Business Framework for Analytics Implementation

Defining and executing a strategy that extends analytics into the operational environment in a world of dynamic and "big" data present a number of challenges. Organizations seek to establish a creative and high impact analytic capability and align those capabilities within the context of the organizations' operational capabilities.

Employing a structured framework that allows managers to identify and prioritize required capabilities, align them with business strategies, and evaluate alternative implementation paths is critical to success. The DMM addresses foundational data management capabilities. By extending DMM practices into the strategy, requirements, and design processes of analytics, an integrated framework is created, to define and implement actionable roadmaps delivering operationalized high impact analytics.

In this discussion, you will learn:
• How the DMM best practices support the alignment of business strategy for analytics
• The role of the DMM in creating and integrating business priorities for enterprise analytics efforts
• The DMM-based framework for creating an analytics roadmap

Ms. Mecca, CMMI Institute’s Director of Data Management Products and Services, led development of the Data Management Maturity (DMM) Model. Her team created a business-centric method for assessing an organization’s capabilities via the DMM, and she leads Assessments for organizations in multiple industries. She directed creation of the Building EDM Capabilities, Mastering EDM Capabilities, and Enterprise Data Management Expert (EDME) courses leading to the EDME certification. In her 30+ years solving enterprise data challenges, Ms. Mecca advocates measuring data management capabilities as the quickest path to business value, and is devoted to empowering our industry through data management education.

Mr. Adams has over 20 years experience in leading requirements, design and implementation efforts for retailers, financial organizations and Federal agencies including Departments of Justice, Commerce and the Treasury as well as the IRS. For the past 10 years, Jonathan has focused on architecting and implementing analytical and data management solutions focused on fraud detection, regulatory compliance and risk management. While at Booz Allen Hamilton, he was a member of the Data Management Maturity Model development team and is a certified Enterprise Data Management Expert (EDME). Since the release of the Data Management Maturity Model, Jonathan has been working on extensions to the DMM that integrate data management and analytical best practices to provide clients with a way to roadmap needed analytical and data management capabilities aligned with business and operational requirements.