Flexibility and timeliness should both be maximised to provide actionable intelligence.
In contrast, credibility and integrity cannot be maximised simultaneously since they evolve in opposite directions.
For instance, a system that achieves high credibility but low integrity provides truthful but incomplete results, while a system that achieves low credibility and high integrity provides comprehensive but unreliable results.
When considering the ability of the system to detect links among forensic case data, integrity is connected to the well-known risk of linkage blindness [13] while credibility is connected to the risk of detecting links that are actually absent.
It is hypothesised that the credibility and integrity of the system are the driving factors for decision-making in performing any forensic intelligence task.
Any selection of a metric or of an evaluation system, any queries in a database or any risk assessment are based on these criteria to balance the decision in order to fit the results to the expectations of operators.
Finding the optimal trade-off between these criteria and the operational needs is a constant challenge for forensic scientist and intelligence analysts.