Skip to main content

The importance of data literacy and data scientists


I was reading up on a subject that caught my attention, namely data literacy and the need of data scientist within corporations.

So, why do I think this is a topic of interest? Since more and more IT budget/purchases are made outside the IT department the need for data literacy is obvious - to prevent a chaos-like IT environment. Also, as innovation speed and customer experience is expected to rise to a totally new level – data scientists will be of the essence!

Two articles caught my attention:


In the first one, Gartner is explaining how the CIOs can make an impact on creating an organisational culture that is data-literate and values information as an asset. The author of the article, Sarah Hippold says:

Literacy is no longer defined as just the ability to read and write. There are several other skills people must master in order to solve problems and gain knowledge. Data literacy — the ability to read, write and communicate data in context — is among the most important abilities for organizations today.

And elaborates under the headlines:

  • Business value of data

    • Get real data to make evidence based decisions, as opposed to hippo based decisions (hippo being highest payed person's opinion)

  • Cultural impacts of a data-driven approach

    • Sharing is caring, data collected in one department can be used in another one

  • Ethical implications of data and analytics

    • Tightly linked to branding and corporate identity


In the second, Eric Colson from Harvard Business Review is writing about why data scientists will have to be generalists instead of specialists and why curiosity will be an important quality.

Eric suggests that, to get the best out of your data scientists you should:

  • Position data science as its own entity

    • Closely cooperating with the entire organisation

  • Equip your data scientists with all the technical resources they need to be autonomous

    • Cloud architecture for elasticity and delivery performance, more information on this: Cloud done the right way by Kirsti Stien

  • Have a culture that supports a steady process of learning and experimentation

    • The culture will not survive on its own, it must permeate the entire organisation


Would you like to read more about culture, my colleague Henrik Gavelli has written a piece on the subject: Culture eats everything for lunch – and certainly digital transformation

I have elaborated on the link between experimentation and innovation and how it affect success in this blog post: The close link between experimentation and innovation.

Enabling core capabilities, internally and externally

The other day I had the pleasure to listen to Stephanie L Woerner giving a presentation on “Digital business model”. She talked about how companies should service enable their core capabilities, internally as well as externally (e.g. expose their APIs).

Also she talked about the important role of IT departments, who are among other, experts on security, compliance and regulations.

They are perfectly suited to help the organisation increase their overall data literacy. For instance through IT playbooks, with advice and guidelines on how to be data-driven. 

Woerner is a research scientist at MIT CISR and co-author of the book ”What's your digital business model?”. Which, through 6 questions help you build the next generation enterprise. The 6 questions are organised under the headlines:

  • Digital threat

  • Business model

  • Competitive advantage

  • Connect

  • Capabilities

  • Leadership


Each worth further exploration and explanation, but I will refrain from doing that in this blog post, with the aspiration to get back to it in a future post.

But what about the ethics?

During the Q&A session after Stephanie's presentation subject of data collection, storing, analytics, usage came into focus. 

With loads of data, possibilities to benefit from it, draw conclusions from it, see patterns, find new revenue streams, and so on – is there a catch? Maybe not a catch but still a really important issue to address. The ethical side to it.

How will we handle the integrity of those that provide us with the data, our customers? How much of the data do we really need? How are we using it? Where does it come from? Some of this is of course regulated by law. But equally important is the data that is not.

We need to sit down and talk about this and draw up guidelines and decide on how we will act to earn the respect of our stakeholders - a miss-used trust can be costly!

Discussing APIs and eco systems with Mrs Evançs

So, how come I started thinking about this in the first place? It was after I meet Mrs Evançs (the name of my book club, of 11 odd years), made up of seven individuals working within insurance, finance, law and consulting.

Last time we meet and were supposed to review the book we had read, we started talking about APIs and eco systems.... Hello! In my book club! Who would have guessed? Not me anyway. 

But at the same time it showed how we are all affected by the digital transformation. All ages, all industries, all roles. This is why we all need to educate ourselves in this field, and to get a bit more data literate. So that we can talk to our data scientists and IT departments in a professional and fruitful way.

And start to explore the immense possibilities of the digital transformation - which is not just about a technology change.

Written by Susannah Eriksson