Intended for grantees under the federal Bureau of Justice Assistance’s (BJA’s) Body-Worn Camera Policy and Implementation Program, this Guide instructs grantees in various aspects of acquiring body-worn cameras (BWCs) for agency personnel.
The Guide notes that it will assist grantees through the complex BWC acquisition process, so they can make an informed decision based on an agency’s distinctive requirements. This includes providing guidance throughout the acquisition process regarding agency needs and local factors that influence the acquisition process for each grantee. Information will be provided on common practices used by currently and former grantees relating to policy development that drives considerations for acquiring BWCs; however, there are certain restraints on the assistance BJA can provide grantees; the agency cannot dictate or even recommend which camera to buy, and it cannot dictate whether a grantee agency should buy system components a la carte or select a package of hardware, software, and services offered to the grantee by a vendor. The Guide discusses the “overarching” considerations related to BWC acquisition. These include state legislation pertinent to BWC acquisition, what an agency must do to prepare for BWC acquisition, and recognition that “up-front” costs are only part of the equation. Other issues discussed in the Guide are the goals and methods of planning for BWC acquisition, the “front-end” research needed, documentation of desired BWC capabilities, and steps in the pilot testing of multiple vendors’ systems. Information to obtain from the vendor is discussed. The Guide’s concluding statement is, ”Thorough research and planning are crucial for navigating your BWC procurement and ensuring that your decision provides the best possible value and utility for your agency.” The BWC Training and Technical Assistance Team can provide a grantee assistance throughout this process.
Downloads
Similar Publications
- Assessment of Sexual Assault Kit (SAK) Evidence Selection Leading to Development of SAK Evidence Machine-Learning Model (SAK-ML Model)
- Police Officer Attitudes toward Pre-arrest Behavioral Health Diversion Programs: Identifying Determinants of Support for Deflection Using a Machine Learning Method
- BetaHub Support for Practitioner-Led Randomized Controlled Trials and Related Research in Correctional Facilities and Law Enforcement Agencies