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A Big Data POV for the C-Suite

Feb 4 2014, 5:00am CST | by , in News

A Big Data POV for the C-Suite

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A Big Data POV for the C-Suite

By Wes Nichols, Co-Founder & CEO, MarketShare | Twitter

As “Big Data” continues to mature from hype and techno-jargon to operational reality, business leaders must ask themselves two key questions: What are Big Data’s implications for my organization? How do we tap its wealth-building power to create value and competitive advantage?

Defining a “point of view” about Big Data, however, is bit like trying to define the Internet. A bit hard to get your arms around. Both are everywhere; part of our fabric of existence. And much as the Internet quickly evolved from curiosity to omnipotence, Big Data is fast becoming part of day-to-day products, services, decision-making and end-to-end business operations.

We are surrounded with data and analytics daily. For example, GE’s jet engines generate thousands of data points per second for aviation analytics. Web-enabled lighting systems from Philips allow consumers and businesses to “program” lighting, including color, intensity, timing and other factors from a smartphone or tablet. Retailers run large scale, real-time A/B tests with sensors that detect how consumers interact with products and store layouts.

The term Big Data, of course, references newfound abilities to collect vast amounts of information from myriad sources, organize and analyze it quickly, and use it to make quicker, smarter decisions that avoid risks, boost sales and build shareholder value. Data available to companies has reached unimaginable levels – terabytes, to petabytes, to exabytes. But it’s just the beginning and will increase exponentially in coming years.

The Internet’s next iteration – the “Internet of Things”– is propelling this data explosion. When almost anything can be connected to the Internet – from cows to cars, and trash cans to tennis rackets –all emitting vast amounts of “digital exhaust,” business models based on old information architectures disappear and new ways of creating value take over.

Fuel for Smarter Decision Making

Think of Big Data as fuel for smarter decision making – oil for the information age. Just as the Web became essential to running any large enterprise, so it is with Big Data. In marketing, for example, combining Big Data with advanced analytics allows organizations to decode an increasingly complex marketing ecosystem, anticipate what will happen next, and make smarter decisions on how, where and when to spend money.

But marketing is just one example of where big data and analytics join to unlock vast stores of value for companies – greater efficiencies; more sales – albeit a powerful one. The benefits extend well beyond optimizing your marketing spend, to the efficient deployment of capital across the entire organization. Firms leading the way in applying learnings from Big Data are pushing tens and even hundreds of millions of dollars in value to their bottom lines.

Creating a Big Data Strategy

At MarketShare, our view is that Big Data – first and foremost – requires a strategy and specifically an analytics strategy for turning data into actionable insight.

Recent history is strewn with the wreckage of companies that lacked an informed Internet strategy, and suffered the consequences. For those proactively pursuing it, Big Data represents a major new source of competitive advantage (or disadvantage if you are the one left behind).

For companies deploying Big Data, the marginal impact of efficiency and sales improvement is more significant than in other capability areas such as manufacturing or service optimization. And while companies possessing superior knowledge and capabilities in Big Data are using it to grow shareholder value, those with a relative deficit in this area face greater value-generation challenges.

Keys to Big Data Success

Big Data without Smart Analytics is just BDD – Big Dumb Data. We see successful Big Data adopters differentiating themselves in these four ways:

  • Clarity of goals: A common factor in successful early adopters of Big Data is clearly defined business goals (with at least one or two critical economic metrics), with agreed-upon frameworks to measure success quickly and expand innovations before competitors.
  • Programmatic integration: Success requires connecting Big Data, related analytics and decision making forums at the right time, in an action driven framework. The best Big Data adopters quickly get the insights and tools into the hands of team members who are empowered (and accountable) to act.
  • Linking insight to action: The most successful organizations are able to embed prescriptive analytic frameworks into decision processes, and successfully identify opportunities to automate and/or integrate decisions at the customer level.
  • State-of-the-art technology: The right tools and technology are essential to developing advanced, Big Data analytics capabilities. Those lacking leading edge tools quickly find themselves falling behind.

The Price of Entry 

Gathering, managing and analyzing Big Data is the price of entry these days. But turning data into insight – effectively and sustainably at scale – takes more than number crunching. Many firms are finding that data analysis methods they’ve embraced for years flounder in an increasingly complex business ecosystem requiring quicker decisions on more granular levels and at far greater scale. Companies win with Big Data analytics by deploying more agile technologies and approaches that reinvent how analytics have been done in the past. 

Opportunities in Big Data are largely industry agnostic. From where we sit leading the field in advanced marketing analytics, some industries, such as healthcare and financial services, are farther along the sophistication curve. But opportunities abound in almost every industry for companies willing to lead.

Wes Nichols, Co-Founder and CEO of MarketShare, writes regularly about advanced marketing analytics and related topics for major websites and publications such as Forbes, The EconomistHarvard Business Review, Analytics Magazine and others.  

Source: Forbes


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