My Digital FootPrint

Tony Fish @My Digital Footprint I have been working with several teams on data driven innovations and failing to create the value expected. Listed below are some mindsets which I have come across that appear to create hurdles to the data opportunity. The theme underlying these views, I believe, is the same as the old philosophy argument on behaviour and judgement which is “are you Fact or Opinion biased?”  Personally I am defiantly and firmly in the “tell me your opinion.” The Internet has allowed the world to find, no matter what the opinion, some data to support it.  As I can/will always find facts to back any story, I want to know what you’re thinking, why you hold that view and what drives you. Why do I think this; because strategy and innovation is a judgement on outcomes and not a science.  I find it interesting that many are trying to prove me right or wrong with their data, rather than accepting that my opinion is mine and it is neither right or wrong but based on

Source : Andrew McAfee’s Blog Source2 : Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach They analysed 700 million words, phrases, and topic instances collected from the Facebook messages of 75,000 volunteers, who also took standard personality tests, and found striking variations in language with personality, gender, and age. In our open-vocabulary technique, the data itself drives a comprehensive exploration of language that distinguishes people, finding connections that are not captured with traditional closed-vocabulary word-category analyses. Our analyses shed new light on psychosocial processes yielding results that are face valid (e.g., subjects living in high elevations talk about the mountains), tie in with other research (e.g., neurotic people disproportionately use the phrase ‘sick of’ and the word ‘depressed’), suggest new hypotheses (e.g., an active life implies emotional stability), and give detailed insights (males

Jake Flomenber talks about how he views the larger big data market. Jake works with the  Accel’s big data fund , which recently opened their second $ 100 million fund, so he knows what he is talking about. He talks with Stefan Groschupf, the chief executive of Datameer, another well-funded Big Data startup with almost $ 37 million in funding.

Source : http://www.mckinsey.com/insights/business_technology/views_from_the_front_lines_of_the_data_analytics_revolution The link above is to a very good McKinsey article titled “Views from the front lines of the data-analytics revolution” Key points for me 1.     Senior management don’t understand Data irrespective if it is big, small, open, flat, simple or complex 2.     Privacy is not the issue – control, controls, authority and rights are 3.     Talent is always a problem but it never seen as a strategic issue

Privacy researcher Christopher Soghoian sees the landscape of government surveillance shifting beneath our feet, as an industry grows to support monitoring programs. Through private companies, he says, governments are buying technology with the capacity to break into computers, steal documents and monitor activity — without detection. This TED Fellow gives an unsettling look at what's to come.

What does the future of business look like? In an informative talk, Philip Evans gives a quick primer on two long-standing theories in strategy — and explains why he thinks they are essentially invalid.

Tony Fish @My Digital Footprint Is this a paradox…..If you are the product ( aka a digital service which is FREE) Who knows more about the product you as being self-aware or your data?

Source : http://www.linkedin.com/today/post/article/20140122165800-37102839-lies-data-tell-us Great article from Steven Thomson He sets out questions to ask next time you're about to make a big decision based on a particular set of data: Are you measuring the right thing? In almost any data-gathering situation, there are far more types of information that could be gathered than you can possibly tackle. Compare the contradictory claims that U.S. wireless phone providers make for their network coverage. No one's lying--they're all just picking different aspects of coverage to measure. Are you measuring it accurately? There are far more ways to screw up a measurement than there are to get it right. Ever compare election results to what the polls had said right up to the end? And political pollsters are the rocket scientists of data gathering--it's downhill from there. Are you interpreting the data wisely? Unless someone is inside trading, all inve

Thinking about data and what it can tell us Is there an equation for intelligence? Yes. It's F = T ∇ Sτ. In a fascinating and informative talk, physicist and computer scientist Alex Wissner-Gross explains what in the world that means.

Source: http://blogs.hbr.org/2014/02/how-to-tell-if-someone-is-lying/ To accurately infer another’s intentions, you need to look for  a set  of cues — gestures that together can more accurately predict or reveal motivation. Here’s how my colleagues and I identified the four key ones (with the help of a robot, of course) and the outcome is that if you express these gestures, you are probably less trustworthy…. 1.        Hand touching 2.        Face touching 3.        Crossing arms 4.        Leaning away So What:   nothing that new, except that it was a robot which was the control, unlike previous studies. As Robots come into play more and more, the person who codes them can become the double bluff.  Trick you with emotions of love and steal your wallet in the process. Don’t believe me then watch – Guy Hoffman: Robots with "soul”

Source :  https://www.facebook.com/notes/facebook-data-science/the-formation-of-love/10152064609253859 This is the Facebook view of the world of relationships which start with a period of courtship on Facebook ( e.g messages are exchanged, profiles are visited, posts are shared on each other's timelines.) = snooping.  The graph shows the average number of timeline posts exchanged between two people who are about to become a couple. We studied the group of people who changed their status from "Single" to "In a relationship" and also stated an anniversary date as the start of their relationship. During the 100 days before the relationship starts, we observe a slow but steady increase in the number of timeline posts shared between the future couple. When the relationship starts ("day 0"), posts begin to decrease. We observe a peak of 1.67 posts per day 12 days before the relationship begins, and a lowest point of 1.53 posts per day 85 days int

Report in full is here .....However, like our current dependence on fossil fuels, Big Data’s current use of  personal information is unsustainable, increasingly resulting in “pollution” via privacy infringement. At the moment, individuals have little, if any, control over their information’s use and disclosure in Big Data analytics. In addition to a host of privacy concerns, this lack of informational self-determination gives rise to an uneven exchange of the economic value. While the owners of Big Data algorithms profit from their use and disclosure of personal information, the individuals the personal information relates to do not—at least not directly. If not properly addressed, the privacy and economic concerns raised by Big Data threaten to decrease individuals’ willingness to share their personal information3—in effect, cutting off the flow of the “oil” on which the analytic “machinery” of Big Data runs. In order to make the interactions between Big Data and indi

By   NATASHA SINGER Source: http://www.nytimes.com/2013/04/28/technology/personal-data-takes-a-winding-path-into-marketers-hands.html The essence of this is article is that we don't know how or why something's happen in a digital world. Our data can go anywhere and is not in our control – nor is what others imply about us based on our data.  When it adds value we love it, when it does not we find it creepy

If data is…. My transaction data. Data from any, all and every transaction – spending, investment, bills, gifts, selling and free – www.mint.com Environment Data.  Where you are, what your environment is like, wind speed, temperature, gas usage, petrol consumption – everything.   www.efergy.com , www.theowl.com www.eco-eye.com www.diykyoto.com  :   Quantified self . Sensor Data from Google Glass , Nike+ sportwatch , Zeo sleep manage , Omron blood pressure monitor , Accu-Check blood glucose meter ,  Fitbit Flex wristband , Sportline heart rate monitor , MoodScope log and 1,000’s of sport apps on your smartphone.  Should the data be in silo or under my control or both? Routes and Routine data.   All your geo data www.waze.com , https://foursquare.com Content Data.   All data about how you create, use, consume, generate, recommend, share, about you, generate for any and all types of media and content – too many to mention Medical data. You and your

Image : http://www.ethics4adigitalworld.org/ Source of viewpoint: http://www.wfs.org/futurist/july-august-2012-vol-46-no-4/secret-life-data-year-2020 This post at The Futurist is by Brian David Johnson (worst linkedIn profile ever!) who is a futurist for Intel and writes about how geotags, sensor outputs, and big data are changing the future. He argues that we need a better understanding of our relationship with the data we produce in order to build the future we want. Personally I am not sure that anyone will think about sensors and the data that is shared but I do think that there will be debate about who decides.  The classic of this is the fictional scenario of the self drive car, a narrow bridge and a school child. Scenario 1.  You and I are being driven by the auto drive and as you cross the narrow bridge the child jumps out in front of us – the sensors go mad and realise that you cannot stop and you are driven through the wall into the raging river bel

Wikibon has  published  its Big Data Vendor Revenue and Market Forecast for 2012 thru 2017, giving insights as to how much revenue big data vendors will derive in the coming years. They have also published an infographic,

  Source http://www.fico.com/analytics   Predictive analytics is not a method by a diversity of methods brought together to enable businesses/ government/ individuals to make smarter, better informed, decisions.   “We know what you will do before you do” …. as long as we have the data!

Whether we know it or not: every piece of information we share on the internet creates a unique profile that speaks volumes about our personality.  Tony fish, founder of the Innovation Warehouse, shocks audiences by showing them how much data is collected from your online presence: without you being aware of it.  He also highly  recommends  the book "Predictably Irrational" by Dan Ariely which delver more into the subject.

Source for new thinking: http://blogs.hbr.org/cs/2013/06/a_new_framework_for_customer_s.html It started with… " You know, I don't think I believe in segmentation anymore." She said it fast and softly, almost in hope that the sounds around us would make it inaudible. But we did hear it, and responded, "Well, we don't either." From observing … " we were finding an increasing disconnect between telling people about segmentation, targeting and positioning on the one hand, and about the increasing shift of control from brands to consumers, on the other " HBR presents a new kind of segmentation based the combinations of jobs that customers need to get done.  Think Ted Levitt's famous comment about selling ¼ inch holes rather than ¼ inch electric drills. They provide this outline…. Step #1: Identify the contexts in which customers are using the company's products. Step #2: Combine information about transactions and cust

My Presentation to Digital Shoreditch Does data understand the meaning of a wink? I believe that the problem we have with understanding data..... is the same fundamental problem, that we have about our views, our independent views, our independent views based on experience, our refined independent views based on on-going experience ; that we suffer when we talk about any political hot potato such as the economy, bank debt, personal credit, environmental change, global warming, privacy, size of government, policing or marriage reform……  we all have unique views and our views are different from the others around us and our views are also different again from our customers views – which apparently are the only ones that count! I contend that personal information, personal data, your data, your digital footprint and its relationship to you, your identity and your rights has the same complex mix, blends and balances that set and counter your personal views and insights.