Here’s the thing – accurately predicting either the weather or future corporate behaviours has historically been exceptionally difficult.   Making accurate predictions in either field requires the development of complex models, the ability to process significant amounts of data in real time and an appreciation of the complex nature of the system. However, it would now appear that the meteorologists are significantly further ahead in their attempts to accurately predict the weather than the “culturologists” are in their attempts to predict corporate behavioural outcomes. Why is this and what, if anything, can culturologists learn from meteorologists?

Since the first cavemen cancelled a hunting trip because of flooding, we humans have yearned to accurately predict the weather – hoping that through accurate insight we could gain control over and reduce the risks posed by our environment. An individual who could, with certainty, forecast droughts and rains, was always highly valued by history’s leaders – making forecasting a popular job – even if the role often had a similar tenure to that of a Premier League manager and a tedious tendency to end in death. Unfortunately, whether it was through determining the texture of seaweed, reviewing the state of an animals entrails or direct trance-like communication with the divine that enabled the forecaster to foretell the meteorological future, it has historically been an incredibly unreliable science.

In fact, it wasn’t until as recently as the 1950’s, and the availability of the computing technology required to run the calculations underpinning the newly developed complex mathematical climate models, that meteorology began to gain any real predictive power.   The 21st century has seen two further developments that have significantly improved the accuracy of forecasting. The first is simply the availability of masses of real-time data from multiple sources and the second is the application of chaos theory to the mathematical climate models that has enabled meteorologists to hone and weight their models to create multiple possible outcomes from similar starting data.

So what does any of this have to do with culture and people risk. Well here’s the thing. This historic desire to accurately predict the future has also applied to human and corporate behaviour as well as the climate – with the disciplines of philosophy, politics, economics, sociology and psychology all attempting to create models capable of predicting future corporate outcomes. Whilst generally faring better throughout the 19th and 20th centuries with regard to the perceived level of usefulness of their descriptive models these social sciences have actually failed to produce models that stand up to scrutiny when assessed for their predictive accuracy. When it comes to models of culture that can predict future behaviour and outcomes then it feels like culturologists are only just getting past the behavioural equivalent of consulting the seaweed.

Cultural systems are, by their nature, incredibly complex and, if we are to understand them it will require all the real-time data, sophisticated mathematical models and appreciation of complexity that the meteorologists required to create reasonably predictive models of our climate. To date predictors of behavioural outcomes have virtually none of these basic building blocks from which to create an effective, predictable model of culture. Most models of culture taking on the appearance of simple explanatory wheels or pyramids with some western orientated homilies in place to support their underlying logic.

Ironically the desire to be able to understand, analyse and predict the risks inherent in a culture are more important than ever. In Financial Services the Financial Conduct Authority (FCA) has committed itself to analysing and assessing the suitability of the culture of the firms they regulate – with a view to sanctioning those firms who have, what they consider, an unsuitable or poor culture. However, unsurprisingly, they have not made reference to any of the tools they might use to carry out this assessment or to suggest how a positive or negative culture might be recognised in anything other than the broadest terms.

So, when it comes to meaningful cultural analysis, is it all doom and gloom and are we (and the FCA) still decades away from being able to accurately predict future business outcomes based on studying the current culture – well mostly – but there are a few bright points beginning to emerge from the darkness.

Perhaps the biggest challenge on the journey towards accurately predicting business outcomes from cultural analysis is to be able to define and agree the elements that exact an effect on a culture.   In meteorology there are an agreed set of variables such as wind speed, air temperature, sea temperature, air pressure and lunar patterns etc. that have all been acknowledged to have an effect on the weather and can therefore be added to the sophisticated mathematical models that underpin meteorological predictions. The arguments amongst meteorologists are then about the level of impact of the elements on the models not about whether or not the element has an effect.

Unfortunately, no such widely agreed set of elements has been derived from the study of culture.   Over the last couple of decades a number of attempts have been made to define the elements that affect a business culture but to date there is no defined list and certainly no sophisticated predictive mathematical models created from the elements in the list. At The Compliance Foundation (TCF), they have their own list of elements but are deeply aware of its limitations and its lack of underpinning scientific rigour. However, it is a start and in their opinion a much more useful model than a homiletic wheel or pyramid.

The second challenge on the journey towards accurately predicting business outcomes from cultural analysis relates to the collection and analysis of real-time cultural data. The good news is that due to recent advances in technology and the emergence of new approaches to capture and analyse “big data” that this problem should be surmountable if we can all agree on the nature of the data that needs to be collected and analysed as per the challenge outlined above. TCF work with technology pioneers in this space to understand how to practically collect and analyse the vast amounts of data required to make a reasonably accurate prediction

The third challenge on the journey towards accurately predicting business outcomes from cultural analysis is related to the concepts of chaos and complexity. Business cultures don’t exist in a vacuum and just as the local weather will be affected by global trends (e.g. global warming), so will a business culture be affected by geo-political trends.   TCF’s models of culture need to a) recognise these trends and b) factor them into our emerging models. At the other end of the scale local weather can be affected by very local events e.g. a volcanic eruption. So too can an organisation’s culture be directly affected by the actions of individuals within it e.g. a CEO’s behaviour. Again models need to acknowledge and factor the potential impact of these localised events into the calculations.

TCF have created a three tiered model that describes the need to consider both the geo-political and individual behavioural impacts on a businesses culture. Again it is far from perfect but it does at least provide a framework for debate and a suggestion of the types of data that should be collected and analysed.

In addition, just like the meteorologists have done, TCF also acknowledge that tiny differences in the starting cultural conditions can, just like the butterfly flapping its wings, make huge differences to the outcome. To that extent TCF are also advocating that whatever models are used to predict cultural outcomes, that they are capable of running multiple scenarios and taking an aggregated view. The predictive weather forecasts we receive today in the UK are generated from at least 50 different possible sequences of events – we want to see our cultural forecasts being constructed in the same way.

To conclude, there is an inordinate amount of work still to do before we can accurately predict business outcomes based on an analysis of the culture, but, if we are prepared to allocate the necessary resources and learn the lessons from meteorology we can relatively quickly start to make good progress.  TCF are committed to working with academic institutions and progressive businesses to test thinking, build better models and create healthier business cultures that the regulators can assess and where necessary improve.

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