We’re all typists, now.

If you work in the Knowledge Economy, you know: We are all our own secretary. The full-time role that some might mistakenly label the “modern secretary” – Executive Assistants – has become more skilled, more specialized, and an industry unto itself. Most people couldn’t hack it as a high-performing EA.

But calendar management, running a meeting, document sharing, and even the simplest Excel usage- these are basic workplace skills expected of all knowledge workers.

That baseline has a corresponding, deeper set of valuable skills. SvN (authors of “It Doesn’t Have to Be Crazy at Work“) has written repeatedly on how the most effective employees are also Managers of One. Such employees clearly execute more than just low-friction calendar management and document sharing. We treat those skills today as basic components of workplace literacy.

Instead, a Manager of One excels at task identification, goal-setting, time management, delegation, and escalation. Per SvN:

When you find these people, it frees up the rest of your team to work more and manage less.

SvN, “Hire Managers of One“

Data Literacy as Workplace Literacy

I argue that Data Literacy carves its own niche with a “deep set” of skills beyond the expected default. Just like the Manager of One increases their value and output with discipline and self-management, a Data Manager of One can do more than crack open a spreadsheet or read a chart.

A Data Manager of One can reason about a set of data, understand its sources, ferret out outliers, and have instincts for how the business changes the data, and how data can change the business. They can smell funky data from a mile off. And most invaluably, they ask precise, pointed questions about the data, and know when and how to delegate and ask for help.

Much has been written on how effective analysts and data architects dive deep with the business experts. There’s no data engineering or analysis without business context. But certainly the opposite rings true, and I have loved seeing it in my colleagues: growth toward facility with data (manipulating, interpreting, questioning) is a healthy career move.

Over time, more elements of Data Literacy will continue to creep into the skill set of the “typical” Knowledge Worker, increasing the demand of skills… and the demand for data. At any organization, this could present itself as either a virtuous cycle of learning and discovery, or a data demand spiral, spilling confusion and report breadlines everywhere.

Finance, already the domain of Excel wizards and set-thinkers, demonstrates this. At time of writing, there are over 11,000 unfilled postings on Indeed for “Financial Analyst + SQL”.

This is not to say all subject experts must learn SQL in particular, or that every team needs its own data engineer. There must be a team tasked with preparing and presenting data for the rest of the company, such that every end user can be more efficient and effective. Philosophies on how to best achieve this differ, but all agree that organizations don’t need everyone repeating the same analyses over and over.

The message for organizations and employees alike is that hiring and training for Data Managers of One speeds up the overall team, and, if supported with the right infrastructure, cultural norms, and documentation, allows you to work more and manage less.

The attendant message for analysts and data engineers remains to never cordon off from the rest of the org; that business context is priceless.

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Nearly everyone could benefit from increased Data Literacy. There are plenty of resources online from BI vendors for generalists to understand general workplace data literacy and, in turn, use their products.

(I don’t necessarily endorse those)

I do endorse SQLzoo as the simplest, best introduction to SQL. It’s where I got started.