You wear activity tracking watches that link to an app that monitors your steps, your calories burned, your sleep patterns. You put samples of your self-collected blood through the post to get results on your phone to monitor your health and to find out your genetic predispositions for diseases. You track your fertility, HIIT classes, glasses of water consumed and running routes.
Now more than ever we have health data at our fingertips and can track and manage our health. Health used to be something akin to luck, something unpredictable and hard to pin down, but no more – we have the data! Organisational culture is currently seen by many as equally ineffable, unmanageable and unpredictable. However, like your health, it doesn’t have to be.
In the previous article ‘Making changes to improve your cultural health‘, we touched on the importance of monitoring when making changes to your organisational culture. Ensuring they are having the desired effect, or indeed any effect at all. But what data points should you track? The amount and quality of the KPIs, metrics and data points an organisation has depends on its size, the nature of its business and the maturity of its management information practices and/or infrastructure. Large matrix organisations often have hundreds of data points, whilst smaller businesses might only track financial metrics.
What should you monitor
After spending many years working with businesses to create culture dashboards, models and complex modelling tools; I have found two approaches particularly useful.
1. Coat hanger questions
The first is defining the overarching questions that you have about your cultural and strategic priorities and build the metrics off those questions, for instance: why are our we not innovating? Why is our organisation slow to make decisions? These ‘coat hanger questions’ allow you to hone in on the metrics that matter. In our health analogy, this is akin to asking the coat hanger question ‘Why I am sleeping badly?’, then monitoring your sleep patterns, coffee consumption and daily activity levels. With your organisation’s culture, one of your priority questions might be ‘Why are we losing staff in x department?’. This could lead you to perform data analysis on engagement scores in that department, performance management scores, sentiment analysis from the free text of leader 360 assessments and exit interview surveys etc.
2. Managing and monitoring
The second is to focus on managing a handful of key metrics (in the health analogy this is akin to measuring cholesterol, blood sugar, iron, liver function, kidney function) and keep monitoring some sub-metrics that help further explore the key metrics (like biomarkers of LDL, HDL, cholesterol ratio, Bilirubin or Globulin). In an organisational setting I’ve seen this as managing employee engagement, gender pay gap, D&I metrics around gender and BAME; alongside monitoring engagement by demographic, discretionary/bonus pay gap, BAME by grade etc.
This is a pragmatic approach that avoids putting all your metrics in a table, mark them red-amber-green and never finding a use for them – or acting on them. This metrics-first model triggered me to develop the culture health model. It is a way of building and evolving culture metrics for organisations, whatever their size, and using them to drill down on cultural issues as they arise. Based on principles of behavioural science, it is split by the key facets of organisational culture. In essence, all good data analytics tools and devices should take complex data and make it so simple it becomes part of our everyday life (cue the success of health devices and apps).
Pioneering organisations can now predict cultural issues before they happen. Whether that be predicting conduct issues on the trade floor through voice recognition technology and instant messenger keyword tracking, or tech giants predicting an employee is about to leave the organisation three months before they formally resign. Predictive analytics for culture can be hugely beneficial for the avoidance of conduct and reputational issues, as well as talent attrition. At Gate One, we work with organisations to develop predictive analytics that spot cultural issues on the horizon and drill down into the key indicators of cultural health.
”Predictive analytics for culture can be hugely beneficial for the avoidance of conduct and reputational issues, as well as talent attrition.