Any individual who’s worked with our simulation tools will know that model validation is an integral part of the modelling process. While it may be perceived as time-consuming and challenging, validating models should be embraced as an opportunity rather than a mere task. It offers a crucial avenue to comprehend historical data, scrutinize inputs, and establish confidence in the analytical model. In a recent session, Mark Bryant guided our attendees through the effective validation of models and the meaningful analysis of scenarios derived from a baseline model.
The Purpose of Model Validation:
The primary question to address is why we validate models. Beyond ensuring the accuracy of inputs, validation plays a pivotal role for analysts and senior leaders. It instils confidence and garners buy-in for the technology employed, providing a vital reality check to confirm that observed outcomes align with the expected feasibility during scenario runs. Integrating model validation into the simulation and modelling process is imperative. Even in cases where historical data quality might be questionable or old processes don’t align with current understanding, a degree of validation should persist to either accommodate a higher tolerance in model outputs or to ensure that the baseline model outputs ‘feel’ right.
Factors Influencing Model Validation Efficacy:
Mark addresses the dangers of data integrity and ensuring that the data input addresses more forcewide performance, in lieu of granular analysis. Ensuring that users of the tool can minimise the amount of assumptions made within the modelling phases of a project cant maximise the efficacy of the validation process.
Nuances in Response and Call Profilers:
Each Response and Call profiler requires specific attention during validation. For Response Profiler, the emphasis should be on ensuring that resource utilizations appear appropriate and that grade 1 and 2 performance levels are reasonable. Call Profiler, while more challenging to validate, has key aspects to observe, including performance levels at specific times of the day as well as abandonment rates.
Key Tips for Effective Scenario Validation:
Mark’s paramount advice for effective scenario validation revolves around one crucial theme: a structured approach with documentation. Creating a ‘back sheet,’ either within the Excel models or on a results workbook, facilitates the compilation of key statistics. This documentation enables the modelling and amendment of key details, while also tracking changes influenced by essential process steps.
In conclusion, the diligence invested in model validation is not merely a procedural necessity but a strategic imperative. It builds confidence, ensures data integrity, and ultimately enhances the reliability and effectiveness of analytical models in the realm of policing.
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