Is your organization struggling to kick-start its data-science journey?
Many organizations struggle at the beginning with their data-science initiatives. Sometimes the issues are political, other times they simply lack the organizational maturity to begin such an initiative. However, quite often, the organization is simply missing one of the key ingredients to success.
So what is it about companies like Google, Amazon, and Facebook that make them so successful at transforming data into actionable insight? Understanding the full picture is a bit complicated. However, there are five key ingredients that I commonly see across all successful data-driven organizations.
First, we need a strategy for becoming a data-driven organization. Our data-science strategy defines key aspects about how we do business. It needs to answer questions like: What people do we need on our data science team? What data should we collect and how should it be collected? What technology will be required to achieve our goals? And how we will grow a culture of data science within our organization?
Second, we need the right people to help execute this strategy. We want people that value evidenced-based reasoning, that think like scientists, and can use data to drive business outcomes. This means acquiring individuals with a background in data science and training existing employees how to think more like a data scientist.
The third ingredient is data. We need data in order to derive actionable insight, so we need access to the right data. In addition, we want our data to be accurate, reliable, timely, and available. So, we need to invest time and resources collecting, cleaning, storing, and organizing our data. Data is an investment in the future of our business so we need to treat it like a strategic asset.
Fourth, we need the right technology. Technology is necessary to build our data-science pipeline, to analyze our data, and automate decision-making processes. Choosing the right technology can make a huge difference in the long-term costs, benefits, and overall ROI of a data-science strategy.
Finally, we need to cultivate a data-driven culture. We need to change the mindset of the entire organization to one that values experimentation, evidence-based reasoning, and data-driven decision making. This is probably the most important of the five ingredients. However, it is also the most difficult because it can’t be bought, hired, or acquired; it has to evolve over time. We do this by encouraging certain data-driven behaviors and discouraging other non-data-driven behaviors.
Unfortunately, we can’t just throw all of these ingredients into an easy-bake oven and expect a data-driven organization to emerge, fully baked. It takes a continuous and deliberate effort in order to transform our organization with data science. However, knowing what the key ingredients to success are, is the first step in this process.
To learn more about becoming a data-driven organization, please check out my online courses on data science.