Improving efficiency of the telecommunication is crucial to the development and growth of Korean economy. Recently, it has become important with the huge development of information technology and its greater potential for extensive impact on the rest of the economy. Hence, it is useful to determine the factors that help enhance efficiency in telecommunication and consider them in improving the evaluation model. This study applies DEA (data envelopment analysis) to evaluate the relative efficiency of 51 branches of a Korean telecommunication company. Using the super-efficiency approach, we tested outliers which may affect the results and ranked the efficient branches. A method of deriving key variables applied to business operation is proposed to identify the key performance indicators for evaluation that takes environmental (non-discretionary) factors into account. We used the extended CCR model proposed by Banker and Morey to investigate the influence of non-discretionary factor. The information provided by the model (slacks, weights) and the sensitivity analysis shows that the most important indicator that affects the branch performance is operating cost. The results of sensitivity analysis show that average efficient score decreases from 0.972 (base case) to 0.863 for CASE2-COST. The average score of the data proves the priority of operating cost over other indicators. The effect of environmental (non-discretionary) variable was found to be significant. The population effect was positive and improved overall efficiency by 0.91% on average. Non-discretionary factor plays a meaningful role explaining the performance of branches. The performance optimization report can help a manager of an inefficient branch to develop branch strategies. Managers can identify the top-performing units, study best practices and adopt the strategy to the organization.

1. Introduction
 2. Literature Review
 3. Method and Data
  3.1 Method
  3.2 Data
 4. Results
  4.1 Influence of the Non-Discretionary Indicator
  4.2 Efficiency Analysis of Telecom BranchPerformance
  4.3 Sensitivity Study of Evaluated Indicators
  4.4 Case Study : Performance Optimization Report
 5. Conclusion
 References

• 권순만(한양대학교 일반대학원 경영컨설팅학과) | Sun-Man Kwon (School of Management Consulting, Hanyang University)
• 한창희(한양대학교 경상대학 경영학부) | Chang Hee Han (School of Business Administration, Hanyang University) Corresponding author