Information Asset Management: Using Asset Valuation to Drive Data Strategy

Learn how to use a framework based on Information Asset Management to make investment decisions that both tech and the business are behind.

The inherent conflict between the Business and Technology is something that many (dare we say ‘most’?) people in the world of Data and Analytics have experienced. The business has their priorities and the tech team have theirs. That’s the way it’s been, so that is the way it will be, right? Not if we can switch the narrative of an organization’s data investment strategy.

It is possible to go from being driven primarily by technology and data management capability factors (which tend to address data as a monolithic entity) to one that manages growth and maturity from the Information Asset’s calculated value and value potential. This way we get a value and value potential that reflects a balance across both business AND technology factors.

Bryan Coker, Data Strategist Consultant for Geckopaw Consulting, has developed a framework that leverages Business and Technical Metadata associated with an Information Asset to provide baseline and target projections that measure the impact of data management investments. This way, organizations can make investments that execute on the data program’s strategic, tactical, and maturity goals in lock step alignment with key corporate business and technical growth strategies.

Join us for this Thought Leadership session as Bryan dives deeper into how we can maximize the value of the Information Asset to enjoy the following benefits:
– Quantifiable Valuation Measures that justify data-centric investments.
– Data Leadership Empowerment through an interdepartmental, cross-organization backing on proposed investments.
– A “Data Culture” Platform to bring business, technical, data management stakeholders to the table as a collective group.
– Precision Business Cases that justify investment to help further corporate target goals and strategies.
– Investment Monitoring that not only justifies a given investment, but also monitors ongoing results achieved by that investment.
– Reduced Time-to-Market of investment as there is a more precise scope of work + projected investment and return + the support/participation of a “data community” (stakeholder) up-front.

About Bryan: Bryan Coker is an accomplished leader in IT Solutions Delivery. He has 15+ years experience driving business improvement initiatives leading software development and information architecture programs. He is a subject matter expert in data architecture, structured methodologies for software development, database design best practices for OLTP and OLAP systems, Enterprise Data Warehousing, and Business Intelligence.

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