How and why SMART decisions are based on SMART analytics
Much of what I know about “big data” and analytics I have learned from Tom Davenport and again I express my deep gratitude to him. In addition, I have read several dozen books by other authors on one or more aspects of one or both subjects and have learned much of value from them, also. I now share four convictions based on what I have learned thus far. First, the name of the game is not Big Data. Rather, it is having a sufficient quantity of the right data. Also, even then, enough of the right data is essentially worthless unless and until they guide and inform (a) the right decisions and (b) effective execution of those decisions. Also, all right data are important but some are more valuable than others. Finally, the relevance, importance, vale, and sufficiency of data can change, sometimes significantly.
For more than two decades, at least since Tim Berners-Lee devised the concept of a worldwide web, business leaders have been struggling to identify their companies’ information needs and then fill them. These are critically important decisions. In recent years, this process has been facilitated, indeed expedited by various electronic technologies, so that better decisions can be made and then executed much faster than ever before.
I agree with Bernard Marr: “The marriage of data and technology is radically changing our world and making it smarter. And business much become smarter too…Today the really successful companies understand where their customers are and, perhaps more importantly, what they are doing and where they are going. They know what is happening as it’s happening and they allow that information to guide their strategy and inform their decision-making. Companies that don’t embrace the SMART revolution will be left behind.” Quite true.
Marr introduces this acronym, SMART, for the business model he recommends:
S = Start with strategy
M = Measure metric s and data
A = Apply analytics
R = Report results
T = Transform business
He devotes a separate chapter to each component of the model. “When you approach data (big and small) and analytics from this narrower more focused and practical perspective you can get rid of the stress and confusion surrounding Big Data, reap the considerable rewards, and ‘Transform your business.'”
These are among the dozens of passages of greatest interest and value to me, also listed to suggest the scope of Marr’s coverage:
o Data collection (Pages 12-17, 57-58, and 85-88)
o Focus to reap rewards (19-22)
o Strategy (23-55)
o The SMART Strategy Board (29-33)
o The pear tree metaphor (33-35)
o SMART questions (43-46 and 52-59)
o Project Oxygen (Google): A mini-case study (48-54)
o Measurement (57-103)
o Datification (64-79)
o Analytics (105-154)
o Transparency (143-149)
o Reporting (155-198)
o Data visualization (156-178, 163-269, and 185-190)
o Transformation (199-230)
It is impossible to exaggerate the importance of asking not only smart questions but the right smart questions. Only then can the right answers, the correct answers, be determined. In this context, I am reminded of Peter Drucker’s observation, “There is surely nothing quite so useless as doing with great efficiency what should not be done at all.”
Once again, I agree with Bernard Marr: “SMART business is a solution that encourages us all to step back from the hype and noise around data – especially Big Data – and take stock of where we are, where we are trying to get to and what data and tools we can employ to get there…One thing is for sure, Big Data and analytics are here to stay and it’s only going to get more sophisticated. We need to embrace it, operate it effectively, deliver value in exchange for the data and apply its significant benefits for the betterment of our world.”
Business leaders who are determined to help their organizations use smart big data analytics and metrics to make better decisions and improve performance will find in this volume almost all that they need to pursue that immensely important strategic objective.