Table of Contents
SLEIPNIR is a tool developed by the Royal Canadian Mounted Police (RCMP) and used in criminal intelligence analysis to assist in the ranking and comparison of the threat of organized crime groups. SLEIPNIR is an example of a structured professional judgement (SPJ) tool similar to the SAVRY.
By using the Sleipnir tool you can determine the level of risk presented by a number of organized crime groups, compare them to each other and determine where intelligence gaps exist. (IALEIA, 2011)
Sleipnir is not designed to be used as a tactical intelligence tool, but rather as a strategic one to assist in setting priorities.
From Strang (n.d.), comes this example image comparing 5 groups along the 19 items:
There are 19 items in the Sleipnir tool which correspond to the threat they pose to Canadian society. In the original tool they are ranked from biggest threat to smallest threat to Canadian society (Strang, n.d.). So for instance, Corruption is considered the largest threat from organized crime, followed by Violence.
In the list below, they have been reverse coded based on the scoring system you’ll see in the next section.
10. Intelligence Use
9. Multiple Enterprises
4. Group Cohesiveness
2. Links to Other Organized Crime Groups
1. Links to Criminal Extremist Groups
Each of the 19 values can be scored (RCMP, 2000) using the following:
- High = 4 x P
- Medium 2 x P
- Low = 1 x P
- Nil = 0
- Unknown = 2 x P
Where P is the number of the subcomponent in the list above. For instance, if Monopoly (#5) is High, Intelligence Use (#10) is Medium and Violence (#18) is Low, they would be scored the following:
- Monopoly = 5 x 4 = 20
- Intelligence Use = 10 x 2 = 20
- Violence = 18 x 1 = 18
The total will be 68. The maximum score is 0 to 760 and a higher score (relative to other organizations being checked) represents a higher level of dangerousness.
There are specific operational criteria for each of the components and scoring levels.
As of this writing I am in the process of obtaining the report (“SLEIPNIR, the long matrix for organized crime : an analytical technique for detecting relative levels of threat posed by organized crime groups”) from the Public Safety Canada Library to determine the copyright that exists on the definitions. Once I have ascertained that it is legal to publish them here, I will do so.
I have since obtained a copy of the report. Because the definitions and ratings (of High, Medium, Low and Nil risk) are under copyright to the RCMP please contact me if you’d like information on how to access them.
In addition to being used in Canada by the RCMP that developed it, Sleipnir has also been used successfully in Honduras where gang violence is endemic. (Ratcliffe & Rose, 2015)
It should be noted that these factors, while ranked as above in the original Canadian research, may not be generalizable outside of Canada. This means that other countries may weigh these factors differently. (Ratcliffe, Taylor & Strang)
Ratcliffe, J., Sorg, E., & Rose, J. (2015). Intelligence-Led Policing in Honduras: Applying Sleipnir and Social Psychology to Understand Gang Proliferation. Journal Of Police And Criminal Psychology, 30(2), 112-123. doi:10.1007/s11896-014-9143-4
Ratcliffe, J., Taylor, R. & Strang, S. (2014). Assessing the success factors of organized crime groups: Intelligence challenges for strategic thinking. Policing, 37(1), 206-227. doi:10.1108/PIJPSM-03-2012-0095
Royal Canadian Mounted Police. (2000). SLEIPNIR: The Long Matrix for Organized Crime, An Analytical Technique for Determining Relative Levels of Threat Posed by Organized Crime Groups. Criminal Analysis Branch, Criminal Intelligence Directorate, Royal Canadian Mounted Police. Ottawa, ON.
Strang, S.J. (n.d.) “Project SLEIPNIR: An Analytical Technique for Operational Priority Setting” Accessed electronically on July 7, 2016 from https://www.e-education.psu.edu/drupal6/files/sgam/Project%20SLEIPNIR%20An%20Analytical%20Technique%20for%20Operational%20Priority%20Setting.pdf
Criminal Intelligence for the 21st Century: A Guide for Intelligence Professionals. (2011) International Association of Law Enforcement Intelligence Analysts (IALEIA). pp.146