Innovation and best practices can be sown throughout an organization—but only when they fall on fertile ground.
ANALYTICS LIFECYCLE BEST PRACTICE AREAS
Analytics involves more than just assembling a group of data scientists and analysts. Analytics leaders must be concerned with a sphere of activities to achieve their business goals. Product managers, project managers, process architects, business analysts, quality managers, and technical developers are all key contributors to achieving analytics success. Organizational capabilities must include the following elements, each of which comprise the Analytics Lifecycle. Each capability is an analytics best practice that will be further described in this and subsequent chapters:
- Problem framing—To support ideation through the clear articulation of a problem, translation of that problem into a question that can be answered by data, investigation of potential root causes, and the effective prioritization of problems to be solved.
- Data sensemaking—To identify and acquire the data that is required to answer a question, then harmonize, rescale, clean, and prepare the data for analytics; also to explore and characterize the data to assess its utility in addressing our business question.
- Analytics model development—To use a variety of techniques including data visualizations, descriptive and inferential statistics, and advanced analytics; to support data storytelling to solve ...