Sunday, 30 June 2019

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. 


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.

Thanks for coming this far in the article and be sure to leave your comments.

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