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How to build a data-driven culture

Photo by Markus Spiske on Unsplash

An effective data-driven organisational culture is essential to optimise a new data platform. But creating and embedding that culture is often far more difficult than the technology project that delivered the new platforms. 

Data-driven decision makers use evidence to make critical business choices and strategies. Changing decision-making processes to use a consistent data source isn’t as easy as it sounds. It’s a shift in mindset which can be really difficult within an organisation. The upside of a data-driven culture is that the entire business takes decisions based on solid evidence, rather than gut feel or any other subjective measure.  

And it’s effective. McKinsey Global Institute has found data-driven business were 20 times more likely to acquire new business and six times more likely to retain customers. This is a cultural change that’s worth making. 

We know cultural change can be difficult but also that it’s not impossible. 

Francis North’s data specialists have shared their tips for building a data-driven culture, based on years of working with clients and observing what works.  

Top-down endorsement 

When executive teams lead by example, they set the behaviour that the rest of the organisation will follow. Demonstrating they’re making decisions based on data, not opinion, will show expected practices to the rest of the organisation. It’s also important for leaders to empower others to use the same data platforms for decision making to democratise their use.   

Furthermore, leaders in an organisation with a data-driven culture will set the expectation that hard numbers should back critical updates and decisions. 


The whole organisation can access data 

The power of data is truly unleashed when the whole organisation uses it. Of course, some data sets may be sensitive and will be rightfully ring-fenced for protection, but the bulk of an organisation’s data should be made available to all staff. From our experience, it’s often more effective to release a small number of key data sets or metrics over a period of time instead of opening the floodgates to everything. This approach will help the organisation gradually understand the data available and how to use it, instead of overwhelming everyone with a tsunami of data. 


Provide training, at the right time 

Naturally, it’s important that all end-users of the new data platform receive training in how to use it. This should also include context for each data set so there’s a common understanding across the organisation about the ‘language’ the data speaks. 


The timing of this training is critical: not so early that the attendees forget what they’ve learned, and not so late that they’re frustrated with trying to work things out themselves. 


Deliver tools to enable self-service 

Ticketing tools like Service Now revolutionised IT Service Desk operations because they enabled the end-user to lodge a request or even fulfil it themselves. The same paradigm applies in the data world. Consider a ticketing tool that logs prioritised requests for the data team to process or, even better, a platform that exposes data to end-users in a meaningful way. 

There are several benefits to this approach: It frees up the data team to focus on data mining and analysis meaning less context switching. It also empowers individuals in the broader business to use basic data sets for key decisions. 


Don’t hide the data team 

The data team will rapidly become an in-demand resource in the organisation. They’ll be busy but they shouldn’t be secreted away. Consider the best organisational structure for this function. It could be that you begin with a decentralised data team and once the organisation is more mature, that could become a centralised function.  


Treat data as a product 

Applying a product mindset to data will help ensure there is a consistent set of features to all data the organisation collects. This approach can help define important aspects of your data, like security, accuracy and consistency.  This enables a consistent understanding of each dataset across the organisation, as well as a consistent approach to collection and analysis. 

Contact us to learn more about creating a data-driven culture in your organisation. 

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