Information Strategy

Information management identified five obstacles to success with data and analytics: lack of a strategy; lack of organizational readiness; lack of direction; lack of execution; and lack of using data and analytics to deliver business impact (link here). The root cause – lack of leadership and focus on purpose. Success with data and analytics will only be as effective as the support and applied authority of its leadership.

A successful Information Strategy addresses the above problems by:

  • Understanding the goals and objectives established by Executive Leadership and their business drivers;
  • Identifying the organizations Data Use Scenarios and Analytic Areas of Opportunity as well as its business information needs;
  • Identifying and ranking information opportunities, uses, and needs to establish their relative importance to and impact on the business;
  • Establishing a future technical architecture framework for supporting identified information opportunities, uses, and needs;
  • Identifies candidate technologies, skills, processes, and organization needed for success with the future data and analytics environment needed for the strategy;
  • Develops a high-level future state data architecture required for
  • Develops a Roadmap identifying a sequence of defined projects, based on opportunity rankings and business priorities for successful implementation of a data and analytics capability that will:
  • Support all business drivers and goals;
  • Satisfy business information needs;
  • Deliver information objects for all data use scenarios;
  • Establish information planning for the entire information lifecycle;
  • Build organizational and technical capabilities for physical data management of trustworthy data.

An information strategy is an extension of a business strategy and should focus on tangible business benefits, such as increasing revenue, reducing costs, improving customer satisfaction, reacting to regulatory issues, managing risk, and so forth.