An Analytical Performance Management Framework Enabiling Enterprise Strategy Management

Performance management has gained noticeable interest from both researchers and executive in the past two decades. Financial measures are no longer a primary emphasis for researchers and executives. One of the most popular performance management methodologies is the Balanced Scorecard. The Balanced Scorecard framework facilitates translating strategy into objectives and initiatives across four perspectives. These perspectives are financial, customer, internal processes, and learning and growth. The second component of the balanced scorecard is strategy maps. Strategy maps outline the cause and effect between the four perspectives, and illustrate the value creation process through transforming leading indicators (operational measures) into lagging indicators (financial measures). This research extends the balanced scorecard framework by introducing Stochastic Timed Strategy Maps (STSM). STSM quantifies the strategic value creation process by quantifying the cause and effect relationship on strategy maps. We introduce three dimensions for the cause effect relationships. These dimensions are quantity, time phase, and uncertainty. The three dimensions quantify the cause effect relationship between the BSC objectives. Monte Carlo simulation is utilized to simulate the quantified scorecard and establish a future view of the financial performance of the enterprise. STSM along with balanced scorecard simulation allow translating various operational measures into expected time-phased financial performance. A simulated case study using data generated as part of the research is analyzed. The case study is used to demonstrate the theoretical feasibility of the framework. In addition, the case study is used to communicate and illustrate the application of the proposed framework in comparison with other methodologies as used in the literature and industry. Simulation results demonstrated that the proposed framework provides a better evaluation mechanism than traditional tradeoff-based approaches. Simulation results also showed the importance of focusing on process improvements as it allows improving both the expected output performance and the variability of the expected values. The research suggests that adopting the proposed analytical framework will provide additional insight and value into strategic planning and execution processes. Keywords; Balanced Scorecard, Strategy Maps, Simulation, Multi Objective Analysis, Performance Management, Strategy Management.