British-Abwehr relations in WW2

Did British forces help Finland in the Winter War against the USSR in 1940? If so, did they cross Nazi-occupied Europe to get to Finland? If they did that, did the German Abwehr facilitate their passage? If the Abwehr did help, how was this help requested and negotiated? Were there secret communications channels between the Abwehr and the British at that time? Some people think that there may have been such channels later in the war. At that time Germany and the USSR were allies (or at least, partners in a non-aggression pact), and Britain was at war with Germany (although not with the USSR, I think).

I am motivated to ask these questions by a sentence in Richard Bassett’s book about Admiral Wilhelm Canaris (then head of the Abwehr), “Hitler’s Spy Chief: The Wilhelm Canaris Mystery” (paperback edition, 2006). Bassett says:

in Finland where the British forces sent to help the Finns against the Soviets in 1940 were actually assisted in their passage by the Germans. German air & land forces were instructed not to interfere with the progress of these British forces.”

For this claim, Bassett cites Frederick Winterbotham, “The Nazi Connection”, p. 164 (London 1978). But Winterbotham’s book seems to have nothing about the Winter War. Finland is not even listed in the index.

Basset also cites Winterbotham for a claim that Luftwaffe General Milch visited the RAF in Britain before the war. However, none of the pages of Winterbotham’s book which mention Milch say this.

Perhaps relatedly, Kermit Roosevelt (son of Teddy) was in Britain at the start of WW II and organized a group of volunteers to go and help Finland. But, according to his Wikipedia page the war ended before this expedition could get underway.

Predicting your opponent's behaviour

I have argued before that I believe few organizations did as much to prevent the Cold War turning into a hot one than the various intelligence agencies, CIA and KGB among them.   The reason for this is that each side lacked accurate knowledge of the true beliefs and intentions of the other side, and the intelligence agencies were at the forefront of identifying, calibrating and verifying those beliefs and intentions.
A good example was the series of NATO military exercises in 1983 which the USSR erroneously feared would be a cover for a pre-emptive nuclear strike against them.   To preclude that possibility, the Soviet leadership came very close to launching their own pre-emptive nuclear strike.  New evidence has come to light about the mis-understandings that each side had about the other, as reported here:

A classified British Joint Intelligence Committee (JIC) report written shortly afterwards recorded the observation from one official that “we cannot discount the possibility that at least some Soviet officials/officers may have misinterpreted Able Archer 83 and possibly other nuclear CPXs [command post exercises] as posing a real threat.”   The cabinet secretary at the time, Sir Robert Armstrong, briefed Thatcher that the Soviets’ response did not appear to be an exercise because it “took place over a major Soviet holiday, it had the form of actual military activity and alerts, not just war-gaming, and it was limited geographically to the area, central Europe, covered by the Nato exercise which the Soviet Union was monitoring”.
Armstrong told Thatcher that Moscow’s response “shows the concern of the Soviet Union over a possible Nato surprise attack mounted under cover of exercises”. Much of the intelligence for the briefings to Thatcher, suggesting some in the Kremlin believed that the Able Archer exercise posed a “real threat”, came from the Soviet defector Oleg Gordievsky.
Formerly classified files reveal Thatcher was so alarmed by the briefings that she ordered her officials to “consider what could be done to remove the danger that, by miscalculating western intentions, the Soviet Union would over-react”. She ordered her officials to “urgently consider how to approach the Americans on the question of possible Soviet misapprehensions about a surprise Nato attack”.
Formerly secret documents reveal that, in response, the Foreign Office and Ministry of Defence drafted a joint paper for discussion with the US that proposed “Nato should inform the Soviet Union on a routine basis of proposed Nato exercise activity involving nuclear play”.

I wonder if the UK Government communicated anything to the Soviets about the exercises not being a cover for a surprise attack.   And, if so, was their message believed?  Of course, as I’ve discussed before, merely telling your enemy something does not mean that they will believe that something, and nor should it.  And this is why Governments need subtle, strategic analysis of intelligence, not merely the raw data.  The case of Yuri Nosenko is a good example where what the other side believes you believe has consequences, and these consequences need to be considered when deciding what to believe.  And for this reason, clever espionage agencies try to ensure the existence of channels of communication to the enemy which the enemy trusts, so that messages sent through the channel are likely to be believed.   Perhaps, for example, British intelligence knew that Kim Philby and his Cambridge colleagues were Soviet agents many years before they fled to the USSR.

Ineffective imperalism

British MP, Rory Stewart, has spoken in Parliament of our failure to deeply understand the cultures of the foreign countries we invade, with the consequence that invasion efforts are doomed not to succeed.   His view relates to an argument he has put before, about the failure of contemporary international aid organizations and personnel to reckon deeply with the cultures of their host countries, in a manner profoundly worse than that of 19th-century colonial administrators.   Colonial administrators may have typically been racist and exploitative, but at least they cared for – and sought to understand – the cultures and languages of the countries they administered, and were prepared to devote their working lives to those countries.
Video here and Hansard Transcript here.  (Note that in his speech, Stewart refers to Gordon Brown by name, but the Hansard reporter has recorded this as, “the right hon. Member for Kirkcaldy and Cowdenbeath (Mr Brown)“.)

Markets as feedback mechanisms

I just posted after hearing a talk by economic journalist Tim Harford at LSE.  At the end of that post, I linked to a critical review of Harford’s latest book,  Adapt – Why Success Always Starts with Failure, by Whimsley.  This review quotes Harford talking about markets as feedback mechanisms:

To identify successful strategies, Harford argues that “we should not try to design a better world. We should make better feedback loops” (140) so that failures can be identified and successes capitalized on. Harford just asserts that “a market provides a short, strong feedback loop” (141), because “If one cafe is ordering a better combination of service, range of food, prices, decor, coffee blend, and so on, then more customers will congregate there than at the cafe next door“, but everyday small-scale examples like this have little to do with markets for credit default swaps or with any other large-scale operation.

Yes, indeed.  The lead-time between undertaking initial business planning in order to raise early capital investments and the launching of services to the  public for  global satellite communications networks is in the order of 10 years (since satellites, satellite networks and user devices need to be designed, manufactured, approved by regulators, deployed, and connected before they can provide service).  The time between initial business planning and the final decommissioning of an international gas or oil pipeline is about 50 years.  The time between initial business planning and the final decommissioning of an international undersea telecommunications cable may be as long as 100 years.   As I remarked once previously, the design of Transmission Control Protocol (TCP) packets, the primary engine of communication in the 21st century Internet, is closely modeled on the design of telegrams first sent in the middle of the 19th century.  Some markets, if they work at all, only work over the long run, but as Keynes famously said, in the long run we are all dead.
I have experience of trying to design telecoms services for satellite networks (among others), knowing that any accurate feedback for design decisions may come late or not at all, and when it comes may be vague and ambiguous, or even misleading.   Moreover, the success or failure of the selected marketing strategy may not ever be clear, since its success may depend on the quality of execution of the strategy, so that it may be impossible to determine what precisely led to the outcome.   I have talked about this issue before, both regarding military strategies and regarding complex decisions in general.  If the quality of execution also influences success (as it does), then just who or what is the market giving feedback to?
In other words, these coffees are not always short and strong (in Harford’s words), but may be cold, weak, very very slow in arriving, and even their very nature contested.   I’ve not yet read Harford’s book, but if he thinks all business is as simple as providing fmc (fast-moving consumer) services, his book is not worth reading.
Once again, an economist argues by anecdote and example.  And once again, I wonder at the world:  That economists have a reputation for talking about reality, when most of them evidently know so little about it, or reduce its messy complexities to homilies based on the operation of suburban coffee shops.

What use are models?

What are models for?   Most developers and users of models, in my experience, seem to assume the answer to this question is obvious and thus never raise it.   In fact, modeling has many potential purposes, and some of these conflict with one another.   Some of the criticisms made of particular models arise from mis-understandings or mis-perceptions of the purposes of those models, and the modeling activities which led to them.
Liking cladistics as I do, I thought it useful to list all the potential purposes of models and modeling.   The only discussion that considers this topic that I know is a brief discussion by game theorist Ariel Rubinstein in an appendix to a book on modeling rational behaviour (Rubinstein 1998).  Rubinstein considers several alternative purposes for economic modeling, but ignores many others.   My list is as follows (to be expanded and annotated in due course):

  • 1. To better understand some real phenomena or existing system.   This is perhaps the most commonly perceived purpose of modeling, in the sciences and the social sciences.
  • 2. To predict (some properties of) some real phenomena or existing system.  A model aiming to predict some domain may be successful without aiding our understanding  of the domain at all.  Isaac Newton’s model of the motion of planets, for example, was predictive but not explanatory.   I understand that physicist David Deutsch argues that predictive ability is not an end of scientific modeling but a means, since it is how we assess and compare alternative models of the same phenomena.    This is wrong on both counts:  prediction IS an end of much modeling activity (especially in business strategy and public policy domains), and it not the only means we use to assess models.  Indeed, for many modeling activities, calibration and prediction are problematic, and so predictive capability may not even be  possible as a form of model assessment.
  • 3. To manage or control (some properties of) some real phenomena or existing system.
  • 4. To better understand a model of some real phenomena or existing system.  Arguably, most of economic theorizing and modeling falls into this category, and Rubinstein’s preferred purpose is this type.   Macro-economic models, if they are calibrated at all, are calibrated against artificial, human-defined, variables such as employment, GDP and inflation, variables which may themselves bear a tenuous and dynamic relationship to any underlying economic reality.   Micro-economic models, if they are calibrated at all, are often calibrated with stylized facts, abstractions and simplifications of reality which economists have come to regard as representative of the domain in question.    In other words, economic models are not not usually calibrated against reality directly, but against other models of reality.  Similarly, large parts of contemporary mathematical physics (such as string theory and brane theory) have no access to any physical phenomena other than via the mathematical model itself:  our only means of apprehension of vibrating strings in inaccessible dimensions beyond the four we live in, for instance, is through the mathematics of string theory.    In this light, it seems nonsense to talk about the effectiveness, reasonable or otherwise, of mathematics in modeling reality, since how we could tell?
  • 5. To predict (some properties of) a model of some real phenomena or existing system.
  • 6. To better understand, predict or manage some intended (not-yet-existing) artificial system, so to guide its design and development.   Understanding a system that does  not yet exist is qualitatively different to understanding an existing domain or system, because the possibility of calibration is often absent and because the model may act to define the limits and possibilities of subsequent design actions on the artificial system.  The use of speech act theory (a model of natural human language) for the design of artificial machine-to-machine languages, or the use of economic game theory (a mathematical model of a stylized conceptual model of particular micro-economic realities) for the design of online auction sites are examples here.   The modeling activity can even be performative, helping to create the reality it may purport to describe, as in the case of the Black-Scholes model of options pricing.
  • 7. To provide a locus for discussion between relevant stakeholders in some business or public policy domain.  Most large-scale business planning models have this purpose within companies, particularly when multiple partners are involved.  Likewise, models of major public policy issues, such as epidemics, have this function.  In many complex domains, such as those in public health, models provide a means to tame and domesticate the complexity of the domain.  This helps stakeholders to jointly consider concepts, data, dynamics, policy options, and assessment of potential consequences of policy options,  all of which may need to be socially constructed. 
  • 8. To provide a means for identification, articulation and potentially resolution of trade-offs and their consequences in some business or public policy domain.   This is the case, for example, with models of public health risk assessment of chemicals or new products by environmental protection agencies, and models of epidemics deployed by government health authorities.
  • 9. To enable rigorous and justified thinking about the assumptions and their relationships to one another in modeling some domain.   Business planning models usually serve this purpose.   They may be used to inform actions, both to eliminate or mitigate negative consequences and to enhance positive consequences, as in retroflexive decision making.
  • 10. To enable a means of assessment of managerial competencies of the people undertaking the modeling activity. Investors in start-ups know that the business plans of the company founders are likely to be out of date very quickly.  The function of such business plans is not to model reality accurately, but to force rigorous thinking about the domain, and to provide a means by which potential investors can challenge the assumptions and thinking of management as way of probing the managerial competence of those managers.    Business planning can thus be seen to be a form of epideictic argument, where arguments are assessed on their form rather than their content, as I have argued here.
  • 11. As a means of play, to enable the exercise of human intelligence, ingenuity and creativity, in developing and exploring the properties of models themselves.  This purpose is true of that human activity known as doing pure mathematics, and perhaps of most of that academic activity known as doing mathematical economics.   As I have argued before, mathematical economics is closer to theology than to the modeling undertaken in the natural sciences. I see nothing wrong with this being a purpose of modeling, although it would be nice if academic economists were honest enough to admit that their use of public funds was primarily in pursuit of private pleasures, and any wider social benefits from their modeling activities were incidental.

POSTSCRIPT (Added 2011-06-17):  I have just seen Joshua Epstein’s 2008 discussion of the purposes of modeling in science and social science.   Epstein lists 17 reasons to build explicit models (in his words, although I have added the label “0” to his first reason):

0. Prediction
1. Explain (very different from predict)
2. Guide data collection
3. Illuminate core dynamics
4. Suggest dynamical analogies
5. Discover new questions
6. Promote a scientific habit of mind
7. Bound (bracket) outcomes to plausible ranges
8. Illuminate core uncertainties
9. Offer crisis options in near-real time. [Presumably, Epstein means “crisis-response options” here.]
10. Demonstrate tradeoffe/ suggest efficiencies
11. Challenge the robustness of prevailing theory through peturbations
12. Expose prevailing wisdom as imcompatible with available data
13. Train practitioners
14. Discipline the policy dialog
15. Educate the general public
16. Reveal the apparently simple (complex) to be complex (simple).

These are at a lower level than my list, and I believe some of his items are the consequences of purposes rather than purposes themselves, at least for honest modelers (eg, #11, #12, #16).
References:
Joshua M Epstein [2008]: Why model? Keynote address to the Second World Congress on Social Simulation, George Mason University, USA.  Available here (PDF).
Robert E Marks [2007]:  Validating simulation models: a general framework and four applied examples. Computational Economics, 30 (3): 265-290.
David F Midgley, Robert E Marks and D Kunchamwar [2007]:  The building and assurance of agent-based models: an example and challenge to the field. Journal of Business Research, 60 (8): 884-893.
Robert Rosen [1985]: Anticipatory Systems. Pergamon Press.
Ariel Rubinstein [1998]: Modeling Bounded Rationality. Cambridge, MA, USA: MIT Press.  Zeuthen Lecture Book Series.
Ariel Rubinstein [2006]: Dilemmas of an economic theorist. Econometrica, 74 (4): 865-883.

Agonistic planning

One key feature of the Kennedy and Johnson administrations identified by David Halberstam in his superb account of the development of US policy on Vietnam, The Best and the Brightest, was groupthink:  the failure of White House national security, foreign policy and defense staff to propose or even countenance alternatives to the prevailing views on Vietnam, especially when these alternatives were in radical conflict with the prevailing wisdom.   Among the junior staffers working in those administrations was Richard Holbrooke, now the US Special Representative for Afghanistan and Pakistan in the Obama administration.  A New Yorker profile of Holbrooke last year included this statement by him, about the need for policy planning processes to incorporate agonism:

“You have to test your hypothesis against other theories,” Holbrooke said. “Certainty in the face of complex situations is very dangerous.” During Vietnam, he had seen officials such as McGeorge Bundy, Kennedy’s and Johnson’s national-security adviser, “cut people to ribbons because the views they were getting weren’t acceptable.” Washington promotes tactical brilliance framed by strategic conformity—the facility to outmaneuver one’s counterpart in a discussion, without questioning fundamental assumptions. A more farsighted wisdom is often unwelcome. In 1975, with Bundy in mind, Holbrooke published an essay in Harpers in which he wrote, “The smartest man in the room is not always right.” That was one of the lessons of Vietnam. Holbrooke described his method to me as “a form of democratic centralism, where you want open airing of views and opinions and suggestions upward, but once the policy’s decided you want rigorous, disciplined implementation of it. And very often in the government the exact opposite happens. People sit in a room, they don’t air their real differences, a false and sloppy consensus papers over those underlying differences, and they go back to their offices and continue to work at cross-purposes, even actively undermining each other.”  (page 47)
Of course, Holbrooke’s positing of policy development as distinct from policy implementation is itself a dangerous simplification of the reality for most complex policy, both private and public, where the relationship between the two is usually far messier.    The details of policy, for example, are often only decided, or even able to be decided, at implementation-time, not at policy design-time.    Do you sell your new hi-tech product via retail outlets, for instance?  The answer may depend on whether there are outlets available to collaborate with you (not tied to competitors) and technically capable of selling it, and these facts may not be known until you approach the outlets.  Moreover, if the stakeholders implementing (or constraining implementation) of a policy need to believe they have been adequately consulted in policy development for the policy to be executed effectively (as is the case with major military strategies in democracies, for example here), then a further complication to this reductive distinction exists.
 
 
UPDATE (2011-07-03):
British MP Rory Stewart recounts another instance of Holbrooke’s agonist approach to policy in this post-mortem tribute: Holbrooke, although disagreeing with Stewart on policy toward Afghanistan, insisted that Stewart present his case directly to US Secretary of State Hilary Clinton in a meeting that Holbrooke arranged.
 
References:

David Halberstam [1972]:  The Best and the Brightest.  New York, NY, USA: Random House.
George Packer [2009]:  The last mission: Richard Holbrooke’s plan to avoid the mistakes of Vietnam in AfghanistanThe New Yorker, 2009-09-28, pp. 38-55.

Strategy vs. Tactics

What is the difference between strategy and tactics?  In my experience, many people cannot tell the difference, and/or speak as if they conflate the two. Personally, I have never had difficulty telling them apart.
The 18th-century British naval definition was that tactics are for when you can see the enemy’s ships, and strategies are for when you cannot.  When you can see the enemy’s ships there are still important unknown variables, but you should know how many ships there are, where they are located, and (within some degree of accuracy) what hostile actions they are capable of.  If you are close enough to identify the particular enemy ships that you can see, you may also know then the identities of their captains.  With knowledge of past engagements, you may thus be able to estimate the intentions, the likely behaviors, and the fighting will of the ships’ crews.   None of these variables are known when the ships lay beyond the horizon.
Thus, tactics describe your possible actions when you know who the other stakeholders are in the situation you are in, and you have accurate (although not necessarily precise) information about their capabilities, goals, preferences, and intentions.   To the extent that such knowledge is missing is the extent to which reasoning about potential actions becomes strategic rather than tactical.  These distinctions are usually quite clear in marketing contexts.  For instance, licking envelopes for a client’s direct marketing campaign is not strategic consultancy, nor is finding, cleaning, verifying, and compiling the addresses needed by the client to put on the envelopes. (This is not to say that either task can be done well without expertise and experience.) Advising a client to embark on a direct marketing campaign rather than (say) a television ad campaign is closer to strategic consultancy, although in some contexts it may be mere tactics. Determining ahead of time which segments of the potential customer population should be targeted with an advertising campaign is definitely strategic, as is deciding whether or not to enter (or stay) in the market.
The key difference between the two is that articulating a strategy requires taking a view on the values of significant uncertain variables, whereas articulating a tactic generally does not.

History under circumstances not of our choosing

British MP Rory Stewart writing this week about western military policy towards Afghanistan:

We can do other things for Afghanistan but the West – in particular its armies, development agencies and diplomats – are not as powerful, knowledgeable or popular as we pretend. Our officials cannot hope to predict and control the intricate allegiances and loyalties of Afghan communities or the Afghan approach to government. But to acknowledge these limits and their implications would require not so much an anthropology of Afghanistan, but an anthropology of ourselves.
The cures for our predicament do not lie in increasingly detailed adjustments to our current strategy. The solution is to remind ourselves that politics cannot be reduced to a general scientific theory, that we must recognize the will of other peoples and acknowledge our own limits. Most importantly, we must remind our leaders that they always have a choice.
That is not how it feels. European countries feel trapped by their relationship with NATO and the United States. Holbrooke and Obama feel trapped by the position of American generals. And everyone – politicians, generals, diplomats and journalist – feels trapped by our grand theories and beset by the guilt of having already lost over a thousand NATO lives, spent a hundred billion dollars and made a number of promises to Afghans and the West which we are unlikely to be able to keep.
So powerful are these cultural assumptions, these historical and economic forces and these psychological tendencies, that even if every world leader privately concluded the operation was unlikely to succeed, it is almost impossible to imagine the US or its allies halting the counter-insurgency in Afghanistan in the years to come.  Roman Emperor Frederick Barbarossa may have been in a similar position during the Third Crusade.  Former US President Lyndon B. Johnson certainly was in 1963. Europe is simply in Afghanistan because America is there. America is there just because it is. And all our policy debates are scholastic dialectics to justify this singular but not entirely comprehensible fact.

Complex Decisions

Most real-world business decisions are considerably more complex than the examples presented by academics in decision theory and game theory.  What makes some decisions more complex than others? Here I list some features, not all of which are present in all decision situations.

  • The problems are not posed in a form amenable to classical decision theory.

    Decision theory requires the decision-maker to know what are his or her action-options, what are the consequences of these, what are the uncertain events which may influence these consequences, and what are the probabilities of these uncertain events (and to know all these matters in advance of the decision). Yet, for many real-world decisions, this knowledge is either absent, or may only be known in some vague, intuitive, way. The drug thalidomide, for example, was tested thoroughly before it was sold commercially – on male and female human subjects, adults and children. The only group not to be tested were pregnant women, which were, unfortunately, the main group for which the drug had serious side effects. These side effects were consequences which had not been imagined before the decision to launch was made. Decision theory does not tell us how to identify the possible consequences of some decision, so what use is it in real decision-making?

  • There are fundamental domain uncertainties.

    None of us knows the future. Even with considerable investment in market research, future demand for new products may not be known because potential customers themselves do not know with any certainty what their future demand will be. Moreover, in many cases, we don’t know the past either. I have had many experiences where participants in a business venture have disagreed profoundly about the causes of failure, or even success, and so have taken very different lessons from the experience.

  • Decisions may be unique (non-repeated).

    It is hard to draw on past experience when something is being done for the first time. This does not stop people trying, and so decision-making by metaphor or by anecdote is an important feature of real-world decision-making, even though mostly ignored by decision theorists.

  • There may be multiple stakeholders and participants to the decision.

    In developing a business plan for a global satellite network, for example, a decision-maker would need to take account of the views of a handful of competitors, tens of major investors, scores of minor investors, approximately two hundred national and international telecommunications regulators, a similar number of national company law authorities, scores of upstream suppliers (eg equipment manufacturers), hundreds of employees, hundreds of downstream service wholesalers, thousands of downstream retailers, thousands or millions of shareholders (if listed publicly), and millions of potential customers. To ignore or oppose the views of any of these stakeholders could doom the business to failure. As it happens, Game Theory isn’t much use with this number and complexity of participants. Moreover, despite the view commonly held in academia, most large Western corporations operate with a form of democracy. (If opinions of intelligent, capable staff are regularly over-ridden, these staff will simply leave, so competition ensures democracy. In addition, good managers know that decisions unsupported by their staff will often be executed poorly, so success of a decision may depend on the extent to which staff believe it has been reached fairly.) Accordingly, all major decisions are decided by groups or teams, not at the sole discretion of an individual. Decision theorists, it seems to me, have paid insufficient attention to group decisions: We hear lots about Bayesian decision theory, but where, for example, is the Bayesian theory of combining subjective probability assessments?

  • Domain knowledge may be incomplete and distributed across these stakeholders.
  • Beliefs, goals and preferences of the stakeholders may be diverse and conflicting.
  • Beliefs, goals and preferences of stakeholders, the probabilities of events and the consequences of decisions, may be determined endogenously, as part of the decision process itself.

    For instance, economists use the term network good to refer to a good where one person’s utility depends on the utility of others. A fax machine is an example, since being the sole owner of fax is of little value to a consumer. Thus, a rational consumer would determine his or her preferences for such a good only AFTER learning the preferences of others. In other words, rational preferences are determined only in the course of the decision process, not beforehand.  Having considerable experience in marketing, I contend that ALL goods and services have a network-good component. Even so-called commodities, such as natural resources or telecommunications bandwidth, have demand which is subject to fashion and peer pressure. You can’t get fired for buying IBM, was the old saying. And an important function of advertising is to allow potential consumers to infer the likely preferences of other consumers, so that they can then determine their own preferences. If the advertisement appeals to people like me, or people to whom I aspire to be like, then I can infer that those others are likely to prefer the product being advertized, and thus I can determine my own preferences for it. Similarly, if the advertisement appeals to people I don’t aspire to be like, then I can infer that I won’t be subject to peer pressure or fashion trends, and can determine my preferences accordingly.
    This is commonsense to marketers, even if heretical to many economists.

  • The decision-maker may not fully understand what actions are possible until he or she begins to execute.
  • Some actions may change the decision-making landscape, particularly in domains where there are many interacting participants.

    A bold announcement by a company to launch a new product, for example, may induce competitors to follow and so increase (or decrease) the chances of success. For many goods, an ecosystem of critical size may be required for success, and bold initiatives may act to create (or destroy) such ecosystems.

  • Measures of success may be absent, conflicting or vague.
  • The consequences of actions, including their success or failure, may depend on the quality of execution, which in turn may depend on attitudes and actions of people not making the decision.

    Most business strategies are executed by people other than those who developed or decided the strategy. If the people undertaking the execution are not fully committed to the strategy, they generally have many ways to undermine or subvert it. In military domains, the so-called Powell Doctrine, named after former US Secretary of State Colin Powell, says that foreign military actions undertaken by a democracy may only be successful if these actions have majority public support. (I have written on this topic before.)

  • As a corollary of the previous feature, success of an action may require extensive and continuing dialog with relevant stakeholders, before, during and after its execution.

    This is not news to anyone in business.

  • Success may require pre-commitments before a decision is finally taken.

    In the 1990s, many telecommunications companies bid for national telecoms licences in foreign countries. Often, an important criterion used by the Governments awarding these licences was how quickly each potential operator could launch commercial service. To ensure that they could launch service quickly, some bidders resorted to making purchase commitments with suppliers and even installing equipment ahead of knowing the outcome of a bid, and even ahead, in at least one case I know, of deciding whether or not to bid.

  • The consequences of decisions may be slow to realize.

    Satellite mobile communications networks have typically taken ten years from serious inception to launch of service.  The oil industry usually works on 50+ year cycles for major investment projects.  BP is currently suffering the consequence in the Gulf of Mexico of what appears to be a decades-long culture which de-emphasized safety and adequate contingency planning.

  • Decision-makers may influence the consequences of decisions and/or the measures of success.
  • Intelligent participants may model each other in reaching a decision, what I term reflexivity.

    As a consequence, participants are not only reacting to events in their environment, they are anticipating events and the reactions and anticipations of other participants, and acting proactively to these anticipated events and reactions. Traditional decision theory ignores this. Following Nash, traditional game theory has modeled the outcomes of one such reasoning process, but not the processes themselves. Evolutionary game theory may prove useful for modeling these reasoning processes, although assuming a sequence of identical, repeated interactions does not strike me as an immediate way to model a process of reflexivity.  This problem still awaits its Nash.

In my experience, classical decision theory and game theory do not handle these features very well; in some cases, indeed, not at all.  I contend that a new theory of complex decisions is necessary to cope with decision domains having these features.

Old Etonians

Congratulations to Rory Stewart, newly-elected Conservative MP for England’s largest electorate, Penrith and the Border.

I heard Stewart speak in December 2009, shortly after his pre-selection, at a bookshop in Penrith.  At the time, he was walking across his prospective constituency as a way to learn about it and to meet people.  He was most impressive – intelligent, urbane, witty, sincere, respectful, and also very laid-back.  He read from his book on Iraq, and talked about Afghanistan and Iraq, even quoting the poetry of TS Eliot.  The audience then had a good debate with him and with each other about do-gooding foreign wars and about the UK-USA relationship.  From their comments, I would say about half the audience were probably Labour voters.

Stewart, as good a facilitator as Bill Clinton or Barack Obama, got us all to say who we were and what were our concerns.     He did not  interrupt anyone, listened attentively and respectfully (even when he disagreed), and remembered everyone’s name and profession; I’m sure he charmed some of the audience there and then into voting for him.    When someone said they’d like to vote for him personally, but could not face voting Conservative (calling it “the Work-House Party”), he laughed at the description and said this was a decision they’d have to make for themself.  He didn’t even present a case for voting for him personally while ignoring the party label, as most politicians I have known would have done at that point.    In fact, he proceeded to give an honest assessment of his own strengths and weaknesses as a candidate – if he was selling himself, this was an extremely soft-sell.

The whole event struck me as remarkable:  Here was a modern-day soldier, colonial administrator, and educator of America’s nomenklatura campaigning in rural Cumbria and doing so very explicitly on his Iraq and Afghan experience.  And, more surprisingly, people seemed to respond with great passion to his message, with its key theme being that the West needs to understand and accept the limits to its own power to change other societies.  It says something about the effect these two wars have had on people in Britain that such a message would have even been listened to seriously in a local campaign, let alone that it would resonate with people.

Some British commentators have compared Stewart to Winston Churchill, who also had had colonial military adventures and had written some damn fine and exciting prose before entering Parliament.   I think that other writer and warrior Teddy Roosevelt is a better comparison, as TR appears (from this distance) to have been more respectful of human diversity and difference than was young Winnie.    One does not have to be a Conservative to be pleased that a person of Rory Stewart’s intelligence, sophistication, integrity, courage and wisdom should now be in the Mother of Parliaments.

NOTES:
Another account of the same meeting here.   My memory is that the dog was not small, and the photographs confirm my memory.

Here is a profile from National Geographic (undated, but before Stewart’s appointment as a Harvard professor).

And here is Ian Parker’s profile in The New Yorker (2010-11-15).

Through his American mother, Winston Churchill knew TR, and once stayed with the Roosevelts in Albany when TR was Governor of New York.