THE INVISIBLE MARKET DATA REVOLUTION The New Age of Data

When Chou En-Lai was asked “What were the historical effects of the French Revolution?” he cryptically responded, “It is too early to tell”. At the beginning of 1789 the Ancien Régime had no inkling of the revolutionary tsunami that was going to sweep not only them, but pre-industrial society into oblivion.

Today we are living in the age of data, which, like it or not, we are all a part of, and is leading us almost blindly to a quietly misunderstood transformation of society, businesses and interaction. Businesses either adapt, or face a Bourbon fate. Talleyrand’s claim they “Had learned nothing, and forgotten nothing” can easily be applied to companies today trying unsuccessfully to avoid the invisible data revolution happening all around us. 

Every company, every person is a data creator as well as being a data consumer in the digital world. The ability to identify, access, then analyse the right data gives immediate advantages in terms of making money, business, politics and works to influence market sentiment, which then translates into commercial activity .

Many businesses, including financial institutions, fail to realise they need to understand and then assess:

1. What data is available for utilisation from internal resources,

2. What data is missing, and therefore must be sourced externally

3. Identify who has the data required, and whether, or not, that source will make the data available

4. Negotiate a licence deal to access and use that data (IP is a huge deal), and,

5. Have the right tools to analyse the data once it is inhouse

Sounds straightforward, but like many other things that appear simple superficially hides the devil of detail, so this presentation analyses what to look out for in revolutionary times.

With revolution, comes discovery. Linear progression once based on the now broken cycle of data production and consumption leading to technical innovation resulting in ever more data creation, now replaced by multi-directional relationships working within common but discreet environments as internal and external data consumers connect more.

Financial institutions must adopt smarter sourcing strategies, while becoming more adaptable with their technology requirements.

Greater number of choices brings increased flexibility (theoretically).

It changes the investment decision dynamic. Different businesses have dissimilar requirements creating the need to trade-off alternative options.

Strategies become fluid as multiple paths open up before them, though each will have their own unique business and cost benefits.

This creates a stimulant to competitiveness forcing businesses to differentiate themselves on the relative strength of their data strategies.

2 comments

  1. Great article, like always, Keiren, to which I would add, that technology is key to be able to process, analyse and permission data IPs safely.

    One big problem regarding data actually is that “the transport is easy”, but with the ever growing importance of data and protection of IPs easy transport becomes a problem as data gets everywhere easily but unprotected.

    Another problem is that once transport and Permissioning is in place data has to be delivered “just in time” and “selectively filtered” so that systems do not get overloaded with data that is not wanted but “filling up the pipes”.

    Technology is key to safe, controlled, filtered and convenient data transport and it becomes more obvious the more and the faster data is sent on a regular basis.

    1. Thanks Mauricio. Good points:

      1. While data and tech are symbiotic, data needs tech as an enabler, and tech needs a purpose which data provides they are two different things. Businesses need to work that out. It is at the intersection point that things get blurred, and the need for IP based control, monitoring and reporting becomes not just nice to have but absolutely essential

      2. Overload is an understated problem. The universal aggregators (Bloomberg and Refinitiv) are drowning their clients in data. One bank told me they have a data wastage rate of 40%. I think this is going to change the emphasis towards a wider range of specialist data sources, or are going to need lightweight tech with IP related functionality built in

      It is worth the discussion, and education,

      Stay safe
      Keiren

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