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tonyfish   [email_address] Investor, entrepreneur and author Connecting the dots…. Source  http://www.mydigitalfootprint.com Nov ‘11
Framing: mobile : digital : loyalty
 
 
“ I was wrong” Profit is secondary
[object Object],[object Object]
Stuff that  Costs money Stuff that  has to be bigger strategy consulting trivia disruption Stuff that money  cannot buy Love Presents for  your wife Networking Faith
Here’s the issue…
customer Spending cash As the product loyalty cost reward marketing BRAND values experience Switching  costs comparison Retain margin pricing position data analysis steer Market pressures…. Mobile makes it easy to swop, compare and reduces barriers….. Conflict between driving cost out and bringing in more engagement.
 
Intangible Active (explicit give data) Facebook Targeting Loyalty card  Amazon Benefit to data provider Tangible Passive (implied indirect) Personal Data Points  FREE “items”  Google
We all need data
Internet and beliefs
 
 
The Internet needs you! create consume store i n t e l l i g e n c e analysis personalisation passive activity what we do what the  web does
web services and value creation of content consumption of content data store analysis Symbiotic Relationship  Web business depend on consumer data   Data business consumer digital data trade
 
Signal Spike Pulse Wave Trend
two sided digital business Actual  User  Data Actual  User  Data Actual  User  Data “ The  Business”  The User Direct feedback In Direct feedback friends social norms
Why is mobile so important? on this screen in this earpiece consume createion x content where time intent direction who
10 unique benefits of mobile ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],http://www.tomiahonen.com/
Personal Data
Personal  branding ME SOCIAL DIGITAL Private Social influence Social capital Algorithmic  authority Pattern  recognition Digital audit Social  branding Social  filters Validation Behavioural DNA Signals Behavioural signals Social intelligence Context  Reputation  Status  Intent  Barter  Profiling  Digital footprint Pulse  Waves Location Preferences Social graph Interest graph
 
Questions ,[object Object],[object Object]
6 models for   ALL DATA   and   My DATA The Righteous model The Visionary model The Idealistic model The Evolution model The Private model The replication model
Questions ,[object Object],[object Object]
The 5 models of  My Data  and  Identity The Related model The Inseparable model The Subset model The GreaterThan model The Multiple Me model
Questions ,[object Object],[object Object]
The 4 models of  My Data  and  Rights The Extension model The Control model The Right model The Real model
A Two Sided Digital Business Model where  your Privacy will be someone else's business !   Tony Fish Oct 2009 Free on line Free PDF Kindle Print
What is a digital footprint? How I react to analysis of my data How my social group in influenced by  the analysis of my data Data embedded in my content and interactions Data embedded in my social networks content and interactions with me What I say about myself What others say about me What the analysis says about What the analysis says about me in my social context
Can you control it? Purchase behaviour Payment  experience settlement Screen experience Device Software Network Billing Access Setup Applications Memory When When  Influence Time Location Need Pressure Urgency Context “ place” Touch Card Wallet Balance Credit History Cash Machine Location Technology Card Bank Receipts Ether Clearing attention intention action bundled data ,[object Object],[object Object],[object Object]
Who creates identity? –  not me
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],So who creates identity? : no one
an identity doesn’t create value
 
Source: My Digital Footprint  http://www.mydigitalfootprint.com/   physical me behavioural me claims and history me DNA finger print iris scan medical records academic  achievements professional  achievements images photos voice eye colour hair colour height home  addresses brands events bank and credit patterns routes routines activity Social me cost value from others from me usage blogs tweets habits friends likes comments attention preferences links blogs friends likes comments links video tags official documents video photos
Google doesn't want your identity –  it wants the data that gives you identity
trigger (spike) reflection (pulse) refinement (wave) stable (signal) reputation influence authority relevancy preference credibility trust reach
If money (a currency) is a token that must be ..... ,[object Object],[object Object],Memory of a previous exchange Store of some value Medium of exchange Measure of value ,[object Object]
Shades of data abuse acceptable unacceptable TRAITS Open Transparent Known Trusted Value add Engaging TRAITS Closed Secret Unknown Un-trusted Value destroying Fraud/ theft  bliss annoying creepy disturbing unethical
@kevinmarks
@tonyfish this is a load of ****!
@tonyfish less disruption, show me the evidence
 
 
take away’s
Don’t assume
Market is completely open
A mobile strategy is not an iApp
Can the digital you be owned?
Do you know the influencer
“ Trust” could be the problem
It is about owning feedback
Match the standards
It what you do with it that matters
Disruption is free - strategy is complex and expensive
Data is a commodity & ownership is unimportant. Value will be retained by those who own the feedback loop, who can get deep & dirty in the transformation of data to create value & can marry complexity with uncertainty   In the new kingdom, loyalty is dead, privacy is a setting, trust is the challenger, the princes’ are brands, the princesses are simplicity, attention is queen and data is king.
Thank you  [email_address]

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Loyalty world

  • 1. tonyfish [email_address] Investor, entrepreneur and author Connecting the dots…. Source http://www.mydigitalfootprint.com Nov ‘11
  • 2. Framing: mobile : digital : loyalty
  • 3.  
  • 4.  
  • 5. “ I was wrong” Profit is secondary
  • 6.
  • 7. Stuff that Costs money Stuff that has to be bigger strategy consulting trivia disruption Stuff that money cannot buy Love Presents for your wife Networking Faith
  • 9. customer Spending cash As the product loyalty cost reward marketing BRAND values experience Switching costs comparison Retain margin pricing position data analysis steer Market pressures…. Mobile makes it easy to swop, compare and reduces barriers….. Conflict between driving cost out and bringing in more engagement.
  • 10.  
  • 11. Intangible Active (explicit give data) Facebook Targeting Loyalty card Amazon Benefit to data provider Tangible Passive (implied indirect) Personal Data Points FREE “items” Google
  • 12. We all need data
  • 14.  
  • 15.  
  • 16. The Internet needs you! create consume store i n t e l l i g e n c e analysis personalisation passive activity what we do what the web does
  • 17. web services and value creation of content consumption of content data store analysis Symbiotic Relationship Web business depend on consumer data Data business consumer digital data trade
  • 18.  
  • 19. Signal Spike Pulse Wave Trend
  • 20. two sided digital business Actual User Data Actual User Data Actual User Data “ The Business” The User Direct feedback In Direct feedback friends social norms
  • 21. Why is mobile so important? on this screen in this earpiece consume createion x content where time intent direction who
  • 22.
  • 24. Personal branding ME SOCIAL DIGITAL Private Social influence Social capital Algorithmic authority Pattern recognition Digital audit Social branding Social filters Validation Behavioural DNA Signals Behavioural signals Social intelligence Context Reputation Status Intent Barter Profiling Digital footprint Pulse Waves Location Preferences Social graph Interest graph
  • 25.  
  • 26.
  • 27. 6 models for ALL DATA and My DATA The Righteous model The Visionary model The Idealistic model The Evolution model The Private model The replication model
  • 28.
  • 29. The 5 models of My Data and Identity The Related model The Inseparable model The Subset model The GreaterThan model The Multiple Me model
  • 30.
  • 31. The 4 models of My Data and Rights The Extension model The Control model The Right model The Real model
  • 32. A Two Sided Digital Business Model where your Privacy will be someone else's business ! Tony Fish Oct 2009 Free on line Free PDF Kindle Print
  • 33. What is a digital footprint? How I react to analysis of my data How my social group in influenced by the analysis of my data Data embedded in my content and interactions Data embedded in my social networks content and interactions with me What I say about myself What others say about me What the analysis says about What the analysis says about me in my social context
  • 34.
  • 35. Who creates identity? – not me
  • 36.
  • 37. an identity doesn’t create value
  • 38.  
  • 39. Source: My Digital Footprint http://www.mydigitalfootprint.com/ physical me behavioural me claims and history me DNA finger print iris scan medical records academic achievements professional achievements images photos voice eye colour hair colour height home addresses brands events bank and credit patterns routes routines activity Social me cost value from others from me usage blogs tweets habits friends likes comments attention preferences links blogs friends likes comments links video tags official documents video photos
  • 40. Google doesn't want your identity – it wants the data that gives you identity
  • 41. trigger (spike) reflection (pulse) refinement (wave) stable (signal) reputation influence authority relevancy preference credibility trust reach
  • 42.
  • 43. Shades of data abuse acceptable unacceptable TRAITS Open Transparent Known Trusted Value add Engaging TRAITS Closed Secret Unknown Un-trusted Value destroying Fraud/ theft bliss annoying creepy disturbing unethical
  • 45. @tonyfish this is a load of ****!
  • 46. @tonyfish less disruption, show me the evidence
  • 47.  
  • 48.  
  • 52. A mobile strategy is not an iApp
  • 53. Can the digital you be owned?
  • 54. Do you know the influencer
  • 55. “ Trust” could be the problem
  • 56. It is about owning feedback
  • 58. It what you do with it that matters
  • 59. Disruption is free - strategy is complex and expensive
  • 60. Data is a commodity & ownership is unimportant. Value will be retained by those who own the feedback loop, who can get deep & dirty in the transformation of data to create value & can marry complexity with uncertainty In the new kingdom, loyalty is dead, privacy is a setting, trust is the challenger, the princes’ are brands, the princesses are simplicity, attention is queen and data is king.
  • 61. Thank you [email_address]

Editor's Notes

  1. Original post is here: http://blogs.hbr.org/cs/2011/11/why_peter_drucker_distrusted_facts.html Management consulting is an industry built on facts. A "fact-based decision" (a phrase that returns 1.8 million Google results) requires legions of analysts to gather and crunch data, and it so happens that consulting firms supply precisely such people. Facts appear to de-politicize decisions, imposing objectivity and facilitating difficult choices. Who but an imbecile could be against reaching for data? Peter Drucker, arguably the greatest management scholar of the past century, was certainly no imbecile, yet one of his most important insights gets ignored in the rush for facts. As he wrote in 1973's  Management: Tasks, Responsibilities, Practices: "Most books on decision-making tell the reader: First find the facts. But executives who make effective decisions know that one does not start with facts. One starts with opinions...The understanding that underlies the right decision grows out of the clash and conflict of divergent opinions and out of serious consideration of competing alternatives. To get the facts first is impossible. There are no facts unless one has a criterion of relevance." Drucker provides several theses supporting this broad assertion: If we do not make opinions clear, we will simply find confirmatory facts. "No one has ever failed to find the facts they are looking for." An opinion provides an untested hypothesis. Once we have clarified the hypothesis, we can test it rather than argue it. "The effective person...insists that people who voice an opinion also take responsibility for defining what factual findings can be expected and should be looked for." Decisions are judgments, not a choice between right and wrong. Oftentimes they are "a choice between two courses of action neither of which is probably more right than the other." So we must understand the alternatives fully. Big decisions may require new criteria. "Whenever one analyzes the way a truly great, a truly right, decision has been reached, one finds that a great deal of work and thought went into finding the appropriate measurement. The effective decision-maker assumes that the traditional measurement is not the right measurement...The traditional measurement reflects yesterday's decision. That there is a need for a new one normally indicates that the measure is no longer relevant." Ironically, opinions break executives free of pre-conceptions and poor imagination. Disagreement is a safeguard against being a prisoner of the organization and seeing an issue just as underlings want. Drucker quotes the famed General Motors boss  Alfred P. Sloan , who after hearing executives unanimously support a decision reportedly said, "I propose we postpone further discussion of this matter until our next meeting to give us time to develop disagreement and perhaps gain some understanding of what the decision is all about." Consider how Drucker's view contrasts with the typical corporate process. Decision makers may have a general sense of stakeholders' opinions, but in their eagerness to act and to avoid controversy they do not probe to understand these perspectives fully. Rather, they quickly make a decision and then marshal facts to support it. Indeed, one top consulting firm has boasted for decades of an approach that develops an early hypothesis and refines it over the course of an engagement — rather than testing many competing hypotheses in the search for the one that best represents the truth. A company channeling Drucker would tackle matters quite differently. It would surface opinions very clearly, possibly through anonymous questionnaires or structured interviews of key staff by a neutral party. The company would also push executives to state the measure of a good decision, pushing them to think about criteria for future success rather than historical metrics. It would insist that opinions be linked to fact-based tests that would validate or disprove the view. Then it would frame a decision as a true choice between well-elaborated and mutually exclusive alternatives. Rather than focus the process on getting the right answer, it would anchor on asking the right questions. Clearly, this approach is more valuable in some situations than others. If a decision is an operational one much like judgments the company has made effectively many times before, and there is little change in the external environment, then there is no reason to tinker with a successful process. However if the company is encountering rapid industry change, poorly understood competitors, or new types of customers, Drucker's view becomes invaluable. The right questions provide a clear compass heading, even if the right answers seem devilishly complex. In a time of major shifts in our economy, when disruptive forces seem to lurk around every corner, Drucker's insight of nearly 40 years ago is more pertinent than ever. By all means, find the facts and create agreement. But first know the opinions and seek dissent.