In case you haven’t heard, the world of data is changing rapidly. What worked before is no longer enough, and what you may have built your career on is in jeopardy if you don’t adapt fast enough. In my book “Smart or Lucky” I talk a lot about how companies need to deal with change in order to survive. Big data is bringing one such tidal wave of change, and the question becomes, are you ready to use it to your advantage?
We’ve never had a problem of not enough data, but previously it was acceptable and standard practice to store information in silos across the organization. In the past, management basically wanted to know was how many widgets were sold, when and in what territory. In predictable times, in predictable markets, it’s easy to figure out what tomorrow might look like based on today. But we don’t live in a predictable world anymore; there are too many factors that contribute to the volatile nature of the market.
Now there are more sources of data than ever. Data generated by sensors, Web-based channels, and customer feedback sites are all part of the flood of data that can potentially impact management decisions. In the past, even if management wanted to leverage all of these information sources, they did not have the tools.
Such a dynamic has created an opportunity for big data to take center stage. If your executive team has not already been asking “What are we doing about big data?” they soon will. While many of them realize the data volumes have increased dramatically, most aren’t aware that all the other components of data – the different types of information, how it is stored, how it is made accessible – have also changed and complicated matters exponentially. From images and videos on devices, to security data taken from sensors in grocery bags, to patient information in hospital databases, the sources of data and the way they are created, collected and managed have expanded astronomically.
Data is now highly distributed. Consider, for instance, how a retailer sees the world of big data. Customer demographic and customer preference data is a no-brainer, but add to that in-store traffic data patterns and comments left on the company’s social networking pages. Retailers are increasingly collecting information about customer buying patterns based on loyalty cards. Therefore, they would like to find techniques that encourage customers to buy related products as they walk through the store. You also need to look at all these information sources in context with each other in order to make better decisions. This is especially difficult because not all of the data is structured – much of this data will beobtained from unstructured sources.
All of this data is easily collectable, but you also have to store it and make sense of it. The low cost of storage and the emergence of the cloud have made it possible to keep track of all that information. And yet, the rearview mirror approach of the past is long gone. You need to help your organization predict what’s next, because your company needs better answers about what is to come. “We did 10 percent more business this quarter than last” still leaves executives asking, “So what?” They need to know about three quarters from now and how the demographics are going to change. Data needs to become actionable like never before. Mixing and matching the information together is what drives value.
To do that you need to address the consistency issue of big data – consistency in the way data is evaluated and consistency in the physical integration of data. When it comes to evaluating the data you have, it’s most likely an uphill battle. You have data from so many sources, and yet, there is no one method to make sense of it all. For example, the word “customer” likely has different definitions across different systems.
Consistency of data integration is another challenge. Not everything is in SQL (none of us would have a job if it was), and unstructured data abounds. Customer comments on a support site, for instance, can provide critical feedback, but if there isn’t way to integrate that information into the business, it’s virtually lost. You can’t find trends if you don’t have all the information at your fingertips. With 1,400 questions about the same product issue, it’s no longer just a customer service concern, but a quality control issue as well. Companies need to look for patterns in their data across silos to be able to flag what problems exist now and what could surface later.
Turning big data into a strategic weapon takes discipline. Yes, you have massive volumes of data, yes it all has potential, but to really make big data a game changer for your company, the key is to evaluate which is the most vital source of data . Step back and evaluate what information you really need to take your company to the next level. Sometimes this might mean understanding techniques that enable you to sell more products, expand your presence in a growing market and therefore gain a bigger market share. This will be especially important when markets are just emerging. In other situations, you might not know what questions to askor you may actually want answers to questions that you haven’t asked. What does all of this information mean? What does this data tell you about how to anticipate a future customer requirement? Big data is not about all the data, but the right data.
From there, you can leverage strong tools and technology to analyze the information. You don’t need someone to calculate it; you need sophisticated technology that can do it for you and lead you to the answers. One such example is predictive analytics, a technology that is experiencing a revival of sorts thanks to the emphasis on big data. My colleague, Fern Halper, has done a lot of research on this topic and found that vendors have improved their offerings to make predictive analytics more user-friendly, catering directly to the business analysts who are finding patterns, uncovering opportunities and operationalizing results.
While companies have always had massive amounts of data, they are able to store and access more sources than ever. At the same time, in order to continue to anticipate new business opportunities, they must be able to turn data into actionable information that can create new value. Make no mistake, big data means big change for a lot of organizations. Understanding how best to capitalize on the information at hand can make all the difference between the companies we know of today and those that won’t be around tomorrow.
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