Decisions from Data

Saturday, July 19, 2014 4:19:00 PM
Big data and analytics are increasingly fashionable in every field - business, science, politics, policy and others. Four vectors - cloud/computing, data, analytics and context - need to come together to enhance value in companies embarking on using these emerging ideas. However, most providers specialize in only one or few of these necessary categories making implementation of complete solutions complex, costly and often not effective. Just as in many of such previous waves - Enterprise Resource Planning (ERP) and Business Intelligence (BI) to mention just two, the hype surrounding big data analytics is probably more than what it will ever deliver. More importantly, the technology companies involved in this wave, just as previous ones, seem to believe that it is an IT opportunity and the users of the plethora of the available analytical tools both inside and outside companies, don't seem to be equipped sufficiently to add value. 
Management consultants, adept at delivering PowerPoint documents filled with one-off analysis, are becoming obsolete. What companies need are not static documents but dynamic models that provide decision guidance based on changing and growing data. Such models have to take into account all types of data - structured and unstructured, deterministic and probabilistic, quantitative and qualitative - in a systematic way to improve decision quality. This is not a mathematical problem - there has not been any new Math for several decades - but a decision problem, something that requires a clear understanding of the context. Information Technology (IT) - a pure commodity - should be fully scalable in a cloud infrastructure - either public (less expensive) or private (more secure). Analytics need to be complete and systematized and should not be delegated to a few people with expensive statistical tools - leading to biases in methodologies utilized and models built. 
A focus on decisions - not data and analytics - is likely a better way to approach this problem. Frameworks that encapsulate all available techniques, operating from a flexible and infinitely scalable cloud infrastructure, leading to models that are able to learn from growing and dynamic data and provide decision guidance at the right time and place - where, what, who, how, how-much - will dominate this market. Companies should be careful not to over invest in hype, doled out by consultants specializing in one or few of the necessary areas - IT, Analytics, Data and Management. The solution has to encompass all of these - and it should begin at the end objectives and goals.
Data and analytics are just raw materials that aid solutions for better decisions. It is obvious that the design of a house will not start from accumulating concrete, wood and steel. This is equally true in big data and analytics.


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