The purpose of this paper is to propose a quantitative methodology for setting targets in the framework of Balanced Scorecard (BSC) in order to achieve vision and goals.
Response Surface Methodology is proposed to find the significant relationships that should be included in the strategy map and the optimal values of performance measures are assessed by using the desirability function-based approach of RSM. The proposed method was created by reviewing the existing literature, modeling the problem, and applying it in an oil company. In fact, RSM is used to execute the design matrix, analyze the collected data, extract models, analyze the results, and optimize the procedures that generate multiple responses.
By applying this methodological design, a clearer picture of the relationships between strategic objectives is obtained and the influence of strategic objectives on one another is determined. Afterward, optimal values for performance measures are determined.
This paper proposes a framework for constructing a strategy map and setting quantitative targets to translate the goals and strategies into corresponding performance measures and targets. Also, this paper presents a case study to demonstrate the applicability and effectiveness of the proposed approach. However, RSM-based techniques require a greater amount of data to generate more accurate results. Although the advent of the Information Age has forced organizations’ decision makers to provide sufficient information and data for business analysis, the data requirements of RSM-based techniques are met.
In practice, the process of setting targets for performance measures can be challenging in terms of reaching a consensus between managers and decision makers. The findings of this paper can offer a new approach for performance evaluation based on the BSC which allows the organization’s decision makers to reach a more accurate picture of the relationship model between organization goals and those objectives within the BSC. It also demonstrates how decision makers can be guided in the process of defining performance target values in the BSC method.
Reviewing the literature on setting quantitative targets within the framework of the BSC showed no prior study in which RSM is used. This approach has two main contributions: the associations among strategic objectives are investigated and obtained in an effective way which analytically identifies the direction and degree of the relations among the performance measures. Considering the performance evaluation structure based on the BSC, quantitative targets have been determined to help in achieving the long-term goals of the organization. The application of the proposed method in a company showed that the contributions of this research are not only theoretical, but practical as well.
AbstractIn reverse osmosis seawater treatment process, membrane fouling can be mitigated by degrading organic pollutants present in the feed seawater. The present study evaluates the effectiveness of employing solar photocatalysis using TiO2/ZnO/H2O2 to pretreat reverse osmosis (RO) feed seawater under solar irradiation. Process optimisation and performance evaluation were undertaken using response surface methodology-desirability function and RSM integrated with genetic algorithm (RSM-GA). Statistical analysis was performed to determine the interactive relationships and main effects of input factors such as TiO2 dosage, H2O2 dosage, pH, reaction time and ZnO dosage. The performance evaluation was determined in terms of percentage removal of total organic carbon (TOC) and chemical oxygen demand (COD). The obtained optimum values using RSM-GA evaluation for TOC and COD removal were found to be 76.5% and 63.9%, respectively. The predicted RSM-GA results correspond well with the experimental results (TOC removal = 73.3%, COD removal = 61.2%). Utilization of renewable solar energy coupled with optimum utilisation of nanophotocatalysts enables this technique to be a unique treatment process for RO pretreatment of seawater and membrane fouling mitigation.