What is the best language to learn in 2021?

guest column:Hamilton Katsvairo

 

Imagine an organisation where the marketing department speaks English, the product designers speak French, the analytics team speaks Spanish and no one speaks a second language. Even if the organisation was designed with digital media in mind, communicating business value and why specific technologies matter would be impossible.

That’s essentially how a data-driven business functions when there is no data literacy. If no one outside the department understands what is being said, it doesn’t matter if data and analytics offer immense business value and is a required component of digital business.

“The prevalence of data and analytics capabilities, including artificial intelligence, requires creators and consumers to ‘speak data’ as a common language,” Valerie Logan, senior director analyst, Gartner said. “Data and analytics leaders must champion workforce data literacy as an enabler of digital business and treat information as a second language.”

As data and analytics becomes a core part of digital business and data becomes an organisational asset, employees must have at least a basic ability to communicate and understand conversations about data. In short, the ability to “speak data” will become an integral aspect of most day-to-day jobs.

What is data literacy?

Gartner defines data literacy as the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied — and the ability to describe the user case, application and resulting value.

This all boils down to a simple question, “Do you speak data?”

Data literacy is an underlying component of digital dexterity

The ability to understand and communicate in a common data language is a core skill for a core technology. It is the difference between successfully deriving value from data and analytics and losing out to competitors who have made it a core competency in their organisations.

Further, data literacy is an underlying component of digital dexterity, which is an employee’s ability and desire to use existing and emerging technology to derive better business outcomes, another important skill for digital business.

Why is data literacy important?

Poor data literacy is ranked as the second-biggest internal roadblock to the success of the office of the chief data officer, according to the Gartner annual chief data officer survey.

Gartner predicted that, by 2021, 80% of organisations will initiate deliberate competency development in the field of data literacy to overcome extreme deficiencies. By 2021, 50% of organisations will lack sufficient AI and data literacy skills to achieve business value.

As organisations become more data-driven, poor data literacy will become an inhibitor to growth.

Ask the right data and analytics questions

Data and analytics leaders are responsible for creating the narrative for data literacy, highlighting the business value to be gained.

Start by assessing data literacy at your organisation with a few questions:

 How many people in your business do you think can interpret straightforward statistical operations such as correlations or judge averages?

 How many managers are able to construct a business case based on concrete, accurate and relevant numbers?

 How many managers can explain the output of their systems or processes?

 How many data scientists can explain the output of their machine learning algorithms?

 How many of your customers can truly appreciate and internalise the essence of the data you share with them?

“Not only must organisations take steps to educate professionals who are involved in crafting data-driven solutions, products and services, they must also ensure those steps achieve the goal of teaching all relevant employees to speak data as their new second language, as well as developing and nurturing communities in which the language will flourish,” says Logan

Establish a data literacy programme

Start by identifying the fluent and native data speakers. Look at business analysts, data stewards and architects who are able to speak data naturally and effortlessly. Also, identify skilled translators who can serve as mediators for business groups.

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