The ability to manage and harness the ever-growing surge of data is important for every organization’s success. However, the goal of any data strategy should be to deliver measurable business outcomes. Most organizations don’t refer to (or align with) business outcomes in their data strategy. In the absence of this alignment, data strategy merely becomes an assembly of architectures, plans, goals, and roadmaps. Data strategy should be thought of as a means of empowering business strategy by delivering durable outcomes.
An outcomes-focused data strategy can deliver systemic value and attract sustained investments over the long term. The key to this approach is to deliver iterative value focused on current business objectives and identify future opportunities. This presentation will cover some practical ways to develop an outcomes-driven data strategy to deliver iterative value. Data architecture modernization and maturity are key byproducts of solving business problems.
Some important questions covered include:
- What is the benefit of data strategy to the business?
- What are the key components of data strategy?
- How can you drive economic value by aligning business strategy with data strategy?
- How do you communicate and/or get buy-in?
- How can you modernize data architecture while being laser-focused on delivering business outcomes iteratively?
- How can you create building blocks of data strategy while remaining focused on current business objectives?
- How do you achieve balance between centralized and decentralized requirements of data and analytics?
- How should you think about governance in a centralized and/or decentralized model?