In various industries, calculation and forecasting techniques are applied to identify the relevant outcomes and consequences of decisions or interventions. In particular, the two most common approaches are utilized – deterministic and probabilistic. According to Muriana and Vizzini (2017), one of the main values of deterministic models is an opportunity to determine the results of specific analyses precisely due to current conditions and the parameter values.
For instance, the authors give an example of project management and offer to consider options under which a responsible person can rely on forecasting due to the existing information, including numerical and other data. Probabilistic methods, in turn, as Whelan et al. (2018) state, do not allow for a clear picture of a particular intervention and suggest potentially distinctive analytical results. For instance, the researchers assess the implications of a particular leadership style in different contexts (Whelan et al., 2018).
At the same time, the values of each of the methods imply using both deterministic and probabilistic approaches in different conditions for evaluating unambiguous or variable outcomes, respectively.
When comparing both methods in terms of their effectiveness, one can assume that the deterministic approach is more valuable than the probabilistic one due to greater accuracy. Wiart (2016) notes that calculation and forecasting models based on these estimates help obtain more objective and unambiguous data, for instance, through the introduction of statistics or other reliable tools.
Moreover, often, for testing any hypothesis, accurate research results are essential to prove specific correlations and relationships or, conversely, disprove them. Consequently, despite the usefulness of probabilistic methods for making variable forecasts, deterministic models are more valuable from the standpoint of the results of analytical activities.
References
Muriana, C., & Vizzini, G. (2017). Project risk management: A deterministic quantitative technique for assessment and mitigation. International Journal of Project Management, 35(3), 320-340.
Whelan, G., Sarmiento, R., & Sprenger, J. (2018). Universal-deterministic and probabilistic hypotheses in operations management research: A discussion paper. Production Planning & Control, 29(16), 1306-1320.
Wiart, J. (2016). Radio-frequency human exposure assessment: From deterministic to stochastic methods. John Wiley & Sons.