It seems that more and more organisations are seeking to be ‘data driven’. This started many years ago now with a small cohort of companies, however it really does seem to be included somewhere in the charter or strategy of almost every company we encounter. And it is something that puzzles me to be honest. Why would you let data drive??
Don’t get me wrong, data is a critical element of any considered strategy. It establishes the science of forecasts, allows for more accurate predictions and trends analysis and measures the effect of change. It also allows us to put economic units on strategies in a meaningful way. Data can be utilised in a myriad of ways, and if you are creative and disciplined enough it will set you apart from your competition.
However, what data doesn’t do is consider options, make decisions, weigh up investors reactions and sentiments, consider risk profiles or interrogate anomalies. However, it does inform all of these activities wonderfully. The critical input (other than quality data of course!) is a human being to interpret the data and take responsibility for the subsequent decisions and outcomes.
We strongly advocate data-informed organisations and strategies. They are scientific, defensible and measurable. Data helps make strategy a living, breathing, relevant thing to employees, stakeholders, shareholders and Boards. Data a key ingredient to success and survival, and will only become more so in the future.
So how do you ensure you aren’t letting the data drive?
Robustly question the data. Valid data will only become more valid and robust under scrutiny. Compare multiple sources and types of data to identify anomalies. This will help identify any issues in the interpretation of the data narrative, or issues in the collection process.Consider how you actually feel not just the data – if it makes you nervous you need to investigate why. Trust yourself to know better – sometimes the data appears to point in the wrong direction. Trust yourself to know when it’s wrong.Set clear desired outcomes – the data needs to be used for a specific purpose. Make sure this is focused. Don’t let the data determine its’ own purpose.