While in South Africa, a couple of weeks ago, I had the privilege of attending a presentation by Ian Thomas, a game tracker and author famous for his work with lions. He gave a very interesting talk which linked his experiences tracking a particularly dangerous lion to decision-making in business today. He and I have since been discussing how his experiences relate to contemporary business issues such as signal-noise ratio and decision-making under uncertainty, so I thought I’d share some of those thoughts here.
Signal to noise ratio
In the business world, we are drowning in data. News sources bombard us with stories, figures, opinions etc, while the stock market is never standing still (and neither are the people paid to try and explain why the stock market is doing what it is doing). In almost any business, but particularly finance, possibly the biggest challenge of decision-making is to separate the signal from the noise and figure out what data actually matters. Then, you rely on the subset of information you think constitutes the signal to make your decision and hopefully get a better result than if you’d taken a stab in the dark or been distracted by noise.
Now, separating the important signal from the more general noise is clearly what a lion tracker like Ian does when he isolates monkey calls, bird calls and hundreds of other markers to help him locate an animal. I have to check this with Ian, but I’m fairly confident that when tracking there are a whole host of distractions and sources of data, only a few of which are relevant. Some signals are pretty clear – a nearby roar, a fresh footprint. But I’m told the situation can be ambiguous at times, leading to either danger (should you stumble across a dangerous animal in a defensive situation) or frustration (should you repeatedly stumble upon nothing). So how do you isolate those signals which are useful? In Ian’s case, through careful research, discussions with a diverse range of experts, relentless (and imaginative) practice, and logical analysis.
Ian wants to relate his experiences to finance and economics, which I think would make for a fascinating discussion about how we look for signals in the business world. The challenge with translating the signal/noise analogy from lion tracking to finance is that it breaks down a bit when translated to trading on financial markets. The trouble with markets is that they are designed to be efficient, and profitable opportunities almost always disappear as soon as people start spotting them. So if finding a lion is akin finding a profitable trade, you can be fairly certain that as soon as more than a few people start using the bird (isolated signal) to find the lion, two things happen: first, the lion disappears (e.g. the price of the stock is bid up) and second, the bird quickly becomes noise again. (Apologies for the clunky analogy)
With commercial decisions and in business environments, though, perhaps the analogy has more merit. People exhibit behavioural patterns. There are signals that endure. Warren Buffett has made a lot of money investing in firms which have certain signals – great management, solid and defensible market position, understandable business model (although even he was distract by rather noisy derivatives…). So it would be interesting to translate experiences from disciplines like tracking to situations in business where signals endure by the nature of their environment – perhaps cases closely related to human behaviour, as these are notoriously tough to change.
Perhaps in these situations the key is to a) know what constitutes your “lion” (have a clear goal), and b) intelligently search for the relevant signals that could lead you to him. And realize that there probably won’t be just one signal, but many (the roar, the monkey, the track, the bird, the cubs). Isolating signals then becomes a matter of understanding key drivers and being sensitive to potential sources of important data, turning to highly experienced people with long memories for help refining your understanding. Recent experience starkly demonstrates that trusting a VAR model run on a year’s data probably won’t be sufficient to inform you of the impending market shifts, nor their potential impact on your portfolio.
Finally, in some people, such signal sensing goes from being logical and deliberative, to being almost instantaneous. Malcolm Gladwell writes about this in “Blink”. Ian talked about almost unconsiously processing a variety of signals and knowing all of a sudden the lion was very close; perhaps only later appreciating that he knew because the lion tracks crossed some bird tracks and yet the bird was still nearby. In some cases you might never be able to explain how you knew. Entrepreneurs can sometimes exhibit this same trait in assessing people (my father once told me that one of his greatest strengths was knowing when something wasn’t right as people were talking about a company, leading him to distrust their testimony although he couldn’t explain why – this alone made him a great asset on boards). UPDATE: I’ve discovered the term for this is “expert intuition”.
Bias and decision-making
One of the most memorable points of Ian’s presentation (which I highly recommend, by the way) was when he was explaining his decision to track a particularly dangerous lion known as “big black”, rather than make the problem go away (kill big black or leave the park), or simply pretend to track but actually avoid ever finding him. Ian made the courageous decision to track the lion, despite realising that there was a very real risk that he could be hurt. One point he made that stuck was that “decisions are often more important than skills” – i.e. that it is the courageous decisions you make that force you into learning and growing, rather than skills that in turn prepare you to succeed when faced with difficult decisions.
One interesting element in this part of Ian’s presentation was the fact that he decided to take on the lion rather than walk away from the park and lose face. Ian’s argument was that at the time he had a big ego, and thus was driven by this to take the risky option. But another factor in play was probably the psychology of losses and gains.
Research into biases in decision-making shows that a loss of $x is more painful than a gain of $x is pleasurable, and that there is a major bias towards the status quo. Hence, most people will prefer a moderate risk of an extreme cost with a small chance to lose nothing, over a definite but moderate loss, even when the two are logically exact in terms of expected outcome. This was shown by Kahneman and Tversky in a 1984 paper called “Choices, Values and Frames” (American Psychologist, 39:4, 341-50).
Perhaps these psychological biases were at play in Ian’s decision to track “big black” despite high risk of being hurt:
a) the prospect of losing of face by admitting defeat weighed particularly heavily on his mind, and was not compensated for by the prospect of continued physical safety as a gain (this was at play regardless of the extent his ego!). (pain of losses exceed pleasure of gain).
b) the status quo was Ian as a celebrated tracker, and there was a major psychological bias within him that rejected giving this up (endowment effect)
c) given the choice between a sure loss in reputation versus the chance of a moderate chance of being hurt and a small possibility of being an even greater-respected tracker, Ian was inclined to chose the latter (framing of outcomes leads to risk-seeking choice).
My colleague Gareth Shepherd also made the point that there might be an additional operative bias in the form of identity/consistency, a la Cialdini’s “commitment and consistency” source of power. Ian identified himself as a celebrated tracker, and to turn down the prospect of tracking a lion, regardless of the high danger involved, would require a repudiation of some aspects of that identity.
These biases might give some interesting food for thought for senior decision-makers to examine what is at play inside their heads when they are confronted with a decision. For Ian, risking his own life impacts primarily him and his family. But for managers, their decisions can impact millions of shareholders, constitutuents etc. A bad decision could have a massive negative impact on others – hence it is important to be aware of these biases at play.
As an aside, perhaps it should be mentioned that when uncertainty is at play, decisions can be distinguished from their outcomes – one can have a good decision with a bad outcome (you hedged as best you could and the risk was acceptable but luck just wasn’t on your side), and a bad decision with a good outcome (you take an overwhelming risk with other people’s money but luck is on your side – a la investment banks between 2002-2008). Then there are of course good decisions with good outcomes and bad decisions with bad outcomes. The trick of course is to try and make good decisions that lead, as far as you can control the outcome, to good outcomes.
What if it wasn’t you who made the decision?
The other element that we discussed was the situation when a manager doesn’t actually have the opportunity to make the decision at all, but must play along anyway. Or, conversely, when you’ve painted yourself into a corner and must make that decision regardless. As Ian suggested, at this stage one often has the choice of pretending to go along with the decision (your own, or others’) versus actually going for it and risking real failure.
In Ian’s case, he could have altered the odds of getting hurt in two ways – first, by pretending to track, but avoiding danger, second, by skilling up as much as possible. He did the latter, in my opinion the truly courageous decision, calling in every resource he knew to improve his tracking skills (to find the lion before it found him) and shooting skills (in case the lion came at him and he had to defend himself). Note that this was courageous not merely because he faced personal danger. It takes real effort, time, money and personal cost to admit what you don’t know and throw yourself whole-heartedly after a goal like that. However, if you are prepared to make these efforts, following through in that manner makes the best of the decision itself by turning the odds in your favour both in the short-term (you are more likely to succeed in tracking the lion) and in the long term (real learning occurs that is likely transferable to later situations).
So for people not making the decision themselves, this is a key point. Faced with a decision one can’t change, one can quit, of course, but more often the imperative is between pretending to do something or actually wholeheartedly going for it. And in the latter case, Ian’s example of being courageous and committing to skill up in order to improve the odds is a great one (as well as an awesome story – you should get him to speak).
Risk v uncertainty
As a final point, in my scenario work I’m spending a lot of time thinking about the distinction between “risk” and “uncertainty”, where risk is viewed as events which can be quantified/estimated in terms of their probabilities, and uncertainty where quantification is impossible. Many people have argued that the recent economic mess was caused by people thinking they were playing in a world of financial risk which was well-modelled, when in fact they were relying on poorly-specificied models which didn’t (and perhaps by definition couldn’t) take into account the broader uncertainties which ultimately led to the crisis. My feeling is that focusing on pure risk is missing the bigger picture of “unknown unknowns” or “black swans”. It’s one thing to control for the risks you know about (being charged). But what about when you’re in a business situation and there are risks you don’t even know about? That’s where it becomes really tricky!
I’m not sure if there were such black swans at play in Ian’s case – his ultimate downside was an unprovoked attack by big black, which he prepared for by practicing over and over shooting a cardboard target that dragged towards him by a friend. But this wasn’t a unknown risk – rather, an extreme but well known one. Should a situation have evolved whereby TWO lions were attacking, that might have been a more uncertain risk, as I’m not sure if Ian’s plans ever anticipated such an eventuality.
My broader point is that even when you commit to a decision, have moved the odds in your favour through thorough research and have prepared for every possible eventuality, it still might be a good idea to spare a thought for those risks that you find it hard to see. Use scenario planning, or ask someone entirely disconnected from your situation to help you imagine what could bring the whole thing down. “What if all the correlations go to one?” was what LTCM should have asked in 1998. “What if US house prices drop 20%” should have been asked two years ago by a far larger number of stakeholders in the global economy.
So, to sum up this post:
What decisions have you made that you need to absolutely commit to?
How might you go about finding the signal amid all the noise, to help you succeed?
What risks are you unable to see yourself, and who can help you identify them and prepare?
Who wants to go on safari with me later this year?