Investigative Decision-Making

• Investigative decision-making is the process of making informed decisions during an investigation. It involves gathering and analyzing information to determine the best course of action.

  • Information gathering: The first step in investigative decision-making is to gather as much information as possible. This can include witness statements, physical evidence, and other relevant data.

  • Analysis: Once you have gathered all the information, it's time to analyze it. This involves looking for patterns, inconsistencies, and other clues that can help you make informed decisions.

  • Decision-making: Based on your analysis, you will need to make decisions about how to proceed with the investigation. This can include deciding which leads to follow up on, which witnesses to interview, and which pieces of evidence to prioritize.

  • Documentation: Throughout the investigative process, it's important to document everything. This includes notes from interviews, photographs of evidence, and any other relevant information. Good documentation can help you stay organized and make informed decisions.

  • Collaboration: Investigative decision-making often involves working with other professionals, such as law enforcement officers, forensic experts, and attorneys. Collaboration can help you gather more information and make better decisions.

Background Theory and Evaluation

• Investigative decision-making originates from various academic fields such as economics, philosophy, mathematics, business, and management studies.

• Pascal's theory of economic utility suggested that humans make rational decisions to maximize benefits and minimize costs.

• Bernoulli agreed with Pascal but argued that people are risk-averse and choose the safest option.

• Game theory suggests that decision-making is rational but also interdependent, considering the influence of others.

• Kahneman and Tversky's work showed that in real-life situations with ambiguity, limited time, and intense pressure, humans use heuristics, which are mental shortcuts to facilitate quick decision-making.

• Decision makers are prone to biases such as belief persistence and confirmation bias, which can be particularly relevant to investigative decision-making.

• Gigerenzer's "fast and frugal" heuristics approach suggests that ignoring some information can lead to more efficient thinking and improve accuracy.

• Heuristics can produce a "less-is-more" effect, improving decision-making.

• The FFH approach has been applied to investigative decision-making, highlighting its usefulness in this field.

• Garcia-Retamero and Dhami (2009) found that both experienced burglars and police officers relied on the same heuristic, take-the-best, when appraising which properties were more likely to be burgled.

Recent Approaches and Development

• The traditional decision theory (TDT) approach was developed through laboratory-based empirical work for theory development.

• However, the Naturalistic Decision-making (NDM) approach, which has emerged over the last three decades, focuses on ecologically valid problem-driven methods. This perspective emphasizes expertise and considers the context in which decision-makers operate.

• Decision-making inevitably takes place in complex environments, which are often dynamic and fluid.

• NDM focuses on how decisions are made in real-world situations, rather than how they should be made in artificial, straightforward situations.

• The NDM approach has generated methods to explore decision-making, such as cognitive task analysis. Recent research has focused on intuition and goal-orientation.

• Decision inertia, which is a failure to act, is a body of research that has emerged in the twenty-first century. It encompasses three subcategories: decision avoidance, redundant deliberation, and implementation failure.

• Inertia research includes context in its broadest sense, including organizational, political, and cultural influences.

• A synthesis of different theoretical and paradigmatic approaches has been called for, with input from the NDM perspective and inertia research being most beneficial for complex, high-stake decisions.