The biggest problem facing companies who are trying to innovate and transform themselves with data is a culture of “we’ve always done it this way.”
A data culture isn’t just about deploying technology alone, it’s about changing culture so that every organization, every team and every individual is empowered to do great things because of the data at their fingertips.
If there is one common theme that runs consistently throughout this book, it is the importance of culture. As we imagine data flowing through the analytics value chain, there are a number of different touchpoints; some are human, and some are technological, but they are all shaped by the prevailing culture. Culture influences who has access, what can be shared, and what investments are made into people and tools. Moreover, as I covered in the previous chapter, culture also determines whether the last link in the chain is driven by HiPPOs or by facts.
In this chapter, I draw out these different aspects more explicitly and in more detail and bring them together in one place to paint a more coherent picture of an idealized data-driven organization. I will first discuss the data-centric foundations: data access, sharing, and broad training to make use of the data. Next, I cover a goals-first culture; that is to say, defining experimental design, metrics, and success criteria up front, and also the ability for results, interpretation, and analysis to be discussed ...