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The Role of Data in Institutional Innovation

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but a thank you and and be
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thank you so the pleasure to be here in Berlin dies 1 of the 1st things that think about whether an audience like this would really enjoy a nice long half an hour worth
of power point and decided perhaps not so on news talk to you about what I'm thinking about when it comes to the role of data in innovation particularly institution to do that it makes sense to to start with the very idea of innovation Fig innovation is different from invention that leads to respect in 1 talks about a change and you can't measure change unless you have some concept of measures the 2nd element is that it talks about the usage good as they used to say you know is that the tree falls in the forest and there's no 1 to hear it does it make a sound an invention of meaningless unless there is
adoption innovation takes place to try and make adoption when I was young I
remember it up an old enough to to remember the 1st ATM's coming through and people people building these huge monolithic systems to help deliver banking services tools in the wall and the theorists turned around and said we have these problems of people stealing identity the concepts of like the bean came through but even in the early 19 nineties the answer became biometrics and there were people in the research to ivory towers who actually believe that when you wanted to get a you know 20 marks out of a war whatever it was in those days that you would actually be interested in putting your eyeball against a laser scanner good no concept of understanding what the human being would actually want to do would you trust in early 1980's laser scanners is that in the wall in order to draw money mean know instinctively at the top to to people that probably are about the answer no way but money was spent on this thing similarly people designed services to say I know what people would do on a rainy Saturday afternoon they will stand in the queue and want to pay their bills to NATO yeah totally normal why don't you want to pay your bills while it's raining in the middle of a that that's when innovation doesn't happen innovation begin when there is adoption and we're looking at all I live in a generation we live in a generation where the idea of adoption in terms of being able to say we uses it how is it used what works what doesn't work these things start having an effect because you have an ability to have feedback loops any engineer wanted them to design products with active feedback loops because it's through the
learning that takes place in the feedback loop that 1 is able to assess what's working what's not working what's getting used was start getting
used to for them to the modern Internet from particularly those with subscription services adoption is not just important it is critical that is the meaning of whether you get your bills paid because if someone isn't using a broader pretty soon but they're not going to be paying the bill it's going to be a decay so being and understand where adoption takes place is critical before we move into that looking further the role of data and adoption this was trying to think about what innovation actually means I spoke about the fact that it is through use is through adoption it is through change but it's a change the use adoption of an invention and the drivers for invention themselves are things that you can sit on as you know as a scientist you would have to say he would be able to classify what drives an invention how it becomes an innovation the 1st the the commonest reason for an invention to exist and for innovation to take place through the adoption and usage of that invention is a perceived need how do you perceive any well 1 way of perceiving the name is to be able to have some model to be able to trace needed and how that need is exposed how do surfaced how it's collected together to to understand the grouping and clustering of the stimuli that make that need In at a macro sense you could turn around say the jet engine was invented before the perceived needs of wanting to be able
to fly further some way of changing from propeller style use
in terms of fuel proved to jet engine the design of the jet engine was to turn around and say well i need to fly at a higher so if you know that I wanted to but within that altitude I'm going to get less air resistance how my going to be able to deal with these to get the trade offs but the perceived need was to be able to fly further and someone like me would be able to be here except for that invention yeah the more common way is not just evening but all observed effect and the observed effect group to creating an invention and then to getting that invention adopted to be able to innovate that comes from being able to look at something record the results track the results understand the results my favorite example of an observed effect becoming an invention is that a Velcro right the idea of saying somebody observes a doll Walter running through Bush's picking up those and then finding that if you could design 1 surface that look like the dog fur another surface that look like that then goes on a bus you got something with high cohesion loose coupling but would not damage either supposal create thing and yet at the same time be able to have the equation to be of the carrier and drive through and over decades it starts getting adopted increased use takes place because the context within which you can do that adopting the starts increasing once you start learning but if you look at something about the very nature of invention and then of innovation is actually based on the ability to observe the ability to record the ability to through assistance but create synthetic the off what you observe and then to be able to build and adapt services as a result for human these we just all that
learning right we learn ourselves from the time they're babies but they constantly
putting forward some mental model testing it see what works and doesn't work and then adjusting our behavior as a result of but that is as true for any invention and is particularly true for innovation because of being able to listen to what the customer is saying about what works and what doesn't work is the difference between seeing adoption for a product or service I'm not seeing this is the way life has always been and many of the failures that we see in innovation many of the inventions that never went off the ground Our where it is not possible to be able to do that remember In many years ago when I was CIO what measures Dusan I was trying to work something out to of apple at a time and the it looked like I was gonna spend some time with Steve Jobs he came into the room and then you will know this was a lot of the other people who know does the actually like doing business was today and he doesn't like CIO the are proxies for for the end customer is really interested in hearing what the end customer wants to do it and that's really important now when I look at an institutional role always making sure that the voice of the customer the what works what doesn't work when it worked when it doesn't work if you look at it in a more burn sort of Internet their organizations 1 of the things they do best is a B test right and that AB is just almost a frame a choice you actually can make that ABC testing for that matter but being precise and saying I'm going to give a set of options and then dried them through I'm going to watch what people don't and having watched having observed and will not allow that to track back to be able to figure out how best to serve the customer yeah that's easy to
say I'm no I I remember the when we do things like building recommendation engines which many of you would have
been used in creating collaborative filters you know people who did they also did the both kind of models a completely based on good feedback loops about customer usage but unfortunately we still haven't quite got to the world where perfection can exist so you take my case in I'm I'm a grandfather had 3 children between 18 and 30 and over the years they all understood that in our dad's a good for at least 1 thing they're usually it looks like this theory and what the wallet is always a useful parent all sort of connection point to have so what happens is that my Amazon account gets used by all my children it which is fine except that when I get recommendations that are based on what they buy it which is completely useless to me so I then represent some hypothetical person which is the conglomerate of for people of different ages and all are buying patterns so the very idea of identity who it is at the other end of what you're watching where there's 1 person or not in some parts of India and some parts of the Far East it in or a PC may represent a village but they a mobile form may represent a
family so the idea of how you actually take that data to allow for
the weaknesses and understand how are you going to be abused to create some way of filtering the outliers there is a way of doing it right and the best way of doing it is slightly above the customer to be able to say why don't you discuss those things that are meaningful to your profile of the area so in summary mechanism I can actually do it obliquely by saying I already have that book or I'm not interested in the so there is a learning that takes place because I'm able to make some feedback on recommendations but the premise is what is important that any form of learning to be able to create didn't mention becoming innovation becoming adoption because it's that sustainable adoption that makes a difference in any form of business and it's not just you know the the the as beer Drucker said the purpose of business is to create a custom having the customer relationship is what drives it and knowing that customer becomes an important element now many of the institutions we're built over the years actually work on a multi tier model where so much has been focused
on production and distribution the touch points of the Customer disappears so you have to know whether it's in the motor industry the
pharmaceutical industry the soft drinks industries have I remember talking some years ago to the guy will that looked after technology at Phillips and why he was so excited about mobile devices smart mobile devices the coming together of the apple notification generation and part and parcel of that was a notion overnight they could move from knowing 0 . 5 % of their customers knowing 99 . 5 % of the customers but suddenly there was a conversation and like the guy said in the Cluetrain Manifesto in 1999 2000 and markets are conversations and conversations are at least bilateral of not multilateral but the feedback it's the word back in that that's important below is a continuous so we have a situation where at least as long as I've been involved with any form of invention and innovation and had to concentrate on adoption that adoption takes place because the voice of the customers the voice of the customers for because I'm trying Egypt attention to what the customer say and then come on the role of the Chief Data Officer what is changed dramatically in the last 20 odd years has been the number of people that are connected the number of devices that exist the number of ways where able to make that conversation takes place it when I look in my bag when I look at a tablet 1 of the 1st things that comes to mind is we have removed a huge barrier to interaction that has existed for perhaps essential the quality keyboard all in Germany I guess psychology as a to keyboard but the premise is that we had created an artificial intermediate between the ability of a human being to engage with many information tools by adopting a keyboard so now my
one-year-old grandson have some basic understanding of what to do with the nite by
because point click zoomed pinch are not things they need to go to school to figure out In fact why migrants in my catch can the and yes there are apps for cats get the premise over there is once again saying feedback loops are possible
because we started removing some of the control points some of the bottlenecks that came in the way of our ability to listen in some ways it's insane for us not to be able to get adoption of products because the customer's voice is
heard in ways that were not possible before that we talk about moving from mainframes to midrange through desktop to more wired to smart mobile to sort of uh now onto the wearables and embedded but 1 of the key things that's changing and all that is not just affordability but the sheer number get everyone and everything is connected if my cats would have an iPod what happens when everyone and everything is connected as we get what multiple referred to as an information overload in order to make sense somehow you have to be able to extract signal from the noise because of everyone and everything is connected you really have a challenge in terms of how to extract valuable information from it but 1 of my favorite professors a guy quotation he said there is no such thing as information overload there's only filter failure and 1 of the reasons why people have gone on to a lot of modern social media tools because something like you know e-mail is what 45 years old or thereabouts over 40 years old and the reason why people are coming on these is that there is a switch from the publisher politer subscriber power I have the ability not to listen I don't have to follow I don't have to subscribe so as soon as you go from thinking that control and filtering happens a publisher level to control and filtering happens at subscriber alone your much more able to figure out what to listen to because the power is in you to choose what to listen to so the 1st thing that happens when you have an infinite array of connections is that you start being able to listen to the right thing by that choice because you're not having to deal with the files tools like Twitter work because you non-halophiles you're able to segment the files into sort of capillary charts I can follow the person and that becomes valuable so again part of what you start thinking about in the evolution of data and why an institution would even have a D 2 officer is to be able to understand these things to be able to know that while we can know having a few years ago they people said the total amount of data that existed since dynamometer Memorial now takes a few years to be created that became a few days to be creative it but it is meaningless because none of us can actually consume that level of data the how does the data that consume because it's RealTravel out as a get filtered because it has been tagged it has been classified it has this CDs of metadata of at tributes that allow me to select what I want that so consumption takes place so institutionally when you start dealing with the world where customers really hot and power to have of what's when they don't just have a voice but they work with multiple screens multiple device where location has now become just an additional critical means to be and to augment information great kindness becomes another critical augmented the way need to think about it is in the modern world all data is just breaks in that sense you know and the bits served themselves agnostic of anything out and the 1st generation of value comes when you're able to associate that data with time and place because suddenly benevolent did on a talk about analytics of Big Data whatever the proposition changes dramatically the filtering capacity because you're able to associate an element of data over time and place at almost no cost gate that's 1 of the things that the mobile devices done to us we take
it for granted but we are auto geo-locating portal timestamp and lots of things that we didn't before after
that even if it's an IP address or sin God or some proxy token for what a person is the next thing that's happening is that we're associating data with a person or people and quite often with the relationship graph of that person or people if you have the permission to be of so and if that has been exports not suddenly you don't just have knowledge of where and when you also have an understanding of the and dolls contextual pieces start refining the quality of the data available in order for you to be able to make sense in ways you couldn't before and all this has been happening silently beyond that comes a revolution that's much harder that's why you see so much being spoken about in Open Data which is that we use labels and these labels are critical you know that when I come to that later I have to know that I'm actually flying to an airport but in 1937 probably was called T x in terms of the character ICA all the name that nobody else would use except the airline industry and in a strange way it's fun because I was born in Calcutta and probably the only part of modern life that camcorder still exists is in an airport core good peaking exists in an airport bonded to some airport code you can't go there anymore but C C U P K M a a B or and they all exist because these labels are very hard to get rid of did they become
part of the way people share information with each other almost adjectival and they construct so
today we have these millions of devices billions of devices by their arguments about where the book of connected elements is going to be between 20 and 50 billion by 2020 they're all capable of being sent source and actuators they collect information and they send information that made available in File losses that tell people what people like or don't like what's being use what's not being used how it's being used what time is being used where it's being used what switches people off what switches people all but being able to make sense of it needs strong had some level of discipline how do you understand the where how do you understand when and how do you understand the whole and how do you do with all this in a way that you protect the customer's privacy a lot of people come ask you know J. D. what you think who owns customer data and the only answer I've had innocence of and ask that question is guys there's a clue in the name skull customer data OK what customers there for a reason but when we come to today and the topic that I promised to speak to you about was to do with institutional innovation on the role of the CDO I wanted to build up to it say 1st understand what innovation is to do that understand what invention is then look at why data has become a valuable or issue come to a point we understand the scale at which that data is available and then finally you will be able to see what the role of a Chief Data Officer it's so that's my role I get policy you know what I do every CDO in a role like mine has for discrete jobs to do 1 is to be a governor you have to sit down and established policies usage patterns through it's boring this block and tackle work but it needs to be done by good data is created because there is discipline the way I like to think of it there is In the old days every large institution had the trust level on data that looked like mother's home cooking OK you trusted whatever came to you because you knew that your mother knew the recipes should always buy stock from the right places you could trust the food and the cooking data was like mother's home cooking because all good data was surface from inside the institutions roll forward the top 40 years now we have connected devices outside the firewall we have mobility we have partners have alliances we have the internet
we have the web most of the data that enters the firm no longer created in the control of the
fire and if we behave as if it was built like models on talking then this what that's like having street food with a blindfold on and then wondering why you get ill 1st Role of the Chief Data Officer create the governance model that people start learning how to consume street food which means recognizing it died in it cleansing at having the necessary protections on 2nd row data is useless if you can't get to it and we have created for ourselves in an environment where you into the data is not easy so there is an engineering element to it how do you make data accessible consistently accessible reusable dropped forwards or need requested on demand with the same answer when you ask the same question there is a thermal sites all this talk about big data is really important but you get the basics 1st you know good data is important small data is important the big guns because you've done the hard work to be able to extract insights insights for what to serve your customers better insights for whom for your customers and finally finally you can talk about building something that becomes a partnership to all your businesses to prosper when your clients to prosper in partnership and
this happens because we understand we live in a completely new world with more data publishers than never existed with feedback loops that allow us to get much but the adoption of our products learning to listen to the customer can
never be a bad thing but remember it's the customer the thank you for your time here so
far the
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Metadaten

Formale Metadaten

Titel The Role of Data in Institutional Innovation
Serientitel re:publica 2016
Teil 164
Anzahl der Teile 188
Autor Rangaswami, JP
Lizenz CC-Namensnennung - Weitergabe unter gleichen Bedingungen 3.0 Deutschland:
Sie dürfen das Werk bzw. den Inhalt zu jedem legalen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen und das Werk bzw. diesen Inhalt auch in veränderter Form nur unter den Bedingungen dieser Lizenz weitergeben.
DOI 10.5446/20646
Herausgeber re:publica
Erscheinungsjahr 2016
Sprache Englisch

Inhaltliche Metadaten

Fachgebiet Informatik
Abstract There is a new sheriff in town – and his title is Chief Data Officer, or CDO. Presented by Deutsche Bank.

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