A new gap has emerged in the marketing community; the gap between the data scientist and the marketer. This gap has become more evident in the past few years with the emerging Big Data industry and the associated data it has brought to bear, resulting in a data literacy issue amongst today’s marketer.
The challenge with data literacy is that it is very difficult to diagnose and even more challenging to solve. There is tremendous growth in the data science community and many organizations are staffing more analysts, but the business side of the equation is not keeping pace.
Still, filling this gap won’t be as challenging as one may think. Social Media tools have helped democratize data, giving people access to their own performance – how many Facebook likes their recent posts achieved, how many people have recently viewed their LinkedIn profile, and what is their Klout score, to name a few. This democratization has created a new class of data consumer. Those armed with enough passive experience with data, but very little knowledge of what is required to actually analyze it. This is often referred to as someone who is “too dangerous for their own good”; someone who has a little bit of knowledge and a good amount of power (or budget).
Getting the business side of the data equation trained will be a business critical activity to help companies, as data is a requirement in all job functions. This challenge won’t be solved in 2015, but we can start.
Data literacy starts with data consumption.
Getting the non-data community familiar and using data is the first step. Data and analysis are often trapped – trapped in presentations, spreadsheets and dashboards. The method on how various analysis were conducted are even more remote, often in the brain of the analyst or documented somewhere deep in the folders of a shared directory.
Surfacing data in ways that people can see and explore are incredibly helpful. Not in quarterly reports or press releases, but in the open, in workspaces, in meeting rooms where people can discuss and hypothesize what is happening.
There are some great examples of organizations helping to increase data literacy and consumption through installations and visualizations.
The Yale School of Management developed a three-story display installation to deliver insightful information and photography from students, staff and guest speakers.
If there is one needle to move, it is to start solving the data literacy challenge. Organizations who do so will benefit. At the very least, it will start new conversations around data. And hopefully it will drive more fact-based decision-making, which can‘t be all that bad.