Analytics programs are diverse, encompassing not only analytics or business intelligence, but analytics governance and even some degree of data management. Though they aim to improve business outcomes, the organization's level of analytics maturity is the key inhibiting factor to their success. We'll talk more about success later. Advances in data management strategy requirements, technology skills, and a vast range of internal and external data sources demand an updated set of maturity indicators. Data maturity is a prerequisite to getting the most from an analytics program. Analytic strategies include; desired business outcomes, people, processes, data, and technologies. As analytics program matures, the optimal architecture will evolve along with the processes and skills needed to support it. To improve their analytics programs, organizations need to do three key things. They should regularly assess the analytics capability maturity then seek support, funding, and advice to advance their capabilities and thereby improve their ability to support the businesses strategic objectives. Second, it should drive all analytics programs with a clear line of sight to a business outcome. Showing where and how business value can be increased through improving the maturity of their analytics capability. Third, we should build out a future-state set of capabilities from a gap analysis of their current capabilities, and those needed for their business strategy. Then, recheck their progress as they build or improve their analytics capability. Analytics leaders are increasingly being tasked with the goal of exploiting analytics as a strategic asset, so they want to know the steps required to achieve this. Enterprises of any size and in any industry can gauge their capabilities in general and for any data in our analytics initiative. Once initiatives have been evaluated and programs prioritized, further analysis of maturity at the specific program level can then occur. A proper assessment measures the maturity of an analytics organizations, processes, and capabilities not of the solutions deployed. A young organization may manage advanced technology and solutions, and a program portfolio with immature practices. Immature practices may achieve near term objectives but will eventually erode the effectiveness of the organization, and the integrity of its solutions, and disciplines, as well as create what's called technical debt, which is simply having to pay later for the shortcuts you take today. By contrast, analytics organizations with mature processes can deliver optimal business results even via older and less modern technology.