Eyram Adjaku
Building a data driven organisation

Data and analytics are currently receiving vast amounts of attention in the media. With the advances being made in both the mathematical sciences and computing systems, it has become relatively easy to implement and deploy extremely advanced machine learning models. In spite of this, most respondents to a recent Gartner survey are in the lowest 3 levels of a 5 level analytics maturity scale. Only 9 percent of companies reported themselves at the highest level where data and analytics are central to their business strategy.
Building a data driven organisation isn't easy. In a previous blog post we wrote about how to start the journey. Regardless of its size or the industry in which it operates, every business has the potential to use their data more effectively. The diagram above shows the different ways in which business units can create value by implementing analytics and data science.
In the diagram, the black text along each arrow describes the relationship between the two entities and the red text shows the data science project or use case that make this relationship more profitable, efficient or optimal. Support areas such as finance, operations and human resources also have opportunities to be more efficient and innovative through analytics and data science.