2024 Data Analytics for Law Enforcement Survey Report 5 1 2 3 Key Findings Most LEAs are still using multiple solutions to analyze their data Only 25.5% of LEAs use one central solution for analyzing their investigation data (Figure 2). Most organizations use multiple solutions, making it harder for them to connect the dots between disparate data sources and generate crucial insights for resolving cases. 69% of FIUs (Financial Intelligence Units) use three or more separate solutions to analyze their data (Figure 3). This is likely due to a combination of challenging data formats and limited tools for investigating them. Again, this increases the odds of important data falling through the cracks, resulting in missing or inaccurate information that could impede the ability of FIUs to resolve cases effectively. Unstructured data is one of the top challenges for LEA investigations A whopping 97% of LEAs admit their current solutions for data analytics have limitations (Figure 6), with 50% claiming that the lack of support for unstructured data is one of the top limitations. This is concerning, given that the data sources LEAs find most challenging to analyze in their intelligence operations and investigations are primarily unstructured (Figure 4), and include financial records (34%), external databases and cyber data (33% each), and digital forensics and crypto data (31% each). Most LEAs plan to expand, upgrade or replace their existing data analytics solution Existing data analytics solutions for law enforcement organizations are often limited and outdated, making it difficult for analysts to keep up with changes in data formats and volumes. It’s therefore no surprise that 75% of law enforcement organizations indicated they are planning, subject to budget approvals, to expand, upgrade or replace their existing data analytics solutions within the next 12 months (Figure 8). Our findings also show there is a correlation between the number of existing data analytics solutions within LEAs and the plans to change them: the more solutions used by the organization, the more inclined it is to expand or replace them (Figure 9) in an effort to streamline and optimize their solutions, in order to reduce the potential risk of data errors hindering their investigations, and improve their performance.