ResiliEnt is your Business Intelligence Partner - Your Success is Our Mission! Do you know where you are in the BI Maturity Life Cycle? Are you wondering "what is a BI Maturity Life Cycle"?
At ResiliEnt prior to any new BI project we require a BI Assessment to determine where the organization is in the BI Maturity Life Cycle. Assessment interviews and JAD sessions have been conducted by ResiliEnt for large and mid-sized organizations in the public and private sector to determine where they fall in the BI/DW life cycle. As a result, four distinct stages of maturity have been identified:
- Pre-infancy (gestation)
Organizations categorized at the gestation (pre-infancy) stage of the BI/DW life-cycle have not selected a standard BI tool and no formal BI application has yet been deployed; however management realizes the need to adopt a BI strategy to meet not only the immediate need, but future ones as well. No formal centralized data management strategy exists. While transactional/operational data is collected the mechanisms for turning the raw data into useful information about the business has not yet been achieved at an enterprise level. No BI/DW tools have been adopted as a company/organization standard.
At this stage of the life-cycle, at least one and quite often multiple tools have been chosen for BI and DW however no standards have been agreed upon or enforced. Some report writing and data management using the tools has been undertaken. At this stage the BI applications and the databases are frequently made up of silos of information often disparate in nature, and there is little to no integration of these information assets.
A web-based self service BI application has not been deployed and no enterprise reporting database model like a data warehouse, data mart or micro-mart has been implemented.
At this stage of the life-cycle, a standard BI and DW tool has been chosen and a significant Web-based self-service BI application has been deployed. Another characteristic of this life cycle stage is an enterprise reporting database model, like a data warehouse, a data mart, or a micro-mart has been implemented.
Companies at this stage have not yet achieved independent and wide-spread end-user access to the data via Web-based ad hoc reporting, and similarly, sophisticated end-user analysis using OLAP tools has not yet been undertaken.
Common characteristics include a data warehouse (DW) strategy for creating a single version of the truth for important data entities, self-service reporting applications have been deployed via the Web and a facility has been rolled out to the end-users to allow data mining and self-sufficiency in composing their own reports and queries.
The dependency on IT by the business community has been significantly reduced and so has the information backlog. All key decision makers and knowledge workers have access to the data that drives their business which results in unbridled problem identification and opportunity discovery. KPI’s are visually presented for at-a-glance review by executive management and in general, via common distribution mechanisms (such as the Web and email) & using an assortment of popular output formats (such as HTML, Excel, PowerPoint and PDF) the health of the business is readily observable at any given time.