In the modern-day Information Age, data is the lifeblood of virtually every organization and functional area in business. Awareness of this reality, however, is only the first step towards solving today’s most endemic organizational problem: how to utilize and apply data assets in ways that directly support business imperatives. Many C-level executives who try to get more out of their data oversimplify the data management process, and accordingly find themselves frustrated by the initiative’s unexpected complexity, how long it often takes to complete it, and the relative lack of deliverable progress they’re ultimately able to make.
Mainstream concepts like “Big Data” and “Data Science” make huge promises and sound great on paper, but alone have proven insufficient for meeting today’s business needs and providing sustainable long-term benefits. To leverage data in support of strategic objectives, designing and implementing an effective data strategy is essential, specifically one centered around three holistic core tenets:
Embrace the realization that data assets need better treatment
Recognize that a universal, organization-spanning strategy for managing data assets and developing workers with new knowledge, skills, and experience is required to meet the challenges of tomorrow
Adopt a socio-technical approach to data assets, so they can be incorporated into all operational parts of the organization
Data is the only non-depletable, non-degrading, and durable strategic asset organizations have in their arsenal - and data strategy is how they can benefit from it. Understanding the role of modeling within this context is critical - several examples will illustrate how models can be used to both uncover existing (or preexisting) aspects of strategy and to set boundaries on selection or development of future IT assets.