Big data represents a disruptive force to the way the world does business. Think of this a company’s ability to plan for the future used to be limited to analyzing past trends. Though somewhat useful, that approach is like relying on the Farmer’s Almanac because the past is never a completely accurate indicator of what will happen in the future. Today, with big data, organizations can harness all their data, both inside and outside the enterprise, to enable smarter, more precise action and planning than ever before. The impact can be huge for revenues, customer satisfaction and brand awareness.
Consider the example of Morton’s The Steakhouse -- and the social media stunt “heard around the world.” When a customer jokingly tweeted the Chicago-based steakhouse chain and requested that dinner be sent to the Newark airport, where he would be getting in late after a long day of work, Morton’s went to work analyzing. They discovered the Tweeter was a frequent customer (and frequent Tweeter), pulled data on what he typically ordered, figured out which flight he was on and then sent a tuxedo-clad delivery person to serve him his dinner. Sure, the whole thing was a publicity stunt (that went viral), but it worked. With just a snippet of data and a little analysis and correlation, Morton’s successfully drove a major brand awareness coup. What if more companies could be capable of something like this?
Like any powerful technology, big data can propel organizations to limitless possibilities, if placed in the right hands. But who are these “right hands?” They are an organization’s leadership, IT teams, and the technology vendor community. These groups are driving innovation at three key levels organizational, technical and financial, respectively. Here, we’ll analyze the roles these groups play in driving Big Data forward, as well as ways their DNA will need to change.
For big data initiatives to have any chance for success, organizations need leaders that understand the importance of doing away with the “silo mentality.” Think of it this way various groups within an organization may be able to glean insights from analyzing the “straws of hay” in their own haystacks. But they miss the opportunity to have an aerial view of all haystacks, and the critical correlations between them that can enhance the inherent value of each individual haystack.
As an example, consider a consumer packaged goods (CPG) manufacturer, whose “haystack” is supply and demand chain data. Social media specialists within the same company may be able to identify broad social sentiment trends across major customer geographies. By parlaying this information across their silo to the supply chain team, this team can enrich their data and achieve an even higher level of precision in their inventory planning. This is what Big Data success looks like small groups of highly efficient, yet connected workers. It does not mean a group of BI analysts or data scientists locked in a room, analyzing and working in isolation.
IT teams are traditionally risk averse, in terms of both operational expenditures and exposing potentially sensitive information to more users. Oftentimes in the world of IT, “less is more” when it comes to infrastructure changes and sharing data.
In a sense, one can’t blame current IT professionals, because many of them were brought up in the RDMBS paradigm. But new world opportunities cannot be tackled with old world solutions, and for the benefits of Big Data to be realized, the conservative mindset that characterizes traditional IT will need to evolve. New types of unstructured data both inside and outside the enterprise, like machine data and social sentiment will need to be brought into the information fold. Moreover, all pertinent data must be collected into a commonly accessible and affordable reservoir, integrating legacy systems and data so that the widest range of discovery possibilities can be realized.
Finally, IT teams will need to realize that their role in big data isn’t simply to support the initiative from a technology platform and analytics software perspective but to also augment it. IT system and production-level data holds a wealth of insights that can be used to optimize internal IT efficiency as well as outward-facing customer marketing and conversions (consider, for example, click-through data on a website). This rich data from IT teams themselves is just waiting to be tapped.
When it comes to financial innovation, today’s technology vendors are leading the charge. The good news especially for Opex-conscious IT teams is that data analytics capabilities are now available on demand, making them much more accessible, easier to work with and thousands of times cheaper than enterprise-scale products. Advanced data analytics are available at a level of speed and sophistication never before seen, to even the most resource-constrained organizations. These solutions offer organizations an opportunity to experiment and start small, without huge up-front investments or the risk of technology obsolescence. Additionally, technology leaders offer expert services representing years of experience and best practices across industries, as well as strong use cases, helping big data users get off to the fastest, most resource-efficient start possible.
Unlocking Big Data Success
Big data is not just this season’s trendy headline it is here to stay. It is still in the nascent stages, and many organizations are just beginning to uncover the wealth of treasures and insights that lies within their data. But unlocking this wealth requires some fundamental changes in several long-standing practices and ways of thinking, particularly in the organizational and technical arenas. These changes, combined with new advances from the technology community, are the elixir for magic in big data.
Colin Mahony is senior VP and general manager, HP Software.
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