Overview
In today's business environment, too much focus is put on capturing data. But just possessing big data is no longer enough. Enterprises need to learn how to translate their data into actionable insights. This is where devising an effective big data strategy for your organization comes into play.
Why You Need a Big Data Strategy
What the heck do we do with all this data? It’s a question sometimes asked in frustration by business executives who fear that there is too much focus on just capturing data and not enough on using it to improve performance.
Clearly, possession is not the point with big data. Even for companies who understand the value of big data (and that’s still not every company on the planet), the move to decision-making and action-taking can be difficult.
The obstacles can be technical – poorly designed big data architectures, with too many silos and too few integration points. Insufficient big data tools. Or they can be cultural – limited data-driven decision making at senior levels, low trust of data or refusal to share information across organizational lines. Or they can be a mix of factors.
An effective big data strategy and methodology can move companies past these challenges. The former defines how the business can and should use big data to get better. The latter is about designing the right architecture to support the full enterprise and put all the data to work, with proven big data techniques and analytical practices, in specific operational contexts.
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
Holistic
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.
Business-Focused
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.
Flexible
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.
The Bottom Line
Getting the most of out big data starts with the right strategies and methodologies, aligned to your specific goals. There is no doubt that whatever your business is trying to do – from personalizing promotional offers or loyalty programs for different customer segments, to shortening supply chain timelines, to de-risking investment portfolio – big data can provide the insights to help you do it better, faster and more sustainably.
Provided, that is, you have the right strategy in place, a strong and unified architecture to manage the data and make it accessible, and a process framework to use big data in the business. Other crucial variables include the right organization and team, including true big data experts, and the cultural commitment to win with big data. So, addressing that big and daunting question – what to do with all this data? – is the first step to creating the most value from your big data investments.
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