Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/22013
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dc.contributor.advisorBandi, Rajendra K
dc.contributor.authorNaskar, Rajarshee
dc.contributor.authorBipinkumar, Shah Smit
dc.date.accessioned2023-06-28T16:09:21Z-
dc.date.available2023-06-28T16:09:21Z-
dc.date.issued2022
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/22013-
dc.description.abstractBeing a contemporary notion, performance monitoring has now become the need of the hour due to increased competition in the different industries. Along with the white collar jobs, where there is a possibility to show off the work unambiguously by the tools such as performance appraisals, skill charting etc. and where it is mostly on the laptop screens or that of desktop computers, measuring the performance of the blue collar workers or labours is also vital. The implementation of such tools facilitates the organizations to perform good by creating the atmosphere of the engagement amongst workers. India is the second most populated country in the world and even though there is a boom of IT industry, the number of blue collar workers are higher and there is an increasing demand of the blue col lar workers. Skil led or non-skilled workers in manufacturing set-ups are known as blue collar workers. Blue collar worker's role is important since they are the main drivers of the production and quality. Considering this it makes sense to monitor the performance of the blue collar workers and collect the data regarding the same to improve the performance of the worker and ultimately the organization. Before Covid, during 2011 the Industry 4.0 was publicly introduced-r nown as The Fourth Industrial Revolution 4.0 which combined the physical assets along with the digital technologies - like Internet of Things (loT), Artificial Intelligence, drones, cloud computing, robotics, big data. There are 4 design principles which is integral to Industry 4.0 interconnection, information transparency, technical assistance, decentralized decisions. Even with the help of Industry 4.0, one of the way of monitoring the machines was mounting the sensors into some parts of the machine, collecting the data and help the organization to preventive or predictive maintenance to improve the efficiency of the machines. There was no focus was on blue collar worker's performance monitoring but recently the trend and needs of the companies are changing. We are in a digital era and after Covid-19 things are changing very rapidly, causing more and more companies to make digital transformation in their style of work and also regarding their internal structure. Use of loTs, sensors, Android, iOS has been increased at an exponential rate and the Covid-19 has done the work of adding fuel and charging the usage at even more speed. We will be working on one such a software product which has an objective of the monitoring the performances of the workers (mostly blue collar) and helping the organizations/HR team to analyse the performance to retain the employees/contractual workers based on the same. For the purpose of studying performance monitoring in blue-collar workers, we have closely worked and observed with a Kerala based start-up, Pradjna lntellisys. The organization mainly work to assess different blue-collar workers and the product serves the client base who would in turn take better decisions through the usage of these modern technology products. These decisions are based upon different integrated mechanisms of data capture and subsequent processing of the same. In order to complete this study and for having better understanding of the methods followed, we have attended several meetings with one of the co-founders of the organization.
dc.publisherIndian Institute of Management Bangalore
dc.relation.ispartofseriesPGP_CCS_P22_133
dc.subjectPerformance monitoring
dc.subjectBlue collar performance monitoring
dc.subjectPradjna intellisys
dc.subjectPerformance monitoring
dc.titleStudy of performance monitoring in blue-collar workers
dc.typeCCS Project Report-PGP
dc.pages18p.
Appears in Collections:2022
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