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Data is everywhere in a modern organisation. So are the tools, platforms, and applications which promise us shortcuts to valuable insights. But are technology alone enough? More business leaders are starting to realise that having a healthy data culture is paramount to becoming a data-driven organisation. The question is: how?
First, let’s take a look at what a data culture is. According to AI thought leader Ganes Kesari, “Data culture is the collective behaviour and beliefs of people in how they use (or don’t use) data for decision-making.” In a healthy data culture, everyone in the organisation – from C-level executives to shop floor operators and store clerks – recognises the value of data, takes ownership over it, and knows where to find and how to access relevant insights.
“It’s all about ‘spreading the data magic’ across the organisation,” says Bart Teetaert, Data Culture Lead at delaware. “No matter how you look at it: everyone is already working with data, even if they don’t realise it. The goal is to make people sensitive to its value and the opportunities it creates, and to instil a sense of responsibility and ownership. This goes way beyond the usual ‘data experts’: in a utilities company, for example, every meter reader plays a crucial role in safeguarding the quality and accuracy of the data.”
According to Bart, there’s a large group of people at almost every company who are actively working with data every day, but wouldn’t consider themselves as such. “They’re the people for whom making spreadsheets is second nature. Without realising it, they’re constantly deriving insights from data. With awareness-building and the right tools and training we could make their lives a lot easier and give them a newfound sense of purpose.”
Does that mean everyone needs to be a data analyst? “No, not at all. But everyone needs to be on board, otherwise any fancy tool you implement will be left unused or misused. If the data and insights are there, but no one goes looking for them, they have no value. For example, if the same production machine keeps breaking down, will you just keep fixing it? Or will your start looking for causes, like current peaks, lack of training, etc.?”
“This example also shows that data culture shouldn’t be limited to finance, controlling and sales & marketing. People on the shop floor need to be aware of the value of data as well, so they can build the intuition to start looking for insights. Moreover, it’s important to realise that everyone in the organisation has different data needs, depending on their role. As an organisation, you need to make sure those needs are met. ”
The data culture team at delaware has identified four foundations for a healthy data culture:
Does everyone in my organisation – from operators to finance controllers and C-level managers – have the mindset, skills and knowledge to fulfil their unique data needs?
How is data organised within the organisation? Is it centralised or decentralised? Who is watching over data accuracy and quality? How are the other roles and responsibilities concerning data divided? Bart: “Without ownership, it’s hard to extract value from data. For example, even if there’s a quality checklist, someone needs to have the mandate to stop production when defective items are produced. Also: make sure everyone has access to relevant data and safeguarding data quality.“
Does everyone know what data are available in the organisation, and where they can find it? Are we aligned on data taxonomy, i.e., do we agree on what constitutes a ‘customer’, ‘prospect’, ‘sale’, etc.? And what KPIs do we have? Bart: “This is crucial for measuring success. If you make the change from one tool to another mandatory, your user adoption rate doesn’t mean a lot. People might be using it, but are they using it right? And do they like using it?”
Is our approach to data widely-supported within the organisation? Do we have solid first-line support in place?
The latter also fits in with Bart’s ideal image of a healthy data culture: “You want to end up in a situation where data questions are coming from within your business community, instead of being imposed by your IT or data team. For example, some field service technician is noticing a certain pattern emerge, has an idea for a potential use case, and asks IT to point them to the right data. I always like to use the sailing metaphor, where the boat is the data community and IT is the wind in its sails.”
Of course, building this kind of culture doesn’t happen overnight. But there’s a lot organisations can start doing right now.
“As the adage goes: ‘data is the new soil on which companies can strengthen their position’,” Bart concludes. “That is, if your people know how to farm the land and can actively use data insights. Only then will we be able to move from gut-driven to data-driven decision making.”
