Building Healthcare 4.0 with Smart Workforce
Pushpendu Rakshit, Ravindra Sharma
DOI: http://dx.doi.org/10.15439/2020KM5
Citation: Proceedings of the 2020 International Conference on Research in Management & Technovation, Shivani Agarwal, Darrell Norman Burrell, Vijender Kumar Solanki (eds). ACSIS, Vol. 24, pages 91–94 (2020)
Abstract. Role of Indian pharmaceutical industry has been significant over the years. It's a leading nation for catering pharma and healthcare services across globe. The development, production, distribution and appropriate utilization of medicines, as well as the supportive functions of regulation, operational research, and training, all require the involvement of competent pharmaceutical professionals. Smart workforce can always contribute for better functioning of healthcare system in a country like India. Adoption of smart technologies by human resource could represent a new competitive advantage for pharma companies exhibiting smart pharma. The dynamic-consolidation, globalization, methodical developments, public policy, and competition-have pushed human resource leaders into new territory to address dynamic needs of pharma business. There exists a digital revamp in life sciences industries even following self-reliant India mission. This is a conceptual explorative research demonstrates future of smart Indian pharma, which is in a verge to become self-reliant. This study helps to focus on pharma workforce challenges such as performance management, compensation management, motivation, promotion, talent management, training and development with the help of AMO model comprising three main components such as ability, motivation, and opportunity. This would also alert both the clinical manufacturers and users resulting in designing personalized based better future of Indian pharma industry. This is an explorative study driven by secondary sources and tends to design prototype. Future Pharma would see the business link paraphernalia across development and dispersal by using better, more reliable larger volumes of data to revolutionize manufacturing.
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