A performance measurement framework combining DEA and balanced scorecard for the UK health sector. (10th October 2011)

• Record Type: Journal Article
• Authors: Ramanathan, Ramakrishnan; Ramanathan, Usha
• Is Part Of: International journal of operational research. Volume 12:Number 3(2011)
• Page Start: 257
• Page End: 278
• Publication Date: 2011-10-10
• Subjects: BSCs -- balanced scorecards -- DEA -- data envelopment analysis -- healthcare hospitals -- performance measurement; Operations research -- Periodicals; 003.05
• Languages: English
• ISSNs: 1745-7645

Abstract

Balanced scorecard (BSC) and data envelopment analysis (DEA) are two popular performance measurement tools for measuring performance of organisational units. However, several shortcomings of the two tools have also been highlighted. A BSC readily provides complex business information to managers at a glance and facilitates improved decision-making. However, BSC in its original form does not include any objective methodology, and when many perspectives are considered in the BSC framework with several measures in each perspective, the ability of managers to comprehend the huge volume of information becomes limited. We propose in this paper that BSC can be advantageously integrated with DEA. Such integration can help overcome some of the shortcomings of the latter, such as the discriminating ability and the problem of a firm with extraordinary performance in terms of only one measure achieving high performance scores. The proposed integration of BSC with DEA, called the balanced efficiency assessment method in this paper, is applied to balanced performance evaluation of health authorities (HAs) in the UK. Six BSC perspectives are employed to evaluate the performance of HAs. Different sets of inputs and outputs are used in a DEA model for each perspective, and the DEA performance scores are aggregated across all the perspectives using arithmetic mean. It is found that there is no single HA that performs consistently well in terms of all the six perspectives and that a HA that performs well in terms of one perspective does not seem to be doing well in terms of others.