Title of article :
A DEA Approach to Measuring Teammate-Adjusted Efficiencies Incorporating Learning Expectations: An Application to Oil & Gas Wells Drilling
Author/Authors :
Nedaei, Hessam Department of Industrial Engineering - Iran University of Science and Technology, Tehran, Iran , Jalali Naini, Gholamreza Department of Industrial Engineering - Iran University of Science and Technology, Tehran, Iran , Makui, Ahmad Department of Industrial Engineering - Iran University of Science and Technology, Tehran, Iran
Abstract :
Data Envelopment Analysis (DEA) measures the relative efficiency of Decision-Making Units (DMUs)
with multiple inputs and multiple outputs. In the case of considering a working team as a DMU, it
often comprises multiple positions with several employees. However, there is no method to measure the
efficiency of employees individually taking account the effect of teammates. This paper presents a
model to measure the efficiency of employees such that they are fairly evaluated regarding relative
performances of their teammates. Moreover, the learning expectations and the effect of learning lost
due to operation breaks are incorporated into the DEA model. This model is thus able to rank the
employees working in each position that can then be utilized within award systems. The capabilities of
the proposed model are then explored by a case study of 20 wells with 160 distinct operations in the
South Pars gas field, which is the first application of DEA in the oil and gas wells drilling performance
analysis.
Keywords :
Data envelopment analysis , Teammate efficiency , Learning , Oil and gas , Drilling
Journal title :
International Journal of Industrial Engineering and Production Research