The Way Data and Analytics Leaders Master Info as a Second Language

It’s the dawn of a new era in business. Such things as data and analytics, artificial intelligence (AI) and machine learning have emerged from the dust as new core components for digital businesses. The demand for those who create and consume solutions made from these components to “speak data” with a common way has never before been greater.

Although data and analytics leaders from multiple industries discuss business professionals, processes and technology related to data, most people do not “speak data” fluently.

“Speaking data” is similar to speaking any language; it begins with the knowing the basics describing the fundamentals.

As data science become present everywhere, the ability to use this new language to communicate effectively with others, to in turn become data-literate, is the new factor to measure organizational readiness. If there isn’t a common method by which to understand sources of data within an organization, there will be roadblocks to communication when trying to leverage business solutions that are grounded in data and analytics.

Per the 3rd annual survey from Gartner of Chief Data Officers, those who responded said that their 2nd most crucial hurdle to overcome to make progress using data and analytics solutions is the lack of data literacy at their organizations, which is rooted in a lack of effective communication over a large range of increasingly different shareholders. It’s vital for leaders of data and analytics teams to learn to treat speaking with data as another language and for data literacy to be seen as a core component in their company’s digital transformation.

Per Gartner, by 2020, eighty percent of organizations will begin deliberate competency training in data literacy, which acknowledges their immense lack of data literacy. Developing data literacy of that type is disruptive. Analyzing the level of data literacy of those who consume and create information is a crucial part in the process of ensuring that a company has the necessary skills to deal with the expectations of a digital business world.

Do you talk the talk with data?

Learning to speak the language of data with fluency is similar to studying any language. It begins with learning the basics and explaining the main, fundamental concepts. When it comes to data, there are 3 main parts to the vocabulary:

  • Data analysis
  • Maintaining the data
  • Implementing the process to data to extract value within context

Businesses must cultivate data as a second language throughout the organization and the stakeholders of IT by doing the following:

  • Determine the base organizational vocabulary
  • Clarify business and industry “dialects”
  • Develop the proficiency levels of the organization

Proof of concept

Leaders in data and analytics must lead and maintain advances in the organization’s program on data literacy by determining areas in which the language of data is fluently spoken and places where gaps exist. Pick a part of the company to establish an information as a second language proof of concept (POC) to show the opportunity and need for improved communication and a common language. Choose an amenable area of the business in which clear deficiencies have arisen, and in which there is a diverse group of people willing to participate. Then ask each person who participates to self-assess their fluency in the language of data.

Lead by example

Speaking the language of data in daily interactions is crucial. This includes using the language of data for everything from board meetings to team calls. It starts with setting the tone for the new communication style.

The recommendation is that with each conversation, leaders of data and analytics teams concentrate on 3 main parts of the language:

  • The involved data
  • The impact on the business
  • The supporting analytics method

Although there are a lot of facets to data literacy and the topic is complex, it’s a powerful way to scale the impact of analytics and data on the business. In order to succeed, analytics and data leaders need to take the reigns so they can drive literacy through the entire organization through a set of common best practices, training certifications, and technology.

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