Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2015, Article ID 102606, 9 pages
http://dx.doi.org/10.1155/2015/102606
Research Article

Developing a Robust Strategy Map in Balanced Scorecard Model Using Scenario Planning

Department of Industrial Engineering, Iran University of Science & Technology, Tehran 16846-13114, Iran

Received 14 November 2014; Revised 22 February 2015; Accepted 27 February 2015

Academic Editor: Jianxiong Ye

Copyright © 2015 Mostafa Jafari et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The key to successful strategy implementation in an organization is for people in the organization to understand it, which requires the establishment of complicated but vital processes whereby the intangible assets are converted into tangible outputs. In this regard, a strategy map is a useful tool that helps execute this difficult task. However, such maps are typically developed based on ambiguous cause-effect relationships that result from the extrapolation of past data and flawed links with possible futures. However, if the strategy map is a mere reflection of the status quo but not future conditions and does not embrace real-world uncertainties, it will endanger the organization since it posits that the current situation will continue. In order to compensate for this deficiency, the environmental scenarios affecting an organization were identified in the present study. Then the strategy map was developed in the form of a scenario-based balanced scorecard. Besides, the effect of environmental changes on the components of the strategy map was investigated using the strategy maps illustrated over time together with the corresponding cash flow vectors. Subsequently, a method was proposed to calculate the degree of robustness of every component of the strategy map for the contingency of every scenario. Finally, the results were applied to a post office.