On uncertainty assessment with Marcello Cavallare, Sergio Sousa, Eusébio Nunes at the PMA 2014 Conference
The presentation “Uncertainty assessment of performance indicators” was offered, in the third day of the PMA 2014 Conference, by Marcello A. L. Cavallare, Sergio d. Sousa and Eusébio p. Nunes, from University of Minho, Portugal.
Their research study focused on providing a model for evaluating performance indicators’ uncertainty, based on Uncertainty Components (UCs). This was achieved by following 5 steps:
- Assessing the level of influence that each UC has on the performance indicators;
- Assessing the performance indicators’ overall uncertainty;
- Establishing the Input and Output variables that are affected by the level of uncertainty;
- Creating rules of treatment for the Input and Output variables;
- Estimating the performance indicators’ uncertainty.
The researchers also performed a case study on 5 companies, by conducting semi-structured interviews based on a questionnaire with the KPI owners. The questions were designed in such manner as to request the interviewee’s perception on how UCs affect performance indicators’ level of uncertainty.
The main conclusions that the Professors arrived at can be summed up as follows:
- Performance indicators are affected by different components of uncertainty that were previously defined;
- Their uncertainty can be predicted by using a specific model;
- UCs definitions can be used to reduce performance indicators’ degree of uncertainty.