Author | Marketer | Speaker

I help companies turn data, ideas and relationships into reach and influence. 

Data Literacy: An Inevitable Opportunity

I wrote this piece for Texas Enterprise in December, 2013, and just received notice that they'll be scrubbing their site of all guest contributions soon. Weird, but OK. My thoughts on data literacy have evolved a bit since then, but I still agree with everything I wrote (as if it's so long ago). 

I'll be speaking about data literacy at C3 in October. Speaking of, well, speaking...I'm doing more and more of it. Click here for more info / to book me. 

One more quick note. I left The Economist to resume consulting full time. Focus areas: brand architecture, positioning, digital/content/social strategy, copywriting. Ping me here if you'd like to discuss working together. 


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Do you want companies to have more of your data?

This question kicked off my exploration of data literacy at the University of Texas at Austin School of Information on Nov. 20. Businesses need to prepare themselves for this question to become commonplace, and very few are even close to being ready.

Consumers have become used to an almost comically lopsided transaction: Companies take and use consumer data for their ends — often without consumer knowledge or real comprehension — while offering them very little in return.

In those rare instances when companies do communicate with consumers about data collection in plain language, they’ll say things like, “We’re using your data to serve you more relevant advertising.”

If that’s the only value proposition your company has when it comes to consumer data, you’re in trouble. Data-literate consumers demand more.   I think data literacy in the general population is on the rise. Here’s the definition I use, which adds an awareness component to the definition offered by UK professors Derek McAuley, Hanif Rahemtulla, James Goulding, and Catherine Souch: Data literacy is “the awareness of data’s presence and potential value, and the ability to identify, retrieve, evaluate and use information to both ask and answer meaningful questions.”

Just as literacy empowers individuals and societies to convert the written word into value, data literacy empowers us to extract value from another abundant resource, data — 2.5 quintillion bytes of which is created each day.

Data, then, is the new written word. In nearly every conceivable realm — from medicine and education to government and business — data is helping us understand and improve the world. But data promises a far greater positive impact if we work to foster data literacy among ordinary people.

But data literacy shouldn’t frighten companies. In fact, the rise of data literacy creates a host of new opportunities. At the core of these new opportunities is the prediction that data-literate consumers will actually share more data with the companies that meet their heightened standards. And this data will be more predictive, accurate, holistic, timely, and actionable.

Data literacy starts with awareness. Someone who is data-aware knows that it is everywhere. This person knows that everything he or she does “emits” data. And this person understands that data is potentially valuable.

When confronted with the question I asked at the outset — “Do you want companies to have more of your data?” — the data-literate consumer evaluates a number of factors in order to determine if the exchange of data under consideration meets their personal criteria for a “good deal.” Among these factors: the company’s reputation, the type of data being requested, difficulty of provision, associated risks, and the degree to which it is identifiable back to the consumer.    

Even the best copywriters in the world can’t do much with a lousy value proposition. For most companies, the question of why consumers should give up their data is hard to answer, and it’s not because they can’t find the right words — it’s that they’re simply not offering a good deal.

So, what do consumers want in exchange for more of their data? We have a few clues, but more research is needed.

A 2013 Intel study found that:

  • 80% of lower-income individuals would trade anonymous personal data for cheaper medications
  • 77% of higher-income individuals would “let an application learn about their work habits to make them more efficient”
  • 53% of Millennials would share purchase histories for “a more personalized world that suits us” 

And a 2013 Infosys study found that:

  • 82% of online consumers “expect their bank to mine personal data to protect against fraud”

If businesses feel that they are offering a fair exchange of data for value, the best thing they can do is to be transparent about the offer. If the offer attracts data-literate consumers without negatively affecting the company’s relationship with less the less data-savvy, it’s on the right track.

Intuit’s Data Stewardship Principles give us a good model. Here the company explicitly states:

  • What they will not do with customer data
  • What they will do with customer data
  • Why they use customer data
  • Their commitments to data stewardship and improving internal data literacy

Educating consumers about data can and should be participatory. For instance, companies can start a conversation about their use of consumer data by showing consumers what is collected and asking them to correct inaccuracies in their “data reflection.” Acxiom’s AboutTheData.com is a leading example of this approach.  

Another way to design participation into the process of data collection is to give consumers more control over the “return” on their data. For example, do they want access to exclusive content, special offers, or loyalty points? It’s a bit like choosing a credit card based on the perks. Since they’ll be getting more of what they’ve asked for, they’ll be incentivized to share more data.

If companies want to address the demands of data-literate consumers, they’ll have to boost their own data literacy first by focusing inward. As the flood of consumer data necessitates that more employees handle it, data literacy must break through common silos (such as finance departments and developer groups) and spread within organizations. Part of that effort will involve external recruitment, and part of it will involve the placement of already data-literate employees in groups that have historically low data literacy.

It also means creating internal training programs to instill useful data literacy in “non-quants.” In parallel with data literacy training, companies should implement standards and evaluate employees against them.

I think of data literacy as an “inevitable opportunity.” As it spreads, businesses can either resist it and perish or embrace it and thrive.

© 2016 Ian Greenleigh