The journey towards data literacy

For companies who aspire to become data-driven, one of the biggest challenges is transforming culture. In my previous blog post, I wrote about the key elements of a data-driven corporate culture. Here I expand upon data-literacy.

The accelerating rate of change is both exciting and daunting. Educators are addressing the broader notion of digital literacy a number of key initiatives. The challenge, of course, is that digital literacy means different things to everyone you ask. To some it’s can you use a computer, to others it’s much more.

The US Department of Commerce (not Education -- but that’s a discussion for a different day) has a useful website on Digital Literacy which lays out a number of key elements which offer a foundation: Using a computer, using software, using the internet, communicating on the web, and protecting children.

Thriving in today’s workforce requires a digital literacy foundation which encompasses:

  • Computational Thinking

  • Security, Privacy, and Ethics

  • Data & Analytics Literacy

Literacy Venn Diagram.png

Computational Thinking

Computational thinking is taking root in K-12 science programs. But what is computational thinking? Dr. Jeannette Wing lays out the following in her paper Computational Thinking: What and Why?:

Computational thinking for everyone means being able to:

  • Understand what aspects of a problem are amenable to computation

  • Evaluate the match between computational tools and techniques and a problem

  • Understand the limitations and power of computational tools and techniques

  • Apply or adapt a computational tool or technique to a new use

  • Recognize an opportunity to use computation in a new way

  • Apply computational strategies such divide and conquer in any domain

She closes her paper with this excellent statement (bold emphasis mine):

Computational thinking is not just or all about computing. The educational benefits of being able to think computationally transfer to any domain by enhancing and reinforcing intellectual skills.

Resources for developing computational thinking skills are becoming broadly available.  Here are some options for youth: Google, Maker Spaces, Green Dot Public Schools.  Courses for college students and professional education are becoming available on platforms like EdX but focus on specific disciplines such as computer science or data science vs. building foundational skills for any discipline.

Security, Privacy, and Ethics Literacy

It’s hard to go a day without hearing about major corporations (think Equifax) who are unable to protect their systems from outsider attacks. But all too often it’s an insider attack (Snowden is a famous example). But what about insider error? Lost flash drives, inadvertently emailed spreadsheets, falling for a phishing attack, installing malware infected software, reusing passwords, not using 2-factor authentication when available, … the bottom line is the more connected companies and individuals are, the greater the risk of simple user error leading to breaches.

Computer security literacy programs can help reduce the incidence rate, though even experts make mistakes. There isn’t a silver bullet which prevents all imaginable security lapses, but with ongoing training, incidences can be reduced in number and severity.

Iowa State University has responded with an in-depth computer security literacy program for high schoolers. Many companies have implemented annual refresher courses for every employee. Here’s an example for the US Government. All companies should invest in annual security training for every employee.

What about Privacy and Ethics?

The security literacy options above don’t go far towards building privacy & ethics literacy for everyone.

Why does this matter?

Because individuals often care deeply about privacy, and governments are beginning to aggressively tackle the right to privacy with legislation. The European Union, in particular, has taken the lead with aggressive privacy legislation the 'GDPR'. The state of California just enacted the Consumer Data Privacy Act. It's not yet clear if every US state will pass their own laws, or if the US Congress will enact legislation for the country (or both).

Privacy law hints at the ethics challenges beyond basic principles but doesn’t yet stray past basic principles of what the privacy rights of individuals are and requiring companies to protect those rights. Dave Wells' blog post on data ethics is a great introduction to the topic.

Facebook’s privacy and ethics missteps have been highly publicized. Which have greatly increased awareness of the ethical choices companies and individuals make every day, but that’s not the same as building an ethical model and making business or individual choices in the context of the model.  Yes, we can but should we?

Data and ethics electives and online courses are being launched, but we’re a long long ways from making data ethics a core literacy for everyone. Companies who are concerned can invest in their people and have leaders take one of these emerging courses and then strive to embed the concepts into executive decision making and business processes.

Data & Analytics Literacy

Data & analytics literacy requires foundational skills in digital, computational thinking, and security, privacy, and ethics. These aren’t skills you can expect to easily find in college hires or even experienced hires. K-18 education is just starting the journey to infuse these concepts into their curricula.

What does it mean to be data and analytics literate? In the report Building a Global Interest in Data Literacy the data-literate individual can:

  • Define problems
  • Wrangle Data
  • Self-Manage Data
  • Choose Methods and Tools
  • Analyze Data
  • Communicate findings
  • Engage in Lifelong Learning

That’s a lot to unpack and will be the focus of my next blog post.

What does it mean for an organization to be data-driven?

What does it mean for an organization to be data-driven?

Many if not most companies have said – We can do that – and started down the road towards the data-driven nirvana. The basic premise has long been deploying a data warehouse, populating it with your company data, hiring a cadre of business intelligence analysts and in no time, we’ll reach nirvana as it’s just over the horizon.