How to succeed with Big Data strategy: The not-so-secret magic ingredient

You can’t have missed the hype about Big Data. According to many, Big Data is the new kid on the block that businesses just cannot afford to ignore. Big Data refers to the technologies and processes associated with collecting and analysing humongous amounts of information—about customers, suppliers, markets, operations, whatever—that is becoming available to businesses through mobile phones, social networks, instrument sensors, transactions on the Internet, and so on.

Observers of this industry have pointed out the characteristics of Big Data as:

• Volume: the flood of data from various sources
• Velocity: the high speed with which data arrives
• Variety: the different kinds of data that become available

Some others add to this:

• Variability: the changes in the flow patterns and types of data coming in
• Complexity: the numerous structures and multiple sources of data make processing and integration very complex

What is significantly missing from the conversation is another ‘V’: Value. How will businesses derive value out of all this data?

That is the central question of business strategy based on Big Data technology.

Trends
IDC predicts that the Big Data infrastructure industry will grow at a rate of 31% annually between 2012 and 2017—which is about 7 times the growth rate of other sectors in the IT industry—and that by 2016, the Big Data services and technology market will expand to $23.8 billion. This is just the technology infrastructure portion. Big Data is also an important driver for the tremendously growing business analytics market that IDC projects will reach $51 Billion by 2016. Another market research firm, Wikibon, estimates that Big Data market will top $18 billion in 2013, a growth rate of 61% over 2012, and that by 2017, the total Big Data market will approach $50 billion.

That’s great news. For Big Data technology vendors, that is. IBM is the biggest vendor in this market with Big Data revenues of $1.6 billion in 2012—two times the earnings of the next player, HP.

However, the more important question is: What does Big Data imply for businesses that are consumers of Big Data technology?

And consequently: How can a company create a strategy around Big Data so that it can gain a competitive advantage and sustain it?

Business Implications of Big Data
A couple of months ago, IBM’s CEO, Ginny Rometty, gave a speech at the Council of Foreign Relations in Washington DC about Big Data and its huge implications for business. She pointed to three instances of where Big Data analytics had made a significant difference.

1. The Memphis Police Department used Big Data analytics and determined that “rapes committed at night were correlated with the presence of pay phones outside convenience stores”. They moved payphones into the stores and rapes dropped by 30%
2. Mexican cement maker CEMEX wanted to develop its first global brand. Faced with the challenges of meeting different specifications for different countries, it built a social network for its product development scientists and engineers across 50 countries; that network helped them leverage and transfer expertise across the enterprise. The global brand was launched in less than one-third of the time it previously took the company to launch a local brand in Mexico
3. Barack Obama’s 2012 Presidential campaign owed its success in large part to its coupling of the power of social media with analytics to track with almost pinpoint accuracy the mindset of the individual voter. This helped the campaign to accurately determine trends and helped them allocate and distribute resources dynamically.

Very importantly, while concluding her speech, Rometty provided a hint of what drives the success of Big Data-based business strategy: She observed that despite all the potential of Big Data, “The challenge is not the technology. The challenge, as always, is culture.”

The not-so-secret-magic ingredient: The Human Element
As we conceptualise Big Data based business strategy, we are swamped by technology issues and are unfortunately, not looking beyond that. Since the dialogue about Big Data is being driven by vendors today and not by businesses that will use Big Data, we hear a cacophony of technical jargon and names of software and associated hardware. Terms like NoSQL database, Hadoop, MapReduce, in-memory databases, predictive analytics, and so on, dominate the sound space. Let me be clear. Big Data has tremendous potential for businesses and these technologies—both software and related hardware—are absolutely necessary for Big Data. But the critical point is that they are necessary but not sufficient for deriving competitive advantage. The missing but not-so-secret-magic ingredient in creating sustainable competitive advantage with Big Data is the human element.

In a recent report titled, “The Big Data Balancing Act: Too Much Yin and Not Enough Yang,” AIIM, the global community of information professionals, made a similar argument: “the combination of the yin and yang elements – the analytics, technology and scientific skills with process, creativity, and business knowledge, is where [businesses] can achieve balance, and business effectiveness.”

Factors that call for human intervention
So, what factors make the human element important in technology-driven strategy in general, and in Big Data based strategy in particular?
There are many. I will list a few.

1. Making business decisions that are appropriate to the pattern unearthed by Big Data

Take the three cases that IBM CEO Rometty discussed in her speech. In all three cases, Big Data analytics pointed out hidden patterns in the data. But the technology stopped with that. It was human decision-making that drove what to do with the patterns that were unearthed. Human decision-making relocated payphones, human decision-making created and shared domain expertise, and human decision-making observed and reallocated resources.

2. Good business strategy calls for prescience, but Big Data analytics is backward-looking

Undoubtedly, Big Data and predictive analytics can predict trajectories of change. However, these predictions are based on history—and in the most advanced state—on current happenings. Making business decisions with these predictions is like driving while looking at an incredibly clear picture in a rearview mirror. This is fine as long as we’re operating in a stable or slow-changing business environment. In turbulent business environments, however, when the past is not a predictor of the future, when intangible factors are more important than tangible ones, humans make better decisions than technology does. In such settings, the prescient forward-looking decision-making that business strategy requires is something that only humans are capable of—at least, at present.

3. Multiple patterns and strategic choice

Pattern detection and knowledge-discovery can create a dilemma of many. When Big Data brings up two or more patterns, how does a business decide which one to pursue? For instance, if Big Data analytics showed the Memphis Police Department two conflicting patterns—(i) rapes happen near payphones outside convenience stores, and (ii) the presence of pay phones at street corners and outside convenience stores has helped victims call for help quickly—Big Data cannot resolve the dilemma. It is ultimately human decision-making that makes the difference.

The myth of achieving competitive advantage with Big Data technology
Many vendors, management analysts, and academics have been claiming that Big Data technology will provide competitive advantage to businesses. Maybe it will, but definitely not with just bringing in the technology. As a resource, a technology is freely available for all players in an industry to buy and install, and so, by itself, a technology cannot give a business competitive advantage. On the other hand, the technology may become a strategic necessity in an industry—the company that does not have the technology falls behind because every other player in the industry has it.

Thus, technology-driven strategy has always been plagued with the Red Queen effect. In Lewis Carroll’s Through the Looking Glass, the Red Queen tells Alice, “Now, here, you see, it takes all the running you can do, to keep in the same place.” Businesses invest in technology not to gain competitive advantage but to not be at a competitive disadvantage. What really gives a business strategic and sustainable competitive advantage is how businesses derive value from the technology—and that of course, is people-driven.

And so, Big Data brings us back to the same old truth that we have learned and re-learned many times in technology-based business strategy: Sustainable competitive advantage comes not from what Big Data technology can do for business, but from what business does with Big Data technology.

The thoughts and opinions shared here are of the author.