A large number of organizations continue to face hurdles in sustaining progress toward higher levels of maturity in the Dresner Advisory Services Hyper-Decisive® Maturity Model (HDMM). These challenges arise mainly due to the highly fragmented nature of enterprise data and analytics across most organizations.
This fragmentation stems in large part from the application-centric approach most organizations adopted, since the inception of enterprise applications, to meet business requirements. The resulting complexity and silos of data and analytics over time—and on a cumulative basis—serve as “friction” limiting progression to higher levels of organizational maturity.
We believe that a threshold exists within the HDMM that, if not crossed, prevents organizations from achieving higher levels of maturity. This barrier to higher levels of maturity results from the state and focus of the data and analytics infrastructure.
Organizations that want to achieve higher levels of maturity in the HDMM competencies of completeness and diversity of data and common trust in data / governance increasingly need to approach data and analytics requirements from the perspective of supported business value chains, rather than business applications that support them.
To pivot optimally from an application-centric approach to data and analytics to one that is data-centric, organizations should transition, over time, to the Dresner Advisory Services Balanced ADI-ODI Model. This model prioritizes data and analytics over enterprise applications within the context of enterprise business value chains.
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