Developing a planning tool for South African prosecution resources: challenges and approach

R Koen, JP Holloway, CD Elphinstone, T Stylianides

Abstract


In every country the prosecution of criminal cases is governed by different laws, policies and processes. In South Africa, the National Prosecuting Authority (NPA) has the responsibility of planning and managing all prosecution functions. The NPA has certain unique characteristics that make it different from other similar organisations internationally. The development of a planning tool that the NPA could use to plan their future resource requirements over the short to medium term required extensive modelling, and its final form included features which, to the best knowledge of the development team, make it unique both locally and internationally. Model design was largely influenced by the challenges emanating from the special requirements and context of the problem. Resources were not forecasted directly, but were derived with the help of simulation models that traced docket flows through various resource-driven processes. Docket flows were derived as a proportion of reported crimes, and these were forecasted using a multivariate statistical model which could take into account explanatory variables as well as the correlations between the patterns observed within different crime categories. The simulation consisted of a number of smaller models which could be run independently, and not of one overarching model. This approach was found to make the best use of available data, and compensated for the fact that certain parameters, linking different courts and court types, were not available. In addition, it simplified scenario testing and sensitivity analysis. The various components of the planning tool, including inputs and outputs of the simulation models and the linkages between the forecasts and the simulation models, were implemented in a set of spreadsheets. By using spreadsheets as a common user interface, the planning tool could be used by prosecutors and managers who may not have extensive mathematical or modelling experience.


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DOI: https://doi.org/10.5784/28-2-105

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ISSN 2224-0004 (online); ISSN 0259-191X (print)

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