Archive for December, 2013
Prepping for the holidays? Some others are dreaming about how big data can help them power through the insanity of holiday shopping!
And check out a very entertaining blog of the #bigdatachat Tweet Chat that I participated in- it was Santa centric and a lot of fun!
Ho ho ho and a lovely holiday season to everyone!
The author prophesies that the importance and definition of a data scientist will change in the next few years- as big data technology is adopted in a more mainstream manner. One of the comments was that data scientist is a misnomer because data science is not really a science. Analysis of data does not make it a science. I cannot agree more. It isn’t data science- it is decision science. Here’s my reply to the comment
“Science has always been about setting a hypothesis and proving it right or wrong. We’re just getting started with BigData. The proper and most beneficial use of big data will be when everyone becomes a decision scientist. The data, the analytics, dashboarding and interfaces will simply be tools that will help a business/ enterprise/ organizational decision maker verify the viability of their hypothesis. That’s the real promise of bigdata. If it isn’t, it should be about being the toolkit for Decision Science.”
“Intuition is a very powerful thing, more powerful than intellect, in my opinion.” – Steve Jobs
When setting new direction or exploring new ideas, business decision makers often rely on recognizing a pattern or developing a notion that they cannot quite articulate. What they do have to rely upon is years of experience, a deep knowledge and expertise in their domain. Massimo Pigluicci, a philosophy professor at City University of New York says “Intuition is the result of your subconscious brain picking up clues and hints and calculating the situation for you, and that’s based solely on experience”. This is the definition of the best kind of intuition in the business world.
Mr. Jobs had a highly refined gut instinct. Most others benefit from the ability to capture, store and measure a flood of data (big data). This deluge of data has empowered organizations to create analytics and metrics to track behavior and predict the future with greater accuracy than ever before. We can now exploit the advantages that big data to better understand competition, customer base, factors that affect productivity, sales & revenue and to determine the courses of innovation. MIT Professor and director of the MIT Center of Digital Business Erik Brynjolfsson’s studies have shown that data driven decision making does indeed improve the decision making performance by 4-6% in productivity and profitability (ref. HBR Oct 2012).
The more data we can gather, the more sophisticated analytical methods we can adopt, the more decisions we can make with little to no human intervention. Does this mean then that intuitive decisions are not the path to success when working with mountains of structured and unstructured data?
We believe that data driven business analysis doesn’t have to be at odds with intuitive decisions making. Intuition and analysis work best when teamed together to enhance the value offered by the other. This is accomplished by utilizing tools such as Genie the intuitive analyst tool from Quicklogix. Business leaders and analysts can use its simple Google-like querying interface to build an evidence story to corroborate their business instinct.
Big data is making us smarter like never before. Complement this with the intangible advantages of knowledge, experience and yes- intuition to derive the best benefits.
“A good decision is based on knowledge and not on numbers” – Plato
What are the guiding objectives for making a business decision? We want to satisfy our customers. We want to be able to demonstrate that the service or product we provided them has quantifiably improved their loyalty or customer satisfaction. We want to increase revenue and profitability. We want to reduce costs and prevent disasters.
Decision science is defined as the design of efficient procedures that either aid a decision maker’s effort or evaluate courses of action according to chosen criteria or policies so that a decision logically follows from the computations (ref: Principia Cybernetica Web). The theories that support these efforts take into consideration the uncertainty of the situation, the information available about consequences, the risks involved, costs & benefits of each action and the time, resources and preferences at the decision maker’s disposal.
Good decision making must take into account logical, environmental and emotional perspectives. Today we have the ability to capture, store and measure a flood of data (big data). This deluge of data has empowered organizations to create analytics and metrics to track behavior and predict the future with greater accuracy than ever before. MIT Professor Erik Brynjolfsson’s studies have shown that data driven decision making does indeed improve the decision making performance by 4-6% in productivity and profitability (ref. HBR Oct 2012).
Companies need to rise to the challenge posed by the availability of this improved predictability. There is no longer the excuse of not having enough data to prove that a proposed solution was bound to succeed or fail. The value of the executive is still his/her ability to create a vision, spot new horizons to explore and chart a map to get there without being afraid to embrace the opportunities offered by the new data paradigm. The value of the domain expert is in his/her ability to ask the right question. The value of the IT team is in their ability to recognize that data proliferation and accessible analytics are essentially the wheels that will propel their organization forward and that they themselves are responsible for keeping the wheels well-oiled.
2500 years after Plato- numbers matter but knowledge still holds its own in the process of decision making.