Data, business & the economy 1: The modern factory is a data factory

     Economics = Land, Labour, Capital               [foundation of economics]

                  Economics = Land, Labour, Capital, Data      [...in the information age?]

Data has value; that we know from the exploits of new economy firms Google, Facebook, Baidu et al.

Such startups, primarily data firms (revenue derived from data), are increasing in numbers.

And with machine learning conventional firms are increasing the role of data in their business.  They now see value in data, once discarded from their daily operations.

This is the beginning.

As society digitises, more data will be tapped and monetised to benefit businesses, governments, citizens.  The latter in ways that is unthinkable a decade ago, even now!

What will industry look like as the data economy enters mainstream?  What is the effect on society? Will the suppliers, we, be compensated if data as The Economist suggest is the most valuable resource?  Will governments offer up their massive data (privacy contained and managed) - now sitting fallow, for a fee?  Can this compensate for the tax we pay?  This post ponders.

Once superfluous, data is becoming important for business in the information age

Alibaba rose with a business model that unlike traditional retailers holds no stocks.  Instead it hosts a digital platform for sellers to list their products.  That is, Alibaba makes money by providing data for buyers and sellers to transact.   The foundation of Alibaba business is data.  Likewise, AirBnB’s and Grab’s revenue derives from data, not physical assets.

Most internet startups are either based on data or data forms a crucial part of their business.  This is similar to the early stage of the industrial revolution.  Just as the new firms (Ford, US Steel, Standard Oil, JP Morgan) then created businesses around commodities such as oil, steel and industrial machines, this one is on data, computers and the internet (Uber, Google, Facebook, Ant Financial).

And while there have always been firms profiting from data, it was never at this scale.  The way data is collected is different too.  Unlike the labouring of traditional data firms, these next-gen firms employ crowdsourcing (a method to source from the crowd, individuals, to participate in an activity, paid or unpaid, but of mutual benefit, over the internet (see crowdsourcing; a tool for business), us, largely based on day-to-day usage of services, itself unusual.

Is data or rather the revaluation of data pointing to new dynamics in the economy?

One effect of data on industry – see Datarisation and its transformative impact on industries

Anything that can be digitised, turned into data – products (music, books, software, media), services (voice phone calls, recruitment, photography, computing), transactions (money) -  and delivered over the internet will have its value reduced, some to zero, transforming industry…messaging apps (telephony and telcos), Amazon (books and retailing), Uber (transportation and taxis), Paypal (money and finance industry), Netflix/YouTube/Spotify (video/music and movie industry).

If your industry involves products that can be digitised, it’s a candidate for transformation.

Yes. 

We have bandied the term ‘information age’ about for decades, but never quite figured out what it all means.  We now have an instance, data has value.  It affects the way business is done.

The modern factory is a data factory

The process is similar to the factories we are familiar with.  Instead of raw materials as input and workers turning them into physical products, these new forms of factories take as input data produced from the usage of services (and other sources) using computers to ‘manufacture’ informational and quasi-informational products.  These ‘finished products’ – specific, tailored information are used to support the sales of ads. They also add value to physical products or to services or to businesses while nuggets of information, refined data and data itself have a market.

The difference is that instead of a factory, this modern version is a digital platform.  Instead of miners, consumers produce the raw material.  Instead of the assembly line, networks of computers use analytics, machine learning and AI to assemble insights of information. 

This suggests that a new form of production is emerging just as moving assembly lines did in the industrial one. 

Prof. Yochai Benkler of Yale in his treatise “Coase's Penguin, or Linux and the Nature of

the Firm” suggest a new resource in the production of goods and services through the open source model” …he is referring to a form of crowdsourcing.  With the open source model, participants from all walks of life partake, out of interest, on a project, be it software, an encyclopaedia (Wikipedia) or even shoe designs.  See Open source business model

This also suggests that personal effort, personal data has value.

In the second post here, we ask if the ‘miners’ that is you and I, should be paid and if this solves the issue of personal data privacy.  Further, we’ll argue that governments could monetise the data throve they have, using the proceeds to benefit society, perhaps reduce tax.

Data, business & the economy 2: Should the ‘miners’, that is you and I be paid?

In the prior first part here the value of data is explored, suggesting that the modern factory is a data factory.

Should the ‘miners’, that is you and I be paid?

There are undercurrents.

Jaron Lanier first wrote about payments in his 2013 book, Who owns the future? suggesting that we get paid for the data we provide.  The rationale was that data tech firms treat data as material, which comes to them at no cost. 

Governments have started considering ownership of data, “Ownership of personal data underpins these issues, which is why debates on introducing the concept of ownership of data as a legal right have recently emerged at the EU level and beyond. In 2017, issues concerning ownership of data occupied regulators’ minds in the United Kingdom, Australia, India, as well as the European Union.”…..regulation is probably the only way the data firms could lose control of the data they make their money, if,… and obviously huge battles lies ahead with this approach.  A more amenable way is for the firm to share ownership with the ‘miners’.  Or an indirect way is for the data firm to allow the user to make available his data to, say, insurance firms, so his premiums are lowered.

Berners-Lee of W3C, a consortium that determines Web technology standards, launched in 2018 a development platform called "Solid" aimed at giving users control of their data.

Judging from their high-profit margins, there may be a case. 

And, I think, inevitable that some payments would be made to the ‘miners’ when society adjusts to the new economy, in the form of tokens (exchange for services), or what I call nanopay, tiny amount, say, 0.01 cent or fractions of a cryptocurrency.  Tiny, because consumer’s data in isolation has little value, aggregated it has.

Payment solves the issue of ownership of data and privacy.  If ‘miners’ choose to monetise all or some of it, privacy becomes a non-issue since now they make the decision.  Laws should, however, be enacted to protect the minors and regulations against unscrupulous use of data.

“The majority of people between 18 and 34 would be willing to let insurance companies dig through their digital data from social media to health devices if it meant lowering their premiums, a survey shows. – june ’18

Data related to insurance could be in their personal data wallets that should include compartment for the car (how they drive), health, data from usage of online services, and so on.

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If so, data wallets aplenty

If personal data has value, we will need somewhere to store it.

Data wallet is a contender.

Beginning with basic data such as sites visited, over time this wallet could store our buying habits, usage data, online behaviour and meta-data.

The consumer can then use it to trade for services eg. bus ride (an instance in the US), make a purchase, reduce insurance fees or watch a paid YouTube channel.  It’s bartering all over again, re-imagined and likely through an online exchange.

A retailer may want to be in that exchange to sell, perhaps at a discount, for consumers’ data.  Or pay consumers access to their data for insights.

Data analytics firms will compete to process personal data; for a fee, a digital token, an exchange or even pro bono.  Processed data adds value to the owner.  They will aggregate data from selected consumers based on clients’ requirements.

Privacy, data, ownership & nano-payments

Is there conflict with the digital model of monetising consumer data exchanging it for using a service? The Cambridge Analytica case where Facebook provided the data implies yes.  But that is a case of abuse.  It’s clear now that personal data should not be sloshed about. After the storm settles an appropriate model will result together with new laws.

Will the service providers stop providing free service? Unlikely because they depend on consumer data in the first place.  What’s more likely is a compromise.

Considering the massive profitability of such firms, there could be space to share it with consumers through nano-payments.  The fines being imposed by EU and others to follow could be the starting point to determine the value.

The issue of privacy vanishes if it is the consumer who decides.  Obviously like money, there should be regulations and a legal framework to protect against the unscrupulous.

If this scenario pans out, we determine if we want to share our data.  We determine our own privacy or more specifically the level of privacy and how it is shared; all, some or specific forms for a price.  It recognises that data has value.

Businesses will have their own wallets and similarly used for trade and for leasing.  Perhaps even the government.

And what of governments?

Governments have a lot of data. 

In an era where data has value, would it be allowed to lie fallow in their data vaults?

This data can benefit society.  And businesses, for which they will pay for.

Government data does not have to be released raw to the buyer.  Instead, they could be processed in-house.  Only the results are provided.  Other ways are to supply anonymized data or partially processed data, stripped of consumer names.

Monetised, the government will now have a new source of revenue, businesses get insights to better their businesses, the tax burden on citizens perhaps reduced.

In this scenario, probably shocking to some officials only because it’s radical presently actually benefits the economy and in particular the citizens.  Patient data from government hospitals can help produce better medicine or lower insurance prices.  Municipal data can reduce crime.

However, governments cannot simply provide data but what if this is treated like a municipal license, say, an annual license to access specific slivers of anonymised data under specific terms?  Obviously, privacy must be respected but there are ways to handle this as discussed earlier.  Data regulations and a legal framework should also be in place.

In a digital economy, it would be a waste if data is left idle when it could be optimised to benefit the country.  As economists say, money needs to move around to improve the economy.  If data now has monetary value, wouldn’t this apply?  It should, so the first data regulation, on sovereignty is puzzling.

In the concluding post here, we ask if businesses could monetise their data besides using them to improve business.  And what could the data ecosystem look like as it grows from its beginnings today.

Data, business & the economy 3: What can businesses take from this?

In the first part here the value of data is explored, suggesting that the modern factory is a data factory

The second here suggests that the ‘data miners’ that is you and I, should be paid and this could solve the issue of personal data privacy.  Further it argues that governments could monetise the data throve they have, using the proceeds to benefit society, perhaps reduce tax.

Data sovereignty at odds with the digital global economy?

Data sovereignty, to me, was incongruous when governments first raised the issue.

If data has economic value and is the basis of the digital economy, shouldn’t the principle of ‘free trade, free movement of goods’ apply as global economic activity digitises?  In this case cross-border data flow.  Data sovereignty impedes the flow.

Pharmaceuticals could improve its R&D if they have easier access to consumer data globally.  Global firms that advertise online would benefit from consumer data worldwide.  Banks aiming to take advantage of digitisation to offer services globally and fintech firms are affected if they cannot access customer data in another country quickly.  Data sovereignty hinders.

Perhaps when data sovereignty first appeared bureaucrats were not cognizant of the emerging digital economy.  Or they were distracted by the major data leaks.

The internet is borderless.  That’s how internet business models and digital commerce operate, on the borderless premise.  Restricting the flow of data will be detrimental to digital commerce.  Data leaks are related to data storage.  Security is really a separate issue.

With the digital economy gaining significance I expect the notion of data sovereignty to be diluted, with strict regulations applied only to data with national security implications and a light touch to the rest.  Processed anonymised data should have freedom. Permissioned data should too.  The exception is geopolitics.

Data commerce and data ecosystem

As the value of data increases an ecosystem will revolve around it.

Data, by then permissioned and regulated will be traded, by businesses, consumers, government entities and with that the data ecosystem enlarges:

• Data exchanges, marketplaces and a futures market allow buyers, suppliers and brokers to lease, supply, process and trade data.  Data could be anonymised, raw, categorised, packaged.  They will be stored in secure data vaults, some offline.
• A pharmaceutical firm may lease data from a specialist heart centre to identify traits to improve their R&D into drugs for treating heart diseases.  But they may utilise a broker to package data from 10 heart centres around the world instead.  Data brokers could source them directly or from the exchanges instead.  Transactions would be done on blockchain-based platforms.
• Face recognition tools are available from a cloud provider today.  Projecting this into the near future, myriads of data analytical cloud services could allow anyone including the pharmaceutical firm to use specialised tools instead of having an expensive in-house team.
• Because in isolation, consumer data has no value, platforms will emerge to serve as aggregators.  Consumers would upload their data wallets into their secure data vaults.  These sites would have the tools to analyse consumer data.  Independent data analytics firms can draw specific insights, adding value to the consumers.
• Data consultants will know what’s available in the market.  They could also to help companies craft data plans. 
• New career categories will emerge: data managers, data architects, chief data officer, data consultants, data brokers, data salespersons, community managers, data regulators

What can businesses take from this?

Data adds value; from insights to improve business operations from its day-to-day operations to direct monetisation.

Much of the focus today is on analytics, machine learning and AI to derive the insights.  But what if data is looked upon also as a revenue source?

Like the digital data firms today.  Facebook’s service generates data for monetisation and also for partners.

Obviously after the Cambridge Analytica fiasco, passing user data to partners is controversial but perhaps it is a growing up experience.  With regulations, proper procedures in place and allowing only specific forms of data such as permissioned data or anonymised data and only to qualified partners, society can benefit.  Such as better medicines.  Users could take a small share of that revenue.

Conventional firms can do the same, in a different way.  Here is one.

If you could listen to a group of customers and consumers chat freely about a product, wouldn’t that information be useful to a business selling that product?  If it is about features they like, wouldn’t that take the guesswork out of the new version of the product?  Involving customers is akin to designing a product the consumer wants.

This example uses a community model.  It’s similar to Facebook platform engaging consumers.

This method, largely bypassed by businesses but evident with startups, can if applied properly, bring valuable data from customers.  And in many cases, you don’t need the complexity of data analytics.  The crowd provides the insights.

Create a digital community, say, of off-road motorcycle enthusiasts around your brand.  Participate and listen in to their conversations.  From time to time, introduce a topic.  If it is on ‘useful add-ons’, the bikers will bring up what they like.  That’s input to the product division.  Unlike surveys or study groups, where the participants may feel compelled, the community model provides a natural setting and a better flow of authentic ideas.  Do this in a transparent manner, so they know what is going on.

How the community manager engages the community, in particular, the topics introduced, determines the type of data generated.

Industry would find such data useful.  They would be willing to pay for it.  So besides using the data internally, they could lease this data (note that this is processed data so there’s no personal information) but don’t forget to reward those contributing ideas.

Data, the digital economy and economics

I’m no economist but data, I’ve noticed in my years studying the digital economy, is not valued economically and neither are its impact (and digital models’ impact) on economic measures such as GDP and productivity appropriately reflected.

Should they?

Consider the following:

• The primary assets of most online firms are now data
• Data is now being deliberately collected as input to businesses, like raw material
• Online firms have a significantly lower number of workers relative to traditional ones
• The open source mechanism replaces internal manpower with external ones
• The sharing economy demonstrate more efficient allocation of resources
• We are witnessing the data industry as a new sector in the economy  

They are a new form of inputs in the production of services and goods, new forms of production, all made possibly through the internet, digital technology and mechanisms of the digital economy.  A common factor in these, crowdsourcing (see crowdsourcing; a tool for business), enabled by the same, has redefined the role of the consumer – once consumer only consumes, now they also produce.  And in doing so, created value in data and introduced a new form of economic production. 

Conclusions

Data now has value.  With that data ownership will move back towards the creator, including the consumers.  Online firms that depend on consumer data will remunerate the consumers for the data.

The socio-economy will alter; with new form of wages and a corresponding change in the tax code while the concept of jobs is redefined.

Finally, would the foundation of economics be adjusted, in the information age?

  Economics = Land, Labour, Capital    [foundation of economics, formulated in the industrial age]

  Economics = Land, Labour, Capital, Data                                       […and in the information age]

I think so.

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