Organizations need to ensure they are fully optimizing their current efforts and have a realistic roadmap for how and why a big data solution will help better decision-making.
Jumping on the "big data" bandwagon without a plan and roadmap is one of the worst investments a CMO may make in the next 18 months. It's clear that to thrive in the digital economy, enterprises must take advantage of their data to spot new trends, act on current problems, and stay relevant. Creating the data is, in many ways, the easy part. According to IBM, 90 percent of the world's data has been created in the past two years. But understanding what to do with it, and how to act on it, is what is getting many marketers into trouble.
Before making new investments of either time or money in big data solutions, organizations need to ensure they are fully optimizing their current efforts and have a realistic roadmap for how and why a big data solution will help better decision-making.
Start by getting your foundational elements in place:
Clean current data. Ensure that all current data sources are clean, trusted, and flexible. While you are working on the future state, make your current inputs as trustworthy and valid as possible. This will not only improve your short-term analysis, but will remove some hurdles when you get closer toward the implementation of a new solution.
Ensure alignment across vendors. Establish a roadmap that ties goals across vendors, ensuring that success is no longer something channel- or campaign-specific. Get all your vendors on the same page about where you are heading and challenge them to deliver recommendations on how they can improve performance with better insight.
Assess emerging trends. Have a clear understanding of how changes in mobile usage, geography, and product line extensions will impact your measurement goals. Look beyond what's working today to where you want to drive future behaviors and identify the elements needed to take you there.
Develop phased roadmap. What are you trying to solve for in the next six to 12 months, and what are your 18-month and beyond-reach goals? Keep in mind that once you start down the big data path, you will have a runway of time before you have enough actionable data to start making decisions. Ensure there are midterm milestones that can help ensure you are on the right path.
With the foundations in place, consider the pillars of big data and how they will be collected, managed, and interpreted:
Diversity. What is the universe of data you would like to collect? Are you able to collect the data internally or through your partners? Will the data be available at intervals necessary to make action, or will it be too lagging to provide value?
Correlation. What are the connection points between the sources of data? What are you trying to solve for? Is it realistic that a set of data, no matter how current, would provide the connections to solve for the need? Do you have the people in place to interpret the data and, more importantly, turn the data points into actionable recommendations?
Quality. What is the degree of quality you can expect from your data? How much of it is self-reported, obtained from new vendors, or subject to interpretation? Are you confident enough in your sources (often external vendors) that you are willing to make investment decisions based on their data points?
Organizational readiness. Is there an infrastructure in place that will enable centralized decision-making about what to include, how to measure it, and more importantly, how to action on it? In decentralized organizations, where each channel and team may be used to collect and assess their individual performance, this group-level analysis may have a disruptive influence.
With a clear vision and detailed roadmap, big data may help you make the leap above your competition and toward higher performance. Without that plan, big data just becomes more expensive data.
Big Data image on home page via Shutterstock.
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