Big Data: Are We Having the Right Conversation?

Despite the spike in conversations about big data, business and marketing leaders should look beyond the hype about data form and focus on the broader picture of gaining a competitive edge through analytics.

Big data—those large, expanding, and multi-form datasets—is an increasing hot topic in technology, analytics, and marketing circles. It implies much more than simply a large volume of datasets but also data that have three key attributes: volume (large datasets in the realm of petabytes), velocity (speed of generation), and variety (combination of structured, semi, or totally unstructured data). These three attributes typify the data from social media, video, third parties, web applications, and main and mobile devices, and these differentiate “big data” from the large structured data organizations have dealt with hitherto. In many instances, standard structured data are now joined by unstructured data, such as text and language as well as RSS and XML.

This blog refrains from discussing timely concepts (the hot topics of the day), but leans more toward timeless (fundamental and perennial) concepts and ideas on analytics, strategy, and planning. It is, however, tough passing up on the excitement (or aptly, ‘titillations’) surrounding big data. This piece looks at big data through the lens of data as a derived demand, and urges leaders to focus on the most important outcome—gaining competitive advantage through the intelligence evaluation of any form of data.

Big conversations
Big data has become a big topic. The conversations, buzz, articles, blogs, conferences, consultancies, and technologies have spiked in recent years. A search of the term “big data” on any search engine, which serve as good guides for social interest, shows a strikingly astronomic growth over the past 12 months. The velocity of big data conversation buzz and searches compares to that of social media in late 2008 through 2010.

For now, and for obvious reasons, most of the conversations and promotions of big data are driven by technology firms such as IBM, EMC, Oracle, Microsoft, SAS, Teradata, and SAP. But a few leading business, marketing, and management publications targeted towards the C-Suite have joined the conversation, making the case for big data.

• Big Data, Analytics and the Path from Insights to Value. Steve LaValle, Eric Lesser, Rebecca Shockley, Michael S. Hopkins, Nina Kruschwitz (Sloan Management Review)
• Big data: The next frontier for innovation, competition, and productivity. James Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, Angela Hung Byers (McKinsey Quarterly)
• Expand Your Digital Horizon with Big Data. Brian Hopkins, Boris Evelson (Forrester)
• Big Opportunities in Big Data. Positioning Your Firm to Capitalize in a Sea of Information. Brian Hopkins (Forrester)
• Make Data Work Throughout Your Organization. Thomas C. Redman, David Walker (HBR)
• How Social CRM Benefits From Big Data. What Social CRM Means to Customer Intelligence. James Kobielus G. (Forrester)
• Are you ready for the era of ‘big data’?Brad Brown, Michael Chui, and James Manyika (McKinsey Quarterly)

Big benefits
Because of the larger and more diverse nature of information contained in big data, such a dataset could theoretically hold a larger set of insights that could translate into major wins for businesses and brands. For example, a dataset rich in consumer perceptual and behavioral footprints should allow firms to answer hitherto impossible questions and translate into significant competitive wins. Big data benefits can be grouped into three broad categories: consumer insights, organization intelligence, and operational benefits.

• Better consumer insights: Probably the most important set of benefits to businesses and organizations because they provide improved consumer understanding, which results in better consumer communications and more relevant products. The availability of technology to harness vast consumer generated data across searches, mobile, and social media have amplified consumer insight possibilities ranging from more accurate consumer segmentation, behavioral predictions to preference inferences and lifetime valuation. Organizations that are able to unlock these insights better and faster than the competition can expect significant wins.
• Better contextual intelligence: Besides the potential for better consumer understanding, ample data on political, social, cultural, environmental, and climatic events and trends can impart significant strategic advantages on the firm that gets it. While firms that serve mass customers will benefit most from better customer insights, a wider range of organizations can extract contextual intelligence from big data.
• Improved internal operational processes: Insights from internal operational datasets including HR, operations, logistics, and finance can help organizations reduce costs, improve talent retention, assess internal risks better and faster, and raise operational efficiency. The organization that commits to big data may also acquire the related technology and reporting capabilities that could improve operational and management reporting.

The right conversation?
But despite the big data buzz and its benefits, is a focus on big data the right conversation for building data analytics credibility and strategic relevance? One can predict with some certainty that big data is a temporary hype that will limp and fade away: too data-focused to matter in the long run. How exiting are the terms customer level data, cookie data, large data sets, or patient level data today? These are mere descriptors. Worthy, lasting and relevant ideas are those that pertain to an idea, a concept, or approach, like customer relationship management, multichannel optimization, or competing on analytics. Search data have been around for years, social media data are not new, neither are cookie level data, mobile location data, or RSS. The business value of these datasets has been addressed under topics like multi-channel optimization, social media analytics, text mining, data mining, media analytics, or simply advanced analytics.

And here’s the core of this piece: That while big data could deliver substantial benefits, and help keep data and analytics in business conversations, the conversations are better positioned under the larger umbrella of advanced data analytics or gaining competitive advantage through analytics; that the data-focused conversation may erode the gains made over the past years in the area of elevating analytics to a strategic, competitive lever. The conversation should not be about the data, but what we do with it or get from it. The data focus may further alienate business that still struggle with making the best of basic datasets for meaningful insights. Like other in-the-moment topics that may have strong underlying value but easily hijacked by trendy perspectives, attention on big data has not adequately focused on the underlying time proven philosophy of data being valued for actionable insights.

Big data is hinged on data-form. Data, a derived demand and the pathway for deriving competitive advantage, follows a four-step process: 1. data to information, 2. information to insights, 3. insights to action, and 4. action to results . The conversation of analytics as a competitive weapon has migrated analytics to the high end of this value chain, but this primary focus on big data is a pullback to the data-oriented base. Although the conversation on big data started with the realization of the tremendous generation and expansion of non-traditional data forms, the topic has expanded beyond data definition to aspects of its capture, storage, analysis, experimentation, insights derivation, dissemination, and generation of competitive advantage. At the core of big data, however, is the large dataset spewed off by technology, connectivity and cheap storage that have enabled organizations access to (or acquisition of) hitherto unanswered questions which may unfortunately have driven data and analytics back to the back-end data form rather than to a higher level of strategic partnership and competition. Data will change and evolve with time and technology, but the demand for actionable insights is perennial. While large datasets are the ingredients for such competitive advantage, the larger focus should continue to be around smart use of data rather than data type.

Big data is a subset of competing on analytics. The discussion of data and analytics as a strategic competitive tool has raised the conversation of data and analytics to the rightful position of strategic relevance. A quick review of the advantages listed above for big data—better customer understanding, better product development, better operational efficiency, better talent acquisition—are roughly the same as those cases for adopting analytics as a competitive weapon. Many firms that have benefited from big data are a subset of those that have committed to analytics as a competitive advantage or those that have developed a strong analytics center of excellence. Firms such as Zynga, Google, Harrah’s, and Oakland A’s have used analytics to deliver notable competitive edge. See article on competing with analytics consultants . While big data discussions involve topics beyond data forms, the conversation should be constantly linked with or subsumed under analytics as a strategic asset.

Some of these limitations may already be reflected in the composition of the primary advocates of these conversations as well as adoption challenges cited by organizations. Data and technology firms, such as IBM, EMC, Oracle, Microsoft, SAS, Teradata, and SAP, currently advocate big data conversations aggressively. Given that most organizations may perceive this advocates data firms working to sell more hardware and data services, more analytics and marketing consulting organizations and agencies have to play a broader role to diversify the advocacy base and force the focus on marketing and strategic value. Respondents to a recent TDWI study on big data analytics found that some key barriers to big data include inadequate leadership support (38%) and weak value proposition (28%). This study reinforces the need to focus on strategic value proposition in order to get executive support and investment commitment. Big data has inherent benefits and business impact, but the positioning and conversation needs a few tweaks to deliver the expected business response and relevance.

Big data has kept the role of data driven insights in the headlines. But the emphasis of the conversation needs to focus on value proposition, analytics center of excellence, and competitive advantage, so that the gains made recently with the awareness of analytics as a competitive weapon are not subsumed under data form conversations