Thinking about big data and the swirling world of analytics that surrounds it can be overwhelming. Broad-based organizational and technological changes are driving a new industrial constitution built on time-to-value and closed-loop systems of organizational and machine learning. As I analyze our next-generation business intelligence benchmark research results, I see trends in collaboration and mobile technology that will have a profound impact on business for generations to come. Given these defining times and technologies, how does one go about thinking of big data and the business analytics value chain?
Until now, we as an industry have been looking at the three Vs of big data: volume, velocity and variety, which have provided a way for people in the technology industry to think about the emerging ecosystems of big data. Most business people, however, have not heard of the three Vs of big data. For them, we need to move beyond the technology-oriented three Vs and provide a simpler way to think about the impact big data has on business.
The approach I suggest is to look at what might be called three Ws of data. (It doesn’t matter whether we’re talking about big data or small data.) The three Ws are the What, which refers to the data and information itself; the So What, which refers to the analysis of the data or the process of deriving implications and meaning from the data; and the Now What, which refers to the decisions made from the data and the resulting actions. (The actions after the decision may also be referred to as the Then What, but for simplicity’s sake we’ll include it in the idea of Now What.) The more we can think about technology and information in a holistic business process and people-oriented manner, the better we can deliver time-to-value (TTV) associated with big data. Let’s dive into each of these Ws a little more and discuss how they relate to technology and the three Vs.
Most technology analysis focuses on the What of big data, for good reason. It’s an exciting space and these are exciting times. The transformation of information system architectures stokes the imagination and opens conversations about timely processing for large sets of unstructured and semi-structured data. Approaches include massively parallel processing and in-memory processing, and may involve entirely new approaches such as Hadoop. In this area, serious information management and quality control issues still need to be addressed in order to make sure our data is trustworthy and actionable. Our benchmark research on business analytics shows that analysts spend two-thirds of their time just preparing data prior to doing actual analysis.
At the same time, we need to move beyond the What. The So What puts us squarely in the arena of business analytics, and in fact constitutes a large part of my own research agenda for 2013. Business analytics involves more than just applying mathematical and statistical approaches to information; it’s about creating useful and actionable insights that support both strategic and tactical decision-making. No matter how much analysis you do, if data just sits in a file or in a dashboard report and nobody takes action because of it, there is no value in the data. Business analytics is a broad area about which we at Ventana Research have built an expansive body of research that extends both into lines of business (LOB) and vertical industries. We’ve been able to establish key term definitions and performance baselines, and tease out the reality from the hype. I will extend this body of research both to highlight trends and to show how newer forms of analytics such as machine learning systems and disaggregated modeling impact organizations’ approaches and decisions. Working backward from the business problem to be solved, I will investigate the tradeoffs businesses need to make when they look at real-time streaming analytics, near-real-time analytics and fully batch-processed analytics. I also plan to explore how analytics is broadening its usefulness from strategy into operations.
The Now What is about decision-making and action. Once analysts have done the exploratory and confirmatory analysis and are clear what the data says, people still need to make business decisions. At the end of the day, this is still a markedly human function. This is where meetings and discussion drive collaboration and mobility tools, not the other way around. It is where attitudinal data comes together with behavioral and profile data, and where institutional knowledge shows its strengths and sometimes its limitations. It is where applications and closed-loop processes need to be pushed out to the front lines of organizations in order to improve overall customer experience and increase brand loyalty. How these tools are to be rolled out and integrated is another area of focus for our firm. Right now there seems to be no single mind in the market as to whether BI platforms, applications or productivity suites will dominate that last mile to the end user. With Windows 8 coming out, cloud deployments becoming more mainstream, and tablets in the hands of just about everybody, 2013 is shaping up to be a defining year at every end-user and customer touch point.
The ground-breaking research that we are planning for 2013 represents just the tip of the iceberg in a very exciting age. Of course, we’re just in the planning stage, so let me know what you think about the road ahead. I look forward to hearing your feedback!
VP and Research Director