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On the road to Big Data - Harnessing analytics to create disruption

ChrisSurdak ‎05-13-2015 12:54 PM - edited ‎05-13-2015 01:04 PM

If you’ve been following HP recently, you may have noticed that we’re “all in” with our bet on Big Data. Every day we see our clients and ourselves being transformed by the power of massive amounts of data being analyzed in new ways, leading to entirely new insights about the world around us. A recent ebook, On the road to Big Data 20/20, discusses how HP IT is using Big Data tools and techniques to create new and disruptive business outcomes.


Much of this discussion comes from Saum Mathur, former CIO of HP Software. Mathur makes three key points in his summary of the work performed by HP IT. Let’s review each in turn and put them in context of our increasingly datafied world:


1. Big Data 20/20: A 360-degree view of data has a way of democratizing data by providing a single source of truth to everyone in the enterprise. Think of it as “analytics for the people.”

Or to put it another way, Data Analytics must become pedestrian. In today’s world, customers are no longer willing to wait for their needs to be met, and with tens of thousands of apps available, there are effectively no switching costs. This means that the fastest organizations will win, and there will be no runners-up. To operate at the speed of customer expectations, insight, knowledge, and most of all authority, must be pushed to the edges of our organizations, rather than at the center and top. All employees must have access to data and to the insights that may be gleaned therefrom. To meet ever growing customer expectations, organizations must be able to act at the speed of insight. This means analytics for everyone.


This will represent a significant challenge for organizations that have dedicated decades to cost cutting, centralized control and rule-based automation. Bureaucracies were built as a means to control the ebb and flow of capital and to parse it out in carefully controlled chunks. But information is now the basis of wealth and power in the world, and information wants to be shared. Organizations that succeed with Big Data will be those that recognize the sociological implications that it brings, rather than just the technical ones.


2. Big Data 20/20: Every product will become an experiment.


In our appified, instant-gratification world, customers expect novelty, intimacy and relevance, in 30 seconds or less. You must anticipate my needs before I know I have them, and you must meet these needs instantaneously. Indeed, leading companies have quickly learned that predictive analytics aren’t enough. These companies have moved to persuasive analytics, where customers are guided towards desired results in a just-short-of-creepy sort of way.


The only way to succeed at this approach is through experimentation, because you should be going places you’ve never been before. This necessarily means that you’ll get it occasionally wrong before you get it right. A successful approach to Big Data requires that you move out of your old comfort zone and begin to try new things. With appified customers expecting deep personalization and persuasive results, doing the same old thing, only more or less, or harder or faster, just isn’t going to cut it any longer. Indeed, half a century of applying the Kaizen approach of tiny, incremental improvements has been played out, and customers now expect the dramatically different.


I often say that in a Big Data world, the difference between “Pilot” and “Production” is revenue. If you’re succeeding at Big Data, you should be learning entirely new insights and these should result in entirely new ways of operating. This will necessarily be disruptive and you’ll need to adapt to these new ways of doing things in fairly short order. When you do stumble upon an insight that makes you more successful with customers they’ll likely act extremely quickly, turning your pilot into production well before you may have anticipated. So, use an experimental mindset in your Big Data efforts, but be prepared to move quickly when you do hit the analytic jackpot.


3. Big Data 20/20: Security and privacy concerns rise to the top.


It seems not a week goes by without a major organization having to reveal that their systems have been compromised, their fortresses breached, and our information stolen by those who would do us harm. The worrying part is not the number of companies who announce that they’ve been penetrated, rather, it is the number of companies who have been penetrated and do not yet know it. Data is the new source of wealth and power in our world, and the incentives for stealing our information are extremely high. You and I want the benefits of predictive and persuasive analytics but we also expect protection from these mounting threats.


The historic approach to security, building digital walls higher, thicker and stronger simply doesn’t work any longer; the fortress has already been breached. Instead organizations must recognize that security is yet another Big Data use case. Predictive analytics, applied in real-time, against massive quantities of structured and unstructured data will be the means by which organizations can fight back. Organizations must rise to this challenge in order to stay relevant, and those who do not will lose their customers’ trust and their wallets.

The art of the possible and the imperative


As the examples presented by Mathur show, obtaining meaningful, impactful results from Big Data is not only possible, it is imperative. In order to remain competitive in our ever-accelerating world, organizations must leverage new data to gain new insights into all aspects of their businesses. But, insight without action is wasted effort. As the examples given suggest Big Data is not about gaining knowledge. Rather, it is about creating new, disruptive outcomes that allow organizations to transform their relationship with their customers.


Join the Big Data revolution: To learn more, check out our complete ebook, On the road to Big Data 20/20. You can also download a free trial of HP Haven, and take our Big Data analytics platform out for a spin.




Read more from the HP Big Data team:
The Goldilocks Scenario: Finding Big Data technologies which are “just right” for business by Walt Maguire
The Big Data shift in a data-driven world by Colin Mahony
How does Big Data change physical security? by Joe Leung

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About the Author


Chris Surdak is a Subject Matter Expert on Information Governance, analytics and eDiscovery for HP Autonomy. He has over 20 years of consulting and technology experience, and holds a Juris Doctor from Taft University, an MS from the Wharton School at the University of Pennsylvania, a CISSP Master's Certificate from Villanova and a BS in Mechanical Engineering from Penn State. Chris is author of the Big Data strategy book, "Data Crush," which was recently nominated as International Book of the Year for 2014, by GetAbstract. Chris is also contributing editor and columnist for European Business Review magazine.

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