7 years, 11 months ago

Anti-clients, kurtosis-risks and public riots

Link: http://weblog.tomgraves.org/index.php/2011/08/10/anticlients-kurtosis-risk-and-rioting/

In quite a few of my posts on enterprise-architecture, you may have seen two unfamiliar terms: anti-client, and kurtosis-risk. To see these two concepts in real-world action, and to get some understanding of how important they are in enterprise-architecture practice, you need look no further than the rioting that’s been taking place in London and elsewhere in Britain in the past few days.

First, though, an essential read to set the scene: Don Tapscott’s article “The World’s Unemployed Youth: Revolution In The Air?” (Note that that article was posted on the Huffington site on 4 June 2011 – more than two months before the riots began.)

An anti-client is someone who in some ways shares the same extended-enterprise as the organisation in scope for an enterprise-architecture – the same space as any of the organisation’s clients. But unlike a non-client, who is in the same conceptual ‘enterprise space’ as the organisation’s clients but has no interaction with the organisation, an anti-client will actively oppose, reject or object to the organisation’s presence in that extended-enterprise. Many businesses will have ‘inherent’ anti-clients: environmentalists in relation to oil-companies or miners, for example. And far too many organisations create their own anti-clients, converting previous good clients into active ‘enemies’ – anti-clients – through poor service, misleading contracts and all manner of other minor dishonesties and ‘game-plays’ that are all too common in the business context and elsewhere.

A key point here is that in ‘the good old days’ of broadcast one-to-many media, when companies all but controlled all access to the airwaves or the press, an organisation’s anti-clients had so little leverage that the organisations could usually afford to ignore them. Some careful PR would keep everything ‘on message’ without too much effort, or cost. But when the internet, SMS and other media allow many-to-many communication, or even many-to-one, organisations find themselves in a radically different game, where there’s no possibility of ‘controlling the message’ – and where even a single aggrieved anti-client can cause huge reputational and other damage with one well-placed viral video. Suddenly, an organisation’s anti-clients can have more power than the organisation itself – a very significant point…

A kurtosis-risk is a risk in which the losses that eventuate from the realisation of the risk exceed the total apparent gains made by ignoring the risk. (It’s sometimes called ‘long-tail risk’ because it’s a risk analogue of ‘long-tail‘ opportunities.) The important point about kurtosis is that it is usually a knowable or identifiable risk: it’s not an ‘unpredictable’, but one whose risk-pattern can be identified within the drivers for the statistical distribution of risk.

The risks from poor customer-service represent an all too common example of a kurtosis-risk: there’s no way to predict which incident will cause a massive blow-up, but we can predict that poor-quality customer-service will lead to a blow-up at some point. And we can also predict the statistical distribution of the scale of the risk in much the same way. And for organisations, one of the key drivers for the scale of risk – in other words, the positioning of the risk on the long-tail, and also the likely loss when the risk eventuates – is the separation between and effective power (or lack of it) of the agents of risk, such as disgruntled (ex)-customers. Separation between agents of risk is a risk-divisor: when separation is high, the effective risk is reduced, or pushed further down the long-tail (but never actually disappears). Separation is at its greatest – and hence risk is at its lowest – when the organisation controls one-to-many broadcast; or, to put it the other way round, the risk-multiplier increases, and the risk moves ‘up’ the long-tail, with increasing availability of many-to-many communication.

So, if we put the two together, anything that risks creating anti-clients, in a context where the media balance shifts from one-to-many (broadcast) to many-to-many (peer-to-peer), represents a context in which the risks are increasingly likely to be unacceptably high. They can no longer be ignored: they must be mitigated. And the only way in which the risk can mitigated is to seek out and pre-empt or resolve any context in which anti-clients could be created.

We can now apply this an enterprise at a very large scale: an entire socioeconomic system.

First, what are the anti-client risks? It doesn’t take much effort to identify that the socioeconomic model in place in Britain creates huge alienation, particularly amongst young males. Real youth unemployment is up above 50% in many inner-urban areas; those young men have have literally nothing to do, no apparent place in the society, no apparent means to gain social-status or even the resources that they need to live, and no apparent prospects or hope for change. It’s the same drivers that lead to the so-called ‘Arab Spring’ – in other words, that lead directly to active revolt against the state. Some people have expressed ‘amazement’ that the youth are ‘destroying their own community’ – but the key point here is that, to the youth themselves, they don’t feel that they belong in that community. It isn’t ‘their’ community: they feel rejected by it – and hence go off to create their own sub-community, in rejection of the ‘host’-community, and, in an all too literal sense, parasitic upon it.  (The crucial point to understand here is that they don’t feel that they have any other choice.) In effect, they have become anti-clients to the entire society in which – in theory only – they supposedly live.

In short, a perfcect recipe for a social explosion.

We then add in two other factors. One is the kurtosis-risk: the fragility of the economic system means that quite small acts of rebellion create disproportionately-large disruption. This is the basis of all asymmetric-warfare – including terrorism. The other factor is the availability of peer-to-peer communication, which enhances both the effective kurtosis-risk and the the cohesiveness of the ‘aliented’ group as a group.

Now add in yet another factor, namely rapidly increasing prices for essentials (the initial trigger for the Arab Spring).

And add in yet another factor, namely a government hell-bent on ‘cutting costs’ by shutting down any ‘unnecessary’ social programmes, especially in socially-stressed areas – at the same time as apparently providing massive subsidies to those already perceived as over-paid and undercontributing. (It doesn’t matter whether this is ‘true’ or not: the crucial factor is whether it is perceived as ‘true’.)

What we end up with is ‘an accident waiting to happen’: a context in which the ‘unexpected’ risks – already dangerously high – were being exacerbated in almost every possible way. And the actions that were known to be needed to reduce the risk were not carried out, on the grounds that they would ‘cost too much’. As Don Tapscott’s article makes all too clear, it may be a shock when it happens, but it should not have been a surprise. As Camila Batmaghelidjh put it in a much-praised opinion-piece in the London newspaper The Independent:

It costs money to care. But it also costs money to clear up riots, savagery and anti-social behaviour. I leave it to you to do the financial and moral sums.

The riots are a classic example of a kurtosis-risk: the cost-savings from cancelling those social-programmes were perhaps a few tens of millions at most, whereas the insurance-costs alone are already running into the billions. Ouch…

That’s what happens at a societal scale. Now bring it down a bit, to the scale of your own organisation. Look at the context architecturally, in much the same way as above: what do you have in the current architecture that risks creating anti-clients? What are the kurtosis-risks for your organisation, particularly around anti-client relationships. It can be an interestingly scary analysis… but one that’s well worth doing. Preferably right now, before the risks for your organisation get any greater?