Big Data : The Winning Strategy-An Insight

Developing a winning #BigData strategy is challenging because it is as much about getting ahead of the trend and acquiring talent as it is about investing in new technology. 

Big Data is exciting stuff, but don't take my word for it. Ask the Academy of Arts and Sciences, who nominated Moneyball -- a movie about Big Data -- for six Oscars. If Hollywood is on board, you know Big Data has gone mainstream. Spin a tale that is both interesting and illustrative of Big Data's transformative potential.

And yet, while a cricket team's creative use of statistical data may have helped it to go from perennial doormat to scrappy contender, it doesn't begin to describe what Big Data can do for an organization.

What is Big Data, anyway? Big Data is having three primary characteristics: volume(amount), velocity (speed of creation and utilization), and variety (types and sources of unstructured data, such as social interaction, video, audio -- anything that isn't neatly categorized within a database). I describe Big Data as datasets so large and diverse, they break traditional IT infrastructures.

What Big Data is, however, isn't as important as what you can do if you harness its potential and uncover new business opportunities through Big Data analytics.

Even in these early days of Big Data, its applications across diverse industries are compelling. Retailers embrace Big Data to combine RFID sensor data, social media data, and GPS coordinates to evaluate location, product selection, and individual profiles in order to deliver geo-specific product promotions to a mobile device. Big Data has been used to analyze entire forests in order to identify individual trees for harvest in order to maximize health, yield, and profit.

We are using Big Data to better understand massive amounts of data associated with processes and costs related to supplier parts, manufacturing, logistics, quality control, customer service, and more, and have used it to establish predictive performance models to address quality issues before they can have a negative effect on customer satisfaction. Yet even these examples only scratch the surface of how Big Data can effect business transformation.

Big Data's potential goes beyond traditional "rear view" business intelligence, revealing patterns in near real time to facilitate making a quantum leap from incremental improvement to predictive business processes and even entirely new business models Aspire Possibilities.

But the Aspire Possibilities requires practitioners who understand the unique mix of "art and science" that characterizes the most transformative Big Data breakthroughs. It requires people who are as comfortable with business concepts and operations as they are adept with the analytical and visualization tools required to process and recognize patterns in the data. We call these professionals Data Scientists. They're able to make quantifiable connections between previously unknown causes and effects; they're adroit at seeing associations others have missed; and they're able to understand how these new insights can be used to fundamentally change operational practices and business and organizational models.

If you are an executive considering a Big Data strategy, you are fishing in a small talent pool -- the banks of which are becoming crowded with a growing number of anglers casting their lines in the water.It is reported that one-third (33%) of business have already begun or are actively considering the implementation of Big Data projects. And with less than one-third (31%) of organizations "confident they can execute a Big Data strategy with their existing staff," the rush is on. That means the Big Data challenge is as much about getting ahead of the trend and acquiring talent as it is about investing in new technology.

Until universities embrace the creation of data science disciplines, like computer science decades ago, how do you compete for such limited resources and achieve the Aspire Possibilities ? I recommend three steps for ensuring your organization has the people it needs.

Educate: Your first step should be to identify people from within your organization who have proven themselves as both technically adroit and analytically creative. Remember, Big Data is about the Aspire possibilites; you need creative thinkers. Don't confine your review to IT professionals; it's vitally important that your Big Data team draws heavily from disciplines able to think beyond typical linear problem solving. Once you've identified your future Big Data rock stars, invest in them through training and certifications in Big Data Analytics and Data Science.

Acquire: A major part of your Big Data talent acquisition strategy should involve bringing in individuals from outside the organization who not only possess skills complementary to your strategy, but who are not burdened by industry and organizational biases. Part of what makes Big Data transformative is its focus on discovering new approaches to solving old problems. That's hard to accomplish when an organization is saddled with the inertia of conventional wisdom and a "that's not how we do it here" mindset. Look outside your walls and outside your industry.

Empower: Nothing will derail a Big Data strategy faster than building a team that is not given the chance to succeed. Conversely, nothing will energize your team more than the knowledge that they are being challenged with creating measurable impact and supported by your organization's senior management. Without this commitment, the time and resources you invest in training the team will end up benefitting your competitors through defection. This will be especially important when your Big Data team challenges the norm and runs up against others in your organization who feel threatened by change (and they will). But by creating an environment outside of the constraints of the IT department where data scientists know their contributions are valued, you'll make recruitment and retention easier.

This advice is born of my experience implementing a Big Data analytics strategy to transform business processes based on the quantifiable insights Big Data affords. Our achievements to date have resulted in significant and measurable improvement in areas such as quality control, logistics, and customer support. They didn't happen overnight, and they didn't happen without conflict, but we were committed to identifying and then acting on these new insights.

The Moneyball approach didn't win the teams a world championship, but it did prove successful enough that, within a year, every major sports organization had adopted a Big Data strategy in some form. And in your industry right now there's a JACK who is analyzing data in new ways, looking for a competitive edge that will become the next Big Data blockbuster. Waiting until Big Data analytics are table stakes means you'll be playing from behind rather than with the lead.

Picture Credits : Google Open Source.

This is an individual opinion based on the research and analysis taking consideration to help people who aspire to build career in BIG DATA.