Big Data
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Big Data

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  • Here is the story….. I wrote a book about digital data, digital footprints, my data, digital exhaust, digital shadows, identity, risk, trust, privacy, intention, reputation, attention, branding and the business models. My remit is to tell you about something that is not is the book and my name for those who cannot work it out is Toe Knee Fish and not the widely acclaimed Indian actor Nail Legs Guppy We are in the use it stream and my deck to you is about who owns you, your data, your insights, your intentions, your history and your future all from your data…..
  • Here is the story….. I wrote a book about digital data, digital footprints, my data, digital exhaust, digital shadows, identity, risk, trust, privacy, intention, reputation, attention, branding and the business models. My remit is to tell you about something that is not is the book and my name for those who cannot work it out is Toe Knee Fish and not the widely acclaimed Indian actor Nail Legs Guppy We are in the use it stream and my deck to you is about who owns you, your data, your insights, your intentions, your history and your future all from your data…..
  • Here is my problem with you as this is a tricky balance… You are an individual and a citizen Your are a professional and a person You are a number and an identity I am speaking to you are a person and individual foremost and then as a professional who has the added issues of conflicts of values and lastly as someone who probably wants a little slice of untracked me time. I believe that you already live in a conflicted world. The conflict is between what you are asked to do as a professional and how the company makes money in new world of digital data exploitation and therefore how you behave, who you want owning your data, how personalised you want services and who has the rights to exploit your yummy data to exploit you.
  • Personally I believe that we are talking about a series of complex and interrelated issues and they are so big that it stop us taking and debating the real issues that matter – therefore want to share some observations about these topic areas with you that I hope enables us to jump over them and focus on real issues and how to make a difference. Worthy of note is that Arguments on these topics defiantly started before Aristotle!
  • Obsession about the complexity forgetting that it has a purpose
  • “Trust, but verify” was said by Ronald Reagan and his view encapsulates the paradox. After all, if you trust someone, why would you feel the need to check them out? And if you only ‘trust’ someone because you’ve rummaged through their sock drawer looking for evidence of hostile intent, surely what you have demonstrated is that you don’t really trust them –
  • Trust is about the most abused word there is and what matters when you think about trust is it is about community, citizenship about doing something together.
  • This goes back to my opening remarks about who we are, our conflicts and how we need to think about balancing what I need to do for success (exploit the person next to you’s data) vs what you would allow that same person to do with your data.
  • Next slides are about why we find it difficult to move forward on these topics with the teams we work with…..and therefore to do that I need to ask some rhetorical questions that I will address and they are all about our expectations of data.
  • What do these questions and models that come from them this tell us - ….. What you expect is different from what others expect What I believe is different from what other expect What your customer expects is different from you want Here is an important question to ask over a glass of wine later “When does broken expectation become creepy” and this is the rub, what is creepy for you is not the same as creepy for someone else in the same way we will all react differently to a film on horror , paranormal, love or war – we confuse what we expect with what others expect so Creepy is about dealing in shades of understanding expectation – once upon a time we called the people who managed this “editors” and successful ones had an affinity with a market - matched expectations.
  • What is new is subtle, … . Explain why a boy my dad used to flip a coin to help me make a decision, already made the decision, just need confirmation. About to occur – know, predicatably irrational Dan Areirly
  • Ahah – the take away slide 
  • By adding an organ-donation tool to Facebook, Mark Zuckerberg is setting up a dynamic of social pressure for virtue. Is that always good? Now getting us to sign our drivers’ licenses so our vital bits can be harvested to save others’ lives is a moderately low-impact decision. But what about the occasional calls for folks to sign up to be tested for a marrow transplant — as in the drive for Super Amit? That’s no easy decision. Imagine tomorrow, God forbid, one of your Facebook friends needs a kidney. There’s a tool staring you in the face asking you to get tested for a match. Do you join that lottery, getting tested and hoping to fail (or win)? Do you risk being shunned by your community if you don’t? Do you join in shunning others if they don’t? I’m not proposing answers to those questions. Technology is pushing at our norms, forcing us to adapt, in so many ways, from how we communicate and converse to how we define what’s polite and what’s rude. This is a mighty poke. It will be fascinating to watch.
  • By adding an organ-donation tool to Facebook, Mark Zuckerberg is setting up a dynamic of social pressure for virtue. Is that always good? Now getting us to sign our drivers’ licenses so our vital bits can be harvested to save others’ lives is a moderately low-impact decision. But what about the occasional calls for folks to sign up to be tested for a marrow transplant — as in the drive for Super Amit? That’s no easy decision. Imagine tomorrow, God forbid, one of your Facebook friends needs a kidney. There’s a tool staring you in the face asking you to get tested for a match. Do you join that lottery, getting tested and hoping to fail (or win)? Do you risk being shunned by your community if you don’t? Do you join in shunning others if they don’t? I’m not proposing answers to those questions. Technology is pushing at our norms, forcing us to adapt, in so many ways, from how we communicate and converse to how we define what’s polite and what’s rude. This is a mighty poke. It will be fascinating to watch.

Big Data Big Data Presentation Transcript

  • Big Data http://www.terrapinn.com/2012/big-data-world-europe/networking.stm
  • Remit : something that is not in
  • You as a professional You as a one of 7 bn people You as a persona
  • RISKTRUST EXPECTATIONPRIVACY IDENTITY
  • There is no one model of IDENTITY that will satisfyeveryone, in all cases, in all places Observation 1
  • From You With some complexity in the middle Observation 2
  • There is no model of TRUSTthat will satisfy everyone, in all cases, in all places Observation 3
  • USIt is aboutTR T Observation 4
  • There is no one model of PRIVACY that will satisfy everyone in all cases andprivacy law is confused with “sharing” Observation 5
  • There is ONLY ONE model of PRIVATE and that is what goes on inside your head Observation 6
  • complexity is created as we balance our individualism withprofessionalism and citizenship Observation 7
  • So tell me something I didn’t know
  • QuestionsHow is All Data and My Data related? Do you believe that everyone has the same opinion as you?
  • The Righteous model The Visionary model The Idealistic model The Evolution model The Private model The replication model6 models for ALL DATA and My DATA
  • QuestionsHow are My Data and Identity related? Do you believe that everyone has the same opinion as you?
  • The Related model The Inseparable modelThe Subset model The Multiple Me model The GreaterThan modelThe 5 models of My Data and Identity
  • QuestionsHow are My Data and My Rights related? Do you believe that everyone has the same opinion as you?
  • The Extension model The Control model The Right model The Real modelThe 4 models of My Data and Rights
  • new model…..
  • context, insights, feedback, fraud, behaviour, Analysis personalisation, “iData” About to occur on display rear-view mirror Collect signals Store Analysis sentiment “Real Time Data” intent“Old Data”
  • What this means is that I can modify the UI/UX in real timebefore you know what you want to do next – extreme….. The only button is NEXT
  • Don’t get bogged down in trying understand this
  • Work out your own attitude towardshow you want your own data to be treated; first!
  • Work out your companies attitude towards your personal data; second
  • Work out your companies attitude towards your CUSTOMERS data; third
  • Articulate your perception ofcreepy in terms of the gaps in expectations
  • our frustration is that those withlower risk have higher authority and that limits our own personal reach, scope, creativity and aspiration
  • and our annoyance is created bythose with a higher risk propensityand a-can-do attitude that want to take us beyond our own boundaries of expectation.
  • If your UI/ UX for collection, analysis, value or feedback (the business elements of a data model) suck…… then your chances ofsuccess are trending towards zero
  • Your data is a commodity & ownership is unimportant. Value will be retained by those who can get deep & dirty in thetransformation of data to create value & can marry complexity with uncertainty In the new kingdom, loyalty is dead, privacy is a setting, trust is thechallenger, the princes’ are brands, the princesses are simplicity, attention is queen, data is king and creepy is our political foe