My Digital Footprint
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My Digital Footprint
- 1. A Two Sided Digital Business Model where your Privacy will be someone else's business ! Tony Fish Sept 2009 http://www.mydigitalfootprint.com
- 2. identity is split, but connected digital identity physical identity bonds bridges relationships reputation privacy risk trust
- 3. physical identity has certain traits digital identity physical identity bonds bridges relationships reputation certification person organisation identification authentication Government & NGO trade privacy risk trust
- 4. digital identity has different traits digital identity physical identity bonds bridges relationships reputation certification person organisation identification authentication Government & NGO trade barriers implementation management characteristics privacy risk trust
- 5. digital identity has different traits digital identity physical identity bonds bridges relationships reputation barriers implementation management characteristics privacy risk trust
- 7. core themes for my digital footprint dependences data mydigitalfootprint value business models collection store analysis relationships security risk privacy trust law regulation identity (physical & digital) intent reputation discovery recommendation protection personalisation trade or barter context who owns the data? two sided model rainbow of trust mobile, web,TV passive/ active need, inspiration, entertainment
- 8. value from mobile, TV and web data Broadcast/ Listen WEB MOBILE Attention Browse Search Click Create Consumer Location Attention Browse Search Time Who Click Create Consume Presence View Preference Time Presence
- 9. in simple terms store click data content my data analysis value social data capture
- 10. stages to build my digital footprint store click data content my data analysis value ownership and movable algorithm = differentiation rights and cash digital footprint Behavioural DNA feedback loop (sensory.net) social data capture
- 11. traditional mobile value chain Application Content Service Provision Terminal Equipment Middle- ware Network operator Network Equipment User
- 12. consumer centric value Internet (IP) mobile access WiFi, WiMax, HSDPA, DVB-H, WCDMA, Bluetooth, GSM, 3G context, payment security, identity music full web browse, search social Blog, RSS, tag Communication Voice, IM, SMS, video entertainment Video, games, mobile TV location Maps, LBS, geotag payment Consumer centric mobile value model www.opengardensblog.futuretext.com
- 13. blind men and elephant The blind men and the elephant © Jason Hunt The blind men and the elephant. © Paul Davenport
- 14. 7 principals of web 2.0 Web 2.0 Harnessing collective Intelligence Data is the Intel inside End of the s/w Release cycle Lightweight Programming models S/W above a Single device Rich user experience Web As A Platform
- 15. unified view of web 2.0 The Intelligent web Harnessing collective Intelligence Harnessing collective Intelligence Data is the Intel inside End of the s/w Release cycle Light wt Programming models S/W above a Single device Rich user experience Web As A Platform
- 17. More ‘OFF’ : Less ‘ON’ on this screen in this earpiece consume createion x content where time intent direction who
- 19. 6 screens of life big screens small screens Cinema (shared with other members of the public) TV (shared privately within our homes) PC (personal or shared use) Fixed/Portable Players (fixed devices in things that move such as cars, planes, etc) Information screens e.g. iPod, radio The mobile device, an individual and personalised handheld device
- 20. value from mobile, TV and web data Broadcast/ Listen WEB MOBILE Attention Browse Search Click Create Consumer Location Attention Browse Search Time Who Click Create Consume Presence View Preference Time Presence
- 22. mashup value from mobile, web and broadcast mashup create consume create create consume consume broadcast MMD WMD BMD mobile web
- 23. digital footprint and behavioural DNA digital footprint Click content my behavioural DNA INPUT ANALYSIS Algorithm OUTPUT service improvement (existing) web TV mobile m2m service discovery (new) web TV mobile m2m trade or barter collection store analysis value social
- 25. types of data input for a digital footprint
- 27. Fish Tail’s, a model to categorise data time Short bursts of data, with varying amount of information Continuous feed of data, may vary on amount of data available Continuous feed of data, depending on use Infrequent and small data bursts
- 28. data is inter-related communication social behavioural payment consumption creation e-mail/ IM/ SMS/ voice links/ FOAF/ click/ review/ tag/ blog routes and routines, loyalty card, professional, clubs, affiliation credit card, debit card, cash, contactless, direct, cheque favourite, preference, style, genre, occurrence, video, music, audio, application type, style, tools, pattern, themes records certificates, health, exam, DOB, Council, government, passport
- 29. two sided digital business Actual User Data Actual User Data Actual User Data “ The Business” The User Direct feedback In Direct feedback collection store analysis value friends social norms
- 30. two worlds collide context personalis- ation recommend- ation requirement/ enforcement/policy security trust login authent ication proof recognition/ desire/ peer pressure/ community attention location time search content create Identity access content consume purchase banking discovery reputation corporate Digital Footprint individual community Inputs collection outputs value who benefits motivation database store/analysis Closed loop of feedback and improvement trade or barter billing accuracy colour intent activity AAS protection Behavioural DNA
- 31. yesterday’s fragmented network wireless voice data video application layer control layer connection layer
- 32. today’s network voice data video cellular application layer control layer all IP connection layer WLAN access and connection
- 33. correlated authentication browser packet access authenticate reverse proxy proxy cached policy rules identity system authN service HSS Enhanced HSS policy server HSS IDS integrations using SAML AuthN and polices (for QoS, SLA, access controls etc)
- 34. example – new way to offer mobile security store moveable digital footprint behavioural DNA adverse behaviour Click content my normal behaviour graceful opening location route time routine restrictions unique override closing time Take raw data to new provider confidence assurance collection analysis value
- 35. creating the virtuous circle collection store analysis value TRUST RISK PRIVACY
- 36. build or erode privacy capital PRIVACY erode build PRIVACY CAPITAL Who You Are Routes And Routines Patterns And Preferences Higher FUD Fear, Uncertainty and Doubt lower FUD positive feedback negative feedback Higher propensity to engage more and get better services lower propensity to engage and only gain standard services
- 37. build or erode risk capital Risk erode build Risk CAPITAL gut feel home and personal business And financial higher FUD lower FUD positive feedback negative feedback Higher propensity to engage more and get better services lower propensity to engage and only gain standard services
- 38. build or erode trust capital Trust erode build TRUST CAPITAL Reputation And Recommendation Patterns And Preferences higher FUD lower FUD positive feedback negative feedback Higher propensity to engage more and get better services lower propensity to engage and only gain standard services
- 39. bonded but not related TRUST RISK IDENTITY PRIVACY SECURITY Increasing closed Increasing open High Control High Value Justification of benefits Justification of barriers
- 42. ‘ Rainbow of Trust’
- 44. migration my-way one-way accept authority untrusting and wise untrusting and stupid
- 45. engaged prepared to engage with my digital footprint NOT prepared to engage with my digital footprint sit back and enjoy the benefits controlling economically unviable
- 46. I own my data I give up my data Enable 3rd party to use and exploit their data to generate benefits in kind and / or cash for a percentage of revenue business model’s Model Enable 3 rd party to use and exploit your data to generate benefits in kind and / or cash for a percentage of revenue 8 Pay for enhancement to service (subscription or one off) 1 Trade data for enhancement directly with service provider 2 Trade data for enhancement via a third party (indirect) such as an aggregation party 3 Pay for services directly (subscription or one off) 4 Pay to protect your identity 7 Trade data for services via a third party (indirect) such as an aggregation party 6 Trade data for service directly with service provider 5
- 47. strategic issues competitor VOT tribes Value Porter’s model focus differentiation/ segmentation lowest cost profit cost services access GYM club no change game changing
- 48. structural problems device tethered generic network platform applications & content closed open locked net neutrality deliver capture closed mobile ecosystem open mobile ecosystem no change game changing
- 49. femtocell
Hinweis der Redaktion
- Field service engineering on a mobile device is about collection not about input At this point you should be screaming PRIVACY, SECURITY, How this takes us to issues of privacy and trust. Lets come back to speak about the rainbow of trust. But lets look at the enterprise 2.0
- Mobile is a platform and not and service. There is more value in getting data off a mobile device than to it. View this chart from the direction of the customer, the story is that the yellow side is how the generic business market operates today and has done and will continue to do so. The green side is this new world of 2.0 thinking. Participation, networking effect and web as a platform. I will conclude that mobile is a platform and that There is more value in getting data off a mobile device than to it. Lets start with who benefits in the yellow, the existing and ongoing way of doing business We took a thin scrape of this data to produce an entire advertising industry. The green side description But how does this lead me to conclude that there is more value in getting data off a mobile device than to it. Lets consider the fact that the mobile is in your pocket from the moment to wake to the time you return to sleep, during that time it knows what you are doing, where you are doing it, applicators. From the consumers perspective this device can become the method for collecting data that could be helpful for other services that I would like to consume. The automation of this collected data can become my performance CV, it could be my reward calculator, it help the serach engine know when I type paris in …. Further - is there more value in know what you are doing or who you are doing it with? Given that sales for your customers is about acquiring new customer, knowing who, as part of your social group, could provide enormous value.
- Service differentiation based on trust Let me start with a consumer walking into carphone warehouse. The person say’s – hello Mr sales man, I am a blue person. What the sales understanding from this is that this person wants an unfettered device, it has not constraints and they will sort out all the IT problems themselves, if they down load something, they will sort it. Mr Red, he only wants to do online and mobile banking Mr purple wants the walled garden Mr beige wants voice and text There customer are differentiated based on their trust in both the device, the SP and their provider of the service. It terms of enterprise customers, they will vary by their attitude to risk. The analysis needed is not but product but by profit and profile to risk. Do you want risk adverse or balanced risk, I don’t know as I don’t know the profit by type.