Study results have shown that effects of firms’ interim performance of brand management like sales, sales growth, market share, customer satisfaction, or brand equity on firms’ final performance like profitability or shareholder value are not consistent. Most studies focusing on the relationship between these two variables ceremonially omit input factors for the brand management in their study design. To deal with such a problem, current study employs brand management efficiency index calculated through Data Envelopment Analysis. Data Envelopment Analysis considers input factors as well as output factors for the calculation of efficiency. In the current study, 4 input factors - assets, salaries, general administration expenses,and advertising and sales promotion - and 3 output factors - sales, 2 year composite sales growth rate, and operating income - are used for the calculation of efficiency indices. Two hypotheses are developed in the study. Hypothesis 1 is about the relationship between brand management efficiency and firm profitability, and hypothesis 2 is about the relationship between brand management efficiency and shareholder value. Because firm profitability has backward looking nature, the relationship between brand management efficiency and firm profitability is hypothesized as having an inverted U shape. In other words, although firm profitability would increase as efficiency gets higher, it would decrease after efficiency exceeds a certain level. The relationship between brand management efficiency and shareholder value is hypothesized as having a U shape due to forward looking nature of shareholder value. That is, initially shareholder value would decrease as efficiency increases. However, as efficiency increases higher over a certain level, shareholder value would eventually turn upward. Using Malmquist Index formula, this study breaks down brand management efficiency into two elements - Efficiency Change and Technical Efficiency (or Frontier Shift), and then tests the effects of these two brand management efficiency indices on firm’s profitability and shareholder value. In the study ROI and Tobin’s Q were used for the measures of profitability and shareholder value respectably. A set of panel data from 103 firms listed in the Korea Composite Stock Price Index(KOSPI) and Korean Securities Dealers Automated Quotation (KOSDAQ) between 1999 and 2007 was collected and used. For the analysis of data, two 2-way error components models using ROI and Tobin’s Q each as a dependent variable. According to analysis results, hypothesis 1 was strongly supported. Efficiency Change index and Technical Efficiency index both positively influence firm profitability,and square terms of two efficiency indices are negative and significant. As hypothesized, firm profitability(ROI) initially goes up as efficiency increases. After a certain level of efficiency,however, firm profitability went downward. Hypothesis 2 was partially supported. Only Efficiency Change worked as hypothesized. Efficiency Change index has a negative effect on Tobin’s Q and its square term has a positive influence on Tobin’s Q. In short, as Efficiency Change index gets higher, shareholder value gets lower. After Efficiency Change index exceeds over a certain level, however, shareholder value starts to increase. For Technical Change index, no significant effect was identified. Results of this study tell us a couple of lessons. First, brand management efficiency should be pushed up only to a certain limit. If a firm’s efficiency level is too high, firm profitability could be negatively affected. Second, performance indices for a firm need to be distinguished into two groups. Forward looking indices like Tobin’s Q, EVA(economic value added), and FCF(future cash flow) represent a firm’s profitability, and backward looking indices like ROI(ruturn on investment), ROA(return on assets), and ROE(return on equity) represent a firm’s market value or shareholder’s value. Effects of efficiency on firm performance are different depending on types of performance index. Limitations and future study for this study are as follow. First, representativeness of sample needs to be improved. More diverse firms should be included in the data set. Second, percentage of variance explained would be improved if more related variables were considered in the model. Examples of such variables include R&D cost, competitive intensity, and customer satisfaction. Third, analysis results using SFA(Stochastic Frontier Approach) would provide an interesting comparison point. DEA results often need to be compared with SFA results (Murthi, Srinivasan, and Kalyananram 1996). Fourth, future research need to figure out why Technical Change index does not have any significant influence on shareholder value. It seems to have an effect, yet the effect was not identified.