Data – is it all a blur?

Data – love it or hate it?

I’m a big fan of data, good data.  How do you feel about it?  Honestly now , how data literate are you?  And how data literate is your team?

It’s a BIG issue

The reason I’m asking this question is that I sense that the word data has taken on a new and mythical meaning ever since we started referring to “BIG data” often in conjunction with the term “AI”. And this is th point at which many people started hearing “BIG (scary) data” and started backing off.

If you’re pretty data literate you may be feeling that I’m making a mountain out of a molehill here but you love data so here are some stats that illustrate the scale of the problem:

  • According to a 2019 study by Accenture, Just 21% of the global workforce are fully confident in their data literacy skills — i.e., their ability to read, understand, question and work with data1
  • 74% report feeling overwhelmed or unhappy when working with data
  • And it’s not something that leaders are immune to –  only 32% of business executives feel able to create measurable value from data 

Trying to fix the problem and inadvertently making it worse

Businesses aware of the value of data and the need to make better use of it have typically introduced either a specialist data-analytics function and/or self-serve data analytics tools (More than 2/3 have access to business intelligence tools and data analytics software according to the Accenture study). While, on the other hand,  just 20% are focused on upskilling their workforce in general.

These efforts often compound the issue as staff, nervous of dealing with data, feel ill-equipped to use the tools provided and the existence of a specialist team confirms their creeping suspicion that data is the domain of data specialists.

Avoid! Avoid!

As data takes on these mythical proportions, perfectly intelligent people start to back away from it because they believe that it’s complex, technical and something they’re not qualified to get involved in. (Check out my blog on “digitisation” which definitely has the same response).  

These feelings result in people avoiding data:

  • The Accenture study found that 1/3 of those who feel overwhelmed by data find a way to fulfil the task without data. Furthermore, a minority of them will just avoid the task entirely.   
  • And leaders are people too – 2/3 of C-suite executives, senior managers and directors would go with their gut feeling over data-driven insight.

Is it any wonder then that 60% +  of all enterprise data is never analysed?

No surrender!

More worryingly still, those scared of data can be inclined to surrender – discounting their own expertise and common business sense “well it doesn’t seem right to me, but I’m not a data expert” laying businesses vulnerable to misuse and misinterpretation of data.

Debunking the myth

We need to debunk the myth that data is something new and scary: data is that stuff you’ve been using for years, the facts and figures about your business, your market, your customers – it might have become bigger but it’s still the same stuff. And this stuff is critically important. So it needs to be on everyone’s job spec not just that of the data science team.

Data is just meaningless numbers unless someone with an understanding of the business and market context is there to specify the data cuts and interpret it.  We need data experts, but we need them to work with the rest of the business. They need to make data accessible and digestible to the business vs blind the team with data science.

It’s all about data literacy

A good way to focus on ensuring the data literacy of your team is by having a data literacy strategy. 

The term data literacy itself can sound quite scary but it’s really not – here’s a very simple definition from MIT Sloan –  the ability to:

  • read data, which means understanding what data is and the aspects of the world it represents.
  • work with data, including creating, acquiring, cleaning, and managing it.
  • analyse data, which involves filtering, sorting, aggregating, comparing, and performing other analytic operations on it.
  • argue with data, which means using data to support a larger narrative that is intended to communicate some message or story to a particular audience.

And another thing that makes this less scary is that, importantly, we don’t all have to master all of these aspects of data literacy to the same level – it’s about having the right level of data literacy for your role.

How to build data literacy

It’s great to see a growing lobby for data literacy to be taught in school, however that doesn’t solve the problem for businesses now.  So it’s down to businesses to make sure their teams are well equipped to make good use of the wealth of data available.  The great news here is that this doesn’t require extensive investment – it’s really accessible to any business. 

There are a wealth of free resources available to guide you in upskilling your team such as those provided by The Data Literacy Project.   

And many how-to guides which typically boil the process down to:

  1. Determine which skills are needed by whom
  2. Develop a roadmap to get there
  3. Provide training to upskill your team

So what’s holding you back?

Fancy some further reading?

This Accenture/The Data Literacy Project report is great for arguing the case for focusing on data literacy in your team.

This MIT Sloan article gives a guide on how to implement a data literacy strategy

And Here’s a handy read from Harvard Business Review which provides a clear guide on how to boost your team’s data literacy.

And do check out the resources provide by The Data Literacy Project.