Devising the right Big Data strategy
Strong big data strategies can be as diverse as the businesses that need them. Much depends on the enterprise mission and overall strategic agenda. In short, are you seeking to:
- Accelerate innovation?
- Predict seasonal demand trends?
- More precisely segment consumers based on lifetime profit potential?
- Discover the most productive supply chain partners?
- Uncover unnecessary overhead costs?
Hallmarks of an effective big data strategy
To set a foundation for long-term success, companies need a big-picture view that recognizes the many different components of an effective ecosystem (including a well designed architecture and robust big data tools), as well as the different dimensions on which big data can deliver value; for example, one of the most effective big data techniques is linking disparate data sets – internal and external data streams, say, or information from different corporate functions – to find new meaningful patterns and correlations.
The link to specific business problems, market opportunities or use cases must serve as the basis for quantifiable business cases; strategic planning for big data should be business-led, with IT leadership fully engaged to inform the process; in other words, big data is not a science project, but rather must be focused on filling real-world business needs.
Big data is here today, of course, but future uses (especially transformational ones like customer microsegmentation and new data-driven products) must be taken into account; strategies and methodologies should avoid common constraints, like excessive reliance on single technologies or partners; because big data-driven transformations don’t happen all at once or immediately across the entire enterprise, strategies must account for incremental value creation and a evolutionary process overall.
Structural and Scalable
Think beyond the pilot to ensure big data strategies can be fully executed and don’t result in just another data silo; for many companies, the major step forward comes through a powerful and adaptable ecosystem that links discovery and data platforms for long-term scalability and connects to the most important external data sources.