You don’t have to be a data scientist to be data savvy. And that’s a good thing.
Many companies are putting massive focus on recruiting the rare beasts that are data scientists. But in doing so, they often forget the need for creating a much more data savvy culture overall.
Data is already becoming ubiquitous in business as well as in daily life. It used to be that the IT department could be contained to its own office or floor, but today, it’s becoming harder and harder to segregate the realm of data from any other aspect of business.
That means that data — and the application and analysis of said data — is going to become more and more important in every department, from sales to HR and from R&D to marketing.
The good news is that you don’t have to know how to code or do advanced maths to become data-savvy. In fact, you don’t have to be particularly tech savvy at all. What you do have to do is adopt a data-friendly mindset.
Whether you are looking to lead the way as a data-savvy employee, or lead the charge for culture change as a manager or C-level executive, here are some suggestions for encouraging everyone in your organization to become data savvy:
Embrace the idea that data is everywhere. It shouldn’t be too hard; the average employee interacts with data every day though his or her phone, personal email, and apps like Netflix and Amazon. Some basic understanding of what data is and how it is collected is all that is needed to start to see the bigger picture. If you can store it, you can analyse it; so what data do you already store in your job? What could you learn from it? Focus on how to ask the right questions rather than the method of arriving at the answers. I’ve written before about the fact that the biggest problem with big data isn’t the data itself, but that we are asking the wrong questions. The average employee doesn’t need to know how to write an algorithm or even query a database. What she does need to learn is how to ask the right questions — the ones that will actually help solve her business problems.
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