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Thursday, 10 April 2014

Three research challenges: my presentation at the NSF Workshop on service innovation

As a workshop participant at the NSF workshop (, I presented what I consider to be the 3 main theoretical challenges for service research. Note that this is not the applied challenge - that is a different challenge entirely and would be a different conversation regarding my work at the institute with industry. Rather, I have focused on theoretical and fundamental challenges because this workshop is about guiding fundamental research, sponsored by the US National Science Foundation and National Academy of Science.

I begin by saying that my approach doesn't assume any sacred cows of knowledge. Instead, I propose that most of our disciplinary knowledge exhibit historical path dependencies and the many assumptions from that history has changed. In other words, when you want to build a house in the 21st century for living, you might need to go back and evaluate the nature of your bricks, wood, mortar and cement and their ability to come together for that modern house, when those materials were made to build a different house 100 years ago.

So what are the challenges?

The customer as endogenous in the system
From a service dominant logic perspective, service is co-creation ( Vargo, Maglio & Akaka, 2008). That means the customer is part of the system and not outside the system. Current movement from Big Data to many systems methodologies do not often take the customer as endogenous in the system. There is a need to develop methodologies, that treat the customer as being an entity in the system ie as a human sensor, a human intelligence, meanings/context creator i.e. a resource integrating and contributing entity.... Something.... We talk about customer as behaviours but not as an endogenous entity within the system (co-creation by another name for scientists and engineers). For example, even when we talk about material technologies, we can talk about its resistive, absorptive etc. properties. Why do we not talk about customer and their abilities within the system. Why do we not talk about their capability to absorb variety (a big capability to scale systems) or their resilience. Because we lack the methodology and the science to understand that. Second, there are two ways to research into at an aquarium as a system: as a viewer looking into at an aquarium, or as a fish within the aquarium. In the former, the research is for the benefit of the manager/policy maker/owner of the aquarium. In the latter, the research is for the benefit of the fish. We need to question the position, mindsets and perspective of the researcher when constructing systems methodologies and the findings from the research. This is becoming increasingly important as customer resources to co-create value is evolving into a more structured resource e.g. personal data. The customer, being a more formalised entity and increasingly empowered through technologies is a driver for future economic opportunities as both a consumer as well as a producer. The application of personal data in co-creating value with a product or service can be a massive multipler effect for the future personal data economy and national economies of the future.

The incomplete product
The boundary between a service and a material product is increasingly obscured. As material technologies evolve, a physical product can be designed to be more dynamically reconfigurable in order to fit in the diverse and dynamic interactions of actors in their contexts. Dynamic reconfigurability as a concept has been widely used in system design, which enable the system to ‘have the capability to modify their functionalities, adding or removing components and modify interconnections between them’ (Rana, Santambrogio and Sciuto 2007).  With the development of pervasive digital technology, dynamic reconfigurability becomes possible in future products because products could have a ‘reprogrammable nature’. This means products could have new capabilities even after a product or tool has been designed, manufactured and sold (Yoo, Boland and Lyytinen 2012, p.1399).  Thus, products may not need to be ‘finished’ to be transferred to the customer but could be designed such that contexts of use could be incorporated into a modular product design and ‘finished’ through customer resources (e.g. personal data) brought into consumption through digital pervasive technologies.  This ‘incompleteness’, resulting in open and flexible boundaries of products, allows offerings to materialise multiple affordances and dynamically alter their affordances with changing contexts. Products evolve to become platforms for service that could provide increasing returns to scale through standardisation even while they can be deeply and uniquely personalised. For example, the iPhone is fully standardised and enjoys economies of scale yet is able to be fully personalised, because of the boundary between the digital ‘app’ layer and the material ‘phone’ layer.

New Transaction Boundaries, Economic and Business Models
An economic model is the model of an ecosystem (like a market) that distributes rents (or revenues) either through the pricing mechanism or regulation, according to what the entity (such as a firm) does to stay within the ecosystem. New economic models, often arising from new business models and/or new entrants, redistributes rents within the ecosystem occasionally resulting in the exit of existing entities (disruption). With the blurring of boundaries between material and digital, firm and customer, product and service, there is a need to understand new ways to obtain revenues and the nature of transactions in the future digital service economy. Transaction is defined as ‘mutually agreed-upon transfers with compensation within the task network’ and ‘serves to divide one set of tasks and others’ (Baldwin, 2008, p.156). Baldwin's (2008) conceptualisation of transaction is developed from a ‘systems of production’ perspective.  This perspective enables us to analyse the dependencies between agents (i.e., consumers and producers). The value-creating context, as a unit of analysis for service, jointly co-created by the customer and the producer, creates an interesting challenge for modularity and product/service architecture for new innovaitons. Modularisations create new thin crossing points where transaction costs are low (p.156) and also create opportunities for new boundaries where new transactions, and new business models can be created. 

The above challenges are not merely research/innovation challenges but impact on education and skills as well as since there are increasingly greater overlaps in domain knowledge, particularly between engineering and computer science and current reductionistic curriculum is not helping in developing future engineers/technologists and managers.

Thursday, 6 March 2014

The HAT (

We live in a world today where data belongs to those who collect it. So even though it's data about me, for example, if it's my purchases at a supermarket, searching online, or spend on my credit card, that data is owned by the supermarket, or by google or by the bank because they own the technology that made the data collection possible. Without the technology, this data won’t even exist. But since we don’t own it and often don’t even have access to it, we can't really benefit from integrating it to make our own lives better. In fact, even if the data is returned to us, we don’t really know what to do with it coz these data are vertically silo-ed – the format and presentation – were all collected to help the institution that collected it and not to help us.

So we now find ourselves in an increasingly digital and connected world where much of our lives can be captured digitally – very diverse types of data on transactions, interactions, movement of people and objects –what we often term as BIG DATA. And as things become connected, through the Internet-of-Things, even more data is being generated.

But again, all this data sits somewhere else owned by different institutions.

And then, as individuals, we become increasingly worried about  privacy, confidentiality, security and trust.

Some of us may get so worried we start to withdraw from becoming too digitally visible, we cancel our Facebook accounts, we stop using google, we don’t want our data stored anywhere because we worry who has what data about us.  Government then takes up this privacy and security issue and could start to regulate, thereby increasing costs. In addition, data starts becoming 'noisy' ie its not true (much like the way I use google search to search for answers on my crossword puzzle so that they wont know if its a genuine search). This means the quality of data goes down. With increasing regulation, decreasing quality of data, this could then lead to institutions become reluctant to invest in innovation and make cool stuff and we don’t get more advanced technologies so this all ends badly for everyone. We get into a downward spiral - Less business opportunities, less innovation, less jobs.

How do we reverse this and help the digital economy spiral upwards?

Introducing the HAT project (….. it’s a Research Councils UK Digital Economy £1.2m funded project with 6 universities, around 20 researchers and a whole host of companies like GlaxoSmithKline, Dyson, DCS Europe…

The HAT takes on the 3 challenges and we’d like to think that we can solve them all but they need to be solved simultaneously to create a upward spiralling effect.

First, about privacy and confidentiality and the ‘shrinking supply’ and 'quality' of data. We are building a human database where the data is owned by individuals, by us. A bit like your email, your HAT, should contain all the data you would like to have to make your life better. That means a place to hold internet of things data from your home, your personal data from social media, your health data etc. etc. If we own our data, we can use it, so that solves all the sharing issues that vertical industries have and if we keep it secure in our trusted environment like we give our money to our bank, it hopefully solves the security and privacy issue. If we owned our data and we treasure it as a digital asset, and it is valuable and useful to us in the way we lead our lives, we would want to generate more of it, basically become more digitally visible but we’ll only to do that if that data is ours and not belonging to someone else. And since we are using the data for ourselves, we will make sure it is as accurate as possible, solving the quality issue.

Second, about the ‘worth’ and ‘value’ of the data. Remember I said that this is still all vertical data and often, a lot of data scientists looking at big data out there are trying to predict us by putting the data on the inside, and the individual on the outside. But making sense from aggregating vertical data is a bit like making sense of snow drift by analysing snow fall. They’re related but not the same. Vertical data needs to be re-organised and transformed in a 'horizontal’ way so that human beings can make better decisions from data. And data can never tell the whole story. It really shouldn’t because human beings interact with our data and we also like to be in control so the human person isn't a passive. we are more like an intelligent and adaptive sensor in a way. the human person can actually perform a service on the data to help in contextualising it to make it meaningful to ourselves and so that we can use it. We don't just want smart things, we want 'smart us'.

So through a service dominant logic we develop a special kind of database. a human schematic database that organises vertical data according to the way we create value with goods and services and use information to live our lives. And we let individuals co-create that database with their own sense making and intelligence. For example, you can have data about temperature in your home from a smart home, temperature in your car by the car company, temperature data from your office building, and the weather data outside and they come from different sources and institutions. but what you really want to know is 'what is the lowest temperature you will encounter today so that you know what to wear?' And to do that you need to acquire all these data into the HAT and then transform it into something useful for your decisions, which is what the HAT can do. So HAT transforms vertical-type data and transform it into horizontal-type data.

What happens next is the fun bit.

When data is meaningful to us, it is not just of VALUE to us, it is now WORTH something,

So the third challenge for the HAT is about creating a market for all this meaningful data. Having all this data to ourselves isn’t going to be useful if we can’t trade it or exchange it and have it surface in the economy so that GDP would grow, wealth and economy would grow and there are more businesses and more jobs, what Economists will call having a multiplier effect. Having all this data is like having money but you hide it under your mattress - it does no one any good. This is where the HAT is also a market platform. Platforms are like meeting places where exchanges can happen e.g. a singles bar is a platform for single men and single women or a bazaar is where buyers and sellers meet to buy and sell. The HAT is not just a database but also a multi-sided market platform for us as individuals to exchange some of our data so that we can maybe buy services like advice on our health, or get some personalised grocery bundles from our diet data. Doing this will create a market for personal data which is important for the future growth of the digital economy but doing it in a way that it fits our lives better, be more democratic with how data is owned and accessed and in general helping institutions tailor what they offer in a way that is scalable.

This is of course not an easy project. We need ethnographers who research into how we use data in our lives, behavioural economists who looks at how our behaviours change, market economists, to understand the incentives on a platform so that both individuals and firms come together to exchange data and products and services, business models, marketing and operations specialists, computer scientists, database programmers, designers for user experiences. The HAT team has all that capability. The best bit is that we are working for both sides – for institutions so that they can give us good advice and personalised products in a way that is scalable, and for us, so that we own a platform to use data better in the way we make decisions.

In summary, the HAT lets you as an individual acquire data,and build your own repository of horizontal and meaningful data that is useful and can help you make decisions (ie contextualisation), and then lets you decide if you want to trade or exchange with firms for discounts or other cool products and services. and when we create a horizontal platform that fit to human lives, we create the next stage of the internet, that of people and things, and an epic collision of all the vertical industry of manufacturing,service and internet companies…and new horizontal-type business and economic models that is human-centric will emerge, and not just the old ways of doing business. That would be just awesome.

Best of all, we think we can bring TRUST back into the digital economy. And we do that by making all of us, who have largely disappeared into words like 'citizens', 'segments', 'big data' into being unique again, paradoxically by becoming making each one of us a 'server' (standardisation) and yet unique with our own data (personalisation). By doing so, we hope to make the use of data more democratic than it is today.

We think that everyone should have a hat of our own data. like the way we have emails or bank accounts. The HAT will be ready in 2015, and we expect it to be free although you can choose your own HAT trusted provider who could differentiate themselves by giving you additional services, like the way your email service, or your bank does. We want to start a revolution to own, control and use our own data, for the good of the economy! So we hope you will follow our blog at and be part of that revolution!

PS: if you are a developer or an institution interested to integrate the HAT into your offerings or develop applications on the HAT, please sign up on our blogsite as well! Software toolkit and APIs will be released from July 2014 in a trade launch and October 2014 will see a HATFest where we expect a week of 'show and tell' sessions of interesting applications around the HAT platform! Consultants helping vertical industries evolve new business models in the horizontal or IoT domain also welcomed!

Monday, 9 December 2013

Service systems group away day

Once a year, I take my team on an 'away' day to discuss the past year, the coming year and do some brainstorming and planning. I thought I'll put down my thoughts on this year's agenda. (We are expecting 18 of us).

This year's agenda is set out in 3 sections

State of knowledge: value, service and business models
Given that there are new members of the team, I'll start with a briefing on the background to the team's approach to knowledge in value, service and business models ie the SDLogic approach. I will do a presentation in this space and then discuss who is doing what interesting research in the space globally. I will divide this space into 4 - thinking (concepts and ideas), tinkering (empirical research), tooling (methods, mechanisms, creations) and telling (publishing, teaching, communicating the research) and talk about which academic teams have 'got' the thinking in SDLogic, those who are still in the old school, the links between service, value and the future of disruptive business models and what knowledge is needed disciplinarily in computing, materials, engineering, business (strategy, Marketing, OBHRM, finance, economics etc.) that has impact on new business/economic models ala SDlogic. I will also discuss where I believe more research/thinking is really needed, integrating what everyone in the team is working on, particularly the doctoral students where "we will watch your career with great interest" #starwarshomage ;) and how the cutting edge work we expect from the doctoral students contributes to knowledge overall. This is of special relevance to the future of incomplete products and integration of personal data to future offerings, IoT markets etc.

State of industry: business models
The next discussion is basically a brain dump from me on all that I see is happening for each industry in terms of their business and economic models - financial services, engineering, telecommunication, education, manufacturing, entertainment/creative - I will discuss their markets and their business models, applying the knowledge we have and where I believe each industry will be looking to innovate, the role of regulation etc. more importantly, I will elaborate on where each industry might be going in a hyper connected IoT era, seen from an SDLogic practice perspective.

State of innovation/investment
I don't usually talk about my entrepreneurial activity in a research meeting but I thought this year I will do it since much of our research is entwined with exploitation. In a year, I usually invest between £50k-£100k of my own money either as an angel investor in startups, or investing in my own ideas/creation. I will talk through the year gone past, what I invested in (and what fruits yielded ;p) and what I look to invest in the coming year and what technological domain and business models I will be watching very closely.

Given all that I have spoken on, I'd like to hear the team's thoughts in terms of skills, capabilities, what areas of research, tools we should be investing in, capacity building etc.

Loads to discuss and I'm looking forward to it!

Sunday, 24 March 2013

From Service Systems to Digital Lives

It has been a long time since I posted any content on this blog (did a few announcements, but no substantial content).

So I thought I should come back to my roots in service systems, service science, value co-creation and explain some of the linkages and how my work is moving on. My students and colleagues constantly say to me 'I don't see you for 2 months and you've moved on'. Some say 'you've left service systems and into technology now' and 'I don't recognise your work anymore'. so I thought its best to articulate my thought processes to show there is method and consistency to this madness they have perceived.

Much of my research in this domain have given me insights into service systems, the boundaries between a material product and a service, the relationship between exchange and experienced value in context.

Service dominant logic suggest that value is always co-created in context of use and experience. Co-creation is not an option (Vargo and Lusch, 2004, 2008).

For a few years, I have repeated that again and again on the lecture circuit. Many nodded. Many agreed. It was a logic, a way of looking at the world and it gave insights and understanding. The problem is, it didn't do much more. And I wanted more.

GD logic is not only very entrenched, it is not helping with a world that is increasingly digital and where business models are being disrupted. GD logic and the firm-centric view of the world was also starting to marginalise individuals in a big way with constant incursions into our privacy, all in the name of stimulating the economy. Data business is worth £50b in the US and we're on this slippery slope starting from 'our data is creating new jobs' onto a full scale marginalization of our rights and our privacy.

SD logic could help, but it hasn't really gone beyond a logic to influence people. At worst, people didn't buy in. At best, people were influenced but didn't know how to put it into action. Part of the challenge is because SD logic stayed largely within the business domain and business schools act only on people (through teaching, professional development, MBAs). What was needed were more methods, systems, tools, stuff that could change processes, infrastructures, outputs and materials, and not just people, into an SD logic mindset. SD logic needs to create a whole new set of tools with a new design and engineering philosophy. It's a bit like when lean thinking was just a logic, a way of thinking, although practiced by Toyota. It was a logic but it didn't stay that way. It spawned methods, certification, tools, performance indicators. The kanban, 5S, value stream mapping; the lean black belt holders, etc. All these created an entire community of champions for that way of thinking. We need that for SD logic because otherwise, it isn't going to change the world. The science of service systems, grounded on value cocreation and taking an SD logic view of the world wasnt going anywhere unless we created better linkages and synthesis to the world of technology, engineering and design. And we need to articulate how an SD logic perspective could or should change what they were currently doing.

Alarmingly, papers within the domain of service science and service systems started to appropriate SD logic to justify some GD logic research, often because they did not really understand SD logic.

Moving things along meant a focus on 2 key aspects. philosophy and methods.

In my mind, an SD logic philosophy is clearly grounded on a sociological and existentialist approach rather than a psychological one. Value cocreation and resource integration is something that exists, and can only be seen, in movements, in verbs and in behaviours i.e. phenomenologically. An SD logic approach is not one that you can run a survey of attitude, behaviours or intentions. The person is embedded in his actions and practices of value creation. The focus on context means the unit of analysis is in the sociology of real life behaviours. A sociological approach makes methods a problem because we've inherited a world where we have created tools from analysing water in a bucket, not by looking at its behaviour in a river.

GD logic is compelling not only because it is entrenched for over 500 years, but also because you could measure its constructs. GDP, sales, revenues, CPI - they are all constructs of a GD logic society. What SD logic needed was better methods and new constructs.

To that end, and rather ironically, I found an ally in digital technology. Here was a world of sensors and actuators with an enthusiastic community looking for novel ways of deploying them into homes and buildings i.e. the internet-of-things. Yes, many of the firms were riding roughshod over privacy issues but could we not turn that into better visibility of behaviours, could we not turn the same technologies used on us into technologies empowering us? So I started to study digital technologies in greater detail, albeit with an SD logic eye, coinciding with my move to WMG at University of Warwick. My background in computer programming and applied physics helped, I suppose, but only to the extent of confidence in learning the material quickly. The field has moved on since the 80s. Recently, Jon Crowcroft, our HAT project partner in Cambridge insisted I read Steven Johnson's book 'Future Perfect' as well as Jaron Lanier's book 'Who owns the future'. Both books grounded on the future of digital technologies, but resonated with SD logic and empowerment.

I also found, as an ally, the thinking around new economic and business models. Here was another strand of literature largely marginalised by mainstream business literature because it was (the way I interpreted it) taking a systemic view of value proposition, value creation and value capture (ie, change one, change all) and the way the organisation had to be agile and transformed for it - which sat very nicely with SD logic. Also, being in the heart of a manufacturing community where pervasive digital technologies were starting to create a set of thinking around 'incomplete products' or personalised (and not customised) products, sat even better with the notion of indirect service, suggested by SD logic. (see a great special issue from Organisation Science by Youngjin on Organising for Innovation in the Digitized World). Customised products are firm centric. Personalised products are customer initiated and empowering. Personalised products also tend to move the product into becoming platforms to afford co-creation, which advanced the notion of symmetry in value co-creation further. Finally, with the advent of platforms, the economics of 2 or multi-sided markets completed my set of theoretical collaborators across economics, business models. manufacturing and technology - aligned to SD logic.

As my research and thinking progressed, I started to think harder into the synthesis between these domains. I found some of the connections to begin with (others could possibly do more) and that synthesis was central in my book 'Value & Worth: Creating New Markets in the Digital Economy' which is now out on Kindle and the printed version by Cambridge University Press out end of the year.

Moving that thinking on, I became convinced that the science of service systems, grounded on SD logic, could not just be a contribution but could create an impact through a carefully designed experiment that could turn the world on its head, empowering the individuals, give us some interesting constructs, methods and measurements in real lives. Thus, together with excellent colleagues in technology and economics, the HAT project was conceptualised. It took some time. We applied to the Leverhulme fund and didn't get the grant and the second outing of the HAT, together with a great team, was funded. I was thrilled. I would highly recommend following the HAT project blog site here. To come to this point was an amazing moment for me and I blogged on the HAT site here. For those who follow SD logic and service science/service systems, you can probably see how it extends the work in the 'background to research'.

I do admit, now having spent years in business, economics, engineering, technology and sociology that I struggle sometimes with the language - Some of my colleagues have accused me of introducing this new 'jargon' that I have developed that is a combination of some 5 disciplines. My approach have been pragmatic - whatever the term or language that persuades you to see the world the way I see it, is what I would use. Not very academic of me (most of my colleagues prefer to argue about definitions). I probably should care, but I don't ;p. Perhaps it might evolve into the jargon of service systems & service science? However, if I know I am speaking to an economist/sociologist/business/technology academic, I would try to use terms in their world -it just makes communicating easier. Inter-disciplinarity comes with a host of interesting issues but I might blog about it some other time.

The HAT project also brought me back into entrepreneurial activity again (a full circle, after being an academic for 15 years) because I didn't just want to create new constructs and methods as an academic, I genuinely want to turn the world inside out, creating an empowered individual and having that balanced and symmetrical view of co-creation and yet create new markets and stimulate the economy. That means the HAT has to move into deployment, becoming a world-wide-HAT so the startup company has to be formed to lead the way. I think I have become Steven Johnson's version of a peer progressive ;)

Watch this space, as well as that of the HAT!

Monday, 11 March 2013

Printed rights of Value & Worth: Creating new Markets in the Digital Economy' acquired

Dear friends, I am most honoured and pleased to inform you that the PRINT version for my e-book 'value and worth: creating new markets in the digital economy' (available at will be acquired exclusively by Cambridge University Press, the oldest printing and publishing house in the world (about CUP here), for all territories and all languages. Paperback and hardback is expected September 2013. I will still retain the electronic rights as I am currently experimenting with knowledge and publishing platform business models. 

I am indeed very honoured that Cambridge University Press has offered for the book to be published as one of their titles. The strong interest this book has had worldwide has reinforced my belief that academic research in service, value and business models should be made more accessible to practice and provide some guidance to an increasingly fragmented and yet connected digital economy. I look forward to seeing the print version soon.

As an aside, I am now in the company of the King James Bible...... if only it will sell just as many ;p

Sunday, 13 January 2013

Release of book: Value & Worth: Creating New Markets in the Digital Economy

The release of my book on Amazon Kindle is finally here! Read all about it at: or

Also, remember to register for new updates on the book and follow the book on twitter at @valueandmarkets

If you have been following this blog and interested in value co-creation, outcome-based contracts, service systems, new business models, new economic models and value, this book brings it all together for the future in understanding digital technologies and the role of value and the customer!

Read the preface of the book (on the websites) to know more!

Thanks to all my twitter followers and to those who follow my research work. I hope you get a lot from it and do feedback your comments on the website!

Wednesday, 31 October 2012

New Economic Models for personal data

Excerpt from the book "Value and Worth: Creating New Markets in the Digital Economy" available in January 2013

Link to book at


New Economic Models for personal data

As the digital age progresses further, more of ourselves can now be potentially commodified. I say potentially, because it depends on the firm’s ability to do so. For practices that are measurably visible and direct such as mouse clicks, button presses, it's commodification potential is obvious. Companies like google or Facebook have sophisticated algorithms to calculate how much a recommendation, a share or a like could translate to creating worth to advertisers. However, since digital connectivity also allows us to interact, we are now digitally more visible – we vote, pay, applaud, and commodification of such practices are much more a challenge. With greater digitisation into the contexts of home and buildings, the digital self in future could be seen more transparently through how we create value within digital contexts i.e. the visibility of elements (nouns), system (verbs), structures (rules), agency, affordance and outcomes in contexts (see chapter 4). We already generate much personal data through our financial transactions, tax records, health behaviours and online interactions. There is a growing concern over our ability to control what information we reveal about ourselves over the Internet, and who can access that information. The US Federal Trade Commission has provided a set of guidelines on widely-accepted concepts concerning fair information practices in electronic exchanges called the Fair Information Practice Principles. The problems is that treating data according to what is ‚good practice’ doesn’t reduce individuals reservations about its collection and use. It breeds a culture of mistrust especially when so much of what we need to do digitally results in signing ‚informed consent’ about what firms could do with our data, documents that we cannot humanly and cognitively process in terms of its implication. In addition, injustice may arise because individuals could buy and use digital offerings under conditions of inequality or necessity which suggest that such practrices are coercive, prompted by the necessities of his situation.

How should we understand our personal data in terms of privacy, vulnerability and security for ourselves on one hand and while we wish to have firms create new offerings to serve us in context on the other? How should we think of personal data as protecting us while at the same time creating new markets?

These are the conditions we often face today for online personal data privacy.

We withhold our consent for personal data to be used because we get nothing in return.
We do not wish to participate in online digital activities for fear of being digitally visible as we do not know who holds our data and what they would do with it.
The firm refuses to compensate for use of personal data because it does not know yet what worth (new offerings) could be created.
The firm owns part of our data and could do with it what they wish, as long as they anonymise it. But they cannot share it with another party so there is limited understanding of the data.

One way of thinking about personal data is start from the position that its ownership is our digital labour. Thus, by allowing it to be owned by someone else such as a firm is allowing for its exploitation, regardless of how the firm anonymises it. This does not mean that firms cannot be allowed access, merely that as a point of principle, the information has to be owned by individuals and firms only give the right to access it. The reason this principle should exist is that personal data could then be seen as our labour for commodification just as the way we see our real work in life as labour for commodification.  This creates a market for digital labour of which firms could ‚buy’ and compensate individuals for. Continuing the logic, digital labour i.e. visible practices on line would then become an asset to individuals. By doing so, individuals may not be so restrained in their digital practices, since its a reduction of their assets, but may be more discerning on whom they could share them with, thereby sharing only when there is benefit to themselves. Firms could offer contextual digital offerings based on these assets they can view and compensate accordingly, to the individual as both digital labourer and as customer. Currently, our compensation for personal data is often what is commonly known as 'a free lunch'. So we may get back coupons, discounts, freebies from the commodification of our practices. By liberating personal data into a format where we could store and be accessible to firms, a market for prosumerism exchanges is created where individual choices can be respected even while markets can be created with new business models for compensation and experience.

This could be a solution because the current personal data held by several insitutions is often not shareable under data privacy acts. Thus different firms hold data that is partial, with visibility that is incomplete. This results in digital labour becoming less valuable to firms and commodification becomes a challenge since firms do not yet know how to create worth from digital labour. Access to a more complete visibility of the customer with suitable compensation to digital labour will create better offerings for individuals allow choice, and could stimulate market creation under conditions of fairness and consent.

Personal data may therefore be seen to be not just a privacy or legal issue but that about market exchanges of rights and the external effects that could be obtained from the creation of such a market. Our consent is not merely an ethical dilemma. It is a right not to 'work' and a right therefore not to be digitally visible, but if we decide to be visible we could be rewarded for that just as labour is compensated through work. When a market of personal data generation and use is created, individuals may be more willing to do digital work as a result, or at least, allow for their data to be visible and accessible. By doing so, they are accumulating a potential resource for a commodification opportunity, with the firm playing the role of developing its capability to create worth from that commodification. Without such a market, individuals may withhold consent and firms, being unable to create worth from partial personal data will not pay for it. With no incentive for participation, what economists would term as market failure results. While firms today talk about ‚big data’, data will get even bigger with greater connectivity and the internet-of-things. Fundamentally allowing firms to aggregate data so that they can serve the population through new services while recognising the rights of those who generate the data is the way forward. We will all benefit from better traffic information if we allow our individual travel data to be collected, aggregated and served back to help us with our travel plans but conversations around big data must recognise both the business and service generation from big data as well as the rights of the data generators who contribute their digital labour and a free market to allow more of this to happen is crucial.

When the economy is based on an exchange of ownership, we create unlimited value (or not) from what we buy. Traditional exchange economy for goods gave little visibility to value creation, especially for things. The economic system only measures worth and not the value created. As firms wish to appropriate more revenues from value creation and change their business models particularly in the digital economy, they may give up the ownership model, and instead, look to business models that derive revenues from use or experience e.g. Power by the hour. By not creating worth from value creating activities, the firm opens itself up to other ways of creating worth. Understanding personal data and how digital activities create value in context becomes a stimulus for new business models and new innovative offerings.


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