A data-driven culture is about replacing gut feeling with decisions based on data-driven facts, be they simple vital figures such as revenue or profit, results from advanced analytics models, or even qualitative data.
For creating a data-driven culture, these 4 D’s of data culture are essential. By developing a surround sound culture of data such that every individual decision-maker can use the data, your team has worked hard to standardize and make it accessible. The surround-sound culture of data, i.e., a data-driven culture, is developed by maturing these Four Ds of Data Culture.
Data Maturity – Solid data maturity is foundational to a culture of data. Your organization’s data maturity manifests in every individual in your organization, having a comfortable and appropriate level of access to the data they need, and the information is clean and accurate. With a well-defined CDO role, most organizations are already on their way to a decent data maturity. In the next blog, I will discuss a measurable way to measure the current state of Data Maturity and how to fix the gap if you find any.
Data-Driven Leadership – Leaders define the culture of any organization. A data-driven leader supports a culture of data by emulating data-driven decision-making and holding their team accountable for their own decisions such that they become data-driven. A data-driven leader sees data as a strategic asset and makes “think and act data” a key strategic priority. In the next set of blogs, I will share more about measuring the current state of maturity of leaders and how to address the gap.
Data-Literacy – If the individual decision-makers don’t have an appropriate literacy level to leverage the data at hand and turn it into insights and decisions, data won’t deliver value, even if leaders are data-driven and data maturity is optimal. So the CDO office needs to invest in enterprise-wide data literacy, where every role gets upgraded with the right level of data science skill. I will talk about the various data literacy persona and assessments in the upcoming blogs in this series.
Data-Driven Decision Making Process – Lastly, there needs to be a structured process of forward-looking decision making and a backward review of those decisions. Additionally, data needs to be an integral part of that decision-making process to get value from data. Most organizations don’t have a systematic, data-driven decision-making process.