Analytics Capability Maturity for an organization evolves over period of time. There are four distinct phases, wherein each subsequent phase progressively gets harder to tackle than the previous phase. Analytics Maturity is similar to the four stages of evolution of data Data–Information–Knowledge–Wisdom.
BI Adoption plays a key role in moving forward in the maturity ladder towards becoming data driven organization. In order for adoption to succeed, the value provided by any BI program should have a direct impact on day-to-day operations of the business. BI and Analytics projects are essentially enablers for impact top line or bottom line.
|Backward Looking||First stage in the journey of Analytics starts with simple reports of events and various metrics in a structured format. Data sources are typically disjoint and emphasis on data integration is low. Strategy focuses on measuring various parameters and providing reports in timely fashion.|
|Backward Looking||Second phase provides avenues for users to perform What-if Scenario analysis, finding Root Cause etc. This requires consistent and integrated data and hence emphasis on ETL is high. Rudimentary optimization and planning functions are also executed on underlying data.|
|Forward Looking||Data Integration is critical with heavy emphasis on Quality and Security. Various algorithms are applied in order to gain insights. Output of algorithms aid in decision making process and various parameters are tweaked iteratively and re-simulated in order to achieve optimal performance.|
|Forward Looking||Advanced algorithms are used to study patterns over period of time. Any scenario is simulated along with the algorithms to foresee outcomes of various decisions. Apart from aiding in decision making, the goal here focuses on providing best in class outcome for any given scenario.|