With the emergence of data and analytics, artificial intelligence (AI) and machine learning as the new core elements of digital business, the ability for creators and consumers of solutions built on these elements to “speak data” in a common way has never been greater.
Opening the Gartner Data & Analytics Summit this week in Grapevine, Texas, Gartner analysts Carlie J. Idoine, Kurt Schlegel and Rita Sallam told the audience filled with data and analytics leaders across multiple industries that although conversant in the people, process and technology capabilities of business models, most professionals do not “speak data” fluently and need to master this new capability.
Learning to “speak data” is like learning any language. It starts with understanding the basic terms and describing key concepts
“As data and analytics become pervasive, the ability to communicate in this language, to becoming data-literate, is the new organizational readiness factor,” says Idoine. “If there is no common language with which to interpret the various data sources in the organization, there will be fundamental communication challenges when using data- and analytics-based solutions.
In Gartner’s third annual chief data officer survey, respondents said that the second most significant roadblock to progress with data and analytics is poor data literacy, rooted in ineffective communication across a wide range of increasingly diverse stakeholders. Data and analytics leaders must learn to treat information as a second language and data literacy as a core element of digital transformation.
Gartner expects that, by 2020, 80% of organizations will initiate deliberate competency development in the field of data literacy, acknowledging their extreme deficiency. “Developing this type of data literacy can be disruptive,” says Idoine. “Assessing the data literacy of people who create and consume information is a critical step to ensure the organization is enabled with the right skills to meet current and future requirements of digital society.”
Do you speak data?
Learning to “speak data” is like learning any language. It starts with understanding the basic terms and describing key concepts. In the case of data, there are three key areas of vocabulary:
- Managing data
- Analyzing data
- Applying data for value in context
Organizations should cultivate information as a second language (ISL) across business and IT stakeholders by first:
- Establishing the base vocabulary
- Clarifying industry and business domain “dialects”
- Developing levels of proficiency
Proof of concept
Data and analytics leaders should drive and sustain improvements to the organization’s data literacy by identifying areas where data is spoken fluently and where language gaps exist. Select an area of the business to establish an ISL proof of concept (POC) to demonstrate the need and opportunity for enhanced communication and a shared language. Pick a “friendly” area where clear gaps have surfaced, and in which you have willing, diverse participants. Then have each member self-assess their data fluency level.
Lead by example
“Speaking data during everyday interactions, from board meetings to team calls, begins to set the tone for the new mode of communication,” explains Valerie Logan, research director at Gartner.
Logan recommends that with each discussion, data and analytics leaders focus on three key aspects of the language:
- The business outcome
- The data involved
- The analytical technique or approach that supports it
Although fostering data literacy is multifaceted and complex, it is an effective means for scaling the value of data and analytics. To be successful, data and analytics leaders must take the lead to drive literacy throughout the organization via shared best practices, technologies, training and eventually certification.