Culture is defined as the ideas, customs and social behaviour of a particular population or society. The word is derived from the Latin ‘cultura’, stemming from ‘colere’, meaning 'to cultivate’.
It generally refers to patterns of human activity and the symbolic structures that give such activities significance and importance.
Culture is made up of the knowledge, beliefs, arts, rules, customs, capabilities and habits of the individuals in these groups.
One can understand how the environment, plus the past, influence the development of culture. A simple example is water: the attitudes of communities in the Amazon versus those living in the Sahara will be very different, but both are shaped by environmental factors.
Organisational culture is no different − it is at once unique and specific to each entity, but at the same time all are influenced by knowledge, ideas, history, etc.
But what about data culture? Is it possible to have a data culture and not even have a data strategy?
What is data culture?
In a business context, it is defined as how a workforce uses analytics and statistics to optimise processes and accomplish their tasks. Data culture is no different to culture in general − it is influenced by behaviour, attitude and execution within specific groups.
Corporate culture and the environment heavily affect the current data culture of individuals, departments, or organisations. In the same way human cultures differ due to external and internal influences, how people respond to data within their organisations is also very different.
Data is the foundation of the digital economy. The first thing to understand about it is that not all data is equal.
For the few who are doubting the existence of data culture, let's get something out of the way quickly and that is that it exists in every organisation, whether they know it or not, and whether they are trying to influence it or not. This brings me to the first point on data culture: companies need to understand what their current data culture is before trying to influence it.
How to assess and start influencing culture
The need to get insight into the beliefs, attitudes, practices and artefacts used in the organisation as it relates to data, is the first step to influencing data culture. This can be done through an informal or more formal guided process of asking specific questions about how the organisation relates to data currently.
Key aspects to workshop include current attitudes towards data at the different levels within the company. There may be a thriving data culture in the sales or finance department due to a dynamic data-driven leader, but the rest of the organisation can be lagging due to a lack of top-down, bottom-up support. This is the starting point.
Data culture cannot be bought and implemented off the shelf, it must be built. Without buy-in from the top, there is no way to put in the sustained effort and resources needed to embed data-driven decision-making as part of the culture.
A one-size-fits-all approach is, therefore, not appropriate. However, certain essential elements need to be present for a data culture to be established, to survive and eventually thrive. I like to think of them as the building blocks of deriving value from data and I will explore how this relates to data culture.
Data, technology and people are the critical elements that need to be in place to build data culture.
Let's tackle these one at a time, starting with data. Data is the foundation of the digital economy. The first thing to understand about it is that not all data is equal.
Yes, data is just data − in that it is a record of identity or activity at a point in time. For example, a customer buying a cup of coffee and a doughnut is recorded on a point-of-sale system, but the way that data is transformed allows various people in the organisation to get quite different insights from it.
The store manager, sales manager, procurement department, and CEO and his board will all look at that transaction in different ways and formats. These can range from overall performance in the executive dashboard, or a daily sales report in the branch manager's inbox, through to tracking actual numbers against budget numbers in a dashboard for the sales director.
Or it may send an alert to ship coffee beans to the shipping and procurement department. So, it is important to support the various functions and delivery of the appropriate data to the right recipient if companies are to support data-driven decision-making across the organisation.
Next, identify the data challenges. Does the data strategy support the business strategy? Are there data pipelines that provide business-ready data and why are they needed?
For a data strategy to have any chance of long-term success and impact, it needs to be aligned with the organisation's strategy and goals. Data is fundamentally a decision support system, and it needs to be structured to answer business questions and provide insights as it relates to the business goals.
When it comes to analytics leadership, where data lives and who drives it is essential. It needs to be lobbied for, well-funded and integral to business strategic planning and embedded in business processes.
Understand where data has touchpoints in the business − both the formal and informal manifestations of data usage. It all forms part of the reality that is current culture.
In my next column in this series, I will expand on the critical elements that need to be in place in order to build data culture.
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