologies.

Data science is playing a pivotal role in redefining the life science businesses starting from discovery phases to commercial activities. Diverse data sources, humongous volume and varied data types such as text, audio, images and video, demand adoption of numerous available algorithms and models for data processing and analysis to aid decision making.

Restarting travel during the Covid-19 pandemic has forced organizations to redefine health & safety practices, inventory & services, and their operating model. In this redefinition process, 'cost excellence' is the top priority, and investments required for ongoing cost excellence are under scrutiny at the highest levels.

Advances in big data and cloud technologies have acted as catalysts for the fast growth of machine learning applications.