by Greg Heist (@goInnovateBlog) for goInnovate

Lately I have found it impossible to scan my numerous RSS feeds without the term "Big Data" staring me in the face on nearly every page.  And there's good reason for that: Big Data is big business. And it's growing all the time.

To add some scale to big data's explosion, consider these statistics from wikibon.org:

  • IDC estimates that by 2020, business transactions on the Internet—both business-to-business and business-to-consumer—will reach 450 billion per day. (Source)
  • In 2008, Google was processing 20,000 terabytes of data (20 petabytes) a day. (Source)
  • Facebook stores, accesses, and analyzes 30+ petabytes of user-generated data. (Source)
  • Walmart handles more than 1 million customer transactions every hour, which is imported into databases estimated to contain more than 2.5 petabytes of data. (Source)
  • ATT's extensive calling records contain the largest volume of data in one unique database (312 terabytes) and the second largest number of rows in a unique database (1.9 trillion). (Source)

As you can see, Big Data is a big opportunity. Wikibon.org also cites an IDC study forecasting the Big Data market is expected to grow from $3.2 billion in 2010 to $16.9 billion globally in 2015. The multi-billion dollar question is this: with players such as IBM, Accenture, SAP, and Microsoft offering both platforms and professional services, can market research agencies ultimately compete in this explosive new space?

The answer is, at least for some, is a clear yes.

There are three core MR competencies that can provide a differentiated offering to prospective clients. I'll walk you though them below:

  • Focusing on the Why: While traditional sources for decision analytics (like transactional data) can help identify what is going on, it is only in the context of why it is happening that an enterprise can drive meaningful change within its organization. At its core, MR is all about the why; the discipline encompasses a myriad of approaches for solving business problems. Assuming they develop competence in working with non-proprietary data sets (no small feat in and of itself), their ability to guide the collection of primary research and deliver answers can be a true competitive edge.
  • Identifying Insights: There's an important human dimension to synthesizing complex data and analytics and translating that into a true "Eureka!" moment.  In a phenomenal piece on the Harvard Business Review blog, Executive Strategist Jim Stikeleather writes on big data's human component: 

"We often forget about the human component in the excitement over data tools. Consider how we talk about big data. We forget that it is not about the data; it is about our customers having a deep, engaging, insightful, meaningful conversation with us — if we only learn how to listen. So while money will be invested in software tools and hardware, let me suggest the human investment is more important."

Sound familiar? Isn't this the drumbeat we've been hearing at MR industry conferences over the past few years? Stikeleather's post strikes right at the heart of the MR big data opportunity: using our expertise in synthesizing data to turn it into insights that inspire conversation and meaningful change among clients. It's something critical to our craft, and one that the top firms in our field have been honing for many years.

  • Storytelling that Brings Insights to Life: Beyond identifying critical knowledge, leading MR firms have increasingly focused on how insights are communicated and socialized within client organizations. It has become critical that non-researchers truly grasp the deep meaning of research. The best way to do this is to tell the story of the research in a non-technical, visually compelling way. While this is an art form in and of itself, the engagement it creates amongst the audience is well worth the effort: there's nothing worse than seeing clients' eyes glaze over as they're barraged with chart after chart. A visually compelling story backed by a deep understanding of the data's meaning is key. As data sets get larger and the analyses become more complex, this skillset will be increasingly important. Clearly an opportunity for MR agencies that have honed their skills in this realm. 

The seeds of potential success are clearly there for insights agencies to capitalize.  Those that successfully transition will have access to a fantastic catalyst for future growth.

However, realizing these opportunities is going to require a quantum leap that I don't believe most MR agencies will ultimately be able to make.  If the statement "we have met the enemy and he is us" was ever true, it will wind up being true here.  Stay tuned. I'll blog about this particular topic soon...

Until I do, however, what do you think?  Can MR agencies thrive in the era of Big Data, or is it ultimately another force for creative destruction for the traditional MR industry?

Market Research compatible with Big Data