Nice, forgiving, tough and clear – all at the same time

Imagine a situation  where two people are arrested on suspicion of a crime. They are interrogated separately so there is no communication between the prisoners who have two choices; to defect (that is,  inform on the other suspect) or to cooperate (with the other suspect, not the police) by saying nothing. I have seen various descriptions of the various outcomes; if they both remain silent, they both go free or suffer a minimal penalty, if they both defect, they both suffer a major punishment while if one defects and the other cooperates, the cooperator suffers the major punishment but the defector goes free and may even reap some reward. This scenario is called the Prisoner’s Dilemma and is, I think, well known in the ‘Game Theory’ world; I believe that it also received much interest in the ’60s and ’70s in the context of the Cold War arms race.  If the situation only arises once, the rational decision is to defect but if the situation arises repeatedly a different optimum emerges.

In the 1970s an academic at Michigan called Robert Axelrod set up a tournament  in which the entrants were required to submit  computer program to play the part of one of the prisoners. The programs were paired of against each other, in the way of a cup competition; each round consisted of 200 cycles of the scenario. The program that won was submitted by an academic from the University of Toronto called Anatoly Rapoport who adopted a very simple strategy called ‘TIT FOR TAT’. TIT FOR TAT cooperated in round one and  then chose to do exactly what the other prisoner had done in the previous round for every round thereafter. This outcome surprised Axelrod and he ran a second tournament sometime later where the challenge was to beat ‘TIT FOR TAT’; not one of 62 entrants succeeded.

‘TIT FOR TAT’ can be characterised as:

• ‘Nice’ in that it never defects first
• ‘Forgiving’ in that it rewards cooperative behaviour
• ‘Tough’ in that it punishes uncooperative behaviour
• ‘Clear’ in that opposing programs (the other prisoner) can work out the pattern pretty easily.

So what is the relevance to business? Perhaps it is in the pertinent questions that are raised about effective behaviours in competitive situations? Who are the prisoners and who the authority structure that can ‘reward’ or ‘punish’? Is business a prisoner in the competitive marketplace and when does cooperation become anti-competitive? Or are business colleagues all prisoners within the business world? What role does performance management have in encouraging or discouraging behaviours? Does it foster nice, forgiving, tough and clear behaviours if these are seen as desirable?

Since Axelrod’s competitions, I believe that there has been considerable development in modelling of the Prisoner’s Dilemma. Eric Beinhocker describes an evolution of ‘TIT FOR TAT’ embodied in a strategy called Fair. This addresses the situation where both prisoners adopt ‘TIT FOR TAT’ and there is the potential for ‘lock in’ to either mutual cooperation or mutual defecting. Axelrod began to look at strategies for situations where the game history suggested that the other prisoner could be bluffed. Lots of interesting stuff and good reading material for those who are so inclined. The Prisoner’s Dilemma is quite well covered in the literature and there is a good general description in a book called ‘The Origin of Wealth’ by Eric Beinhocker, already mentioned ( see pages 221 to 233) and in ‘Complexity’ by Mitchell Waldrop (pages 262 to 265).

The Prisoner’s Dilemma is an example of a ‘non zero sum’ phenomenon; the net loss of freedom if both cooperate is minimal while the net loss of freedom if one or other defects or if both defect is an order of magnitude greater.

Cooperation then gives the best overall outcome for two prisoners but it is unlikely that the majority of cooperations within business will operate on a one to one basis. Inevitably our cooperations are many to many and these can probably be represented usefully as a series of networks with multiple nodes. It is important for the business then to understand how networks operate in order to ensure that our knowledge and competency networks are cooperative, robust and resilient. There is quite a body of academic research in this area which is relevant at many levels within business and the research is important in order to extract  simple rules from complex phenomena (for instance, be nice, be forgiving, be tough, be clear).

Old insight, fresh perspective?

When Ralph Stacey looks at the complexity matrix (seen here being used by the medical profession) he drew up some years ago he could be forgiven for feeling a glow of satisfaction. For him it is perhaps ‘old hat’ but for many of the rest of us his matrix provides a helpful fresh perspective on the confusing economic, financial and political climate in which we find ourselves. His matrix suggests that in situations where we are far from agreement and far from certainty having recourse to rational decision making (and this I would qualify to mean linear rational thinking), political decision making or judgement based decision making will not necessarily be very effective. Brenda Zimmerman of York University, Toronto on whose analysis the above reference is based acknowledges that traditional management teaching has concentrated on decision making where (linear) reasoning, politics and judgement can be effective, which focus has left a gap in management teaching. This raises a couple of questions: how useful could the Stacey matrix be in the prevailing circumstances – which can well be described as far from certain and far from agreement? How aware are the current business leaders of this material, given that many of them will have completed their formal education before it was published?

In Stacey’s matrix this region (far from certainty and far from agreement) is divided into two zones, the zone of complexity and the zone of chaos. With reference to the zone of chaos, Zimmerman says, with no little understatement, this is a region ‘… that organizations should avoid as much as possible.’ So, looking on the bright side, let’s assume that we are in the zone of complexity. If traditional management tools are not necessarily effective in this region, what tools are there that we can use?

Some strategic thinkers are looking to see what complexity science can offer in the military sphere and this book by James Moffat serves well as a starting point: Complexity Science and Network Centric Warfare. In amongst the non linear maths there is a wealth of analytical thinking that lays down a foundation for the application of complexity science on which to build models of operations in what is described as the information age.

I don’t want to say more about complexity science here apart from commenting that its use in this context is to help break the mould of traditional command and control structures and to create the philosophical and intellectual framework for de-centralised command and control. Hold the idea of using complexity science in this way while we explore another line of thought.

A recent copy of the Economist includes a special report on the middle class, particularly in emerging markets (Burgeoning Burgeoisie, Economist, 14th February 2009 – to see the link may require a subscription). There is an interesting discussion on who or what are the middle classes but two particular correlations stand out; one between the middle class and economic growth and the other between the middle class and democracy. As the report recognises the former case is easier to make and even it is unlikely to continue without interruption through a recession. Daaron Acemoglu of the Massachussetts Institute of Technology is quoted as attributing the importance of the middle class to growth in the emerging markets to the fact that “… they are more committed than the elite to a mixed, competitive economy.” This is related in the Economist report to Maslow’s hierarchy of needs; I suspect that account also needs to be taken of an economy of exclusivity alongside the economy of wealth.  The former is a zero sum economy while the latter is not; as an emerging middle class starts out with little to lose in either economy it does not have to balance a loss of exclusivity against any gains in wealth. This brings us back to complexity science because it provides one of the perspectives for understanding the dynamics of non zero sum economics as is very ably expounded by Eric Beinhocker in his book, The Origin of Wealth.

What puzzles me in the current climate is that with all the scholarship that has gone into complexity science over the past 20 years I am not hearing more reference to its use in responding to the current uncertainties. Perhaps I am listening at the wrong windows; I hope so because I find much to attract me in the philosophical underpinnings of complexity science and much that I would like to investigate as a means of addresssing the difficulties that present themselves to me.

James Moffat acknowledges the role of the Santa Fe Institute in the early development of this field of multidisciplinary research and the institute provides a treasure trove of relevant expertise and reference material. Ralph Stacey is professor at University of Hertfordshire and was recently interviewed here.