The big data manifesto by the Wikibon community asserts that leveraging big data is the definitive source of competitive advantage in the future across all industry segments.
The importance of understanding and using insights delivered by big data and analytics has become so important that many industry watchers and journalists go so far as to assert that “data is the new oil.” They are entirely justified; taming data, especially when it grows at the rate of several petabytes every day, and understanding it requires enhanced capabilities of part of an organization.
Resources or capabilities?
Traditionally, corporations have considered a large asset base as a source of competitive advantage through cost efficiencies resulting from scale economies. These organizations had pursued resource-centric strategies that motivated them to integrate across the value chain -- upstream, downstream, or sometimes both -- as means of increasing the resource base and thus erect entry or competition barriers. This strategy, though useful, does not suffice to reflect, explain, or exploit the fast-paced dynamics in today’s tightly integrated and global marketplace. It is highly inadequate in explaining why some business entities, of sizes and asset bases comparable to those of their competitors, consistently outperform their other industry peers. Hence a theory that shifts the focus more on intrinsic capabilities that a firm develops over a period of time, rather than its competitive positioning, is relevant.
Substantial IT investments had largely been the privilege of corporations with deep pockets. Though many firms made the necessary investments in technology and IT infrastructure, very few considered IT a strategic asset; in most organizations, the IT department was relegated to the role of a support organization that delivered services essential to the normal business operation, but were non-core to the underlying business itself. In these organizations, business intelligence performed on historical transactional data constituted the entire analytics repertoire.
Enter cloud computing
With cloud computing and “pay-as-you-go” pricing models, the IT infrastructure is now available for all organizations, regardless of their size or scope. As a result, IT investments and infrastructure have greatly diminished in their importance as a source of competitive advantage. In other words, cloud computing has leveled the playing field, forcing companies, both large and small, to rethink their business and customer relationship models, drive innovation in their products and services to deliver superior value, and eventually create consumer surplus. Such customer-centricity is increasingly accepted as the means to recruit, nurture, cultivate, and retain a loyal consumer base and strategy to increase brand equity. Given this context, it is beyond the means and abilities of any human to process and correlate the various factors that are material to achieving business outcomes. Computers and information technology are indispensable tools that aid in sifting through volumes of data, identifying common denominators, mapping causations and correlations, etc.
Hence, IT is increasingly emerging as a capability mandating diligent consideration and application. Today, value comes only from considering IT a strategic asset and making optimal use of the IT infrastructure by understanding the underlying raison d'ętre of IT -- to process data and extract meaningful information that is relevant and applicable in the broader business environment.
Data, data, everywhere
Furthermore, the volume of data today that an organization has to cope with has exploded; much of the valuable consumer insights now rest in data of various forms, both structured and unstructured. Competitive advantage emerges through a comprehensive big data strategy to manage such large data sets and design algorithms and develop analytics capabilities in-house to extract relevant information and leverage the resulting insights in business operations ex tempore. Taming the 4Vs of big data -- volume, variety, velocity, and variability -- and extracting insights through data science definitely unveils a number of opportunities and creates value for business across numerous business functions, such as new product innovation, improved customer response, enhanced demand management, and increased profitability.
Red or blue?
Traditionally, customer segmentation focused largely on the averages and the obvious mass markets. These markets were identified by higher volumes, but lower profit margins with 20 percent of the products contributing to 80 percent of the overall sales, in line with Pareto’s 80-20 law. With almost all companies producing the identified 20 percent product subset and pursuing the same customer base, bloody price wars result, which gradually reduces and eventually wipes out the profit margins; the underlying mechanism is thus aptly called “red ocean strategy.” The traditional modus operandi focused extensively on technology, algorithms, and mathematical models that were well suited for analyzing historical transactional data and decision effectiveness a posteriori.
However, considering the pace of business in today’s interconnected world, such rearview analysis simply won’t suffice. In the current constellation, it is obligatory that the business is well equipped to handle transactions as and when they happen, implement robust, automated decision frameworks, and is able to predict future opportunities a priori and control events by staying ahead of the curve.
Big data, data science, and analytics bestow upon an organization the ability to segment the customer base at a finer granularity. Such an approach helps identify virgin markets and customer segments that are non-obvious using the traditional segmentation approaches. Such markets, called micro-markets, lie in the long tail outside the traditional market boundaries, are practically infinite in their size, and proffer virtually no competition. These long tail micro-markets are characterized by the diverse and unique needs spawning from the market participants’ unique needs and desires that can only be captured by the various permutations and combinations of the underlying product or service attributes. In these segments, the market participants, namely the users, have such unique and varying needs that cannot be catered to by the classical marketing or product development approach. Pursuing such a virtually competitor-free market mandates product or service differentiation and innovation akin to pursuing a “blue ocean strategy.” Furthermore, the micro-markets’ players are accommodative to higher price points, which have the direct benefit of higher profit margins to firms catering to this user base.
Need of the day
Identifying such long tail markets requires processing large volumes of data, robust algorithms and analytical tools, and scalable technology in the form of computing firepower, including hardware and software. Using big data analytics, useful semantic relationships and patterns across disparate data sets can be automatically extracted based on simplified statistical models and large data sets using machine learning mechanisms. Sophisticated algorithms and predictive analytics coupled with such concepts as micro-level segmentation delivers deeper insights about the factors that drive customer behavior.
It also requires qualified professionals, namely the data scientists, who wear many hats from computer programming to speaking the business jargon, and are analytical, could seamlessly navigate through the various organizational levels, and easily toggle between micro- and macro- aspects of business, from data to the overarching corporate strategy. Hence, it is easy to envision the cultural change required of organizations as they align themselves to leverage these forces unleashed upon them by developments in the big data arena.
In closing, the source of differentiation rests in taming the inexorable and increasing volume, variety, and velocity of data. Leveraging analytics capabilities to identify the “patterns” and “collectives” in the long tail micro-market segments is the source of sustainable competitive advantage. It is no longer the prerogative of the “big and the mighty Goliath” to set the rules of the game, but rather that of “smart and agile” David. Simple mathematical models, cheap computing resources, robust algorithms, and out-of-the-box thinking go a long way in today’s competitive landscape.
The age of big data has long arrived, and those firms that make the most of data wins.
User Rank: Exabyte Executive 4/20/2013 | 4:40:05 AM
Re: Hyper Segmentation Yes, Tesco is a great example. Measurement and technologies will surely impact acceleration of Big-Data for 2013. Loyalty marketing, loyalty automation and loyalty trends should continue to be a big growth area with the enterprises.
Re: Hyper Segmentation Then, of course, the likes of Tesco here in UK (who have announced this week they are pulling out of US) have used the data from their loyalty card so effectively that they get some of the highest returns on direct mail and other marketing tools.
Not only did they ensure they collected the data, they ensured they had the tools to analyse it and use it.
Re: Hyper Segmentation In the retail sector we have to do this segmentation already. While we have core products in all stores we have specific ranges and sizes in local stores relative to local demographics and buying patterns. But it would have been so much quicker to have interpreted this from big data!
User Rank: Exabyte Executive 3/16/2013 | 5:48:53 AM
Re: David Meets Goliath: How Big Data Is Leveling the Playing Field Mithun, great article. I very much like your concept of micro-markets. Especially since it shifts the focus of Big Data as an 'IT-thing' to micro-segmentation, or micro markets as you call it, as a customer or marketing related thing. It will more engage marketing VPs in the Big Data discussion.
Hyper Segmentation I wonder what long term impact this could have on the way we see customers and people in society in general. The overall demographics at the moment, almost act like stereotypes... to be able to drill down into differing tastes and needs, will this be a seachange in what we expect from certain types of people?
User Rank: Blogger 3/1/2013 | 11:42:23 AM
Re: Micro markets are the key @Saul that's it exactly. It's like the difference between reading through an entire library for research, which could easily take a lifetime, and having a searchable database that allows you to query the uploaded information for just what you need in minutes or even seconds.
Re: Micro markets are the key The amazing thing is that that data has been available for a long time... and we could have raked through it and put the pieces together by hand, creatively assembling these micro-markets and mini demographics, but it sounds like one of the least efficienct uses of time. Processing power and Hadoop is now here to cut through the time barrier, so it will be interesting to see if that creative energy can be invested in this process now.
User Rank: Exabyte Executive 3/1/2013 | 10:30:00 AM
Micro markets are the key Great blog. First time I've heard micro-markets mentioned but I believe they are the key to leveraging Big Data and making the argument to bring Big Data implementations into organizations. It's the fine art of making Big Data relevant data.