This study seeks to use the concept of Data Envelopment Analysis for setting benchmarks of efficiency using two inputs and two outputs. In the
process, the study highlights the inherent contradictions in the application. In case of deficient divisions, instead of increasing the inputs to better the output, the DEA analysis recommends reducing the inputs.
Design / Methodology / Approach: Cross-sectional study of data is used for analysis of the performance of
the various divisions in NMIMS.
Findings: Data Envelopment Analysis (DEA) is a wonderful method for benchmarking and enhancing productivity of services. As services are entirely different from products, concepts like productivity cannot be applied without modifications. Further,
services being customer-centric characterised by customer participation, simultaneity, perishability, intangibility, and hetereogeneity, the concept of an ‘absolute’ benchmark is also not feasible. With the input and output metrics being ill-defined,setting milestones and targets for improvement become difficult. DEA technique uses the concept of ‘relative’ benchmark and also provides sufficient directions for
Practical Implications: In the Indian context, these concepts become very relevent because in the present state of evolution of services, we have much to improvise. Further, India being a geographical expanse with wide variation in customer preferences, expectations and preceptions, the process of improvement of services becomes more complex. At present, the demand for services exceeds supply and hence, the need for competitiveness is not felt. In the near future when the performance metrics of services becomes an important criteria for business success,
the role of DEA will be crucial for productivity improvements and in deciding the viability of service outlets.
Originality / Value: This DEA analysis in the Indian higher education context is one of the few analyses that demonstrate the utility of the DEA technique, its limitations and its role in qualitative aspects of services benchmarking. DEA analysis is applied in the context
of linear relationships of inputs and outputs with the focus on controlling the inputs rather than focusing on output performance. The outputs in terms of performance are more difficult to manage whereas the inputs are comparitively easy to manage.
Keywords: Benchmarking, Data Envelopment
Analysis, Productivity, efficiency, shadow price.
The Indian Prime Minister, Shri Narendra Modi, while speaking at the World Economic Forum, Davos, in January 2018, spoke about Foreign Direct Investment in India (FDI) and that every Indian sector is now open for foreign investors. He went on to say that India is not far from being a US$ One Trillion economy and the third largest economy in the world. This growth cannot be achieved only by growth in the manufacturing sector, but by an exponential growth in the services sector in India. Besides the IT service companies in India, services providers like Amazon, Wal-Mart, Alibaba, etc. are all present here. With the growth in services comes the requirement of efficiency and competitiveness for new and existing players. Services by nature are intangible and heterogeneous and thus, the concept of “good” service is mostly the perception of the consumer. The adage “Beauty lies in the eyes of the beholder” is apt for services because the concept of “good” service is very subjective. How then should a service organisation go about bettering their service offerings for their customers? How would the service organisation decide on an efficient service outlet that would be a benchmark for other service outlets to emulate? How can a service outlet identify the ‘problem child’ for improvements and / or decide to close down a service outlet that can never be productive? Which service outlets should be investigated for inefficiencies and what could be an improvement target?