Over the past year big improvements in how to install, configure and operate video analytics were made that will enable the acceleration of growth in adoption of video analytics. As any technology matures, new features are added and capabilities increase. With so much already invested in the development of these highly complicated video algorithms, however, it’s time to get a return on these investments. What enabled manufacturers to see this return was the adoption of the KISS model or Keeping it Simple. As a result of this adoption, existing video analytics providers and several new startup companies have employed different strategies that fall into three, much easier-to-support categories: rules-based configuration wizards, self-learning systems and the “search” analytics capability. Each of these analytic types solves the big challenges associated with highly complicated systems: Simplifying the support and competency required, while unleashing the value that comes as a result of user-customized video analytics.