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Research Article

Searching for alternatives to the closest targets: Identifying new directions for improvement while controlling additional efforts

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Pages 2770-2782 | Received 26 May 2020, Accepted 29 Aug 2020, Published online: 29 Sep 2020
 

Abstract

Setting the closest targets is an appropriate approach for planning. Closest targets minimize the gap between actual performances and best practices, so they are the ones that require the least effort from organizations for their achievement. However, this paper shows that, in practice, we can find alternative targets, which do not require significant additional efforts (with respect to those involved in the achievement of the closest ones) and define directions for improvement that might be more aligned with management. For this reason, we propose here to complement that approach with the search of alternative targets controlling additional efforts. In order to do so, a search algorithm based on some bi-objective Data Envelopment Analysis benchmarking models is developed, which allows us to explore the strong efficient frontier of the production possibility set while keeping the distance within some limits. Decision making is the core of planning, and involves the selection of a future course of action from alternatives for the purpose of improving performance. The proposed approach is thus consistent with those principles of planning, as it relies on the availability of alternatives, so that decision makers can make a choice through an ex post evaluation of potential ways for improvement.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 We note that the idea of closeness to the efficient frontier has also been investigated for purposes of developing efficiency measures that satisfy some desirable properties (see Ando et al., Citation2017; Aparicio & Pastor, Citation2014; Fukuyama et al., Citation2014a, Citation2014b, Citation2016).

Additional information

Funding

This research has been supported through Grant MTM2016-76530-R (MCI/AEI/FEDER, UE).

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