Establishing an Analytics Maturity Model

The world of video surveillance has changed considerably over the past several decades. Analog cameras have fallen by the wayside in favor of internet protocol (IP) cameras capable of providing better image quality and vastly increased processing power. This has paved the way for the emergence of video analytics tools that can greatly enhance the value of any surveillance network. While different individuals and organizations will have different levels of analytics knowledge, one thing remains constant: whether they are analytics experts or just getting started, there are exciting new analytics solutions that can have a significant impact on security, safety, and operations.

With that in mind, Axis Communications recently published a helpful new analytics framework titled “Building a maturity model for video analytics.” The goal of the paper is to outline the different levels of familiarity and experience with analytics that today’s organizations tend to exhibit, to help organizations understand where they may fall and help integrators and developers understand how to meet their needs. Below, you can find an overview of what the paper covers at the beginner, intermediate, expert, and developer levels. For a more thorough examination of those levels, including recommendations on the specific solutions organizations may be looking for, we urge you to read the full publication.


Those just getting started may have only a rudimentary understanding of video analytics. That’s okay—but it means education is critical. Proper guidance can help beginners explore the available technology and better understand what they are capable of implementing without the need for significant expertise. For beginners, security capabilities are usually most important, along with getting up to speed on analytics terminology and concepts like machine learning. Integrators can help identify the specific technologies—and technology partners—that can meet beginners’ needs.


At the intermediate level, users likely have a more advanced understanding of analytics on a conceptual level but need help identifying the right tools for the right jobs. Intermediate users are also generally focused on security, but many may also be interested in additional use cases to broaden their understanding. The knowledge gap is smaller at this level, but the need for education still exists, and personnel restrictions may limit what organizations can take on. Intermediate users may want to seek out manufacturers and integrators to help them gain a clear understanding of their goals and begin to realize the full potential of video analytics.


Experts generally know what they want and have considerable familiarity with analytics. With that in mind, pain points tend to center around finding ways to integrate the vast amounts of data that they are collecting and identify the most relevant information. Expert users often want to unify wide ranging tools under a single umbrella, and integrators can them in areas like finding more effective storage solutions as their data needs expand. A “one-size-fits-all” approach will almost never work with experts—they have unique needs, so when they reach out to integrators and manufacturers, they will want a thorough and detailed explanation of available products and services.


Developer needs are nearly as important as customer needs, and manufacturers should look to identify ways to encourage developers to build new applications and tools for their devices. There are a wide range of ways to do this, including providing strong software development kits (SDKs) and maintaining an open dialogue with developers. This helps ensure that both manufacturers and developers have a thorough understanding of the challenges they face and can work together to overcome them. It can also help developers avoid stumbling blocks by ensuring they have proper documentation to work with. Developers should feel empowered to communicate directly with manufacturers, maintaining a two-way dialogue that benefits both parties.

Analytics technology is constantly evolving, and so are the needs of customers, vendors, and integrators. That means it’s important to always be learning. And as applications and use cases change, helping customers understand where they fall on the model and providing them with the support and advice that they need to accomplish their goals can go a long way toward enabling them to realize the promise of today’s video analytics technology. Customers, manufacturers, and integrators should all understand what a modern analytics maturity model looks like, in order to better position themselves to make the most of today’s advanced analytics solutions.

To read the full report:

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