Operationalization

The analytics landscape has matured, broadened, and totally transformed in recent years. This transformation has been driven by a wide range of factors including big data, the cloud, the increase in processing capability, the decrease in storage and processing costs, and the near-ubiquitous availability of algorithms. As a result, an organization must also totally transform the tools and processes it uses for analytics if it is to recognize its analytics potential. Many organizations still use legacy analytics software, many of which now include updated functionality to handle the new data and platform environments. However, it is critical that organizations also begin to take advantage of modern analytics approaches that have been built from the ground up to take advantage of today’s full range of capabilities, among the most crucial of which is operationalization:

• Moving beyond purely code-based environments and toward workflows that are easy-to-use, visually appealing, and intuitive
• Expanding analytic creators and consumers
• Enabling collaboration among every single user (independent of their role or department)
• Easing the deployment effort to operationalize and maintain analytics processes
• Simplifying the integration of analytics with applications and other business processes both simpler and safer

At WITSIDE, we offer solutions where operationalization is a predefined objective. We build models with repeatable, reliable results that do not depend on any single person or working environment to operate. Our model outputs become available to end-users in a timely and useable manner. Performance is monitored on an ongoing basis to ensure quality and alert people to any degradation over time. For us, operationalization of our solutions is the adoption path.