What's In A Name?

There is an article in the current edition of The Economist (Baby Names, Thanks Mum) which explores the different rules around the world for baby names. For example, it is illegal to call your child "*" in New Zealand. Using names that suggest rank is also banned in NZ - so perhaps "My Name is Earl" is not broadcast there.

More interestingly, there is evidence that people called George are more likely to become Geologists, while a Dennis is more likely than most to become a Dentist.

Since many of our names derive from our real or hoped-for activities (surnames often reflect profession or trade) while given names are often encouragements to virtue or success - for example "Patience Potter".

I've long wondered the extent to which names are destiny - in other words whether causation flows from the name to the nature rather than the other way round. Are people called Patience really more patient? Would that which we call a Rose by any other name smell as sweet?

I think HR departments may have some explaining to do here. The British military spokesman in former Yugoslavia in the 1990s was a Colonel Coward. He was replaced by a Colonel Chicken - was this pure coincidence? I once visited a Royal Navy ship whose captain was called Commander Thicknesse. He was replaced by Commander Bone ("bone" is military slang for "stupid").

And do people with problematic surnames suffer in the marketplace - both professionally and personally? Is Miss Hoare more likely to marry hastily and Mr Snodgrass more likely to remain a batchelor? Is Master D'eath drawn irresistably towards medicine?

Do you have any experience of nominal determinism? If so please share!

Creating value from data - secrecy, invention and layering

I once knew a vital national security secret for a period of 10 minutes.  I could have sold that secret for a high price during its 10 minutes of importance.  I didn't.  Moments later, the information was no longer vital or secret - and it flowed into the public awareness barely remarked.

Recently I've been studying the ways a number of organisations use data to create value, and I identify 3 broad approaches: secrecy, invention and layering.  My interest is in helping organisations build sustainable value positions, so here I briefly consider the pros and cons of these approaches and how they inform business development.


Secrecy - creating value by trading data

Trading state secrets is tricky, since the market is very imperfect.  Counterparties are unreliable, transaction costs are high and the market is hard to predict.  Quality is notoriously variable and verification difficult.  Penalties are high.  As a result, it's best avoided unless you have deep pockets, ideological convictions, and ideally, a state sponsor.

Commercial, technical and personal secrets also have the potential to command a great premium in the right market - but making and sustaining these markets is tricky.  Networking and transaction costs remain high since security must be tight to protect sources, but the real or perceived value of the information may make these costs acceptable.

The whiff of Martini and intrigue can help canny participants to increase the premiums paid, but trading on secrecy of this kind is ultimately a niche activity since volumes are small, relationships expensive to maintain and pipelines hard to predict.  Most worryingly, secret information can lose its value at any time.  To build sustainable value the information must be protected.


Invention - creating value by creating data

Inventors get to harvest the sustainable value of their information by securing intellectual property rights.  Of course this is only an option for those who can demonstrate that they are the creators or developers who have added a distinct definable intellectual asset.  Once protection is in place then depending on the quality of the asset, it can be developed and delivered.

While this is the basis of many a successful sustainable enterprise, it depends on the creation of proprietary intellectual property.  If you don't have any on the drawing board, you can still create sustainable value from data in other ways.


Layering - creating value by comparing data

The quantity of freely or very cheaply available data continues to grow geometrically, and without the Research and Development costs of invention, or the transaction and protection costs of secret information, it can provide a versatile feedstock for value creation.  It is often a simple task to create value by adding information from different sources, or to discover correlations in unexpected places.

Free information - for example from a mapping service like Google Maps - can be supplemented by time-sensitive information - traffic, weather, fuel price etc, to create premium packages that retain their value but have low marginal costs.

Services like Wonga illustrate the benefits of analysis and iterative learning.  By gathering client data, cross-referring against socio-demographic profiles and credit data it's possible to identify profitable market segments (in Wonga's case for short term loans) which previously went unserved.

At Bmycharity we found correlations in our data that gave insights into donor and consumer behaviour that reached far beyond charitable giving - and guided our strategy as we set out to disrupt the commission-pricing model of the online fundraising market.

Now, with the development of ever-more powerful analytical tools like Hilbert and ever-larger data sets, The Economist notes that some organisations are embarking on ambitious efforts to identify a wide spectrum of targets, from valuable social influencers, to fraudsters and terrorists.

Creating value by layering and analysing data offers the prospect both of sustainable value creation and a ready stock of raw materials.  With the continuous improvement of analytical tools available, this part of the market for creating value from data will grow and grow.