Extracted 07SEP2011 from http://www.accenture.com/us-en/outlook/Pages/outlook-journal-2011-edge-csuite....TmYoazKQOSJ.twitter
[We don't usually promulgate opinions through this digest but we do so here because this article is so stunning in its concise clarity and honesty about the authentically complex issues pertaining to science in business. Also for this reason, we have departed from the practice of limiting our digest to fewer than 1000 characters. We highly recommend reading the entire article available at the link above.]
By Kishore S. Swaminathan (February 2011)
Case study after case study has confirmed the value proposition for analytics across a wide range of business functions, including pricing, demand prediction, targeted marketing, supply chain optimization, CRM and HR. In my view, analytics is something much more than a technology with an ROI; it’s a transformational phenomenon that will fundamentally change how business discourse will be conducted and decisions made...
Much the same way that an empirically based scientific method became the basis of our understanding of the world around us, analytics will eventually bring empiricism into business discourse and dethrone many of today’s business practices...
[Use of] data is a double-edged sword. When properly used, it can lead to sound and well-informed decisions. When improperly used, the same data can lead not only to poor decisions but to poor decisions made with high confidence that, in turn, could lead to actions that could be erroneous and expensive... [the author goes on to describe three potential problems in the use of data: timescales, granularity, and oversteering]
Businesses thrive on stability and repeatability... By contrast, an analytically based enterprise of the future will have to be designed around volatility rather than repeatability... Volatility—or rapidly changing decisions that are context- and time-sensitive—will be a big challenge for enterprises. Decisions are no longer easily explainable; capital investments cannot be based on mass repeatability but must cater to endemic volatility.
Today’s enterprises have more information than they can act upon because the information is siloed in so many ways: technologically (data in different systems that cannot be brought together), organizationally (data in different governance units that cannot be brought together) or by ownership (inside versus outside the enterprise). The enterprise of the future will be (or will be forced to be) “conscious” in the sense that it will know that it must integrate everything it has access to.
The end of analysis-paralysis...experimentation has a price and inaction has a price, so an analytically literate organization will be characterized by a clear understanding of data gaps and the value of experimentation to break the logjam... most companies do not know or articulate their risk tolerance clearly and are much more likely to penalize failed action than inaction... An analytically literate organization will have a firm grasp of its risk tolerance. With guidelines and models for action under uncertainty, it will restore the symmetry between how it treats failed action and inaction.
Science is purely empirical and dispassionate, but scientists are not. Science is objective and mechanical, but it also values scientists who are creative, intuitive and can take a leap of faith... A good scientist knows when there is enough data to warrant a theory, when there isn’t, what new data to gather and how to design an experiment to gather the right data.
...for completely new lines of products that will change a user’s experience or behavior, the only useful data is experiential data, not commentary and reactions from those who have never used the product... Intuition, creative leaps and clever experimentation are not incompatible with empiricism; in fact, the value of these traits will be even better understood in the future enterprise by analogy to theoretical and experimental scientists.