We’re Not Risk-Averse, We’re Variance-Averse

Risk Averse or Variance Averse?

Often, people tell me that they can’t innovate, because they are in risk-averse organisations.

I don’t think this is true.

First off, think about insurance companies.  They buy risk – they are actually risk-loving firms.  But many of them struggle to innovate – they are often deeply conservative.  What gives?

They buy risk because when they have enough collective risk, it averages out to (normally) a fairly predictable set of outcomes.  The whole business is built to reduce variance.  The innovation difficulty comes not from risk aversion, but from a fear of variance.

In my classes I often use an innovation simulation that illustrates some of the challenges of dealing with radical innovation.  Often, when students go through the complex version of this exercise the first time, they get fired.  Why? Because there is too much variance between their forecast sales and their actual results.

In the simulation, the firm is dealing with high levels of risk – but it’s not the risk that gets you fired, it’s the variance.

People like predictable outcomes.  Managers often need predictable outcomes.

So when someone says that their firm is risk-averse, it almost always means that, really, they are variance-averse.

 The Plate Tectonics of Innovation

This variance-aversion is ok, if your firm lives in a completely stable environment.  But it is a problem if we suppress variance – because that only leads to big (usually unpleasant) surprises.

Plate tectonics make a good analogy here.  Here is a diagram of a typical subduction zone that leads to earthquakes, volcanoes, and tsunamis.

subduction zone

The oceanic plates slowly expand over time.  When they meet the thicker continental plates, they slide underneath them.  The oceanic plate melts, and this heat causes volcanoes.

It is friction between the plates that causes earthquakes.  As the two plates slide past each other, they catch and become stuck.  Over time, the pressure builds up, until it becomes so great that the plates eventually jump past each other.  That’s an earthquake.

If the plates just slid continuously past each other, we wouldn’t have this type of earthquake.  There would be no pressure to release.

When the environment that we operate in changes, we have two choices.  We can adjust on a more or less continuous basis (innovation!) – this increases variance in returns, but it also reduces friction between our business model and the environment it operates within.  Since people don’t like this increase in variance, we often try to suppress it.  If we do this, the changes slowly build up pressure on our business model, until the pressure (and the business model) bursts.

Experimenting to Increase Variance

This is exactly the issue that Nassim Nicholas Taleb addresses in Antifragile.  He says:

We can simplify the relationships between fragility, errors, and antifragility as follows. When you are fragile, you depend on things following the exact planned course, with as little deviation as possible—for deviations are more harmful than helpful. This is why the fragile needs to be very predictive in its approach, and, conversely, predictive systems cause fragility. When you want deviations, and you don’t care about the possible dispersion of outcomes that the future can bring, since most will be helpful, you are antifragile. Further, the random element in trial and error is not quite random, if it is carried out rationally, using error as a source of information. If every trial provides you with information about what does not work, you start zooming in on a solution—so every attempt becomes more valuable, more like an expense than an error. And of course you make discoveries along the way.

In order to avoid being blown up by innovation tectonics, we need to experiment.  That is the point of the Innovation Loop:

The Innovation Loop

This is an approach that can help your organisation learn to love variance – and that is a healthier approach over the long-term.

The next time someone tells you that their organisation is risk-averse, stop to consider whether or not it is really variance that they are trying to avoid.  If it is, Shane Parrish outlines five steps from Taleb that can help you learn to love variance instead.

You should check them out, and use the Innovation Loop to help you build your experimental approach to business and innovation.  That will make it less likely that your business model will blow up.

(diagram from Wikimedia Commons under a Creative Commons License)

 

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Student and teacher of innovation - University of Queensland Business School - links to academic papers, twitter, and so on can be found here.

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8 thoughts on “We’re Not Risk-Averse, We’re Variance-Averse

  1. Tim- Like you I think there are innovation tectonic plates. I wrote about this in a post sometime back I’d like to share. It opens with I’ve always loved this: “appropriate adaptiveness is not a natural tension- it has to be designed.”

    http://paul4innovating.com/2011/10/28/designing-appropriate-tension-into-the-innovation-process/

    The insight can be often applied to innovation:

    “The dynamics of the system will be dominated by the slow components, with the rapid components simply following along. Slow constrains quick, slow controls quick”

    Tension occurs as faster changing layers sheer against slower ones, impatience and resistant ‘kick in’ when innovation is demanded, or promised and is not delivered as expected. Knowing the tension points and recognizing their negative effect needs designing out. Again we need to have appropriate adaptiveness designed in, we need to place tension into a context and we need to keep it creative in tension.

    So for me it is less about variance more about the tensions this sheering effect has on the innovation system- Does this make sense? Regards Paul

    • Thanks for sharing that Paul. I see what you mean about the sheering effect, & I agree with it. I think we’re talking about two slightly different things – you’re discussing tempo (which is a really interesting angle) and I’m on to variance. Different issues, same metaphor!

  2. Tim, I enjoy your posts. I hope your students appreciate that they have you as an instructor. I agree with what you describe. Another related and interesting phenomena: very often in a corporate setting, there is insufficient time built in to experiment. There is also almost never slack time built in to schedules. As a result, many companies assume unnecessary risk in their development programs that could be avoided through more careful planning.

    • Thanks Michael. The issue of slack is a huge one, and I haven’t really addressed it yet on the blog. It’s a very under-discussed issue, and one of the main reasons that the drive for efficiency can be so counter-productive.