Resumen de Development of systemic methods to improve management techniques based on balanced scorecard in manufacturing environment
The Balanced Scorecard (BSC) as a Performance Management Method (PMS) has been spread worldwide since Kaplan and Norton (1992) established its theoretical foundations. Kaplan (2009) claimed that the use of the BSC and especially turning strategies into actions was more an art than a science. The lack of evidence of the existence of such cause and effect relationships between Key Performance Indicators (KPIs) from different perspectives and the lack of robust methods to use it as a scientific tool were some of the causes of its problems. Kaplan placed the scientific community to confirm the foundations of the BSC theory and to develop methods for its use as a scientific tool.
Several works have attempted to enhance the use of the balanced scorecard. Some methods use heuristic tools, which deal with qualitative variables. Some others use statistical methods and actual KPIs data, but applied to a specific period, which is a static vision and needing long-term samples and expertise resources to apply advanced analytic methods each time executives need to assess the impact of strategies. This thesis also tackles the lag between "input" and "output" variables. Moreover, there is a lack of works focused on the manufacturing environment, which is its main objective.
The first objective of this work is to develop a methodology to assess and select the main output KPIs, which explains the performance of the whole company. It is taking the advantage of the relationships between variables from different dimensions described by Kaplan. This method also considers the potential lag between variables. The result is a set of main output KPIs, which summarizes the whole BSC, thus dramatically reducing its complexity.
The second objective is to develop a graphical methodology that uses that set of main output KPIs to assess the effectiveness of strategies. Currently, KPIs charts are common among practitioners, but only Breyfogle (2003) has attempted to distinguish between a significant actual change in the metrics and a change due to the uncertainty of using samples. This work further develops Breyfogle's method to tackle its limitations.
The third objective is to develop a method that, once the effectiveness of those strategies and actions have been proved graphically, quantifies their impact on the set of main output KPIs.
The ultimate goal was to develop a method that, using data analytics, will focus on the diagnosis of the quality management system to reveal how it works in terms of the relationships between internal (within the company) and external (costumer-related) KPIs to improve customer satisfaction.
The application of the four methods in the right sequence makes up a comprehensive methodology that can be applied in any manufacturing company to enhance the use of the balanced scorecard as a scientific tool. However, professionals may choose to apply only one of the four methods or a combination of them, since the application of each of them is independent and has its own objectives and results.
