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Let’s start from the very beginning. The Internet that we know and love today is an open channel that uses free standards for communication. It is an equal-opportunity channel when it comes to traffic/content creation and delivery. The bottleneck is primarily the bandwidth that each individual user has available.
Now let’s say there are two companies providing media sharing capabilities using the SaaS model. Today traffic to and from Company A (mega establishment) and Company B (fledgling start-up) are treated equally by the broadband service provider. Today it is illegal for the broadband provider to treat the traffic from the two companies differently (assuming similar and legal content from both companies).
Now imagine if the broadband company could tell these companies- hey if you pay me an additional fee- your traffic will get higher priority on my network! It’s easy to see how Company A could easily edge out any competition from a startup like Company B based purely on its financial advantage. Bigger and better funded companies can bury competition by simply buying out the bandwidth from the Internet providers.
This essentially can kill technological innovation.
The Openness of the Internet is not a privilege we enjoy- it is and must be a fundamental right. We have a chance now to go and tell the FCC that we want the Internet to remain a free, fair and equal-opportunity channel. The FCC is taking comments from the public on this proceeding (also referred to as preserving Net Neutrality).
The site will remain open for 120 days (starting May 15 2014).. so the clock is ticking!
File your comment here. Proceeding number is 14-28
Net Neutrality is important- or else all the content, access and service we get over the Internet will be based on the highest bidder for bandwidth usage.
Take action. Do it now! #NetNeutrality
Have you been on the receiving end of a Sales call where you know that the rep is from a company that plays in the same market space as yours? This has quickly become one of my biggest pet peeves. Here are a three important things that every sales person must do before making that call to a prospect, lead or contact:
1. Research: Visit the company website. Arm yourself with basic information about the company- what do they do, how big are they, how long have they been around, who are their immediate competitors, has there been any interesting news about them in recent times? Look up the contact on social media sites such as LinkedIn.
2. Common Sense: I was tempted to couple this with research but I do believe this deserves to be mentioned separately. While researching the company and the contact- stop and think. Are you following up to a specific conversation or is this a cold call? If it is the latter- then consider if this company is a potential competitor, potential partner or potential customer. What is the purpose of your call to this contact? Why would they be interested in talking to you? If you’re just going through a list of leads with the same script- then you’re most likely wasting your time and theirs.
3. Story Telling: It is completely okay to call me even if you play in the big data analytics or the BI space. However I am not and cannot be a regular sales call. If there is a specific reason I should take the time to talk to you- then be prepared with a compelling story ahead of time. If you are calling a more promising prospect- then of course- the importance of your story cannot be over emphasized. Remember that you story must be malleable to fit their needs. Don’t forget to listen for the needs before starting the pitching. Nobody likes a pushy sales person.
I’m a gen-Xer and unabashedly addicted to texting. I was on a marathon session with a friend when he said something that struck a chord with the Big Data technologist inside me. He said “Doesn’t all knowledge lead to questions and vice versa?”
Indeed. Isn’t the primary purpose of putting Big Data technologies in place to satisfy this quest for knowledge and insights? And isn’t the best technology solution one that will not only let you get you the answer to the first question that you started with- but allow you to satisfactorily explore the potential possibilities that can be validated by all the disparate data that you have gathered as an enterprise? So if you’re looking to adopt a big data technology-based solution- why would you not make accessibility a primary RoI criterion? And why not tack on the requirement that the solution must add VALUE beyond the obvious?
Value is the fifth V of the Big Data world and when it comes to value- it’s all about what the technology can do for the organization. This is exactly what we set out to do with the QuickLogix Genie solution. It’s the solution that encourages you to ask the next question in your data-exploration journey. This results in better business insights and better business decisions. All using Natural Language Processing (NLP) technology- so you don’t have to be a SQL or scripting guru to gain access to the knowledge buried in the data. Visit http://www.quicklogix.com to learn more.
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.