taking your data business through the raw data transition barrier

Inhibited Views

If you go up to the Peak in Hong Kong what should be one of the World’s greatest views is tarnished by a beige coloured stain that sits right across the sky at about 1,000 feet. It exists as a sort of a transition barrier between the polluted streets of Hong Kong and the clear sky above.

In many ways data businesses face their own, yet unseen, transition barriers, the one where their core raw data products and services essentially reach saturation point in the markets they serve. The thing about the raw data is that while on its own it has value, when it is put to work it has greater value because of what can be done with it to create indicators for making informed decisions.

The exchanges provide the best examples of the challenges this dilemma represents, though all data sources at some point need to break through this barrier. Their markets are surprisingly limited, focused almost exclusively on financial professionals at institutions and market data vendors who supply information. To further develop their data businesses some exchanges are moving higher up the data chain.

Breaking Conventions

Traditionally exchanges managed to expand their revenue footprint by;

  • introducing new charges for data usage, such as fees for non-display, derived data, and index creation
  • adding new datasets
  • splitting up old datasets into separate products
  • relying on audits to discover and bill for non-compliant/unlicenced data usage

Then comes the point in time this strategy adds little more than incremental value to the business while still remaining under the transition barrier.

Yet many exchanges are perfectly content with inertia and maintaining the status quo because that is the easy option, unlike the more progressive exchanges which are developing innovative approaches to breaking through the transition barrier. Once beyond they discover new horizons which are more profitable, larger and wider.

The first problem these progressive exchanges overcame was knowing that the transition barrier exists, though naturally this is not what they would have called it. The first question they asked themselves was “What do we do next?”, and the second was “What resources are available to do the next thing?”

Inevitably the second question gets answered first. For all exchanges taking the next steps means looking in the mirror, then realising what can be done in-house is nearly always limited either by lack of expertise or simply not enough people. Then there is the question of having the monies to put new strategies in practice.

Above the Beige Stain

Unsurprisingly the larger the financial markets, the more revenue they produce for data which then gets put to ever more sophisticated use. Both of these factors have driven why specific exchanges have moved beyond their peers. It is no accident that in these clear skies we find CBOE, Deutsche Börse, ICE/NYSE, the London Stock Exchange Group, NASDAQ, and are now being joined by mid-tier exchanges like the ASX, SGX and TMX.   

The approaches these exchanges take once through the transition barrier have tended to be acquisitive because it is far easier, as well as more cost effective, to buy in expertise, complete with an incumbent client base, than re-invent the wheel. Again, this is a strategy common across the data business world.  

What this is all about is adding value to the data, making it more than it already is. For exchanges this allows them to break out from the constraints of their own individual services to offer products relevant to all other exchanges as well. This means the data chain starts vertically and can then diverge in different directions including horizontally.

Adding Value to Data and Turning Data into More Dollars

The strategies the progressive exchanges have pursued are all inter-related and revolve around value added services, i.e. data that can be charged at a premium. As stated the preferred mantra is to ‘Buy Not Build’.

What are the exchanges doing?

  • Analytics. This is the entry level strategy. CBOE, DBAG, ICE, LSEG and NASDAQ have each aggressively targeted offering analytical services covering trading, investment decision tools, risk management, and solutions right across the trading life cycle. Albeit with varying success. For exchanges slow to the party, offering analytical services is the easiest and cheapest option for transitioning from a raw data business.
  • Indices and Benchmarks. LSE though FTSE has expanded rapidly over the last 10 years buying Russells, Mergent (for analytics) and a host of smaller specialists. DBAG has adopted a similar strategy through STOXX, and both NASDAQ and NYSE offer widely followed indices. SGX has also joined the fray through acquiring Scientific Beta. Indices are very high margin, incredibly sticky and provide a strong platform for developing financial products as well.
  • Buying Data Vendors/Aggregators. Not the most popular strategy but one that stands out for the size of the deals, first ICE purchasing InterActive Data for $5 Billion, then LSEG taking over Refinitiv in a blockbuster $27 Billion deal. ICE has made a success of its target, the jury is likely to take time on LSEG/Refinitiv. SIX Group is unique in starting up a data vendor inhouse. However future opportunities look limited for this strategic approach.
  • Creating Data Malls. This might appear an odd one, in that it is not obvious that it adds value to data, yet they do by creating access to specific datasets that are highly valuable but would be otherwise hard to access. Unfortunately, with the exception of ASX, it is not clear exchanges realise the opportunities Data Malls present. What is unique about ASX’s Datasphere is that is not only a business in its own right, it fills a gap in the market by making available market information not normally available then blending with analytical tools

Each of these strategies is all about adding value to raw data.

Not Interested in Breaking the Transition Barrier?

Exchanges that miss these important links will find out later, and to their cost, that other exchanges will be offering important services to their own clients right inside their home markets, effectively locking them out from building up their own data businesses. The warning signs are already there.

Summary, Sputniks & The Next Transition Barriers

If we go back to the original analogy of an atmospheric transition level in Hong Kong, where does the next barrier lie? Simple it is the atmosphere itself with space beyond. For the exchanges their Earth is Capital Markets and the financial institutions that trade on them, above that Troposphere resides Wealth Management and FinTech, beyond the Exosphere lies a lot of space in digital media and the retail market.

These are the opportunities awaiting the barriers to be breached.    

However, the exchanges themselves are not yet prepared for journeys so far out, their business models, pricing structures, IP and licences are not fit for these purposes, but it is not hard to see which exchanges are likely to launch their Sputniks first.   

In the meantime the more progressive exchanges will continue to invest in and develop their value added strategies which will increasingly support, and supplant in revenue terms, their core trading venue businesses.

Keiren Harris 13/05/2021

www.datacompliancellc.com

Please email knharris@marketdata.guru for a pdf or information about out consulting services

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